Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity

IntroductionThe success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance.MethodsWe report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls.ResultsIn contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients.DiscussionThese features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges

A clinical evaluation of an ex vivo organ culture system to predict patient response to cancer therapy

IntroductionEx vivo organ cultures (EVOC) were recently optimized to sustain cancer tissue for 5 days with its complete microenvironment. We examined the ability of an EVOC platform to predict patient response to cancer therapy.MethodsA multicenter, prospective, single-arm observational trial. Samples were obtained from patients with newly diagnosed bladder cancer who underwent transurethral resection of bladder tumor and from core needle biopsies of patients with metastatic cancer. The tumors were cut into 250 μM slices and cultured within 24 h, then incubated for 96 h with vehicle or intended to treat drug. The cultures were then fixed and stained to analyze their morphology and cell viability. Each EVOC was given a score based on cell viability, level of damage, and Ki67 proliferation, and the scores were correlated with the patients’ clinical response assessed by pathology or Response Evaluation Criteria in Solid Tumors (RECIST).ResultsThe cancer tissue and microenvironment, including endothelial and immune cells, were preserved at high viability with continued cell division for 5 days, demonstrating active cell signaling dynamics. A total of 34 cancer samples were tested by the platform and were correlated with clinical results. A higher EVOC score was correlated with better clinical response. The EVOC system showed a predictive specificity of 77.7% (7/9, 95% CI 0.4–0.97) and a sensitivity of 96% (24/25, 95% CI 0.80–0.99).ConclusionEVOC cultured for 5 days showed high sensitivity and specificity for predicting clinical response to therapy among patients with muscle-invasive bladder cancer and other solid tumors

Dry matter partitioning coefficient,water budget and evapotranspiration data observed in drip irrigated rice cultivation

Dry matter partitioning coefficient (PC) of aerobic rice (Conventional) compared to drip irrigation with aerobic rice treatments. Crop evapotranspiration calculated for the cropping period. Total Water Applied (TWA: mm), Irrigated Water (IW: mm) and Effective Rainfall (ER: mm) of aerobic rice cultivated under drip and conventional practice