Cancer immunotherapy has emerged as a promising approach in the treatment of diverse cancer types. However, the development of novel immunotherapeutic agents faces persistent challenges due to poor translation from preclinical to clinical stages. To address these challenges, the integration of microfluidic models in research efforts has recently gained traction, bridging the gap between in vitro and in vivo systems. This approach enables modeling of the complex human tumor microenvironment and interrogation of cancer-immune interactions. In this review, we analyze the current and potential applications of microfluidic tumor models in cancer immunotherapy development. We will first highlight current trends in the immunooncology landscape. Subsequently, we will discuss recent examples of microfluidic models applied to investigate mechanisms of immune-cancer interactions and for developing and screening cancer immunotherapies in vitro. First steps toward their validation for predicting human in vivo outcomes are discussed. Finally, promising opportunities that microfluidic tumor models offer are highlighted considering their advantages and current limitations, and we suggest possible next steps toward their implementation and integration into the immunooncology drug development process. Cancer remains a leading cause of death globally despite the approval of many novel therapies, including some with long-lasting therapeutic benefits. In recent years, the paradigm-shifting approach of cancer immunotherapy has emerged as a transformative strategy, harnessing the body's own immune system to combat and even eradicate malignant tumors, thus revolutionizing the landscape of oncology treatment. In line with this, immunotherapy currently is the most rapidly growing field in cancer treatment, with the most prominent examples being divided into antibody-based and cell-based approaches. Monoclonal antibodies (mAbs), which are targeted against many cancer-associated markers  or checkpoint molecules, represent a large and rapidly growing class of cancer (immuno)therapies today, constituting of over 50% of more than 100 antibodies currently available for routine clinical use . Many BsIn addition to bispecific antibodies and checkpoint blockers, chimeric antigen receptor (CAR)-transduced T cells constitute the third pillar of approved T cell-recruiting immunotherapies. Typical CAR constructs are composed of an extracellular single chain antibody connected via a transmembrane region to intracellular activation  and costimulatory domains  . Dependi. [. [In addition to CAR T cells, other engineered cell products are being developed and show promising results in early clinical studies. As an alternative to CAR-T, engineered T cell receptor (TCR)-expressing T cells (TCR-T) have been suggested for treatment of solid tumors. Recent clinical results of TCR-T therapies have been reviewed by Baulu et al. . Natural. [. ). Aside . [. . Followi. [.  or melan. [. . Additio. [. .Despite the significant promise of cancer immunotherapies, the process of developing novel ones remains complex, time-consuming and costly, with low numbers of approvals, putting a price tag for a single oncology agent in a range of up to $4.5 billion according to market analysts , 15. Thi. Among materials used for manufacturing microfluidic chips, PMDS remains the most widely used material. PDMS is a low-cost, easily accessible material. Its optical transparency allows high-resolution imaging on-chip; flexibility enables production of valves and deformable elements; biocompatibility and gas permeability makes it an excellent material for biomedical applications [Microfluidics emerged in the 1980s and is now a rapidly evolving field offering promising tools to bridge the gap between conventional in vitro models and in vivo models. In microfluidics fluids are manipulated at the micrometer scale with the help of miniaturized devices featuring interconnected channels, chambers and reservoirs with diameters typically ranging from tens to hundreds of micrometers. This allows for low Reynolds numbers and therefore laminar flow, giving more spatiotemporal control over the flow and molecule concentrations. The key interest in biomedical research is to accurately represent the physiology of tissues in so-called organs-on-chips, as it serves as a fundamental technology for creating physiologically relevant tissue models, ensuring better representation of the 3D tissue environment . Dependiications . One of e.g., electrical signals, pH, oxygen), reviewed by Ko et al. [.[The use of microfluidic devices also permits a multi-parameter readout, control of gradients (including oxygen control), compression and stretching of the tissue, application of sheer stress and interstitial flow, as well as integration of sensors measuring physical and chemical parameters  by Cui et al. [i et al. . They dei et al. .Leukemia: A microfluidic model of a leukemia niche was developed and used to study CAR-T cell immunotherapy by Chen et al. [n et al. . The PDMn et al. .Liver cancer: Another recent application of microfluidic systems in T cell-based therapies is exemplified by Preece et al., who investigated the efficacy of T cell receptor (TCR)-engineered T cells to kill hepatoma tumor cells using a commercially available standard, three-lane chip model [ip model . The autip model .. conducted a study that validated their lung- and intestine-on-a-chip microfluidic models and demonstrated their application for the safety assessment of immunotherapies [Kerns et alherapies . The autherapies .There are concerns regarding the utilization of T cells in microfluidic tumor models for T cell-based therapy due to the risk of alloreactivity. However, it is important to note that alloreactive responses typically require a longer timeframe than what is typically employed in in vitro research, along with the involvement of other components of the adaptive immune system. Although in vitro studies with T cells, including microfluidic models, do not often report tumor cell killing without stimulation, the topic of alloreactivity is frequently overlooked. If necessary, mitigating alloreactivity can be achieved through measures such as matching HLA/MHC types between the tissue and donor T cells or utilizing patient explants and T cells from the same donor .In summary, these examples underscore the versatility and potential of microfluidic models in unraveling the complexities of T cell-based cancer therapies, allowing for fine-tuned investigations into therapeutic efficacy, immune responses, and personalized treatments.The investigation of NK cell behavior and anti-cancer function within microfluidic tumor models offers valuable insights into their potential applications for cancer research and treatment. In studies by Nguyen et al.  and MarzWhile the previous studies focused on NK cell-cancer interactions and their functional aspects, there are additional investigations involving different treatments, primarily anti-PD1/anti-PD-L1 antibodies, similar to the mAb therapies mentioned earlier. The utilization of NK cell-activating mAb therapies, like anti-PD1 antibodies, constitutes a promising approach in cancer immunotherapy. By targeting the PD1/PD-L1 immune checkpoint, these therapies restore NK cell activity and enable enhanced tumor cell destruction, as highlighted in the studies described below.50 dose of small molecule chemotherapeutics when combined with NK cells and antibodies[As a first example, Gopal et al.  conductentibodies. Similarntibodies investigIn summary, these mAb-based studies further underscore the capacity of microfluidic platforms to dissect NK cell behaviors within intricate tumor microenvironments, contributing new insights into both the effectiveness of tumor cell killing and the broader implications for tissue interactions and tolerability.While most studies investigating monoclonal antibody (mAb) efficacy focus on T cell or NK cell function, two studies that we discuss below explored the effectiveness of mAbs using different effector cell populations, namely a repertoire of patient-derived tissue-resident immune cells or monocyte-derived macrophages.Patient-derived immune cells: Ao et al. conducted a study to assess the efficacy of murine and human anti-PD1 antibodies (including pembrolizumab) in mammary carcinoma models [a models . They uta models .Monocyte-derived macrophages: In our own research, we focused on the phenotype and function of monocyte-derived macrophages as myeloid effector cells in an MDA-MB-468 breast cancer model [er model . We studer model . Our finer model . AlthougIn essence, these two studies diverge from convention by illuminating mAb effectiveness through different effector cell types, reaffirming the dynamic capacity of microfluidic platforms in deciphering the complexities of cancer immunotherapies.Microfluidics additionally aids the study of emerging immunotherapies like cytokine targeting, oncolytic viruses, vaccines, and RNA-based agents. Cytokine targeting adjusts the immune response by modulating key signaling molecules, while oncolytic viruses selectively infect cancer cells for targeted destruction and immune activation. Cancer vaccines introduce tumor-related antigens to trigger immune responses. RNA-based methods, including vaccines, utilize RNA molecules to modify immune responses. Microfluidic platforms evaluate these strategies on cancer cells, fibroblasts and immune cells, highlighting their potential for enhancing cancer cell killing and immunostimulation in tumor models.Cytokine targeting and oncolytic virus: In one study, Es et al. used a commercially available three-lane microfluidic chip to investigate the effects of pirfenidone (PFD), an antifibrotic agent with anti-inflammatory and antioxidant properties, on cancer-associated fibroblasts (CAFs) in a breast cancer model [er model . They foer model . Mencatter model  utilizeder model .Vaccine and RNA-based approaches: In the context of bladder cancer immunotherapy, Kim et al. [m et al.  created m et al. . Hong etm et al.  used a Pm et al. .The field of microfluidic tumor models is rapidly expanding, with a growing number of applications in cancer immunotherapy. Compared to previous proof-of-concept studies with small molecules, the current state of the art in microfluidics enables integration of functional immune components to develop and study immunotherapies. Currently, such models are predominantly used for studying monoclonal antibodies, with many focusing on PD-1 blockade, aligning with the extensive research and widespread clinical approvals of PD-1 blockade as one of the most established clinically approved cancer immunotherapies at the moment . As micrBy enabling precise control over microenvironmental conditions, the presence or absence of specific cell types and advanced capabilities to follow in real-time on-chip molecular processes, the discussed studies have elucidated previously unexplored facets of immunotherapy, thereby generating novel insights into how they work at the molecular level and provide avenues for generating the next generation of immunotherapeutic approaches. A short-term implication is that the insights in T cell-based mAb therapies may yield novel strategies to better select patients that are likely to respond to specific existing immunotherapies, while in the long term these insights will facilitate the discovery and development of novel agents, which will expand beyond T cell-based mAb therapies and other existing therapies to fully novel immunotherapeutic approaches relying on activating a variety of immune cells, including but not limited to dendritic cells, NK cells, macrophages and neutrophils.Despite the advantages microfluidic models offer in the immunotherapy development, certain challenges remain. The fabrication process can be complex and often requires specialized expertise, limiting widespread adoption of microfluidic systems. Currently, the majority of end users are academic laboratories engaged in proof-of-concept studies. Standardization and reproducibility are additional challenges, as user-to-user variability can arise due to the intricate nature of the models and the inclusion of multiple compartments and parameters. Therefore, along with growing model complexity, there is a drive toward higher throughput, transitioning from custom home-made devices used in proof-of-concept studies to large-scale screening platforms compatible with automated loading, maintenance, and readout. Moreover, microfluidic model validation approaches face challenges. Although in vivo validation is deemed necessary, the scalability to human organs and the need for animal validation present practical constraints and may not fully reflect the complexity of the human immune system.One key trend in microfluidic tumor models is the increasing complexity by implementation of more cell types, by including vascularization to simulate extravasation of therapeutic agents and immune cells and by establishing gradients on-chip. Furthermore, with a move toward coupling multiple tissues, the microfluidic field is evolving toward the development of multi-organs-on-chip systems .To fully harness the potential of microfluidic tumor models in immunotherapy development, several necessary steps need to be taken. Standardization and further scaling are essential to reduce costs and enable automation and facilitate widespread adoption. Validation of microfluidic models, particularly their predictive value for immunotherapeutic responses , remains a critical aspect, which can be achieved through either the use of animal tissues and comparison with the respective animal models, or through direct use of patient material on-chip correlated with clinical outcomes. Combining on-chip experimental platforms with in silico modeling approaches will enhance their predictive capabilities when used together. Additionally, addressing oxygen control within the system is crucial, with current efforts focusing on developing spheroids with a hypoxic core and generally improving control over oxygen and pH levels in tumors-on-chips, which are particularly relevant in cancer research . Finally


Lymph node involvement is a prognostic determinant in the diagnostic work-up and management of muscle-invasive bladder cancer. Thus, it is crucial to provide an accurate staging of the bladder tumor to better identify the best therapeutic strategies to improve the chances of survival and the quality of life of patients affected by bladder cancer. Positron Emission Tomography/Computed Tomography (PET/CT) has been increasingly used in bladder cancer staging to improve the accuracy of lymph node detection and to overcome the lack of sensitivity and the understaging showed by conventional imaging. The aim of this narrative literature review is to provide an overview of the current evidence on the use of 18F-FDG PET/CT in the diagnosis, staging, and restaging of bladder cancer, with a particular focus on its sensitivity and specificity for the detection of LN metastasis. We aim to provide clinicians with a better understanding of 18F-FDG PET/CT’s potential benefits and limitations in clinical practice. Despite the heterogeneity of the studies in the literature and the lack of a consensus, 18F-FDG PET/CT provides important incremental staging and restaging information that can potentially influence the clinical management of patients affected by muscle-invasive bladder cancer.Introduction: Lymph node (LN) involvement is a crucial determinant of prognosis for patients with bladder cancer, and an accurate staging is of utmost importance to better identify timely and appropriate therapeutic strategies. To improve the accuracy of LN detection, as an alternative to traditional methods such as CT or MRI, 18F-FDG PET/CT has been increasingly used. 18F-FDG PET/CT is also used in post-treatment restaging after neoadjuvant chemotherapy. The aim of this narrative literature review is to provide an overview of the current evidence on the use of 18F-FDG PET/CT in the diagnosis, staging, and restaging of bladder cancer, with a particular focus on its sensitivity and specificity for the detection of LN metastasis. We aim to provide clinicians with a better understanding of 18F-FDG PET/CT’s potential benefits and limitations in clinical practice. Materials and Methods: We designed a narrative review starting from a wide search in the PubMed/MEDLINE and Embase databases, selecting full-text English articles that have examined the sensibility and specificity of PET/CT for nodal staging or restaging after neoadjuvant therapy in patients with bladder cancer. The extracted data were analyzed and synthesized using a narrative synthesis approach. The results are presented in a tabular format, with a summary of the main findings of each study. Results: Twenty-three studies met the inclusion criteria: fourteen studies evaluated 18F-FDG PET/CT for nodal staging, six studies examined its accuracy for restaging after neoadjuvant therapy, and three studies evaluated both applications. To date, the use of F-18 FDG PET/TC for detection of LN metastasis in bladder cancer is controversial and uncertain: some studies showed low accuracy rates, but over the years other studies have reported evidence of high sensitivity and specificity. Conclusions: 18F-FDG PET/CT provides important incremental staging and restaging information that can potentially influence clinical management in MIBC patients. Standardization and development of a scoring system are necessary for its wider adoption. Well-designed randomized controlled trials in larger populations are necessary to provide consistent recommendations and consolidate the role of 18F-FDG PET/CT in the management of bladder cancer patients. Bladder Cancer (BCa) is a widespread disease that is ranked as the 10th most commonly diagnosed form of cancer globally. It has a notable effect on the wellbeing and longevity of individuals affected, in particular in situations where the cancer has progressed into a muscle invasive disease [In fact, even if 70% of bladder cancer is represented by non-muscle-invasive tumors, the remaining 30% of patients have muscle-invasive bladder cancer (MIBC) associated with a high risk of lymph node (LN) involvement and distant metastases ,3.The presence of LN involvement in patients with BC, which indicates that cancer has progressed beyond the organ, is a crucial determinant of prognosis, with significant implications for treatment response and overall survival. The prognosis in cases of node-positive disease depends on multiple factors, including the stage and extent of the disease, as well as the presence of other risk factors such as advanced age, performance status, and comorbidities . As suchIt is important for these patients to receive an accurate staging of the bladder tumor to better identify timely and appropriate therapeutic strategies to improve their chances of survival and their quality of life . Before In routine clinical practice, preoperative staging of muscle-invasive bladder cancer (MIBC) typically involves performing a computed tomography (CT) scan of the chest, abdomen, and pelvis. Pelvic Magnetic Resonance Imaging (MRI) can also be used, although not routinely in clinical practice. However, despite their accuracy in detecting primary bladder disease, both CT and MRI have not proven to have high sensitivity for nodal staging. With a sensitivity of 50–85% for the detection of pelvic LN involvement, both CT and MRI understage about 1/3 of patients. CT and MRI remain valuable tools in the preoperative staging of muscle-invasive bladder cancer and can provide useful information for guiding treatment decisions. To improve the accuracy of LN detection, other imaging modalities such as positron emission tomography (PET) or sentinel LN biopsy may be considered in selected cases .To overcome this lack of sensitivity in identifying lymph node involvement, Positron Emission Tomography/Computed Tomography (PET/CT) has been increasingly used in bladder cancer staging.PET/CT is a non-invasive imaging modality which has gained increasing popularity in the evaluation of patients with cancer and provides whole-body imaging, even if imaging of chest, abdomen, and pelvis might be enough for many cancers .PET/CT combines the functional information supplied by PET with the anatomic detail of CT, providing comprehensive information about the metabolic and structural changes in the body.In particular, 18 F-fluoro-2-deoxy-D-glucose (18F-FDG) PET/CT confers information based on glucose uptake and identifies cells with a high uptake such as neoplastic cells with their increased utilization of glucose.Since metabolic alterations occur before the morphological ones, 18F-FDG PET/CT enables an early detection of locoregional disease, distant metastases, and cancer recurrence, before they become evident by conventional imaging like TC or MRI.Another important topic about MIBC is the post-treatment restaging after neoadjuvant chemotherapy.In fact, an early evaluation of NAC response and of presence of residual disease is important to guide the perioperative management of patients. For example, patients with advanced disease and persistent LN involvement even after NAC have poor prognosis, and a multidisciplinary team has to evaluate whether to proceed with a radical cystectomy, intended for palliative rather than curative purpose. Patients who are unresponsive to neoadjuvant chemotherapy (NAC), particularly those with localized disease (cT2-T4aN0M0), might see more benefits from an immediate radical cystectomy rather than continuing NAC, especially considering chemotherapy-related side-effects.Methods traditionally used for post-treatment restaging, such as cystoscopy, urine cytology, routine blood tests, CT, and MRI scans, do not have high diagnostic accuracy, and there is no consensus recommendation regarding restaging imaging during NAC.18F-FDG PET/CT is already used to monitor response to NAC in other types of cancers, while its use in bladder cancer restaging is relatively new and controversial.The aim of this narrative literature review is to provide an overview of the current evidence on the use of 18F-FDG PET/CT in the diagnosis, staging, and restaging of bladder cancer, with a particular focus on its sensitivity and specificity for the detection of LN metastasis. By synthesizing the available evidence on the use of 18-FDG PET/CT in MIBC, we aim to provide clinicians with a better understanding of its potential benefits and limitations in clinical practice.A comprehensive literature search was performed in the PubMed/MEDLINE and Embase databases to identify relevant studies regarding the use of 18F-FDG PET/CT in the diagnosis, staging, and restaging of Muscle-Invasive Bladder Cancer (MIBC). Two independent authors (VS and MB) conducted the search using various combinations of the following terms: “PET/CT”, “18F-FDG PET/CT”, “bladder”, “locally advanced”, “cancer”, “tumour”, “carcinoma”, “pelvic lymph node”, and “staging”. The search strategy aimed to minimize bias and ensure a thorough review of the existing literature.To further enhance the literature search, the reference lists of included studies and relevant reviews were manually screened to identify any additional pertinent publications. Additionally, a search for unpublished studies and conference abstracts was carried out to minimize the risk of publication bias.Studies that examined the sensitivity and specificity of PET/CT for nodal staging or restaging after neoadjuvant therapy in patients with bladder cancer.Studies published in English with no temporal restrictions.Studies conducted in humans.Two authors (VS and MB) independently screened the titles and abstracts of the identified articles for relevance, and any disagreements were resolved by a third author (AM). Full-text articles were retrieved for those that met the following inclusion criteria:Only English-language articles were considered eligible. Both prospective and retrospective clinical studies were included, such as cohort studies and case–control studies. Case reports, case series, and review articles were excluded from the review.The methodological quality of the included studies was assessed independently by two reviewers (VS and MB) using appropriate quality assessment tools. For randomized controlled trials, the Cochrane Risk of Bias tool was employed, while the Newcastle–Ottawa Scale was used for cohort and case–control studies. Any discrepancies in quality assessment were resolved through discussion and consensus or, if necessary, by involving a third reviewer (AM).Study design.Patient characteristics .PET/CT parameters .Main findings of each study , Negative Predictive Value (NPV), and accuracy).The two reviewers independently extracted data from the included studies using a standardized form. The extracted data encompassed the following categories:Any discrepancies in the extracted data were resolved through consensus. A narrative synthesis approach was employed for analyzing and synthesizing the extracted data. The results were presented in a tabular format, with a summary of the main findings of each study.The extracted data were synthesized using a narrative synthesis approach, taking into consideration the various factors that could influence the performance of 18F-FDG PET/CT in bladder cancer diagnosis, staging, and restaging. The results were presented in a tabular format, with a summary of the main findings of each study. Based on the findings of this narrative review and the identified gaps in the current literature, recommendations for future research were formulated.A total of twenty-three studies, published between 2005 and 2019, met the inclusion criteria for this literature review. Histology was reported in fifteen studies reported, of which eight studies presented only patients with Transitional Cell Carcinoma. Instead, seven studies included also patients with histological variants such as adenocarcinoma, squamous cell carcinoma, epidermoid, papillary, neuroendocrine, and paraganglioma .All included studies, except one, reported the timing of image uptake after the administration of 18F-FDG, with eighteen studies acquiring the first PET/CT images 60 min after administration. This standardized timing of image acquisition was assessed for ensuring consistency and accuracy in the interpretation of PET/CT results across studies. Two authors performed the first acquisition earlier, respectively, at 30 and 45 min; two authors posticipated the first acquisition, respectively, at 75 and 90 min.Of the included studies, nine studies highlighted the use of furosemide as a diuretic, and eight studies specified the timing of PET/CT image acquisition following diuretic administration. In all the studies to evaluate the sensitivity and specificity of the technique, 18F-FDG PET/CT findings were compared to pathological reports; for distance metastases, moreover, it is necessary to also perform a comparison to follow-up imaging.The distribution of studies reporting both staging classification by 18F-FDG PET/CT and pathological staging is presented in Anatomical pathology was the reference test used in all but one of the studies included. Clinical T stage was reported in seven (30%) of the twenty-three studies while clinical node and metastasis were reported in nineteen (82%) of the studies reviewed.The pathological N stage was evaluated in twenty (86%) of the twenty-three studies included with an expected good and promising concordance between the clinical and the pathological data.It should be noted that not all included studies reported both types of staging classification, highlighting the variability in reporting practices across studies. Sensitivity of 18F-FDG PET/CT was reported in all the studies, but not all authors provided interquartile range. All the studies provided specificity of 18F-FDG PET/CT, except one.Sensitivity, specificity, PPV, NPV, and accuracy of the studies included are summarized in The Positive Predictive Value (PPV) and Negative Predictive Value (NPV) were reported in seventeen (74%) of the twenty-three included studies, providing important information on the diagnostic accuracy of 18F-FDG PET/CT for bladder cancer. Additionally, thirteen (56%) of the twenty-three studies evaluated the accuracy of PET/CT through various parameters, such as different radiotracers, acquisition protocols, and patient characteristics. Sensitivity, specificity, PPV, NPV, and accuracy of the studies are summarized in 18F-FDG PET/CT has demonstrated promising results in detecting and staging various human cancers, as evidenced by previous studies . HoweverSeveral measures may be employed to improve the accuracy of 18F-FDG PET/CT in bladder cancer imaging. These include oral pre-hydration to dilute the urinary tracer and the use of diuretics to enhance local regional accuracy in scans following furosemide administration. Bladder catheterization may also be effective in limiting 18F-FDG accumulation in the bladder and ureters, thereby improving the detection of bladder wall lesions and regional LNs. While these measures may improve the accuracy of 18F-FDG PET/CT in bladder cancer imaging, their routine use may not be practical or feasible in all patients, and their benefits should be weighed against potential risks and inconveniences ,35. To dPrevious studies have suggested that the advantage of combined PET/CT over CT alone in detecting bladder cancer is minimal, likely due to the significant overlap between standardized uptake values (SUVs) of malignant lesions and active inflammatory processes. This overlap in SUVs can limit the specificity of 18F-FDG PET/CT in detecting bladder tumors and regional LNs, particularly in cases where there is significant inflammation or infection in the bladder or adjacent tissues.While the combination of PET and CT imaging may still provide some additional information beyond what can be obtained with either modality alone, the limited advantage in diagnostic accuracy suggests that the routine use of combined PET/CT for bladder cancer imaging may not be justified in all cases.A review of 2012 showed a sensitivity for combined PET-CT scan of 82% (95% CI: 0.72–0.89) .Girard et al. in 2018 concluded that 18F-FDG PET/CT correctly detect LNs involvement in an additional 8% of patients compared to CT alone and that 18F-FDG PET/CT accuracy is 82% compared to 74% of CT alone . SeveralAccording to Goodfellow et al., PET scans are considered useful if they result in a change in management for more than 10% of patients. In such cases, routine use of PET scans would be recommended. When PET scans lead to a change in management in 5–10% of patients, they should be used selectively for certain patients. However, if PET scans result in a change in management for less than 5% of patients, their routine use may not be justified. These recommendations highlight the need for careful consideration of the potential benefits and limitations of PET imaging, and the importance of individualized decision-making in the management of bladder cancer .A recent review of 2022 on preoperative detection of pelvic LN involvement confirmed a higher sensitivity and specificity combining PET and CT scan when compared to the traditional imaging modalities . A recen18F-FDG PET/CT has multiple applications beyond preclinical staging, including post-treatment restaging after neoadjuvant chemotherapy (NAC). Traditional modalities, such as cytology, cystoscopy, CT scans, MRIs, and routine blood tests, are often inaccurate in detecting residual disease or assessing treatment response. Early assessment of NAC response and/or residual disease is crucial for guiding perioperative management, limiting chemotherapy-related side effects and improving quality of life. 18F-FDG PET/CT is a reliable tool for monitoring response to chemotherapy in various cancer types and has been shown to be more accurate than conventional imaging. Recent studies have identified 18F-FDG PET/CT as an effective method for detecting both residual and recurrent disease, with superior accuracy in detecting post-treatment recurrence outside the urinary tract, primarily bone lesions, compared to conventional restaging techniques. Despite its potential benefits, there is currently no consensus on the use of 18F-FDG PET/CT for identifying chemo-sensitive bladder tumors during NAC. Nonetheless, the use of 18F-FDG PET/CT in post-treatment restaging may help to guide treatment decisions, such as whether to proceed with radical cystectomy or continue with NAC, based on the presence or absence of residual disease .In addition to its potential role in bladder cancer staging, 18F-FDG PET/CT has applications in sentinel lymph node (SLN) mapping to aid in the resection of selected, invaded LNs during pelvic LND . This apThe complexity of bladder cancer staging using PET/CT prompts the need for a scoring system to improve its precision. This system should integrate key parameters like standardized uptake values (SUVs), indicative of tumor metabolic activity, and primary tumor size, which could correlate with disease progression. Lymph node involvement, particularly peri-vesical nodes, and the presence of distant metastases identified by PET/CT should also be incorporated due to their prognostic implications. Furthermore, changes in PET/CT findings post-neoadjuvant chemotherapy (NAC) could provide insights into tumor chemosensitivity and could thus influence the score. This score has been explained in detail in The development of this scoring system calls for rigorous validation through future studies, correlating the score with patient outcomes in various settings and patient groups. Such a scoring system could reconcile PET/CT discrepancies and enhance its utility in bladder cancer assessment. However, ongoing research is essential to confirm the value of this proposed scoring system, as it presents a promising avenue to optimize PET/CT’s role in bladder cancer management.Despite its potential benefits, 18F-FDG PET/CT has several limitations, including high cost, higher radiation exposure, lack of anatomic reference frame when performed alone, and prolonged lag time between PET and staging CT scans. A full-dose diagnostic staging CT with intravenous contrast medium may provide a better assessment of LNs and metastases than the CT component of the PET scan. False positive results can also lead to delay of treatment, unnecessary procedures, and additional costs. Therefore, PET scan results should be interpreted with caution in conjunction with CT scan and clinical judgment, particularly in cases of benign tumors or inflammatory lesions. Nonetheless, accurate staging information provided by 18F-FDG PET/CT can significantly influence therapeutic management and serve as an important prognostic indicator for progression-free survival (PFS) and overall survival (OS).Although 18F-FDG PET/CT has shown promise as a feasible and reliable tool for bladder cancer staging, evidence for its use in diagnosis and staging is not yet strong. Like all radiological exams, 18F-FDG PET/CT is limited by the inability to retrieve a histological sample. Its non-invasive nature also makes it a potential tool for follow-up, but further studies are needed to evaluate its effectiveness in this setting. A standardized reporting system for characterizing bladder cancer using 18F-FDG PET/CT is still lacking, and efforts should be aimed at developing and validating a scoring system to improve its accuracy in staging. Despite these limitations, 18F-FDG PET/CT remains a valuable tool in the management of bladder cancer and can provide important information for treatment planning and prognostication.In conclusion, 18F-FDG PET/CT provides important incremental staging information that can potentially influence clinical management in MIBC patients, although it can also lead to false positive results. However, supporting clinical evidence for its use is limited and requires further confirmation. Standardization of this approach and development of a scoring system are necessary for its wider adoption. In addition, 18F-FDG PET/CT has potential applications in sentinel LN mapping, which can guide the resection of selected and suspicious LNs during pelvic lymph node dissection. Sentinel LN biopsy is commonly used in breast and skin cancer treatment and can simplify histopathological examination and reduce the extent of LND.


Liquid chromatography-high-resolution mass spectrometry(LC-HRMS)is widely used to detect chemicals with a broad range of physiochemicalproperties in complex biological samples. However, the current dataanalysis strategies are not sufficiently scalable because of datacomplexity and amplitude. In this article, we report a novel dataanalysis strategy for HRMS data founded on structured query languagedatabase archiving. A database called ScreenDB was populated withparsed untargeted LC-HRMS data after peak deconvolution from forensicdrug screening data. The data were acquired using the same analyticalmethod over 8 years. ScreenDB currently holds data from around 40,000data files, including forensic cases and quality control samples thatcan be readily sliced and diced across data layers. Long-term monitoringof system performance, retrospective data analysis for new targets,and identification of alternative analytical targets for poorly ionizedanalytes are examples of ScreenDB applications. These examples demonstratethat ScreenDB makes a significant improvement to forensic servicesand that the concept has potential for broad applications for alllarge-scale biomonitoring projects that rely on untargeted LC-HRMSdata. The acquired data set is rich, with eachanalytical compound identified as an m/z-retention time pair, possibly supported by additional parameterssuch as the fragment ions, adduct pattern, or isotopic pattern. LC-HRMSdata originally acquired for one purpose is reanalyzed to answer newresearch questions using retrospective screening,7 metabolomicsapplications,11 and nontargeted screening.2 The data files are mostly queried at the batch level using vendoror open-source software via open file formats. The data analysis strategiesfor re-use of >1000 LC-HRMS data files typically involve eithersignificantdata reduction or are limited to the original research question, therebyrequiring process-heavy reanalysis for new questions. This articlereports a novel data analysis strategy for LC-HRMS data that involvesthe additional storage of peak deconvoluted data in a structured querylanguage (SQL) database format, allowing for quick reanalysis to answernew research questions.Liquid-chromatography-high-resolutionmass spectrometry (LC-HRMS)is widely used for comprehensive screening of complex samples in environmental,13 This noveldata analysis strategy for LC-HRMS data is scalable to at least 40,000data files, although only the server hardware theoretically sets thelimit. SQL archiving is thus ideal for active storage of large amountsof comparable LC-HRMS data sets if the data owner wishes to frequentlyquery data.Untargeted and unannotated analyticaldata from our LC-HRMS forensicdrug screening collected in 8 years was parsed to an SQL database,referred to as ScreenDB. Forensic analyses adhere to strict qualityassurance schemes to ensure the traceability and reproducibility ofresults. After a method development, validation, and implementationphase, a screening workflow will run with only minor modificationsresulting in data that is comparable over time. ScreenDB was set upwith the objective of linking the screening data with other forensicmetadata, and the database should allow the access to all relevantdata layers including adduct, isotope, and fragment ions. Our applicationsof ScreenDB show functional data workflows with >10,000 LC-HRMSdatafiles.2 Briefly, chromatographicretention was performed with reversed-phase LC in the gradient modewith a total run time of 15 min. Data were acquired on three differentXevo G2-S QTOF HRMS instruments  with comparableparameters and sensitivities, in the MSE data-independentacquisition mode.The sample preparation, LC-HRMS settings,and subsequent data evaluation workflow were previously describedby Mollerup et al.–1. The qualityof every batch and injection was verified as part of routine forensicdata analysis. Only data from analytical runs that fulfilled set forensicQC criteria were transferred to the database. All data was analyzedin UNIFI instrument software  and then exportedas the UNIFI export package format (.uep). Since the data was previouslyused in forensic drug screening workflows, data files were reprocessedto remove annotations and to lower the ion count threshold. The countthreshold was lowered to allow evaluation of these set thresholds.Internal standards were added to allsamples prior to sample preparation. Within-run quality control (QC)samples included blank matrices, internal-standard blank injections,and injection of three methanolic standard mixtures, each containingapproximately 100 compounds at 0.5 mg LLC-HRMS measurement variables were readdirectly from the uep data files and subsequently parsed to the SQLarchive. To prepare plots, data were extracted from ScreenDB withthe SQL server , and subsequentanalysis steps were made using Python. Data variables of internalstandards for all biological samples and selected QC analytes analyzedbetween 2014 and 2020 were extracted from ScreenDB with one diagnosticfragment ion with precursor ion limits of exact mass ± 3 mDa.These ions were then grouped using the mean-shift clustering algorithmfrom the SciKit-learn Python package. All peaks were scaled usingtolerances of 3 mDa and 0.5 min between samples. The mean-shift clusteringalgorithm was subsequently applied using a bandwidth of 1. Diagnosticfragment ions were grouped if present at 0.015 min from the precursorion.Tables S1 and S2 presenting the most important variables parsed from the uep files.A sample table holds sample-specific information, such as the sampleidentifier, file directory, run name, and a unique data identifier(uid) assigned to the raw data using vendor software. Each analyticalinjection corresponds to one line in the sample table. In the peaktable, each line corresponds to one ion signal from either low- orhigh-energy channels. Each signal has an accurate mass, retentiontime, and signal intensity, together with diagnostic variance parameterscalculated in the compression (componentization) process from theprofile data. The UNIFI componentization step involves peak detectionand subsequent grouping of co-eluting ions in the high- and low-energyspectra,14 and thus filtering out of somebackground signals that do not show chromatographic retention. Theprecursor ion, in-source fragment ions, isotopes,and adducts are available from the low-energy spectra, and the residualprecursor ion and fragment ions are available from the high-energyspectra, along with some co-eluting interferences. Ions are decomponentizedin ScreenDB, meaning that each measured ion at a given retention timeresults in a line in the peak table, and it can be queried independentlyfrom the assigned component. Variables available from the ScreenDBpeak table are illustrated in Figures S1A and S2A, respectively, from the lock-mass corrected and centroidedraw files and from the uep files from the same injection as that in S2B to illustrate data retention in the componentizationstep. Complex, multiparametric queries are not easy to build in vendorsoftware but can be coded in general-purpose programming languageswith extracts from ScreenDB. A legacy version of ScreenDB used forearlier applications13 was based on mascot generic formatfiles that associated each low-energy ion with the component’shigh-energy spectrum. This inflated the legacy ScreenDB and also requiredconversion of the data files prior to storage. Reading the uep filesdirectly allows the retention of more analytical information and accessto the extra data layers arising from profile acquisition. The useof the mascot generic format in combination with MS1-levelfeatures is used in feature-based molecular networking, where onlyrepresentative MS2 spectra are selected to eliminate thisdata inflation.15 Feature-based LC-HRMSdata with linked fragment ion spectra could work well in an SQL databasestructure, although ions recorded in low and high energy would havevariable levels of information. The database architecture would haveto be modified accordingly and may need separate tables for featuresand fragment ions. Other acquisition and processing software or peak-pickingalgorithms provide different data variables available for parsing.Without the UNIFI componentization step, another lock-mass correctionand peak-picking algorithm should be used to centroid ions in themass and retention time domains. It is, however, crucial for retrospectiveand non-targeted data analysis workflows that the data layers remainaccessible separately for flexible queries that are not locked infeature formats. Our purpose of making this structured digital archivewas to mirror and support the in-house screening, which uses UNIFIpeak components, and therefore, alternative approaches were not evaluatedas this would not fulfill our research goals.Different types offorensic cases were screened with the same LC-HRMS method, includingdriving-under-the-influence-of-drugs, drug seizure, biological samplesfrom autopsy, and drug-facilitated crime cases. Registration and documentationare handled through a laboratory information management system, STARLIMS. The sample name, analyticalrun number, and analysis identifier nomenclature in ScreenDB referto the entries in the LIMS. Via this structured connectivity, datafrom each LC-HRMS injection can be matched with well-curated dataconsisting of quantitative results from complementary methods, thesample age, case characteristics, and other historical data. ScreenDBconsists of two tables, with 12Reproducible measurements areimperative for the meaningful comparison of data variables acquiredover years of analysis. A strength of ScreenDB is that stored QC samplevariables and internal standard signals are accessible for furtherquality check and to set informed limits. Histograms of the protonatedmolecules in the mass and retention time domains from internal standardsin around 14,000 biological samples are presented in In accredited analytical laboratories,systems are regularly maintained and evaluated with system suitabilitytesting. Monitoring of system performance with ScreenDB variablessupports informed decisions during troubleshooting sessions, as exemplifiedin 13 A toxicological screening is frequently carried out with positiveelectrospray ionization and therefore has lower sensitivity for neutraland acidic compounds. Comparing the LC-HRMS data from samples withknown positive and negative quantitative results for a given drugallows the identification of alternative targets , and then, we can query 8 years’ worthof LC-HRMS data with the same level of information available in vendorsoftware but with both flexibility and speed. Scalable data analysisapproaches as presented here are necessary as large-scale biomonitoringwith LC-HRMS becomes more prevalent. Active storage in SQL databasescan expand the impact of large-scale biomonitoring projects by makingthe data more accessible, reusable, and interoperable. However, robustanalytical systems that are evaluated with QC systems are imperativeto compare data over long periods of time.Readily retrievable,curated, and untargeted analytical data enablefast and simple retrospective analyses for new targets and activeuse of stored intelligence in historic LC-HRMS data. Consequently,transferring data to a structured digital archive augments activedata reuse and, in our case, improves forensic services.


Background: Atrial fibrillation (AF) and chronic obstructive pulmonary disease (COPD) have been independently associated with increased mortality; however, there is no evidence regarding beta-blocker cardioselectivity and long-term outcomes in patients with AF and concurrent COPD. Methods: This post hoc analysis of the MISOAC-AF randomized trial (NCT02941978) included patients hospitalized with comorbid AF. At discharge, all patients were classified according to the presence of COPD; patients with COPD on beta-blockers were classified according to beta-blocker cardioselectivity. Adjusted hazard ratios (aHRs) were calculated by using multivariable Cox regression models. The primary outcome was all-cause mortality, and the secondary outcomes were cardiovascular mortality and hospitalizations. Results: Of 1103 patients with AF, 145 (13%) had comorbid COPD. Comorbid COPD was associated with an increased risk of all-cause , 1.02 to 1.73) and cardiovascular mortality , but not with increased risk of hospitalizations . The use of cardioselective versus non-cardioselective beta-blockers was associated with similar all-cause mortality , cardiovascular mortality , and hospitalizations . Conclusions: In recently hospitalized patients with AF, the presence of COPD was independently associated with increased risk of all-cause and cardiovascular mortality. No difference between cardioselective and non-cardioselective beta-blockers, regarding clinical outcomes, was identified. Atrial fibrillation (AF) is the most commonly treated arrhythmia , and is Beta-blockers (BB) are indicated for rate control in patients with AF . ContrarBoth cardioselective and non-cardioselective BBs are absorbed from the gastrointestinal tract and reach peak plasma concentrations within 1–3 h, reducing, thereby, the effects of adrenaline and noradrenaline, and lowering heart rate, blood pressure, and heart contractility. They are primarily metabolized in the liver , and are mainly eliminated through renal excretion. The metabolic pathways and elimination  of BBs can vary depending on the specific drug, which might affect their duration of action and the potential for drug–drug interactions .Nonetheless, selective beta-blockades with beta-1-blockers have been associated with a survival advantage in patients with COPD and concurrent chronic heart failure (HF) or myocardial infarction ,24. HoweWith regard to the above, we conducted a retrospective analysis on a cohort of patients discharged from the hospital with AF. We examined the association of comorbid COPD with mortality and hospitalizations. In the subset of patients with AF and COPD, we explored the association of BB cardioselectivity with these outcomes.ClinicalTrials.gov identifier: NCT02941978). Briefly, the MISOAC-AF trial examined the effect of a combined motivational–educational intervention on adherence to prescribed oral anticoagulation therapy in patients with AF following an acute hospitalization. The design, the selection criteria, and the main results of the MISOAC-AF trial have been previously published [This observational study constitutes a post hoc analysis of the randomized controlled MISOAC-AF trial  with a primary or secondary diagnosis of AF. After hospital discharge, patients were followed up from December 2015 to June 2018. The database of the MISOAC-AF trial included information on COPD status and prescription of BBs at discharge. Prescription of BBs was further classified according to BB selectivity (cardioselective and non-cardioselective BBs). Baseline demographic; clinical; laboratory; and echocardiographic data, as well as comorbidities; medication; and prospective clinical outcomes were extracted from the MISOAC-AF database for the purpose of this study.The diagnosis of AF was established through electrocardiograms showing irregular RR intervals and no distinct P waves for more than 30 s. Diagnosis of COPD was determined through identification of prescribed inhalation therapy (short-acting (SABA) and long-acting (LABA) beta2-agonists and inhaled corticosteroids). Data concerning medication therapy of COPD were acquired, either from discharge letters or through the Greek electronic medical prescription system.The primary outcome was all-cause mortality. Secondary outcomes were cardiovascular mortality and hospitalizations after discharge. Cardiovascular mortality was predefined in the MISOAC-AF trial .Follow-up was conducted by independent researchers annually, through phone calls or in-person interviews. Mortality during the MISOAC-AF trial was ascertained through the Greek Civil Registration System. The follow-up period was extended until May 2020.t-test and Wilcoxon–Mann–Whitney test were used for continuous numerical variables, according to the normality of their distribution. Chi-squared tests or Fisher’s exact tests were used for categorical variables. For the survival analysis, Kaplan–Meier curves were constructed and log-rank tests were performed. Cox regression models were calculated in both comparisons to acquire an adjusted hazard ratio (aHR) for the effects of the explanatory variables. The maximum number of independent variables, that could be included in the final model, was determined by the rule of one predictor variable for ten outcomes of interest. Variable selection was based on literature research, and a p-value cut-off of 0.1 was set in univariate analysis. Variables used for adjustment were age, BBs, diabetes mellitus, left ventricular ejection fraction (LVEF) ≤ 40%, and history of coronary artery disease (CAD) as well as prior stroke. To ensure no violation of the assumptions of the Cox regression models, Schoenfeld residuals were examined. The level of significance (α) was set to 5%. Two-tailed p-values were calculated. The multiple imputations method was performed to impute any missing data. The number of imputations was 20 for 10–30% missing data and 40 for >50%. In regression analyses, the results were pooled into one point estimate according to Rubin’s rule. Additionally, we also performed survival Cox regression analyses based on the initial dataset (with missing non-imputed variables). The results derived from these analyses are shown in the The student’s 2DS2-VASc score or a prior history of stroke and similar prescription rates of BBs and oral anticoagulants (OAC) compared to non-COPD patients  had a concomitant diagnosis of COPD. In general, patients with COPD were more frequently smokers, had a higher CHApatients . Of patipatients . Interesp = 0.002 by log-rank test)  died. A univariable analysis showed a significantly higher all-cause mortality rate in COPD patients than in non-COPD patients  a. Signifnk test) .p < 0.001 by log-rank test)  deaths documented during the follow-up period. Of patients with AF and COPD on BB therapy, the rate of death was 47.9% (57 deaths in 119 patients). COPD was a significant prognostic factor for cardiovascular mortality in AF  . That isnk test) b. Duringnk test) c.When we conducted the aforementioned Cox regression analyses, based on the initial dataset (with significant number of missing non-imputed variables), COPD was not an independent predictor of those clinical outcomes, despite its univariate association with increased risk of mortality, CV mortality or hospitalizations during follow-up .p = 0.78 via the log-rank test  occurred in COPD patients on BB therapy. At the time of discharge, 71 patients were treated with cardioselective BBs and 32 of them died (45.1%), as compared with 25 of 48 patients treated with non-cardioselective BBs (52.1%). Statistical analyses did not reach significance on all-cause mortality between cardioselective and non-cardioselective BBs .p = 0.85 via the log-rank test . No siank test c.The cardioselectivity of BBs was also not significantly associated with the occurrence of these clinical outcomes according to the analyses performed, based on the initial dataset (with a significant number of missing non-imputed variables) .This retrospective study examined the prognostic implications of COPD and BB cardioselectivity on the clinical course of AF in hospitalized patients with comorbid COPD followed up after their discharge. We validated the high prognostic significance of COPD comorbidity in all-cause and cardiovascular mortality of AF patients. No significant association regarding BB cardioselectivity and clinical outcomes in AF patients with comorbid COPD was demonstrated. To our knowledge, this is the first study investigating the association of BB cardioselectivity, in patients with AF and COPD, with clinical outcomes.The prevalence of concomitant COPD in our population 13.1%) was within the rate published in the current literature. The later ranges were between 10.8% and 25% ,13,14. O.1% was wOur findings are in accordance with published data concerning mortality in AF-COPD comorbidity. According to a recently published meta-analysis, the odds of all-cause mortality were approximately 2 to 3 times higher in AF patients with COPD compared to patients with AF alone, while the odds of cardiovascular mortality were up to 143% higher in cases of COPD comorbidity ,9.Moreover, our study found no association between BBs and long-term patient outcomes. Our findings are in accordance with the prospective cohort study of Proietti et al. 2016) and a recently published meta-analysis, which did not identify BB use as a risk factor for clinical outcomes in patients with concurrent AF and COPD ,14. On t and a reThe comparison between cardioselective and non-cardioselective BBs did not reach statistical significance with regard to long-term outcomes. The use of BBs and their cardioselectivity, in patients with COPD and cardiovascular diseases, has been previously investigated. A meta-analysis of Yang et al. (2020), on concurrent COPD and cardiovascular diseases, showed no association of cardioselective and non-cardioselective BBs with the acute exacerbation of COPD events and heart rate control . HoweverThe strengths of this study include the long follow-up period and the availability of information concerning medication and inhalation therapy. COPD medications, such as inhalation therapy and corticosteroids, are not often mentioned in studies examining AF–COPD comorbidity.However, the sample size was relatively small regarding the comparison between cardioselective and non-cardioselective BBs and there was a high percentage of missing values regarding the outcome of hospitalization (40–50%). Moreover, COPD diagnosis was not based on GOLD criteria, and identifying patients with COPD using an already-known spirometry-based diagnosis might have been more accurate than just using a treatment-based diagnostic criterion. Furthermore, the severity of COPD was not taken into account in our analysis. Additionally, changes in medication during follow-up were not captured. The documentation of any drug-related adverse events or a sub-analysis on the precise cause of mortality, or the individual BB drug and dose, could not be achieved in our study due to the unavailability of the required data. Furthermore, the study population consisted of patients who likely live in an urban environment or have access to a university hospital, and have been hospitalized due to a cardiological cause.In recently hospitalized patients with AF, the presence of COPD comorbidity was associated with increased all-cause and cardiovascular mortality. No significant difference of cardioselective and non-cardioselective BB use with the clinical outcomes of AF–COPD patients was identified. Further prospective trials are warranted prior to reaching definite conclusions for the optimal medical management of this challenging comorbidity.


Foodborne viruses have been the leading cause of acute gastroenteritis worldwide. There is a great need for novel approaches to inactivate or control foodborne viruses as food products commonly associated with foodborne viruses are not suitable for heat treatments. Furthermore, most foodborne viruses, especially noroviruses, are resistant to alternative treatments and preservatives that can be used to control foodborne bacterial pathogens. With the latest scientific knowledge on foodborne viruses and new cultivation techniques for human noroviruses (HuNoVs), scientists around the world have been investigating and developing new controlling methods and strategies. Therefore, we launched the Research Topic in July 2021.Escudero-Abarca et al. characterized the efficacy of eight commercial hand sanitizers , alongside with 60% ethanol solution as a benchmark, against HuNoV with an epidemic GII.4 HuNoV strain by an in vivo fingerpad method, and found that product performance was variable and none of the products were able to completely inactivate the HuNoV. Using a small-scale system, Song et al. evaluated the efficacy of slightly acidic electrolyzed water (SAEW) combined with ultraviolet C-light-emitting diode (UVC-LED) in inactivating a GII.4 HuNoV strain, on a stainless-steel surface. They found that the specific treatment conditions for inactivation of the HuNoV strain were an SAEW droplet volume of 180 μL with 30 ppm available chlorine concentration and a UVC-LED exposure dose of 2 mJ/cm2, and suggested that the combined treatment could effectively prevent the spread of HuNoVs. Xu et al. investigated the direct interactions between lettuce-encapsulated bacteria that expressed histo-blood group antigen-like substances and a GII.4 HuNoV strain and through simulated environmental experiments, including short-time high-temperature treatment (90°C) and UV exposure, they demonstrated that binding of HuNoVs with bacteria expressing histo-blood group antigen had detrimental effects on the HuNoV reduction. Cantú-Bernal et al. examined the anti-rotavirus effect of probiotics Bifidobacterium longum and Lactiplantibacillus plantarum in combination with microalga Chlorella sorokiniana in a dairy product flan, and observed a potent anti-rotavirus effect of C. sorokiniana, as well as increased anti-rotavirus activity of the probiotics with the combination of C. sorokiniana.This volume includes four articles with research subjects of HuNoV and rotavirus. Taken together, we hope this collection of articles provide useful and applicable information in controlling and inactivating foodborne viruses, to help prevent illness and outbreaks caused by foodborne viruses.XL: original draft preparation and editing. DL and GS: editing. All authors have approved the article.


This study aimed to predict the molecular features of endometrial carcinoma (EC) and the overall survival (OS) of EC patients using histopathological imaging.n = 215) and test set (n = 214) in proportion of 1:1. By analyzing quantitative histological image features and setting up random forest model verified by cross-validation, we constructed prognostic models for OS. The model performance is evaluated with the time-dependent receiver operating characteristics (AUC) over the test set.The patients from The Cancer Genome Atlas (TCGA) were separated into the training set (p < 0.001).Prognostic models based on histopathological imaging features (HIF) predicted OS in the test set (5-year AUC = 0.803). The performance of combining histopathology and omics transcends that of genomics, transcriptomics, or proteomics alone. Additionally, multi-dimensional omics data, including HIF, genomics, transcriptomics, and proteomics, attained the largest AUCs of 0.866, 0.869, and 0.856 at years 1, 3, and 5, respectively, showcasing the highest discrepancy in survival (HR = 18.347, 95% CI [11.09–25.65], The results of this experiment indicated that the complementary features of HIF could improve the prognostic performance of EC patients. Moreover, the integration of HIF and multi-dimensional omics data might ameliorate survival prediction and risk stratification in clinical practice. Endometrial carcinoma (EC) is the sixth most commonly encountered type of cancer in women and one of the most prevalent malignancies of the female reproductive system. Epidemiological data related that its incidence has risen globally in the last decades , which cBiopsy and resection histopathological images are extensively used for cancer diagnosis, staging, prognosis, and treatment. With the takeoff of computer-aided image analysis systems, digital pathological images can now be examined more accurately, rapidly, and consistently than ever before. Moreover, they assist in reducing the pressure resulting from the shortage in manual evaluation . DigitalThe multi-omics model has been extensively applied in EC, and molecular indicators for EC have been incorporated into the NCCN Guidelines. Studies based on multi-omics and The Cancer Genome Atlas (TCGA) database divided EC into four distinct molecular subgroups: (1) polymerase epsilon (POLE) ultra-mutated group, (2) microsatellite instability (MSI)-hypermutated group, (3) copy number abnormalities-low (CN-L) group, and (4) copy number abnormalities-high (CN-H) group . In addiThe goal of this research was to establish an image processing pipeline into which digital histopathological slides could be introduced; the system would then automatically extract their features and conduct sequential, systematic analyses to determine features correlated with those detected on the slides. This study also aimed to predict the mutations and molecular subtypes of EC using HIF and different machine-learning methods. To begin, the prognostic model was built using image feature to establish its robustness and reliability. Next, its performance was evaluated on the test set. Different multi-dimensional omics models were developed to compete for higher accuracy so that the survival risk could be more accurately predicted and to boost personalized medicines for EC patients.The dataset in this study comprised genetic, transcriptional, and clinical information of EC patients from the TCGA database. Moreover, the corresponding protein profiles were collected from the Cancer Proteome Atlas (TCPA) repository. Variance-stabilizing transformation (VST) of the DESeq2 R package was applied to the mRNA sequencing data for normalization so as to extend the generality of the current model.A total of 735 hematoxylin and eosin (H&E)-stained histopathological images of 465 patients were downloaded from The Cancer Imaging Archive (TCIA) to create the image features . For adeThe flowchart of image segmentation and multi-omics model construction is illustrated in Classifying molecular features: An attempt was made to predict the molecular features of EC using HIF. The data from the TCGA cohort were randomly split into a 1:1 ratio obtain a training set and a test set. Random splits maintain consistency at a positive rate. Several machine-learning algorithms were applied, including least absolute shrinkage and selection operator (LASSO), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and random forest (RF), to screen features in order of importance and subsequently narrow down the dimensionality of the data herein to 20 features. Next, RF, GBDT, ADABAG, logistic regression (LR), naive Bayes (NB), support vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN) were selected to build classifiers based on the selected features to predict molecular substyles  and molecular mutations . Finally, five-fold cross-validation was applied to fine tune the hyperparameter in the training set. Here, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve served as evaluation metrics.p < 0.05 was considered as statistically significant.The TCGA cohort was divided into training and test sets. Patients in the training set were divided into high-expression and low-expression groups according to the median value of each histopathological imaging feature. Cox regression analysis was used to calculate the hazard ratio (HR) and the 95% confidence intervals of the overall survival (OS). Next, the Kaplan-Meier survival curve and the log-rank test were employed to estimate differences in survival outcomes between the two groups. The genomic features and transcriptomics were screened to lower the dimensionality of data, and the top 100 most common somatic mutations in the training set were selected. One hundred of the most differently expressed genes (DEGs) of the training set patients, including the long-term (OS ≥ 60 months) and short-term (OS of 1–12 months at death) survival group, were chosen for survival prediction.via the R randomForestSRC package to establish prognostic models. Moreover, patients were divided into high-risk and low-risk groups according to the median risk score estimated from the models. A time-dependent ROC curve was plotted to display the predictive capability of our prognostic model. Thereafter, the Kaplan-Meier method and log-rank test were applied to evaluate the survival difference between the two risk groups. Furthermore, to yield an in-depth understanding of the net clinical benefit of the models, decision curve analysis (DCA) was conducted with the threshold probabilities of each model based on a 5-year OS by the R “DCA” package.The usefulness of different combinations of features, like single features  and the combination of two types of features , in the prognostic model was evaluated and compared. Based on the HIF and genomic data, random survival forest (RSF) models were trained with five-fold cross-validation in the training set Comparisons over different machine learning methods were performed on a 4 × 8 cross-test basis using four algorithms  for feature selection and eight algorithms  to build classifiers. The most outstanding performance was rendered by our RF model despite the feature engineering process . Among 3p < 0.05)  . Among tnce_3_90 . The difnce_3_90 . Taken tFurthermore, patients were stratified into two subgroups based on survival time: the high-risk group (OS < 1 year) and the low-risk group (OS ≥ 5 years). Four features with discrepant categories showed up with their highest significance. They were further illustrated by high-expressed and low-expressed prognostic features . As dispThe RSF algorithm was included in our integrative model to validate the possibility of integrating histopathological and genomics data and to evaluate the value of genomics data in predicting prognosis. The 20 most common somatic mutations in the training set are presented in The test set was divided into a high-risk group (greater than the median) and a low-risk group (less than the median) according to the median value of the survival risk score predicted by the machine-learning models. Based on the Kaplan-Meier survival curves, our three models exhibited a satisfactory predictive value for the OS of in the high-risk and low-risk groups of the test set . Among ohttp://metascape.org) exposed that was closely associated with cell differentiation, anticoagulation, and blood circulation  and long-term survivors (OS ≥ 60 months). For mRNA sequencing data, the DEGs between the short-term and long-term groups were analyzed for dimension reduction. Gene Ontology (GO) enrichment analysis using Metascape  data with the inclusion of 203 proteins . On the p < 0.001)  had a better ability to predict the OS of EC patients. Therefore, the impact of integrating all the omics and histopathology image features in optimizing the results was assessed. In the test set, the AUC of OS at 1-year, 3-year, and 5-year was elevated to 0.866, 0.8969, and 0.856, respectively . Cox reg< 0.001) . Additio< 0.001) .Herein, the molecular subtypes, molecular mutations, and the prognosis of EC patients were predicted with HIF data, genomics data, transcription data, and proteomics data by applying image-processing and data analysis pipelines to extract HIF from histopathological images. Thereafter, molecular features were predicted with machine learning. HIF was subsequently used to predict the survival outcomes in EC patients. However, the predictive results from models using single-omics features or HIF were mediocre and far from ideal. Therefore, HIF and multi-omics information were integrated for patient survival prediction, with the expectation of superior overall performance. The integrated model was constructed to demonstrate that histomolecular integration could boost predictive performance. In other studies, several researchers predicted the therapeutic targets and different types of molecular mutations and features with multi-omics data . MoreoveMachine-learning models were established to predict CTNNB1, PIK3CA, PIK3R1, and PTEN mutations in EC patients with HIF. EC can be classified into several histological subtypes, which could be used to guide treatment decisions and determine the prognosis of EC patients . MeanwhiSimultaneously, the two types of EC were classified according to the four TCGA molecular subgroups of endometrial cancer . Among the TCGA groups, the MSI group stands out with a predominating role, given that it represents great biological heterogeneity. The analysis demonstrated a correlation between molecular subgroups and patient outcomes, where the POLE ultra-mutated and copy number-high subgroups were associated with superior and unsatisfactory outcomes, respectively. In contrast, the microsatellite unstable hypermutated and copy number-low subgroups were linked to an intermediate outcome . In the There is a marked difference in the prognosis of EC depending on the histological types . TherefoSince the occurrence and biological development of tumors are rather complex, multiple molecular-level data might help discover more features of tumors, which could subsequently lead to a better prognostic assessment and therapeutic intervention. This hypothesis led to the integration of different types of data in our models. Some researchers have coupled HIF with transcriptional data, resulting in significant improvement in EC survival predictions . In ordeNevertheless, this study had some limitations that cannot be overlooked. To begin, the small sample size of positive cases of genetic variation and subtype limited the predictive accuracy of our models. Secondly, some confounding factors, such as alcohol consumption, complications, and chemotherapy, were not available in the TMA dataset; hence, the validity and generalizability of the combined prognostic model remained untested. Noteworthily, the multivariable Cox analysis demonstrated that although various interfering factors were present, the multi-group model could still deliver promising outcomes. Data on other interfering elements, such as optimal chemotherapy disassembly status and chemotherapy cycles that might have been associated with prognosis, were missing in the TCGA cohorts. Thus, it might be necessary to gather more information on confounding factors prior to assessing the prognostic power of the metabolomics models. Finally, the risk score threshold was based on the median value; for better patient stratification performance, the threshold of risk score should be tested more rigorously in large-scale studies.Collectively, this study put forth the great potential to predict genetic abnormalities, transcription subtypes, and survival outcomes in EC patients using histopathological features. In addition, the multi-omics predictive model combined with imaging, genomic, transcriptomic, and proteomic features could enhance the survival prediction of EC patients and assist in the prescription of individualized medicines for EC patients. Our model is anticipated to help clinicians assess the therapeutic options and prognosis of EC patients.10.7717/peerj.15674/supp-1Supplemental Information 1735 hematoxylin and eosin (H&E)-stained histopathological images of 465 patients from The Cancer Imaging Archive (TCIA).Click here for additional data file.10.7717/peerj.15674/supp-2Supplemental Information 2The RF models were impressive in predicting common gene aberrations in EC, as they achieved relatively high AUC.Click here for additional data file.10.7717/peerj.15674/supp-3Supplemental Information 3Referring to the median value of each HIF, we split the training set into high-expression and low expression groups, and univariate Cox analyses were conducted to identify their prognostic value of OS.Click here for additional data file.10.7717/peerj.15674/supp-4Supplemental Information 4A total of 100 most significant DEGs were chosen for modeling on the training set.Click here for additional data file.10.7717/peerj.15674/supp-5Supplemental Information 5Besides transcriptomics profile, we established the prognostic models using reverse phase protein array (RPPA) data with 203 proteins included.Click here for additional data file.10.7717/peerj.15674/supp-6Supplemental Information 6Cox regression analysis and Kaplan-Meier curves showed a significant difference in survival between high-risk and low-risk patients.Click here for additional data file.10.7717/peerj.15674/supp-7Supplemental Information 7Click here for additional data file.


Chronic granulomatous disease (CGD) is a rare X-linked or autosomal recessive disorder of early childhood due to defective nicotinamide adenine dinucleotide phosphate (NADPH) oxidase enzyme in leukocytes. It increases susceptibility to infections by catalase-positive bacteria and fungi. We report a case of an 18-year-old man with CGD who presented to the hospital with septic shock due to bacteremia, pneumonia, and osteomyelitis due to multiple rare microorganisms. Despite aggressive management, he did not survive. Increasing awareness about the common infections in this rare disease, their prevention, and lifelong treatment is warranted. Chronic granulomatous disease (CGD) is a rare X-linked or autosomal recessive disorder that usually presents in early childhood between one to three years of age . It affeAn 18-year-old man presented to the Emergency Room (ER) with shortness of breath and cough of three weeks duration. He also reported low-grade fever and episodic vomiting. His past medical history was significant for CGD since early childhood, and a three-year history of pulmonary aspergillosis. Unfortunately, he was non-compliant with prophylactic levofloxacin and voriconazole. The patient’s family history was significant for CGD in his brother.On physical examination, he had a temperature of 97.6 F, blood pressure of 97/61 mmHg, pulse of 137 per minute, respiratory rate of 30 per minute, and oxygen saturation of 82% on room air. He was in respiratory distress with diffuse bilateral crackles on lung examination. Despite initial resuscitation with fluids and oxygen, his hemodynamic instability escalated to require emergent intubation, initiation of mechanical ventilation, and vasopressors within a short time after the presentation. Laboratory results revealed leukocytosis, elevated transaminases, and acute renal failure -D-Glucan were positive  or Nitroblue Tetrazolium (NBT) test is performed to diagnose CGD. Following positive results, genetic testing is performed to determine the type of CGD: X-linked or autosomal recessive . LifelonThe patient in the present case was non-compliant with the antimicrobial prophylaxis for about one year despite having a past history of pulmonary aspergillosis. This drastically placed him at extreme risk for recurrent infections. Also, there was a significant delay in seeking medical attention. Despite aggressive resuscitation and the institution of broad-spectrum antibiotics and antifungals, an untoward outcome could not be averted.This case provides a classic clinical presentation of a rare clinical entity. The patient was found to have infections with two catalase-positive organisms: Burkholderia and Aspergillus. His imaging also revealed bilateral diffuse granulomas classically seen in pulmonary aspergillosis. Pneumonia and osteomyelitis due to such rare organisms leading to septic shock were unique to this case. Although rare, this case highlights the importance of knowledge of the infections CGD patients are susceptible to. Increasing life expectancy among these patients means more patients with CGD present with infectious manifestations in adulthood. Hence, knowledge about CGD, early diagnosis, and aggressive management of infections are essential. Life-long prophylaxis with antimicrobials reduces the rate of severe infections and remains the cornerstone of CGD management.