Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems

We propose an infinitesimal dispersion index for Markov counting processes. We show that, under standard moment existence conditions, a process is infinitesimally (over-) equi-dispersed if, and only if, it is simple (compound), i.e. it increases in jumps of one (or more) unit(s), even though infinitesimally equi-dispersed processes might be under-, equi- or over-dispersed using previously studied indices. Compound processes arise, for example, when introducing continuous-time white noise to the rates of simple processes resulting in Levy-driven SDEs. We construct multivariate infinitesimally over-dispersed compartment models and queuing networks, suitable for applications where moment constraints inherent to simple processes do not hold.Comment: 26 page

Bacterial microcompartment-mediated ethanolamine metabolism in E. coli urinary tract infection

Urinary tract infections (UTIs) are common, in general caused by intestinal Uropathogenic E.coli (UPEC) ascending via the urethra. Microcompartment-mediated catabolism of ethanolamine, a host cell breakdown product, fuels competitive overgrowth of intestinal E. coli, both pathogenic enterohaemorrhagic E. coli and commensal strains. During UTI urease negative E. coli thrive, despite the comparative nutrient limitation in urine. The role of ethanolamine as a potential nutrient source during UTI is understudied. We evaluated the role of metabolism of ethanolamine as a potential nitrogen and carbon source for UPEC in the urinary tract. We analysed infected urine samples by culture, HPLC, qRT-PCR and genomic sequencing. Ethanolamine concentration in urine was comparable to the most abundant reported urinary amino acid D-serine. Transcription of the eut operon was detected in the majority of urine samples screened containing E. coli. All sequenced UPECs had conserved eut operons while metabolic genotypes previously associated with UTI (dsdCXA, metE) were mainly limited to phylogroup B2. In vitro ethanolamine was found to be utilised as a sole source of nitrogen by UPECs. Metabolism of ethanolamine in artificial urine medium (AUM) induced metabolosome formation and provided a growth advantage at the physiological levels found in urine. Interestingly, eutE (acetaldehyde dehydrogenase) was required for UPECs to utilise ethanolamine to gain a growth advantage in AUM, suggesting ethanolamine is also utilised as a carbon source. This data suggests urinary ethanolamine is a significant additional carbon and nitrogen source for infecting E. coli

Inapparent infections and cholera dynamics

In many infectious diseases, an unknown fraction of infections produce symptoms mild enough to go unrecorded, a fact that can seriously compromise the interpretation of epidemiological records. This is true for cholera, a pandemic bacterial disease, where estimates of the ratio of asymptomatic to symptomatic infections have ranged from 3 to 100 (refs 1-5). In the absence of direct evidence, understanding of fundamental aspects of cholera transmission, immunology and control has been based on assumptions about this ratio and about the immunological consequences of inapparent infections. Here we show that a model incorporating high asymptomatic ratio and rapidly waning immunity, with infection both from human and environmental sources, explains 50 yr of mortality data from 26 districts of Bengal, the pathogen's endemic home. We find that the asymptomatic ratio in cholera is far higher than had been previously supposed and that the immunity derived from mild infections wanes much more rapidly than earlier analyses have indicated. We find, too, that the environmental reservoir(5,6) (free-living pathogen) is directly responsible for relatively few infections but that it may be critical to the disease's endemicity. Our results demonstrate that inapparent infections can hold the key to interpreting the patterns of disease outbreaks. New statistical methods(7), which allow rigorous maximum likelihood inference based on dynamical models incorporating multiple sources and outcomes of infection, seasonality, process noise, hidden variables and measurement error, make it possible to test more precise hypotheses and obtain unexpected results. Our experience suggests that the confrontation of time-series data with mechanistic models is likely to revise our understanding of the ecology of many infectious diseases.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62519/1/nature07084.pd

Gene Flow in Genetically Modified Wheat

Understanding gene flow in genetically modified (GM) crops is critical to answering questions regarding risk-assessment and the coexistence of GM and non-GM crops. In two field experiments, we tested whether rates of cross-pollination differed between GM and non-GM lines of the predominantly self-pollinating wheat Triticum aestivum. In the first experiment, outcrossing was studied within the field by planting “phytometers” of one line into stands of another line. In the second experiment, outcrossing was studied over distances of 0.5–2.5 m from a central patch of pollen donors to adjacent patches of pollen recipients. Cross-pollination and outcrossing was detected when offspring of a pollen recipient without a particular transgene contained this transgene in heterozygous condition. The GM lines had been produced from the varieties Bobwhite or Frisal and contained Pm3b or chitinase/glucanase transgenes, respectively, in homozygous condition. These transgenes increase plant resistance against pathogenic fungi. Although the overall outcrossing rate in the first experiment was only 3.4%, Bobwhite GM lines containing the Pm3b transgene were six times more likely than non-GM control lines to produce outcrossed offspring. There was additional variation in outcrossing rate among the four GM-lines, presumably due to the different transgene insertion events. Among the pollen donors, the Frisal GM line expressing a chitinase transgene caused more outcrossing than the GM line expressing both a chitinase and a glucanase transgene. In the second experiment, outcrossing after cross-pollination declined from 0.7–0.03% over the test distances of 0.5–2.5 m. Our results suggest that pollen-mediated gene flow between GM and non-GM wheat might only be a concern if it occurs within fields, e.g. due to seed contamination. Methodologically our study demonstrates that outcrossing rates between transgenic and other lines within crops can be assessed using a phytometer approach and that gene-flow distances can be efficiently estimated with population-level PCR analyses

Competitive Performance of Transgenic Wheat Resistant to Powdery Mildew

Genetically modified (GM) plants offer an ideal model system to study the influence of single genes that confer constitutive resistance to pathogens on the ecological behaviour of plants. We used phytometers to study competitive interactions between GM lines of spring wheat Triticum aestivum carrying such genes and control lines. We hypothesized that competitive performance of GM lines would be reduced due to enhanced transgene expression under pathogen levels typically encountered in the field. The transgenes pm3b from wheat (resistance against powdery mildew Blumeria graminis) or chitinase and glucanase genes from barley (resistance against fungi in general) were introduced with the ubiquitin promoter from maize (pm3b and chitinase genes) or the actin promoter from rice (glucanase gene). Phytometers of 15 transgenic and non-transgenic wheat lines were transplanted as seedlings into plots sown with the same 15 lines as competitive environments and subject to two soil nutrient levels. Pm3b lines had reduced mildew incidence compared with control lines. Chitinase and chitinase/glucanase lines showed the same high resistance to mildew as their control in low-nutrient treatment and slightly lower mildew rates than the control in high-nutrient environment. Pm3b lines were weaker competitors than control lines. This resulted in reduced yield and seed number. The Pm3b line with the highest transgene expression had 53.2% lower yield than the control whereas the Pm3b line which segregated in resistance and had higher mildew rates showed only minor costs under competition. The line expressing both chitinase and glucanase genes also showed reduced yield and seed number under competition compared with its control. Our results suggest that single transgenes conferring constitutive resistance to pathogens can have ecological costs and can weaken plant competitiveness even in the presence of the pathogen. The magnitude of these costs appears related to the degree of expression of the transgenes

Upregulation of GALNT7 in prostate cancer modifies O-glycosylation and promotes tumour growth.

Prostate cancer is the most common cancer in men and it is estimated that over 350,000 men worldwide die of prostate cancer every year. There remains an unmet clinical need to improve how clinically significant prostate cancer is diagnosed and develop new treatments for advanced disease. Aberrant glycosylation is a hallmark of cancer implicated in tumour growth, metastasis, and immune evasion. One of the key drivers of aberrant glycosylation is the dysregulated expression of glycosylation enzymes within the cancer cell. Here, we demonstrate using multiple independent clinical cohorts that the glycosyltransferase enzyme GALNT7 is upregulated in prostate cancer tissue. We show GALNT7 can identify men with prostate cancer, using urine and blood samples, with improved diagnostic accuracy than serum PSA alone. We also show that GALNT7 levels remain high in progression to castrate-resistant disease, and using in vitro and in vivo models, reveal that GALNT7 promotes prostate tumour growth. Mechanistically, GALNT7 can modify O-glycosylation in prostate cancer cells and correlates with cell cycle and immune signalling pathways. Our study provides a new biomarker to aid the diagnosis of clinically significant disease and cements GALNT7-mediated O-glycosylation as an important driver of prostate cancer progression

ST6GAL1-mediated aberrant sialylation promotes prostate cancer progression

Aberrant glycosylation is a universal feature of cancer cells, and cancer-associated glycans have been detected in virtually every cancer type. A common change in tumour cell glycosylation is an increase in α2,6 sialylation of N-glycans, a modification driven by the sialyltransferase ST6GAL1. ST6GAL1 is overexpressed in numerous cancer types, and sialylated glycans are fundamental for tumour growth, metastasis, immune evasion, and drug resistance, but the role of ST6GAL1 in prostate cancer is poorly understood. Here, we analyse matched cancer and normal tissue samples from 200 patients and verify that ST6GAL1 is upregulated in prostate cancer tissue. Using MALDI imaging mass spectrometry (MALDI-IMS), we identify larger branched α2,6 sialylated N-glycans that show specificity to prostate tumour tissue. We also monitored ST6GAL1 in plasma samples from >400 patients and reveal ST6GAL1 levels are significantly increased in the blood of men with prostate cancer. Using both in vitro and in vivo studies, we demonstrate that ST6GAL1 promotes prostate tumour growth and invasion. Our findings show ST6GAL1 introduces α2,6 sialylated N-glycans on prostate cancer cells and raise the possibility that prostate cancer cells can secrete active ST6GAL1 enzyme capable of remodelling glycans on the surface of other cells. Furthermore, we find α2,6 sialylated N-glycans expressed by prostate cancer cells can be targeted using the sialyltransferase inhibitor P-3FAX-Neu5Ac. Our study identifies an important role for ST6GAL1 and α2,6 sialylated N-glycans in prostate cancer progression and highlights the opportunity to inhibit abnormal sialylation for the development of new prostate cancer therapeutics

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707