Correlates of disease severity in bluetongue as a model of acute arbovirus infection.

Most viral diseases display a variable clinical outcome due to differences in virus strain virulence and/or individual host susceptibility to infection. Understanding the biological mechanisms differentiating a viral infection displaying severe clinical manifestations from its milder forms can provide the intellectual framework toward therapies and early prognostic markers. This is especially true in arbovirus infections, where most clinical cases are present as mild febrile illness. Here, we used a naturally occurring vector-borne viral disease of ruminants, bluetongue, as an experimental system to uncover the fundamental mechanisms of virus-host interactions resulting in distinct clinical outcomes. As with most viral diseases, clinical symptoms in bluetongue can vary dramatically. We reproduced experimentally distinct clinical forms of bluetongue infection in sheep using three bluetongue virus (BTV) strains (BTV-1IT2006, BTV-1IT2013 and BTV-8FRA2017). Infected animals displayed clinical signs varying from clinically unapparent, to mild and severe disease. We collected and integrated clinical, haematological, virological, and histopathological data resulting in the analyses of 332 individual parameters from each infected and uninfected control animal. We subsequently used machine learning to select the key viral and host processes associated with disease pathogenesis. We identified and experimentally validated five different fundamental processes affecting the severity of bluetongue: (i) virus load and replication in target organs, (ii) modulation of the host type-I IFN response, (iii) pro-inflammatory responses, (iv) vascular damage, and (v) immunosuppression. Overall, we showed that an agnostic machine learning approach can be used to prioritise the different pathogenetic mechanisms affecting the disease outcome of an arbovirus infection.

Effects of polystyrene microspheres on the swimming behavior and metabolism of grass carp (Ctenopharyngodon idella).

Microplastics (MPs) are a heterogeneous class of pollutants fouling aquatic environments and they are hazardous to aquatic organisms. This study investigated the size-dependent effects of polystyrene microspheres (PSMPs) on the swimming ability, metabolism, and oxidative stress of juvenile grass carp (Ctenopharyngodon idella). Test fish were exposed to four sizes of PSMPs (0.07, 0.5, 5, and 20-µm), and swimming ability was tested after different exposure times (2, 7, and 15 days). To measure the effect on swimming ability, critical swimming speed (Ucrit) was determined, and to assess metabolic effects, oxygen consumption (MO2), routine metabolic rate (RMR), maximum oxygen consumption (MMR), and excess post-exercise oxygen consumption (EPOC) were determined. To assess the effects on oxidative stress, the activities of two antioxidant enzymes, superoxide dismutase (SOD) and catalase (CAT) were determined in the liver and gills of test fish. After exposure to 20 µm PSMPs, there was a significant drop in Ucrit compared to the control group (P<0.05), with decreases of 22 % on Day 2 and Day 7, and 21 % on Day 15. The RMR and MMR increased significantly (P<0.05), the RMR by 23.9 % on Day 2 and the MMR by 17.2 % on Day 2 and on Day 15, 44.7 % and 20.0 % respectively. The EPOC decreased with exposure time, by 31 % (0.07-µm), 45 %-(0.5-µm), 49 % (5-µm), and 57 % (20-µm) after 15 days. Exposure to the larger PSMPs increased CAT and SOD activity more than the smaller PSMPs and the increases began with SOD activity in the gills. The larger PSMPs were consistently more harmful to juvenile grass carp than the smaller PSMPs. Our results clearly show that PSMPs have detrimental effects on juvenile grass carp and provide additional scientific evidence that environmental monitoring and regulation of microplastic pollution is necessary.

Impact of prior cancer history on survival in brain malignancy: A propensity score-adjusted, population-based study.

BACKGROUND: Individuals with a Prior Cancer History (PCH) are often excluded from clinical trials. However, a growing body of evidence suggests that prior cancer history does not present adverse outcomes on cancer patients. The evidence on the survival of brain cancer patients in this regard remains widely unknown. METHODS: We conducted a retrospective cohort study to estimate the prevalence and impact of prior cancer on survival of patients diagnosed with brain cancer. Data of patients who were diagnosed with brain cancer as their first or second primary malignancy between 2000 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity Score Matching (PSM) was used to ensure comparable baseline characteristics among the patients. Survival analysis was conducted using the Kaplan-Meier method, as well as multivariate Cox proportional hazard and multivariate competing risk models. RESULTS: Out of 42 726 patients, 1189 (2.78%) had PCH. Genitourinary (40.4%), Breast (13.6%), Hematologic and Lymphatic (11.4%), and Gastrointestinal malignancies (11.3%) were the most common types of prior cancer. PCH served as a significant risk factor for Overall Survival (OS) (Adjusted Hazard Ratio [AHR] 1.26; 95% CI [1.15-1.39]; p < .001) but did not have a statistically significant impact on Brain Cancer-Specific Survival (BCSS) (AHR 0.97; 95% CI [0.88-1.07]; p = .54). Glioblastoma exhibited the most substantial and statistically significant impact on survival as compared to other histological types. Of all the organs systems, only prior Gastrointestinal and Hematologic and Lymphatic malignancies had a statistically significant impact on OS of patients. CONCLUSION: Our findings indicate that PCH does not exert a substantial impact on the survival of brain cancer patients, except in cases involving gastrointestinal or hematologic and lymphatic PCH, or when the brain cancer is glioblastoma.