The Relationship Between Parasite Infection, Body Condition, and Migration in White-Crowned Sparrows and California Towhees

Long-distance animal migration plays a large role in the spread of infectious disease, potentially causing an increase or a decrease in infection. These outcomes can be serious, as infection has the ability to induce a variety of effects on the host, all which may impact their overall health. The consequences of infection on a host can be measured using body condition. Changes to an individual’s body condition are central to the mechanisms involved in migration’s ability to both increase (ex: susceptibility) and decrease infection (ex: migratory culling). Therefore, when assessing potential migratory effects, it is important to consider relationships between infection and body condition. To determine migration’s role in infection-body condition dynamics, we studied measures of coccidia infection and body condition in a migratory species, White-crowned Sparrows (WCSPs), and controlled for migration using a non-migratory species, CA Towhees. Data was collected in Claremont, CA twice per year for each species, once after WCSP migration in the fall and once before their migration in the spring. We analyzed two data sets, one with both condition and parasite data, and one much larger data set that lacked infection data. Overall, we found significant differences in body condition across species, but only in the subset of individuals with infection data did we see significant seasonal variations and a significant interaction effect of season and species on body condition. Additionally, infection status significantly differed across species, and infected birds were found to be in greater condition than those uninfected. Future research needs to address any potential biases found in the data set with infection data, in addition to increasing sample sizes, to truly understand migration’s role in the relationships between infection and body condition

Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by random circuit perturbation.

Stem cells can precisely and robustly undergo cellular differentiation and lineage commitment, referred to as stemness. However, how the gene network underlying stemness regulation reliably specifies cell fates is not well understood. To address this question, we applied a recently developed computational method, random circuit perturbation (RACIPE), to a nine-component gene regulatory network (GRN) governing stemness, from which we identified robust gene states. Among them, four out of the five most probable gene states exhibit gene expression patterns observed in single mouse embryonic cells at 32-cell and 64-cell stages. These gene states can be robustly predicted by the stemness GRN but not by randomized versions of the stemness GRN. Strikingly, we found a hierarchical structure of the GRN with the Oct4/Cdx2 motif functioning as the first decision-making module followed by Gata6/Nanog. We propose that stem cell populations, instead of being viewed as all having a specific cellular state, can be regarded as a heterogeneous mixture including cells in various states. Upon perturbations by external signals, stem cells lose the capacity to access certain cellular states, thereby becoming differentiated. The new gene states and key parameters regulating transitions among gene states proposed by RACIPE can be used to guide experimental strategies to better understand differentiation and design reprogramming. The findings demonstrate that the functions of the stemness GRN is mainly determined by its well-evolved network topology rather than by detailed kinetic parameters

The effect of frailty on survival in patients with COVID-19 (COPE): a multicentre, European, observational cohort study

Background The COVID-19 pandemic has placed unprecedented strain on health-care systems. Frailty is being used in clinical decision making for patients with COVID-19, yet the prevalence and effect of frailty in people with COVID-19 is not known. In the COVID-19 in Older PEople (COPE) study we aimed to establish the prevalence of frailty in patients with COVID-19 who were admitted to hospital and investigate its association with mortality and duration of hospital stay. Methods This was an observational cohort study conducted at ten hospitals in the UK and one in Italy. All adults (≥18 years) admitted to participating hospitals with COVID-19 were included. Patients with incomplete hospital records were excluded. The study analysed routinely generated hospital data for patients with COVID-19. Frailty was assessed by specialist COVID-19 teams using the clinical frailty scale (CFS) and patients were grouped according to their score (1–2=fit; 3–4=vulnerable, but not frail; 5–6=initial signs of frailty but with some degree of independence; and 7–9=severe or very severe frailty). The primary outcome was in-hospital mortality (time from hospital admission to mortality and day-7 mortality). Findings Between Feb 27, and April 28, 2020, we enrolled 1564 patients with COVID-19. The median age was 74 years (IQR 61–83); 903 (57·7%) were men and 661 (42·3%) were women; 425 (27·2%) had died at data cutoff (April 28, 2020). 772 (49·4%) were classed as frail (CFS 5–8) and 27 (1·7%) were classed as terminally ill (CFS 9). Compared with CFS 1–2, the adjusted hazard ratios for time from hospital admission to death were 1·55 (95% CI 1·00–2·41) for CFS 3–4, 1·83 (1·15–2·91) for CFS 5–6, and 2·39 (1·50–3·81) for CFS 7–9, and adjusted odds ratios for day-7 mortality were 1·22 (95% CI 0·63–2·38) for CFS 3–4, 1·62 (0·81–3·26) for CFS 5–6, and 3·12 (1·56–6·24) for CFS 7–9. Interpretation In a large population of patients admitted to hospital with COVID-19, disease outcomes were better predicted by frailty than either age or comorbidity. Our results support the use of CFS to inform decision making about medical care in adult patients admitted to hospital with COVID-19

Prognostic value of estimated glomerular filtration rate in hospitalised older patients (over 65) with COVID-19: a multicentre, European, observational cohort study

Background: The reduced renal function has prognostic significance in COVID-19 and it has been linked to mortality in the general population. Reduced renal function is prevalent in older age and thus we set out to better understand its effect on mortality. Methods: Patient clinical and demographic data was taken from the COVID-19 in Older People (COPE) study during two periods (February–June 2020 and October 2020–March 2021, respectively). Kidney function on admission was measured using estimated glomerular filtration rate (eGFR). The primary outcomes were time to mortality and 28-day mortality. Secondary outcome was length of hospital stay. Data were analysed with multilevel Cox proportional hazards regression, and multilevel logistic regression and adjusted for individual patient clinical and demographic characteristics. Results: One thousand eight hundred two patients (55.0% male; median [IQR] 80 [73–86] years) were included in the study. 28-day mortality was 42.3% (n = 742). 48% (n = 801) had evidence of renal impairment on admission. Using a time-to-event analysis, reduced renal function was associated with increased in-hospital mortality (compared to eGFR ≥ 60 [Stage 1&2]): eGFR 45–59 [Stage 3a] aHR = 1.26 (95%CI 1.02–1.55); eGFR 30–44 [Stage 3b] aHR = 1.41 (95%CI 1.14–1.73); eGFR 1–29 [Stage 4&5] aHR = 1.42 (95%CI 1.13–1.80). In the co-primary outcome of 28-day mortality, mortality was associated with: Stage 3a adjusted odds ratio (aOR) = 1.18 (95%CI 0.88–1.58), Stage 3b aOR = 1.40 (95%CI 1.03–1.89); and Stage 4&5 aOR = 1.65 (95%CI 1.16–2.35). Conclusion: eGFR on admission is a good independent predictor of mortality in hospitalised older patients with COVID-19 population. We found evidence of a dose-response between reduced renal function and increased mortality

Decoding the coupled decision-making of the epithelial-mesenchymal transition and metabolic reprogramming in cancer

Summary: Cancer metastasis relies on an orchestration of traits driven by different interacting functional modules, including metabolism and epithelial-mesenchymal transition (EMT). During metastasis, cancer cells can acquire a hybrid metabolic phenotype (W/O) by increasing oxidative phosphorylation without compromising glycolysis and they can acquire a hybrid epithelial/mesenchymal (E/M) phenotype by engaging EMT. Both the W/O and E/M states are associated with high metastatic potentials, and many regulatory links coupling metabolism and EMT have been identified. Here, we investigate the coupled decision-making networks of metabolism and EMT. Their crosstalk can exhibit synergistic or antagonistic effects on the acquisition and stability of different coupled metabolism-EMT states. Strikingly, the aggressive E/M-W/O state can be enabled and stabilized by the crosstalk irrespective of these hybrid states’ availability in individual metabolism or EMT modules. Our work emphasizes the mutual activation between metabolism and EMT, providing an important step toward understanding the multifaceted nature of cancer metastasis