Significance: Fifty percent of diffuse large B cell lymphoma (DLBCL) evade immune-surveillance via somatic genetic lesions abrogating the expression of the class I major histocompatibility complex (MHC-I) complex on the cell surface, thus preventing the presentation of tumor neoantigens to the immune system. The results herein significantly extend these findings by showing that an additional 40% of DLBCL cases, despite expressing MHC-I, carry monoallelic HLA-I genetic alterations that limit the repertoire of neoantigens for presentation to immune cells. Both MHC-I ^NEG and MHC-I ^POS /monoallelically disrupted cases have significantly higher mutational load. Notably, homozygosis of HLA-I loci is significantly and preferentially enriched in the germline of DLBCL patients, suggesting a stepwise process by which limited neoantigen presentation is selected during DLBCL development.

Background: At the dawn of the pandemic, severe forms of COVID-19 were often complicated by thromboembolisms. However, routine laboratory tests cannot be used to predict thromboembolic events. The objective of this study was to investigate the potential value of the thrombin generation test (TGT) in predicting hypercoagulability and thrombotic risk in the aforementioned set of patients. Methods: The study panel comprised 52 patients divided into two groups (26 COVID-19 positive and 26 COVID-19 negative); COVID-19-positive patients were further grouped in “severe” (n = 11) and “non-severe” (n = 15) categories based on clinical criteria. The routine blood tests and TGT of these patients were retrospectively analyzed. Results: All 26 COVID-19-positive patients showed decreased lymphocyte, monocyte and basophil counts and increased lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and alanine transaminase (ALT) compared with control patients. Conversely, we did not observe statistically significant differences between severe and non-severe patients despite anecdotal variations in the distribution patterns. TGT without thrombomodulin (TM) addition showed statistically significant differences in the thrombin peak heights between COVID-19-positive and negative patients. After addition of TM, peak height, Endogenous Thrombin Potential (ETP) and velocity index were increased in all COVID-19-positive patients while the percentage of inhibition of ETP was reduced. These trends correlated with the severity of disease, showing a greater increase in peak height, ETP, velocity index and a drastic reduction in the percentage of ETP inhibition in more severely affected patients. Conclusions: Our data suggest that all COVID-19 patients harbor a hypercoagulable TGT profile and that this is further pronounced in severely affected patients.

Fast, accurate, and affordable bacterial identification methods are paramount for the timely treatment of infections, especially in resource‐limited settings (RLS). However, today, only 1.3% of the sub‐Saharan African diagnostic laboratories are performing clinical bacteriology. To improve this, diagnostic tools for RLS should prioritize simplicity, affordability, and ease of maintenance, as opposed to the costly equipment utilized for bacterial identification in high‐income countries, such as matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS). In this work, we present a new high‐throughput approach based on a simple wide‐field (864 mm²) lensless imaging system allowing for the acquisition of a large portion of a Petri dish coupled with a supervised deep learning algorithm for identification at the bacterial colony scale. This wide‐field imaging system is particularly well suited to RLS since it includes neither moving mechanical parts nor optics. We validated this approach through the acquisition and the subsequent analysis of a dataset comprising 252 clinical isolates from five species, encompassing some of the most prevalent pathogens. The resulting optical morphotypes exhibited intra‐ and interspecies variability, a scenario considerably more akin to real‐world clinical practice than the one achievable by solely concentrating on reference strains. Despite this variability, high identification performance was achieved with a correct species identification rate of 91.7%. These results open up some new prospects for identification in RLS. We released both the acquired dataset and the trained identification algorithm in publicly available repositories.