Night shift work and indicators of cardiovascular risk: A systematic review and meta-analysis - Johanna Samulin Erdem; Mrinal K. Das; Evi De Ryck; Øivind Skare; Jenny-Anne S. Lie; Merete Bugge; Barbara Harding; Ingrid L. Jorgensen; Ingrid Sivesind Mehlum; Manolis Kogevinas; Karl-Christian Nordby; Shan Zienolddiny-Narui (Environmental Research, 2025)

Associations between light at night and mental health: A systematic review and meta-analysis - Andy Deprato; Prasun Haldar; José Francisco Navarro; Barbara N. Harding; Paige Lacy; Robert Maidstone; Saibal Moitra; Anna Palomar-Cros; Hannah Durrington; Manolis Kogevinas; Subhabrata Moitra; Ana Adan (Science of The Total Environment, 2025)

Indoor and outdoor artificial light-at-night (ALAN) and cancer risk: A systematic review and meta-analysis of multiple cancer sites and with a critical appraisal of exposure assessment - Anna Palomar-Cros; Andy Deprato; Kyriaki Papantoniou; Kurt Straif; Paige Lacy; Robert Maidstone; Ana Adan; Prasun Haldar; Saibal Moitra; José Francisco Navarro; Hannah Durrington; Subhabrata Moitra; et al. (Science of The Total Environment, 2024)

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review - Eline Verscheure; Rob Stierum; Vivi Schlünssen; Anne Mette Lund Würtz; Dorian Vanneste; Manolis Kogevinas; Barbara N. Harding; Karin Broberg; Shan Zienolddiny-Narui; Johanna Samulin Erdem; Mrinal K. Das; Konstantinos C. Makris; et al. (Environmental Research, 2023)

Active breeding seabirds prospect alternative breeding colonies - Jelena Kralj; Aurore Ponchon; Daniel Oro; Barbara Amadesi; Juan Arizaga; Nicola Baccetti; Thierry Boulinier; Jacopo G. Cecere; Robin M. Corcoran; Anna-Marie Corman; Leonie Enners; Abram Fleishman; et al. (Oecologia, 2023)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Glycoconjugate vaccines against Salmonella enterica serovars and Shigella species: existing and emerging methods for their analysis - Aleksandra Bazhenova; Fang Gao; Barbara Bolgiano; Stephen E. Harding (Biophysical Reviews, 2021)
The global spread of enteric disease, the increasingly limited options for antimicrobial treatment and the need for effective eradication programs have resulted in an increased demand for glycoconjugate enteric vaccines, made with carbohydrate-based membrane components of the pathogen, and their precise characterisation. A set of physico-chemical and immunological tests are employed for complete vaccine characterisation and to ensure their consistency, potency, safety and stability, following the relevant World Health Organization and Pharmacopoeia guidelines. Variable requirements for analytical methods are linked to conjugate structure, carrier protein nature and size and O- acetyl content of polysaccharide. We investigated a key stability-indicating method which measures the percent free saccharide of Salmonella enterica subspecies enterica serovar Typhi capsular polysaccharide, by detergent precipitation, depolymerisation and HPAEC-PAD quantitation. Together with modern computational approaches, a more precise design of glycoconjugates is possible, allowing for improvements in solubility, structural conformation and stability, and immunogenicity of antigens, which may be applicable to a broad spectrum of vaccines. More validation experiments are required to establish the most effective and suitable methods for glycoconjugate analysis to bring uniformity to the existing protocols, although the need for product-specific approaches will apply, especially for the more complex vaccines. An overview of current and emerging analytical approaches for the characterisation of vaccines against Salmonella Typhi and Shigella species is described in this paper. This study should aid the development and licensing of new glycoconjugate vaccines aimed at the prevention of enteric diseases.

The Potato Association of America - Steven R. James; Lori Wing; Ronald Knight; Barbara Harrity; Devid H. Lambert; Bud Platt; Al Reeves; Bill Bohl; Lind Sanford; Alexander D. Pavlista; Ed Plissey; Richard Sawyer; et al. (American Journal of Potato Research, 2000)