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Naturally evolved genomes tend to be unnecessarily large and redundant, and are not optimised for biotechnological or research applications. In this review, the authors explore genome minimization and re-functionalisation approaches, and discuss their potential for industrial applications.

There is growing evidence that fat accumulation in the pancreas can have consequences for metabolic health. This Review discusses the methods for detecting pancreatic fat and the potential causes and pathogenic consequences of pancreatic fat accumulation.

A combination of therapeutic vaccination with Ad26/MVA and stimulation of innate immune responses leads to improved virologic control and delayed rebound in SIV-infected macaques following discontinuation of antiretroviral therapy.

Bloemeke et al. develop a method for measuring Aβ oligomers in plasma to diagnose Alzheimer’s Disease. Correlation analysis between cerebral spinal fluid and plasma oligomer concentrations indicates an impaired clearance of Aβ oligomers that is dependent on ApoE ε4 status.

Hettle et al. investigate the ability of marine Pseudoalteromonas sp. to metabolise carrageenan, a polysaccharide abundant in red algae. They isolate and characterise previously unstudied strains and find that the recently identified κ/ι-carrageenan specific polysaccharide utilization locus (CarPUL) is required for growth on carrageenan, and biochemically map out many of the steps.

Felton et al. conduct a systematic review to determine the utility of islet autoantibodies as biomarkers of type 1 diabetes heterogeneity. They find that islet autoantibodies are most likely to be useful for patient stratification prior to clinical diagnosis.

Global change, including climate change, urbanization and global travel and trade, has affected the emergence and spread of infectious diseases. In the Review, Baker, Metcalf and colleagues examine how global change affects infectious diseases, highlighting examples ranging from COVID-19 to Zika virus disease.

Members of the hydrogen deuterium exchange mass spectrometry (HDX-MS) community provide their ‘best practices’ recommendations for HDX-MS data collection, analysis and reporting.

Coincidence experiments at free-electron lasers enable time resolved site-specific investigations of molecular photochemistry at high signal rates, but isolating individual dissociation processes still poses a considerable technical challenge. Here, the authors use electron-ion partial covariance imaging to isolate otherwise elusive chemical shifts in UV-induced photofragmentation pathways of the prototypical chiral molecule 1-iodo-2-methylbutane.

Combining molecular modeling and in vitro bioassays, Sokkar et al. provide an understanding of how EPI-X4, an endogenous peptide antagonist, interacts with its receptor CXCR4. With computational model, validated by mutagenesis studies, they design a series of derivatives with optimized receptor antagonizing properties as new leads for the development of CXCR4 inhibitors.

In an inter-laboratory study, the authors compare the accuracy and performance of three optical density calibration protocols (colloidal silica, serial dilution of silica microspheres, and colony-forming unit (CFU) assay). They demonstrate that serial dilution of silica microspheres is the best of these tested protocols, allowing precise and robust calibration that is easily assessed for quality control and can also evaluate the effective linear range of an instrument.

Ahmad, Lim, Morieri, Tam et al perform a systematic review and meta-analysis of biomarkers, genetic markers, and risk scores for prediction of cardiovascular outcomes in Type 2 diabetes. A few prognostic markers are identified that provide incremental predictive utility beyond established cardiovascular risk factors.

Naylor et al. systematically review the efficacy of treatments for beta-cell monogenic diabetes. Limited evidence from the mostly non-randomized, small studies supports no treatment in glucokinase-related hyperglycemia and sulfonylureas for HNF1A-diabetes; further evidence is needed on the optimum treatments in these and other monogenic subtypes.

Murphy, Kevin, Pollin et al. perform a systematic review of the evidence on the criteria used to select individuals with diabetes for genetic testing and of the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. Based on the findings the authors make recommendations and highlight challenges for the field.

Felton et al. conducted a systematic review to evaluate studies testing disease-modifying therapies and features linked to treatment response for type 1 diabetes prevention. While the quality of prevention and intervention trials is found to be high, precision analyses on factors associated with treatment response are of poorer quality.

Jacobsen, Sherr et al. evaluate the utility of novel technologies in the treatment of type 1 diabetes. Their systematic review finds technologies such as continuous glucose monitoring, insulin pumps, and decision support tools improve important measures (e.g., HbA1c, time in range, quality of life) allowing precision-directed uptake of technology.

Takele et al. conduct a systematic review and meta-analysis of the effects of intervention characteristics on preventing gestational diabetes. Group or healthcare facility-based physical activity interventions are found to be more effective in preventing gestational diabetes than community-based interventions.

Young, McInnes, Massey et al. systematically review published studies evaluating features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies in people with type 2 diabetes. They find limited current evidence on treatment effect heterogeneity, for glycaemic, cardiovascular and renal outcomes.

Francis et al. perform a systematic review and meta-analysis to evaluate studies comparing perinatal outcomes among individuals with gestational diabetes mellitus (GDM). Their review and post hoc analysis find that maternal preconception weight and non-glucose-dependent biochemical markers could be a precision diagnostic approach to reducing variability in clinical outcomes following treatment.

Lim et al. perform a systematic review and meta-analysis to identify participant characteristics associated with response to gestational diabetes prevention. Characteristics such as BMI, polycystic ovary syndrome and being in the preconception phase could determine responses to certain preventive interventions.

Bodhini et al. systematically review the evidence on sociodemographic, clinical, behavioral, and molecular factors that modify the effect of interventions for type 2 diabetes prevention. The certainty of evidence that such factors modify the effectiveness of lifestyle and behavioral interventions is low to very low.