Primary effusion lymphoma is a rare distinct large B-cell neoplasm that is associated with Kaposi’s sarcoma–associated herpesvirus (KSHV) infection. Over recent years, 9 KSHV-positive/Epstein-Barr virus (EBV)-negative PEL cell lines have been established. Tumor cells were collected from the pleural effusion of a 49-year-old male with AIDS. Cells were grown in RPMI1640 culture medium supplemented with 10 % fetus bovine serum. Single cell cloning was performed successfully by a limiting dilution method in a 96-well plate. The cell line obtained was designated SPEL. SPEL cells showed gourd-shaped morphology with a polarized nucleus, expressing CD38, CD138, and Blimp-1, but not B cell markers such as CD19 and CD20. Polymerase chain reaction analysis revealed that SPEL cells were positive for KSHV but negative for EBV. Tetradecanoylphorbol acetate induced expression of KSHV lytic proteins and the production of KSHV particles in SPEL cells. Subcutaneous inoculation of SPEL cells into severe combined immunodeficiency mice resulted in the formation of solid tumors. Next-generation sequencing revealed the 138 kbp genome sequence of KSHV in SPEL cells. Suberic bishydroxamate, a histone deacetylase inhibitor, induced the expression of KSHV-encoded lytic proteins and cell death in SPEL cells. A new KSHV-positive and EBV-negative PEL cell line, SPEL was established. This cell line may contribute to furthering our understanding of the pathogenesis of PEL and KSHV infection.

Background/Objectives: Eosinophilic myocarditis (EM) is a rare, life-threatening inflammatory cardiomyopathy driven by eosinophil cytotoxicity and extracellular trap formation. Interleukin-5 (IL-5) inhibition may disrupt this pathogenic cascade. We reviewed contemporary evidence on IL-5 blockade in EM and contextualized it with an illustrative case. Methods: We searched PubMed through May 2025 for reports of EM treated with mepolizumab or benralizumab. Inclusion criteria were consistent with prior cohorts: acute cardiac symptoms with biomarker elevation plus abnormalities on transthoracic echocardiography and/or cardiac magnetic resonance imaging (CMR), along with documented IL-5-targeted therapy. We extracted clinical, imaging, biopsy, treatment-timing, and outcome data and included one institutional case. Results: Twenty-one episodes were analyzed (median age, 45 years; 10 men). Underlying conditions included eosinophilic granulomatosis with polyangiitis (10 cases; 48%), hypereosinophilic syndrome (5 cases; 24%), drug reaction with eosinophilia and systemic symptoms (DRESS, 3 cases; 14%), and eosinophilic asthma (3 cases; 14%). Treatments involved mepolizumab in 17 cases (81%) and benralizumab in 4 (19%); 4 patients received “early-start” therapy within 14 days of EM diagnosis. Among the 11 episodes with reported left ventricular ejection fraction (LVEF) at baseline and follow-up, the median baseline LVEF was 40% (range, 30–62), with 10 of 11 (91%) <50%. On follow-up, all 11 patients improved: 4 normalized (≥50%) and 7 improved to 40–49%. CMR (n = 18) demonstrated late gadolinium enhancement in 14 cases (78%), edema in 9 (50%), and intracardiac thrombus in 4 (22%). Endomyocardial biopsy confirmed eosinophilic infiltration in 13 of 15 cases (87%). Outcomes included one death (fulminant DRESS), one recovery following veno-arterial extracorporeal membrane oxygenation, and one successful heart transplantation. Illustrative case: A 24-year-old man on a steroid taper received mepolizumab 300 mg on Day 4. His LVEF improved from 47% to 59% by Day 15, accompanied by biomarker decline and successful steroid tapering. Conclusions: Across published cases and our institutional experience, IL-5–targeted therapy appears safe, steroid-sparing, and associated with rapid ventricular recovery, particularly when initiated early. Although limited, these findings support the need for prospective trials to define the optimal agent, dosing, timing, and integration with standard immunosuppression and anticoagulation.

Exact comprehension of the prevalence of SARS-CoV-2 infection is essential for the preventive measures. In the clinical settings, however, patients infected with SARS-CoV-2 may not be fully detected by PCR. In the long-term prevalence study, cut-off of IgG assay may not be appropriate due to waning IgG titer. 24 PCR-negative subjects suspected of COVID-19 were categorized into cohorts termed “presumed COVID-19 positive” and “presumed COVID-19 negative” by chest CT images. IgG against nucleocapsid protein of SARS-CoV-2 (IgG (N)) and IgG against receptor biding domain of SARS-CoV-2 (IgG (RBD)) were measured in sera of the subjects and the concordance with the cohort categorization was assessed by receiver operating characteristics (ROC) analyses. Area under the curves (AUC's) by the ROC analyses with the 24 subjects were 0.982 with IgG (N) and 0.854 with IgG (RBD). Even when we excluded the subjects whose initial PCR was performed after five days from symptom onset, the AUC's were 0.967 with IgG (N) and 0.800 with IgG (RBD). The ROC analysis indicated 0.2 S/C as the optimum cut-off forIgG (N). Both IgG (N) and IgG (RBD) titers were significantly elevated in subjects whose PCR never showed positive but suggestive of SARS-CoV-2 infection, which indicated the necessity of serological tests in complementing the shortcomings of PCR. For a long-term prevalence study, a cut-off lower than the one used in the ongoing infection phase (e.g. 0.2 S/C vs. 1.4 S/C) was indicated to be more appropriate for IgG (N).

Background: To control COVID-19 pandemic is of critical importance to the global public health. To capture the prevalence in an accurate and timely manner and to understand the mode of nosocomial infection are essential for its preventive measure. Methods: We recruited 685 healthcare workers (HCW’s) at Tokyo Shinagawa Hospital prior to the vaccination with COVID-19 vaccine. Sera of the subjects were tested by assays for the titer of IgG against S protein’s receptor binding domain (IgG (RBD)) or IgG against nucleocapsid protein (IgG (N)) of SARS-CoV-2. Together with PCR data, the positive rates by these methods were evaluated. Results: Overall positive rates among HCW’s by PCR, IgG (RBD), IgG (N) with a cut-off of 1.4 S/C (IgG (N)_1.4), and IgG (N) with a cut-off of 0.2 S/C (IgG (N)_0.2) were 3.5%, 9.5%, 6.1%, and 27.7%, respectively. Positive rates of HCW’s working in COVID-19 ward were significantly higher than those of HCW’s working in non-COVID-19 ward by all the four methods. Concordances of IgG (RBD), IgG (N)_1.4, and IgG (N)_0.2 against PCR were 97.1%, 71.4%, and 88.6%, respectively. By subtracting the positive rates of PCR from that of IgG (RBD), the rate of overall silent infection and that of HCW’s in COVID-19 ward were estimated to be 6.0% and 21.1%, respectively. Conclusions: For the prevention of nosocomial infection of SARS-CoV-2, identification of silent infection is essential. For the detection of ongoing infection, periodical screening with IgG (RBD) in addition to PCR would be an effective measure. For the surveillance of morbidity in the population, on the other hand, IgG (N)_0.2 could be the most reliable indicator among the three serological tests.

Background: Patients’ clinical status often evolves rapidly after an initial diagnosis, with each patient exhibiting a distinct disease trajectory. As a result, static risk scores fall short in supporting timely interventions—an issue highlighted by COVID-19, where deaths have stemmed from heterogeneous pathways such as pneumonia, multiorgan failure, or exacerbation of preexisting conditions. Objective: This study aims to propose a dynamic prognostic risk assessment framework based on longitudinal data collected during hospitalization, using COVID-19 as an example. Our aim was to develop and validate an interpretable framework that (1) screens prognosis at admission and (2) dynamically updates mortality risk throughout hospitalization, thereby providing clinicians with early, explainable warnings while minimizing additional cognitive load. Methods: In this retrospective study, we extracted electronic medical records of 382 COVID-19 cases treated at Tokyo Shinagawa Hospital between January 27 and September 30, 2020. At admission, gradient boosting decision trees (Light Gradient Boosting Machine) were used to predict the maximum clinical deterioration, including death, based on data available at initial diagnosis. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). For in-hospital monitoring, random survival forests (RSF) were trained on a longitudinal dataset that combined static demographic characteristics with serially measured vital signs and laboratory results. The model dynamically assessed daily mortality risk by calculating a 7-day cumulative hazard function, with risk scores recalculated each day during hospitalization. RSF accuracy was evaluated in an independent one-third test set using the concordance index (C-index), an integrated Brier score (1-50 days), and mean time-dependent AUC. SurvSHAP(t), an extension of Shapley Additive Explanations, was applied to provide time-dependent explanations of each variable’s contribution to the prediction. Results: The prediction at initial diagnosis showed good agreement with the actual severity outcomes (AUC of 0.717 for predicting hospitalization/severity ≥2; 0.878 for severity ≥3; 0.951 for severity ≥4; 0.952 for severity ≥5; and 0.970 for death/severity=6), although some cases exhibited discrepancies between the predicted and actual prognoses. The dynamic mortality risk assessment during hospitalization using the RSF achieved a test-set C-index of 0.941, an integrated Brier score of 0.315, and a mean time-dependent AUC of 0.936. This dynamic assessment was able to distinguish between dead and surviving patients as early as 1‐2 weeks before the outcome. Early in hospitalization, C-reactive protein was an important risk factor for mortality; during the middle period, peripheral oxygen saturation (SpO₂) gained importance; and immediately before death, platelets and β-D-glucan were the primary risk factors. Conclusions: Integrating static admission triage with daily, explainable RSF predictions enables early identification of patients with COVID-19 at high risk of deterioration. By surfacing phase-specific, actionable predictors, the framework supports timely interventions and more efficient resource allocation. Prospective, multicenter studies are warranted to validate its generalizability and clinical impact.