Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy.

BACKGROUND: Acute kidney injury (AKI) is a critical complication of immune checkpoint inhibitor therapy. Since the etiology of AKI in patients undergoing cancer therapy varies, clarifying underlying causes in individual cases is critical for optimal cancer treatment. Although it is essential to individually analyze immune checkpoint inhibitor-treated patients for underlying pathologies for each AKI episode, these analyses have not been realized. Herein, we aimed to individually clarify the underlying causes of AKI in immune checkpoint inhibitor-treated patients using a new clustering approach with Shapley Additive exPlanations (SHAP). METHODS: We developed a gradient-boosting decision tree-based machine learning model continuously predicting AKI within 7 days, using the medical records of 616 immune checkpoint inhibitor-treated patients. The temporal changes in individual predictive reasoning in AKI prediction models represented the key features contributing to each AKI prediction and clustered AKI patients based on the features with high predictive contribution quantified in time series by SHAP. We searched for common clinical backgrounds of AKI patients in each cluster, compared with annotation by three nephrologists. RESULTS: One hundred and twelve patients (18.2%) had at least one AKI episode. They were clustered per the key feature, and their SHAP value patterns, and the nephrologists assessed the clusters' clinical relevance. Receiver operating characteristic analysis revealed that the area under the curve was 0.880. Patients with AKI were categorized into four clusters with significant prognostic differences (p = 0.010). The leading causes of AKI for each cluster, such as hypovolemia, drug-related, and cancer cachexia, were all clinically interpretable, which conventional approaches cannot obtain. CONCLUSION: Our results suggest that the clustering method of individual predictive reasoning in machine learning models can be applied to infer clinically critical factors for developing each episode of AKI among patients with multiple AKI risk factors, such as immune checkpoint inhibitor-treated patients.

Outcomes of thoracic endovascular aortic repair using fenestrated stent grafts in patients with thoracic aortic distal arch aneurysms.

OBJECTIVES: Thoracic endovascular aortic repair (TEVAR) for aortic arch aneurysms is challenging because of anatomical restrictions and the presence of cervical branches. Revascularization of the cervical branch is required when conventional commercial stent grafts are used. TEVAR using fenestrated stent grafts (FSG) often does not require additional procedures to revascularize cervical branches. This study aimed to evaluate the features and initial and midterm outcomes of TEVAR using fenestrated stent grafts. METHODS: From April 2007 to December 2016, 101 consecutive patients underwent TEVAR using fenestrated stent grafts for distal aortic arch aneurysms at a single centre. Technical success, complications, freedom from aneurysm-related death, secondary intervention and aneurysm progression were retrospectively investigated. RESULTS: All the patients underwent TEVAR using fenestrated stent grafts. The 30-day mortality rate was zero. Cerebral infarction, access route problems and spinal cord injury occurred in 4, 3 and 2 patients, respectively. Each type of endoleak was observed in 38 of the 101 patients during the course of the study; 20/38 patients had minor type 1 endoleaks at the time of discharge. The endoleak disappeared in 2 patients and showed no significant change in 8 patients; however, the aneurysm expanded over time in 10 patients. Additional treatment was performed in 8 of the 10 patients with type 1 endoleaks and dilatation of the aneurysm. The rate of freedom from aneurysm-related death during the observation period was 98%. CONCLUSIONS: TEVAR with FSG is a simple procedure, with few complications. Additional treatment has been observed to reduce aneurysm-related deaths, even in patients with endoleaks and enlarged aneurysms. Based on this study, the outcomes of endovascular repair of aortic arch aneurysms using a fenestrated stent graft seem acceptable.

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-ß signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.

Preemptive Intravenous Human Immunoglobulin G Suppresses BK Polyomavirus Replication and Spread of Infection In Vitro.

BK polyomavirus (BKPyV) infection causes various diseases in immunocompromised patients. Cells from human lung and kidney were infected with BKPyV and treated with commercially available intravenous immunoglobulin G (IVIG). Its effects on BKPyV replication and spread of infection were investigated, focusing on administration timing. IVIG treatment 3 hours after infection suppressed BKPyV replication assessed by real-time PCR and expression of the viral capsid protein 1 and large T-antigen. IVIG effectively reduced the number of BKPyV-infected cells 2 weeks after infection in an antibody titer-dependent manner. Virus release in the culture supernatants was not influenced by IVIG treatment 6-80 hours and 3-9 days after infection. Collectively, IVIG did not affect viral release from infected cells but inhibited the spread of infection by neutralizing the released virus and blocking the new infected cell formation, indicating greater efficacy in early localized infection. BKPyV replication resumed in IVIG-treated cultures at 7 days after IVIG removal. Early prophylactic administration of IVIG is expected to reduce the growth and spread of BKPyV infection, resulting in the reduction of infected cell lesions and prevention of BKPyV-associated diseases.

Exploring the mechanism of BK polyomavirus-associated nephropathy through consensus gene network approach.

BK polyomavirus-associated nephropathy occurs in kidney transplant recipients under immunosuppressive treatment. BK polyomavirus is implicated in cancer development and invasion, and case reports of renal cell carcinoma and urothelial carcinoma possibly associated with BK polyomavirus has been reported. Further, it has been suggested that the immune responses of KT-related diseases could play a role in the pathogenesis and progression of renal cell carcinoma. Thus, we thought to examine the relationship between BK polyomavirus-associated nephropathy and renal cell carcinoma in terms of gene expression. To identify the common and specific immune responses involved in kidney transplantation-related diseases with a specific focus on BK polyomavirus-associated nephropathy, we performed consensus weighted gene co-expression network analysis on gene profile datasets of renal biopsy samples from different institutions. After the identification of gene modules and validation of the obtained network by immunohistochemistry of the marker across kidney transplantation-related diseases, the relationship between prognosis of renal cell carcinoma and modules was assessed. We included the data from 248 patients and identified the 14 gene clusters across the datasets. We revealed that one cluster related to the translation regulating process and DNA damage response was specifically upregulated in BK polyomavirus-associated nephropathy. There was a significant association between the expression value of hub genes of the identified cluster including those related to cGAS-STING pathway and DNA damage response, and the prognosis of renal cell carcinoma. The study suggested the potential link between kidney transplantation-related diseases, especially specific transcriptomic signature of BK polyomavirus associated nephropathy and renal cell carcinoma.

Increased abundance of Ruminococcus gnavus in gut microbiota is associated with moyamoya disease and non-moyamoya intracranial large artery disease.

Moyamoya disease (MMD) is a rare cerebrovascular disease endemic in East Asia. The p.R4810K mutation in RNF213 gene confers a risk of MMD, but other factors remain largely unknown. We tested the association of gut microbiota with MMD. Fecal samples were collected from 27 patients with MMD, 7 patients with non-moyamoya intracranial large artery disease (ICAD) and 15 control individuals with other disorders, and 16S rRNA were sequenced. Although there was no difference in alpha diversity or beta diversity between patients with MMD and controls, the cladogram showed Streptococcaceae was enriched in patient samples. The relative abundance analysis demonstrated that 23 species were differentially abundant between patients with MMD and controls. Among them, increased abundance of Ruminococcus gnavus > 0.003 and decreased abundance of Roseburia inulinivorans < 0.002 were associated with higher risks of MMD (odds ratio 9.6, P = 0.0024; odds ratio 11.1, P = 0.0051). Also, Ruminococcus gnavus was more abundant and Roseburia inulinivorans was less abundant in patients with ICAD than controls (P = 0.046, P = 0.012). The relative abundance of Ruminococcus gnavus or Roseburia inulinivorans was not different between the p.R4810K mutant and wildtype. Our data demonstrated that gut microbiota was associated with both MMD and ICAD.

Everolimus reduces BK polyomavirus infection by suppressing its replication and spread of infection.

BK polyomavirus-associated nephropathy is one of serious complications in transplant recipients. Everolimus-a mammalian target of rapamycin inhibitor-has been shown to reduce the incidence of BK polyomavirus infection in transplant recipients. In this study, the effects of everolimus were examined on viral replication and the spread of infection in BK polyomavirus-infected cultures. BK polyomavirus replicated in renal and pulmonary cells, contrary to that in hepatocytes, and spread as diffusely scattered patterns of infected cells, unlike plaque formation through the cell-to-cell mode. BK polyomavirus is stable to heat up to 65 °C with a particle per infectivity ratio of 5000, and the replication cycle was for approximately 34 h. Everolimus administration remarkably reduced the viral replication to 20% in cells treated with 0.1-10 ng/mL, the concentration at which everolimus reached the serum of transplant recipients. In addition, it reduced the amount of viral capsid protein 1 at 5 ng/mL without reducing the ratio of viral capsid protein 1 versus ß-actin, and it also retained the pattern of viral capsid protein 1 localization in the nuclei. Everolimus suppressed the number of infected cells to 32.8% during a 14-day treatment, indicating the reduction of BK polyomavirus-infected cell mass to 18.8% of untreated cultures by modifying cellular functions. The reduction in the total number of BK polyomavirus infected cells by everolimus indicates that everolimus alleviates BK polyomavirus infection, including nephropathy in transplant recipients.

CBNplot: Bayesian network plots for enrichment analysis.

SUMMARY: When investigating gene expression profiles, determining important directed edges between genes can provide valuable insights in addition to identifying differentially expressed genes. In the subsequent functional enrichment analysis (EA), understanding how enriched pathways or genes in the pathway interact with one another can help infer the gene regulatory network (GRN), important for studying the underlying molecular mechanisms. However, packages for easy inference of the GRN based on EA are scarce. Here, we developed an R package, CBNplot, which infers the Bayesian network (BN) from gene expression data, explicitly utilizing EA results obtained from curated biological pathway databases. The core features include convenient wrapping for structure learning, visualization of the BN from EA results, comparison with reference networks, and reflection of gene-related information on the plot. As an example, we demonstrate the analysis of bladder cancer-related datasets using CBNplot, including probabilistic reasoning, which is a unique aspect of BN analysis. We display the transformability of results obtained from one dataset to another, the validity of the analysis as assessed using established knowledge and literature, and the possibility of facilitating knowledge discovery from gene expression datasets. AVAILABILITY AND IMPLEMENTATION: The library, documentation and web server are available at https://github.com/noriakis/CBNplot. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Acute aortic thrombosis in the ascending aorta after cisplatin-based chemotherapy for esophageal cancer: a case report.

BACKGROUND: The risk of thrombus development is considered to be increased by malignant tumors and chemotherapy. In addition, thrombosis of the ascending aorta is rare. We report a case of ascending aortic thrombectomy in a patient with esophageal cancer who developed ascending aortic thrombus after starting neoadjuvant chemotherapy, including operative findings and surgical treatment. CASE PRESENTATION: A 63-year-old man with esophageal cancer was administered chemotherapy comprising cisplatin plus 5-fluorouracil. A week after completing 1 cycle of chemotherapy, computed tomography angiography showed acute aortic thrombosis at the ascending aorta. The risk of embolization appeared high because the thrombosis was floating, so we performed emergency ascending aortic thrombectomy. The postoperative course was good and uncomplicated. A month after this surgery, the patient underwent surgery for esophageal cancer. As of 1 year after the cancer surgery, neither cancer nor thrombosis has recurred. CONCLUSION: We describe a case of acute aortic thrombosis in the ascending aorta after cisplatin-based chemotherapy, that was treated by aortic thrombectomy. The treatment strategy should depend on thrombus location and the condition of the patient, but surgical treatment should be considered where possible to achieve better prognosis.

Maximum Standardized Uptake Value on Positron Emission Tomography is Associated With More Advanced Disease and High-risk Features in Lung Adenocarcinoma.

18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) has been widely used for preoperative staging of lung adenocarcinomas. The aim of this study was to determine whether a high maximum standardized uptake value (SUVmax) could correlate with pathological characteristics in those patients. We retrospectively reviewed patients with clinical stage 0-IA lung adenocarcinoma who underwent preoperative 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography followed by curative anatomical resection. To identify more advanced disease and high-risk features, representing visceral pleural involvement, pulmonary metastasis, lymph node involvement, and lymphovascular involvement in resected surgical specimens, univariate and multivariate logistic regression analyses were performed. The optimal cutoff point for the SUVmax was determined by receiver operating characteristic analysis. In 2 groups divided according to the cutoff point, the disease-free survivals were calculated and compared using the Kaplan-Meier method and the log-rank test. More advanced disease and high-risk features were identified in 55 (18.9%) of the 291 patients. SUVmax was significantly correlated with more advanced disease and high-risk features, as did the consolidation/tumor ratio on computed tomography. Only 2 (1.2%) of the 169 patients with a SUVmax <3.20 showed more advanced disease and high-risk features, compared with 43.4% of patients with a SUVmax ≥3.20. The disease-free survival was significantly higher in patients with a SUVmax <3.20 than in those with a SUVmax ≥3.20 (P = 0.002). A high SUVmax correlates with more advanced disease and high-risk features in patients with clinical stage 0-IA lung adenocarcinoma. The SUVmax should be considered when deciding treatment strategy in early-stage lung adenocarcinoma.

[Determination of Endograft Size in Thoracic Endovascular Aortic Repair for Blunt Thoracic Aortic Injury:Report of a Case].

Although the efficacy of thoracic endovascular aortic repair( TEVAR) for blunt thoracic aortic injury (BTAI) has been reported, the determination of the proper endograft size for TEVAR in BTAI cases is yet to be established. The management of BTAI by TEVAR may not be effective if a wrong endograft size is selected, possibly leading to fatal outcomes. In this case report, a hemodynamically unstable patient with BTAI was saved by TEVAR, and the preoperative and postoperative changes in the aortic diameter were compared. In TEVAR for BTAI, the effects of hemodynamic instability should be considered and the appropriate device size should be determined based on blood pressure, pulse, and inferior vena cava diameter.

Evaluation of Kidney Histological Images Using Unsupervised Deep Learning.

INTRODUCTION: Evaluating histopathology via machine learning has gained research and clinical interest, and the performance of supervised learning tasks has been described in various areas of medicine. Unsupervised learning of histological images has the advantage of reproducibility for labeling; however, the relationship between unsupervised evaluation and clinical information remains unclear in nephrology. METHODS: We propose an unsupervised approach combining convolutional neural networks (CNNs) and a visualization algorithm to cluster the histological images and calculate the score for patients. We applied the approach to the entire images or patched images of the glomerulus of kidney biopsy samples stained with hematoxylin and eosin obtained from 68 patients with immunoglobulin A nephropathy. We assessed the relationship between the obtained scores and clinical variables of urinary occult blood, urinary protein, serum creatinine (SCr), systolic blood pressure, and age. RESULTS: The glomeruli of the patients were classified into 12 distinct classes and 10 patches. The output of the fine-tuned CNN, which we defined as the histological scores, had significant relationships with assessed clinical variables. In addition, the clustering and visualization results suggested that the defined clusters captured important findings when evaluating renal histopathology. For the score of the patch-based cluster containing crescentic glomeruli, SCr (coefficient = 0.09, P = 0.019) had a significant relationship. CONCLUSION: The proposed approach could successfully extract features that were related to the clinical variables from the kidney biopsy images along with the visualization for interpretability. The approach could aid in the quantified evaluation of renal histopathology.

Genetic Background and Clinicopathologic Features of Adult-onset Nephronophthisis.

INTRODUCTION: Recently, nephronophthisis (NPH) has been considered a monogenic cause of end-stage renal disease (ESRD) in adults. However, adult-onset NPH is difficult to accurately diagnose and has not been reported in a cohort study. In this study, we assessed the genetic background and clinicopathologic features of adult NPH. METHODS: We investigated 18 sporadic adult patients who were suspected as having NPH by renal biopsy. We analyzed 69 genes that cause hereditary cystic kidney disease and compared clinicopathologic findings between patients with and without pathogenic mutations in NPH-causing genes. RESULTS: Seven of 18 patients had pathogenic NPH-causing mutations in NPHP1, NPHP3, NPHP4, or CEP164. Compared with patients without pathogenic mutations, those with pathogenic mutations were significantly younger but did not significantly differ in the classic NPH pathologic findings, such as tubular cysts. On the other hand, the number of tubules with thick tubular basement membrane (TBM) duplication, which was defined as >10-µm thickness, was significantly higher in patients with genetically proven adult NPH than in those without pathogenic mutations. α-Smooth muscle actin (α-SMA)-positive myofibroblasts were detected inside thick TBM duplication. CONCLUSIONS: In adult patients with NPH, thick TBM duplication was the specific finding. Our analysis also suggested that older patients tended to have no pathogenic mutations, even when they were suspected to have NPH by renal biopsy. These findings could be the novel clinical clue for the diagnosis of NPH in adult patients.

Medicine at mass gatherings: current progress of preparedness of emergency medical services and disaster medical response during 2020 Tokyo Olympic and Paralympic Games from the perspective of the Academic Consortium (AC2020).

Mass gatherings are events characterized by "the concentration of people at a specific location for a specific purpose over a set period of time that have the potential to strain the planning and response resources of the host country or community." Previous reports showed that, as a result of the concentration of people in the limited area, injury and illness occurred due to several factors. The response plan should aim to provide timely medical care to the patients and to reduce the burden on emergency hospitals, and to maintain a daily emergency medical services system for residents of the local area. Although a mass gathering event will place a significant burden on the local health-care system, it can provide the opportunity for long-term benefits of public health-care and improvement of daily medical service systems after the end of the event. The next Olympic and Paralympic Games will be held in Tokyo, during which mass gatherings will occur on a daily basis in the context of the coronavirus disease (COVID-19) epidemic. The Academic Consortium on Emergency Medical Services and Disaster Medical Response Plan during the Tokyo Olympic and Paralympic Games in 2020 (AC2020) was launched 2016, consisting of 28 academic societies in Japan, it has released statements based on assessments of medical risk and publishing guidelines and manuals on its website. This paper outlines the issues and countermeasures for emergency and disaster medical care related to the holding of this big event, focusing on the activities of the academic consortium.

Classification of glomerular pathological findings using deep learning and nephrologist-AI collective intelligence approach.

BACKGROUND: Automated classification of glomerular pathological findings is potentially beneficial in establishing an efficient and objective diagnosis in renal pathology. While previous studies have verified the artificial intelligence (AI) models for the classification of global sclerosis and glomerular cell proliferation, there are several other glomerular pathological findings required for diagnosis, and the comprehensive models for the classification of these major findings have not yet been reported. Whether the cooperation between these AI models and clinicians improves diagnostic performance also remains unknown. Here, we developed AI models to classify glomerular images for major findings required for pathological diagnosis and investigated whether those models could improve the diagnostic performance of nephrologists. METHODS: We used a dataset of 283 kidney biopsy cases comprising 15,888 glomerular images that were annotated by a total of 25 nephrologists. AI models to classify seven pathological findings: global sclerosis, segmental sclerosis, endocapillary proliferation, mesangial matrix accumulation, mesangial cell proliferation, crescent, and basement membrane structural changes, were constructed using deep learning by fine-tuning of InceptionV3 convolutional neural network. Subsequently, we compared the agreement to truth labels between majority decision among nephrologists with or without the AI model as a voter. RESULTS: Our model for global sclerosis showed high performance (area under the curve: periodic acid-Schiff, 0.986; periodic acid methenamine silver, 0.983); the models for the other findings also showed performance close to those of nephrologists. By adding the AI model output to majority decision among nephrologists, out of the 14 constructed models, the results of the majority decision showed improvement in sensitivity for 10 models (four of them were statistically significant) and specificity for eight models (five significant). CONCLUSION: Our study showed a proof-of-concept for the classification of multiple glomerular findings in a comprehensive method of deep learning and suggested its potential effectiveness in improving diagnostic accuracy of clinicians.

The relationship between cigarette smoking and the tongue microbiome in an East Asian population.

Background: The oral microbiome, which consists of various habitats, has been shown to be influenced by smoking. However, differences in the tongue microbiomes of current and former smokers, as well as their resultant functional consequences, have rarely been investigated in East Asian populations. Methods: We used 16S rRNA amplicon sequencing of tongue-coating samples obtained from East Asian subjects who were current, former, or never smokers to identify differences in their tongue microbiomes and related metagenomic functions. Two sets of participants from 2016 to 2017 (n = 657 and n = 187, respectively) were analyzed separately. Results: We found significant differences between the overall microbiome compositions of current versus never smokers (p = 0.0015), but not between former versus never smokers (p = 0.43) based on the weighted UniFrac distance. Twenty-nine of 43 investigated genera showed significantly different expression levels in current versus never smokers. Neisseria and Capnocytophaga were less abundant, and Streptococcus and Megasphaera were more abundant in current smokers. Moreover, the abundances of metagenomic pathways, including those related to nitrate reduction and the tricarboxylic acid cycle, were significantly different between current and never smokers. Conclusions: The tongue microbiomes and related metagenomic pathways of current smokers differ from those of never smokers among East Asians.

Metagenomic analysis of bacterial species in tongue microbiome of current and never smokers.

Cigarette smoking affects the oral microbiome, which is related to various systemic diseases. While studies that investigated the relationship between smoking and the oral microbiome by 16S rRNA amplicon sequencing have been performed, investigations involving metagenomic sequences are rare. We investigated the bacterial species composition in the tongue microbiome, as well as single-nucleotide variant (SNV) profiles and gene content of these species, in never and current smokers by utilizing metagenomic sequences. Among 234 never smokers and 52 current smokers, beta diversity, as assessed by weighted UniFrac measure, differed between never and current smokers (pseudo-F = 8.44, R2 = 0.028, p = 0.001). Among the 26 species that had sufficient coverage, the SNV profiles of Actinomyces graevenitzii, Megasphaera micronuciformis, Rothia mucilaginosa, Veillonella dispar, and one Veillonella sp. were significantly different between never and current smokers. Analysis of gene and pathway content revealed that genes related to the lipopolysaccharide biosynthesis pathway in Veillonella dispar were present more frequently in current smokers. We found that species-level tongue microbiome differed between never and current smokers, and 5 species from never and current smokers likely harbor different strains, as suggested by the difference in SNV frequency.

Renal-limited vasculitis with elevated levels of multiple antibodies.

Renal-limited vasculitis (RLV) is a type of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis that presents with crescentic glomerulonephritis with no other organ involvement. Although several studies reported patients with crescentic glomerulonephritis who were dual positive for proteinase 3 (PR3)-ANCA and myeloperoxidase (MPO)-ANCA or ANCA and anti-glomerular basement membrane (GBM) antibody, patients positive for all three antibodies, i.e., triple-positive patients, were rarely reported. We herein report the case of a male with pauci-immune type crescentic glomerulonephritis positive for MPO-ANCA, PR3-ANCA, and anti-GBM antibody. Renal biopsy led to the definitive diagnosis of RLV with pauci-immune-type crescentic glomerulonephritis. Fluorescence immunostaining showed no linear deposition of IgG on GBM, indicating no involvement of anti-GBM associated diseases. Intensive therapy, including prednisolone, plasma exchange, and intravenous cyclophosphamide, was effective. We report the case of triple-positive patient with crescentic glomerulonephritis, who was successfully treated with glucocorticoid, plasma exchange, and cyclophosphamide, suggesting that treatment for RLV in the patient with serological triple antibodies positivity in the absence of linear IgG deposition could benefit from the combination therapy regimen for plasma exchange and primary induction of remission against microscopic polyangiitis.