Staphylococcus aureus gene expression in a rat model of infective endocarditis

Background: Diabetes mellitus is a frequent underlying comorbidity in patients with Staphylococcus aureus endocarditis, and it represents a risk factor for complications and a negative outcome. The pathogenesis of staphylococcal endocardial infections in diabetic hosts has been poorly characterized, and little is known about S. aureus gene expression in endocardial vegetations. Methods: We utilized a rat model of experimental S. aureus endocarditis to compare the pathogenesis of staphylococcal infection in diabetic and nondiabetic hosts and to study the global S. aureus transcriptome in endocardial vegetations in vivo. Results: Diabetic rats had higher levels of bacteremia and larger endocardial vegetations than nondiabetic control animals. Microarray analyses revealed that 61 S. aureus genes were upregulated in diabetic rats, and the majority of these bacterial genes were involved in amino acid and carbohydrate metabolism. When bacterial gene expression in vivo (diabetic or nondiabetic endocardial vegetations) was compared to in vitro growth conditions, higher in vivo expression of genes encoding toxins and proteases was observed. Additionally, genes involved in the production of adhesins, capsular polysaccharide, and siderophores, as well as in amino acid and carbohydrate transport and metabolism, were upregulated in endocardial vegetations. To test the contribution of selected upregulated genes to the pathogenesis of staphylococcal endocarditis, isogenic deletion mutants were utilized. A mutant defective in production of the siderophore staphyloferrin B was attenuated in the endocarditis model, whereas the virulence of a surface adhesin (ΔsdrCDE) mutant was similar to that of the parental S. aureus strain. Conclusions: Our results emphasize the relevance of diabetes mellitus as a risk factor for infectious endocarditis and provide a basis for understanding gene expression during staphylococcal infections in vivo. Electronic supplementary material The online version of this article (doi:10.1186/s13073-014-0093-3) contains supplementary material, which is available to authorized users

High Order Correction Terms for The Peak-Peak Correlation Function in Nearly-Gaussian Models

One possible way to investigate the nature of the primordial power spectrum fluctuations is by investigating the statistical properties of the local maximum in the density fluctuation fields. In this work we present a study of the mean correlation function, $\xi_r$, and the correlation function for high amplitude fluctuations (the peak-peak correlation) in a slighlty non-Gaussian context. From the definition of the correlation excess, we compute the Gaussian two-point correlation function and, using an expansion in Generalized Hermite polynomials, we estimate the correlation of high density peaks in a non-Gaussian field with generic distribution and power spectrum. We also apply the results obtained to a scale-mixed distribution model, which correspond to a nearly Gaussian model. The results reveal that, even for a small deviation from Gaussianity, we can expect high density peaks to be much more correlated than in a Gaussian field with the same power spectrum. In addition, the calculations reveal how the amplitude of the peaks in the fluctuations field is related to the existing correlations. Our results may be used as an additional tool to investigate the behavior of the N-point correlation function, to understand how non-Gaussian correlations affect the peak-peak statistics and extract more information about the statistics of the density field.Comment: Accepted for publication in A&

Influenza pandemic and professional duty: family or patients first? A survey of hospital employees

BACKGROUND: Conflicts between professional duties and fear of influenza transmission to family members may arise among health care professionals (HCP). METHODS: We surveyed employees at our university hospital regarding ethical issues arising during the management of an influenza pandemic. RESULTS: Of 644 respondents, 182 (28%) agreed that it would be professionally acceptable for HCP to abandon their workplace during a pandemic in order to protect themselves and their families, 337 (52%) disagreed with this statement and 125 (19%) had no opinion, with a higher rate of disagreement among physicians (65%) and nurses (54%) compared with administrators (32%). Of all respondents, 375 (58%) did not believe that the decision to report to work during a pandemic should be left to the individual HCP and 496 (77%) disagreed with the statement that HCP should be permanently dismissed for not reporting to work during a pandemic. Only 136 (21%) respondents agreed that HCW without children should primarily care for the influenza patients. CONCLUSION: Our results suggest that a modest majority of HCP, but only a minority of hospital administrators, recognises the obligation to treat patients despite the potential risks. Professional ethical guidelines allowing for balancing the needs of society with personal risks are needed to help HCP fulfil their duties in the case of a pandemic influenza

Transethnic meta-analysis of rare coding variants in PLCG2, ABI3, and TREM2 supports their general contribution to Alzheimer's disease

Rare coding variants in TREM2, PLCG2, and ABI3 were recently associated with the susceptibility to Alzheimer's disease (AD) in Caucasians. Frequencies and AD-associated effects of variants differ across ethnicities. To start filling the gap on AD genetics in South America and assess the impact of these variants across ethnicity, we studied these variants in Argentinian population in association with ancestry. TREM2 (rs143332484 and rs75932628), PLCG2 (rs72824905), and ABI3 (rs616338) were genotyped in 419 AD cases and 486 controls. Meta-analysis with European population was performed. Ancestry was estimated from genome-wide genotyping results. All variants show similar frequencies and odds ratios to those previously reported. Their association with AD reach statistical significance by meta-analysis. Although the Argentinian population is an admixture, variant carriers presented mainly Caucasian ancestry. Rare coding variants in TREM2, PLCG2, and ABI3 also modulate susceptibility to AD in populations from Argentina, and they may have a European heritage.Acknowledgements: This work was supported by grants from the International Society for Neurochemistry (ISN) and Alexander von Humboldt Foundation (to M.C.D.); Agencia Nacional de Promoción Científica y Tecnológica (PBIT/09 2013, PICT-2015-0285 and PICT-2016-4647 to L.M.; PICT-2014-1537 to M.C.D.); GENMED Labex and JPND PERADES grant; and JPND EADB grant (German Federal Ministry of Education and Research, BMBF: 01ED1619A)

Chemical Synthesis of Staphyloferrin B Affords Insight into the Molecular Structure, Iron Chelation, and Biological Activity of a Polycarboxylate Siderophore Deployed by the Human Pathogen

Staphyloferrin B (SB) is a citrate-based polycarboxylate siderophore produced and utilized by the human pathogen Staphylococcus aureus for acquiring iron when colonizing the vertebrate host. The first chemical synthesis of SB is reported, which enables further molecular and biological characterization and provides access to structural analogues of the siderophore. Under conditions of iron limitation, addition of synthetic SB to bacterial growth medium recovered the growth of the antibiotic resistant community isolate S. aureus USA300 JE2. Two structural analogues of SB, epiSB and SBimide, were also synthesized and employed to investigate how epimerization of the citric acid moiety or imide formation influence its function as a siderophore. Epimerization of the citric acid stereocenter perturbed the iron-binding properties and siderophore function of SB as evidenced by experimental and computational modeling studies. Although epiSB provided growth recovery to S. aureus USA300 JE2 cultured in iron-deficient medium, the effect was attenuated relative to that of SB. Moreover, SB more effectively sequestered the Fe(III) bound to human holo-transferrin, an iron source of S. aureus, than epiSB. SBimide is an imide analogous to the imide forms of other citric acid siderophores that are often observed when these molecules are isolated from natural sources. Here, SBimide is shown to be unstable, converting to native SB at physiological pH. SB is considered to be a virulence factor of S. aureus, a pathogen that poses a particular threat to public health because of the number of drug-resistant strains emerging in hospital and community settings. Iron acquisition by S. aureus is important for its ability to colonize the human host and cause disease, and new chemical insights into the structure and function of SB will inform the search for new therapeutic strategies for combating S. aureus infections.Alfred Benzon Foundation (Postdoctoral fellowship)Pacific Southwest Regional Center of ExcellenceAlfred P. Sloan Foundatio

Reduced Neutrophil Apoptosis in Diabetic Mice during Staphylococcal Infection Leads to Prolonged Tnfα Production and Reduced Neutrophil Clearance

Diabetes is a frequent underlying medical condition among individuals with Staphylococcus aureus infections, and diabetic patients often suffer from chronic inflammation and prolonged infections. Neutrophils are the most abundant inflammatory cells during the early stages of bacterial diseases, and previous studies have reported deficiencies in neutrophil function in diabetic hosts. We challenged age-matched hyperglycemic and normoglycemic NOD mice intraperitoneally with S. aureus and evaluated the fate of neutrophils recruited to the peritoneal cavity. Neutrophils were more abundant in the peritoneal fluids of infected diabetic mice by 48 h after bacterial inoculation, and they showed prolonged viability ex vivo compared to neutrophils from infected nondiabetic mice. These differences correlated with reduced apoptosis of neutrophils from diabetic mice and were dependent upon the presence of S. aureus and a functional neutrophil respiratory burst. Decreased apoptosis correlated with impaired clearance of neutrophils by macrophages both in vitro and in vivo and prolonged production of proinflammatory tumor necrosis factor alpha by neutrophils from diabetic mice. Our results suggest that defects in neutrophil apoptosis may contribute to the chronic inflammation and the inability to clear staphylococcal infections observed in diabetic patients

COVID-19 in cancer patients: clinical characteristics and outcome—an analysis of the LEOSS registry

Introduction Since the early SARS-CoV-2 pandemic, cancer patients have been assumed to be at higher risk for severe COVID-19. Here, we present an analysis of cancer patients from the LEOSS (Lean European Open Survey on SARS-CoV-2 Infected Patients) registry to determine whether cancer patients are at higher risk. Patients and methods We retrospectively analyzed a cohort of 435 cancer patients and 2636 non-cancer patients with confirmed SARS-CoV-2 infection, enrolled between March 16 and August 31, 2020. Data on socio-demographics, comorbidities, cancer-related features and infection course were collected. Age-, sex- and comorbidity-adjusted analysis was performed. Primary endpoint was COVID-19-related mortality. Results In total, 435 cancer patients were included in our analysis. Commonest age category was 76–85 years (36.5%), and 40.5% were female. Solid tumors were seen in 59% and lymphoma and leukemia in 17.5% and 11% of patients. Of these, 54% had an active malignancy, and 22% had recently received anti-cancer treatments. At detection of SARS-CoV-2, the majority (62.5%) presented with mild symptoms. Progression to severe COVID-19 was seen in 55% and ICU admission in 27.5%. COVID-19-related mortality rate was 22.5%. Male sex, advanced age, and active malignancy were associated with higher death rates. Comparing cancer and non-cancer patients, age distribution and comorbidity differed significantly, as did mortality (14% vs 22.5%, p value < 0.001). After adjustments for other risk factors, mortality was comparable. Conclusion Comparing cancer and non-cancer patients, outcome of COVID-19 was comparable after adjusting for age, sex, and comorbidity. However, our results emphasize that cancer patients as a group are at higher risk due to advanced age and pre-existing conditions

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results

Aligning the goals of learning analytics with its research scholarship: an open peer commentary approach

To promote cross-community dialogue on matters of significance within the field of learning analytics (LA), we as editors-in-chief of the Journal of Learning Analytics (JLA) have introduced a section for papers that are open to peer commentary. An invitation to submit proposals for commentaries on the paper was released, and 12 of these proposals were accepted. The 26 authors of the accepted commentaries are based in Europe, North America, and Australia. They range in experience from PhD students and early-career researchers to some of the longest-standing, most senior members of the learning analytics community. This paper brings those commentaries together, and we recommend reading it as a companion piece to the original paper by Motz et al. (2023), which also appears in this issue.Horizon 2020(H2020)883588Algorithms and the Foundations of Software technolog