Bifidobacteria shape antimicrobial T-helper cell responses during infancy and adulthood

Microbial infections early in life are challenging for the unexperienced immune system. The SARS-CoV-2 pandemic again has highlighted that neonatal, infant, child, and adult T-helper(Th)-cells respond differently to infections, and requires further understanding. This study investigates anti-bacterial T-cell responses against Staphylococcus aureus aureus, Staphylococcus epidermidis and Bifidobacterium longum infantis in early stages of life and adults and shows age and pathogen-dependent mechanisms. Beside activation-induced clustering, T-cells stimulated with Staphylococci become Th1-type cells; however, this differentiation is mitigated in Bifidobacterium-stimulated T-cells. Strikingly, prestimulation of T-cells with Bifidobacterium suppresses the activation of Staphylococcus-specific T-helper cells in a cell-cell dependent manner by inducing FoxP3+CD4+ T-cells, increasing IL-10 and galectin-1 secretion and showing a CTLA-4-dependent inhibitory capacity. Furthermore Bifidobacterium dampens Th responses of severely ill COVID-19 patients likely contributing to resolution of harmful overreactions of the immune system. Targeted, age-specific interventions may enhance infection defence, and specific immune features may have potential cross-age utilization.

IL-13 determines specific IgE responses and SARS-CoV-2 immunity after mild COVID-19 and novel mRNA vaccination

After recovery, mild and severe COVID-19 diseases are associated with long-term effects on the host immune system, such as prolonged T-cell activation or accumulation of autoantibodies. In this study, we show that mild SARS-CoV-2 infections, but not SARS-CoV-2 spike mRNA vaccinations, cause durable atopic risk factors such as a systemic Th2- and Th17-type environment as well as activation of B cells responsive of IgE against aeroallergens from house dust mite and mold. At an average of 100 days post mild SARS-CoV-2 infections, anti-mold responses were associated with low IL-13 levels and increased pro-inflammatory IL-6 titers. Acutely severely ill COVID-19 patients instead showed no evidence of atopic reactions. Considering convalescents of mild COVID-19 courses and mRNA-vaccinated individuals together, IL-13 was the predominant significantly upregulated factor, likely shaping SARS-CoV-2 immunity. Application of multiple regression analysis revealed that the IL-13 levels of both groups were determined by the Th17-type cytokines IL-17A and IL-22. Taken together, these results implicate a critical role for IL-13 in the aftermath of SARS-CoV-2 mild infections and mRNA vaccinations, conferring protection against airway directed, atopic side reactions that occur in mildly experienced COVID-19.

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

BACKGROUND

Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes.

METHODS

A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported.

RESULTS

1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict "survival". Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients' age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy.

CONCLUSIONS

Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration "ClinicalTrials" (clinicaltrials.gov) under NCT04455451.

[Identification and economic evaluation of anesthesiologic secondary diagnoses on the basis of intraoperative medication]

BACKGROUND

Complications and comorbidities are encodable in the German diagnosis related groups (G-DRG) system and can improve revenues. In this study, secondary diagnoses were identified through drug administrations during anaesthesia and were economically evaluated by regrouping these cases.

METHODS

All intraoperative drug administrations from 2008 were extracted from a database. After exclusion of synonyms and procedure-specific drug administrations, all remaining drugs were matched to explicit secondary diagnoses. All cases were regrouped with their newly defined secondary diagnoses by G‑DRG grouper software, and changes in cost weight were evaluated.

RESULTS

A total of 29 drugs could be assigned to 18 secondary diagnoses. From 22,440 anaesthesia the § 21 data record could be extracted in 1,929 cases and was regrouped with 2,976 secondary diagnoses, according to additional proceeds of 125,330.25 € in 2008 and 103,542.35 € in 2014. Intraoperative secondary diagnoses influence cost weight only in small parts. The average increase in revenue in this study could have been about 50 € per case. From 2008 to 2014 secondary diagnoses were continuously devaluated, although some of them, e. g. afibrinogenemia, have were revaluated.

DISCUSSION

Our retrospective method of making a diagnosis and assuming a correct indication of drug administration is inapplicable to daily routine. The anaesthesiologic documentation has to make drug administration and thereby the secondary diagnosis plausible.

Protection against photic damage in retinitis pigmentosa

Experiments on photic damage to the retinas of rats with hereditary retinal dystrophy and some tentative clinical evidence on human patients suggest that, in human retinitis pigmentosa, one could try to protect the retina and especially the rods from bright light in an attempt to delay the retinal degeneration and to prolong the period of useful vision. Several theoretical criteria have been proposed for protection of RP patients from possible photic retinal damage. Observing these criteria, Adrian developed a brownish ophthalmic filter which absorbs the short wavelengths preferentially, thus protecting the rods primarily. Whether or not use of these filters will be efficacious has yet to be determined and will require careful experimentation and the accumulation of clinical experience. Several brown ophthalmic filters also have been tested against the criteria for a protective device. The NoIR Amber 7% plastic glasses satisfy these criteria quite well and thus can be considered as a substitute for the Adrian lens. The characteristics of the two types of filters are compared. Experience with different methods of protection may show whether it is better to attempt to delay degeneration of both retinas simultaneously by decreasing their illuminations with filters or to exclude light completely from one eye in an attempt to preserve it while the other eye degenerates in the usual course of the disease. In any event, given the present state of knowledge, it seems to be appropriate, especially in the early stages of the disease, to suggest that RP patients protect their retinas from excessive light.