Cytomegalovirus gastritis as a rare adverse event during combined ipilimumab and nivolumab in a patient with melanoma.

Immunotherapy has improved survival outcomes of patients with advanced melanoma. Lower gastrointestinal tract immune-related adverse events (irAEs) are common during treatment; however, gastritis is not frequently observed. Herein, we report a case of severe cytomegalovirus (CMV)-related gastritis in a patient treated with ipilimumab and nivolumab for metastatic melanoma. This report presents a 60-year-old woman with stage IV BRAF wild-type melanoma. After the second course of ipilimumab-nivolumab, the patient reported epigastric discomfort after meals, anorexia, and subsequent nausea, vomiting, epigastric pain, and weight loss. Disease staging with PET/CT scan showed very good partial response and diffuse gastroduodenitis. The patient underwent esophagogastroduodenoscopy, showing severe esophageal candidiasis and diffuse hemorrhagic, edematous, and ulcerative mucosa in the whole gastric wall. Biopsies of the gastric wall were obtained. Before receipt of the final pathology report, the patient was empirically started on corticosteroids based on the clinical suspicion of immune-related gastritis, without improvement of symptoms. The hematoxylin-eosin staining demonstrated active gastritis with diffuse nuclear cytopathic viral inclusions in epithelial and interstitial cells; CMV infection was confirmed with immunohistochemical staining. The patient started ganciclovir and fluconazole, with rapid improvement of symptoms. This case presents a rare instance of CMV gastritis in a patient receiving combined anti-PD1 and anti-CTLA4 , in the absence of immune-suppression to manage an irAE. In the case of suggestive symptoms of irAEs, a high index of clinical suspicion is required to rule out concomitant or isolated infective disease. Guidelines for prophylaxis and treatment of these patients are needed, to optimize treatment results.

Computational prediction of diagnosis and feature selection on mesothelioma patient health records.

BACKGROUND: Mesothelioma is a lung cancer that kills thousands of people worldwide annually, especially those with exposure to asbestos. Diagnosis of mesothelioma in patients often requires time-consuming imaging techniques and biopsies. Machine learning can provide for a more effective, cheaper, and faster patient diagnosis and feature selection from clinical data in patient records. METHODS AND FINDINGS: We analyzed a dataset of health records of 324 patients having mesothelioma symptoms from Turkey. The patients had prior asbestos exposure and displayed symptoms consistent with mesothelioma. We compared probabilistic neural network, perceptron-based neural network, random forest, one rule, and decision tree classifiers to predict diagnosis of the patient records. We measured classifiers' performance through standard confusion matrix scores such as Matthews correlation coefficient (MCC). Random forest outperformed all models tried, obtaining MCC = +0.37 on the complete imbalanced dataset and MCC = +0.64 on the under-sampled balanced dataset. We then employed random forest feature selection to identify the two most relevant dataset traits associated with mesothelioma: lung side and platelet count. These two risk factors resulted so predictive, that decision tree focusing on them achieved the second top accuracy on the complete dataset diagnosis prediction (MCC = +0.28), outperforming all other methods and even decision tree itself applied to all features. CONCLUSIONS: Our results show that machine learning can predict diagnoses of patients having mesothelioma symptoms with high accuracy, sensitivity, and specificity, in few minutes. Additionally, random forest can efficiently select the most important features of this clinical dataset (lung side and platelet count) in few seconds. The importance of pleural plaques in lung sides and blood platelets in mesothelioma diagnosis indicates that physicians should focus on these two features when reading records of patients with mesothelioma symptoms. Moreover, doctors can exploit our machinery to predict patient diagnosis when only lung side and platelet data are available.

Strongyloides stercoralis Hyperinfection in an HIV-Infected Patient Successfully Treated with Subcutaneous Ivermectin.

A 39-year-old Ethiopian HIV-positive man with peripheral T-cell lymphoma developed Strongyloides stercoralis hyperinfection. The patient was initially treated with oral ivermectin for three weeks without response, most likely due to malabsorption because of concomitant paralytic ileus. Given the persistence of larvae in the body fluids, the worsening respiratory status and clinical malabsorption, veterinary parenteral formulation of ivermectin was administered. The very high plasma concentration of ivermectin achieved in the patient after parenteral administration led to a rapid improvement in his clinical condition and rapid disappearance of the parasite from biological samples, without any adverse reaction.

PPP1R35 is a novel centrosomal protein that regulates centriole length in concert with the microcephaly protein RTTN.

Centrosome structure, function, and number are finely regulated at the cellular level to ensure normal mammalian development. Here, we characterize PPP1R35 as a novel bona fide centrosomal protein and demonstrate that it is critical for centriole elongation. Using quantitative super-resolution microscopy mapping and live-cell imaging we show that PPP1R35 is a resident centrosomal protein located in the proximal lumen above the cartwheel, a region of the centriole that has eluded detailed characterization. Loss of PPP1R35 function results in decreased centrosome number and shortened centrioles that lack centriolar distal and microtubule wall associated proteins required for centriole elongation. We further demonstrate that PPP1R35 acts downstream of, and forms a complex with, RTTN, a microcephaly protein required for distal centriole elongation. Altogether, our study identifies a novel step in the centriole elongation pathway centered on PPP1R35 and elucidates downstream partners of the microcephaly protein RTTN.

Presence of multiple genotypes in subjects with HPV-16 infection is highly associated with anal squamous intraepithelial lesions in HIV-1 infected males.

OBJECTIVES: The aim of the study was to determine the prevalence of abnormal cytological findings, high risk (HR)-HPV genotypes and to identify factors associated with an abnormal cytological findings in a cohort of HIV-infected males. PATIENTS AND METHODS: Retrospective observational study on HIV-infected male patients who performed screening in the absence of clinical symptoms. Cytological abnormalities were classified as atypical squamous cells of undetermined significance (ASC-US), low-grade(LSIL) or high high-grade squamous intraepithelial lesion (HSIL). Logistic regression models were used to identify predictors of having LSIL/HSIL. RESULTS: Among 875 pts, abnormal cytology findings were observed in 254 (29%, 95% CI: 26.1%-32.1%) subjects: 142 (16%) had LSIL and 49 (6%) HSIL. Overall, 581 (66%, 95%CI: 63.2%-69.5%) subjects had ≥1 HR-HPV type and 269 (31%) had ≥2 HR HPV types. Multivariate logistic regression showed that subjects with multiple HR-HPV genotypes (OR = 1.351, 95%CI: 1.005-2.111) and with HPV-16 type (OR = 2.032, 95%CI: 1.313-3.146) were more likely to have LSIL/HSIL in addition to a lower CD4+/CD8+ ratio, a previous diagnosis of syphilis and a positive viral load. In another multivariate model, the presence of multiple HPV types in subjects with HPV-16 type was associated with the highest adjusted OR of having a LSIL/HSIL (OR = 2.598, 95%CI: 1.460-4.624). CONCLUSIONS: In HIV-infected men, the prevalence of abnormal cytological findings was of 29% and of HR-HPV was 66%. The concomitant presence of HPV-16 and multiple HR genotypes was associated with an increased risk of abnormal cytological findings. These data highlight the importance of screening multiple HPV genotypes in HIV-infected patients.