An in silico approach for modelling T-helper polarizing iNKT cell agonists

Acute sarcopenia changes following hospitalization: influence of pre-admission care dependency level

INTRODUCTION

Hospitalization is associated with acute changes in sarcopenia status in older people, but the influencing factors are not fully understood. Pre-admission care dependency level as a risk factor has not yet been investigated.

OBJECTIVE

Evaluate if pre-admission care dependency level is an independent predictor of sarcopenia changes following hospitalization.

SETTING AND SUBJECTS

Data came from the Sarcopenia 9+ EAMA Project, a European prospective multi-centre study. For this study, 227 hospitalised older people were included from four different hospitals in Belgium, Spain and Poland, between 18 February 2019 and 5 September 2020.

METHODS

Sarcopenia status at admission and discharge were calculated using a combined score (desirability value) based on muscle mass (calf circumference), strength (grip) and function (walking speed). Ratio of admission to discharge status was the outcome (desirability ratio; 1.00 meaning no difference). Predictor variable was the pre-admission care dependency level, classified into three groups: independent older people living at home, dependent older people living at home and older people living in a care home. Linear regression models were applied, considering potential confounders.

RESULTS

Mean desirability ratio for dependent older people living at home ('middle dependent group') was lower (0.89) compared to independent older people (0.98; regression coefficient -0.09 [95% CI -0.16, -0.02]) and care home patients (1.05; -0.16 [95% CI -0.01, -0.31]). Adjusting for potential confounders or using another statistical approach did not affect the main results.

CONCLUSION

Dependent older people living at home were at higher risk of deterioration in sarcopenia status following hospitalization. In-depth studies investigating causes and potential interventions of these findings are needed.

The use of databases, data mining and immunoinformatics in vaccinology: where are we?

INTRODUCTION

Vaccinology has evolved from a sub-discipline focussed on simplistic vaccine development based on antibody-mediated protection to a separate discipline involving epidemiology, host and pathogen biology, immunology, genomics, proteomics, structure biology, protein engineering, chemical biology, and delivery systems. Data mining in combination with bioinformatics has provided a scaffold linking all these disciplines to the design of vaccines and vaccine adjuvants. Areas covered: This review provides background knowledge on immunological aspects which have been exploited with informatics for the in silico analysis of immune responses and the design of vaccine antigens. Furthermore, the article presents various databases and bioinformatics tools, and discusses B and T cell epitope predictions, antigen design, adjuvant research and systems immunology, highlighting some important examples, and challenges for the future. Expert opinion: Informatics and data mining have not only reduced the time required for experimental immunology, but also contributed to the identification and design of novel vaccine candidates and the determination of biomarkers and pathways of vaccine response. However, more experimental data is required for benchmarking immunoinformatic tools. Nevertheless, developments in immunoinformatics and reverse vaccinology, which are nascent fields, are likely to hasten vaccine discovery, although the path to regulatory approval is likely to remain a necessary impediment.

Relationships between Th1 or Th2 iNKT cell activity and structures of CD1d-antigen complexes: meta-analysis of CD1d-glycolipids dynamics simulations

A number of potentially bioactive molecules can be found in nature. In particular, marine organisms are a valuable source of bioactive compounds. The activity of an α-galactosylceramide was first discovered in 1993 via screening of a Japanese marine sponge (Agelas mauritanius). Very rapidly, a synthetic glycololipid analogue of this natural molecule was discovered, called KRN7000. Associated with the CD1d protein, this α-galactosylceramide 1 (KRN7000) interacts with the T-cell antigen receptor to form a ternary complex that yields T helper (Th) 1 and Th2 responses with opposing effects. In our work, we carried out molecular dynamics simulations (11.5 µs in total) involving eight different ligands (conducted in triplicate) in an effort to find out correlation at the molecular level, if any, between chemical modulation of 1 and the orientation of the known biological response, Th1 or Th2. Comparative investigations of human versus mouse and Th1 versus Th2 data have been carried out. A large set of analysis tools was employed including free energy landscapes. One major result is the identification of a specific conformational state of the sugar polar head, which could be correlated, in the present study, to the biological Th2 biased response. These theoretical tools provide a structural basis for predicting the very different dynamical behaviors of α-glycosphingolipids in CD1d and might aid in the future design of new analogues of 1.