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Weight loss, hyperglycaemia and diabetes are known features of pancreatic cancer. We quantified the timing and the amount of changes in body mass index (BMI) and glycated haemoglobin (HbA1c), and their association with pancreatic cancer from five years before diagnosis. A matched case-control study was undertaken within 590 primary care practices in England, United Kingdom. 8,777 patients diagnosed with pancreatic cancer (cases) between 1st January 2007 and 31st August 2020 were matched to 34,979 controls by age, gender and diabetes. Longitudinal trends in BMI and HbA1c were visualised. Odds ratios adjusted for demographic and lifestyle factors (aOR) and 95% confidence intervals (CI) were calculated with conditional logistic regression. Subgroup analyses were undertaken according to the diabetes status. Changes in BMI and HbA1c observed for cases on longitudinal plots started one and two years (respectively) before diagnosis. In the year before diagnosis, a 1 kg/m2 decrease in BMI between cases and controls was associated with aOR for pancreatic cancer of 1.05 (95% CI 1.05 to 1.06), and a 1 mmol/mol increase in HbA1c was associated with aOR of 1.06 (1.06 to 1.07). ORs remained statistically significant (p < 0.001) for 2 years before pancreatic cancer diagnosis for BMI and 3 years for HbA1c. Subgroup analysis revealed that the decrease in BMI was associated with a higher pancreatic cancer risk for people with diabetes than for people without (aORs 1.08, 1.06 to 1.09 versus 1.04, 1.03 to 1.05), but the increase in HbA1c was associated with a higher risk for people without diabetes than for people with diabetes (aORs 1.09, 1.07 to 1.11 versus 1.04, 1.03 to 1.04). The statistically significant changes in weight and glycaemic control started three years before pancreatic cancer diagnosis but varied according to the diabetes status. The information from this study could be used to detect pancreatic cancer earlier than is currently achieved. However, regular BMI and HbA1c measurements are required to facilitate future research and implementation in clinical practice.

Deroceras reticulatum in arable fields display spatio-temporally stable slug patches that have been well documented under typical soil moisture conditions. The effect of abnormally high soil moisture on slug patch stability, however, is unknown. In this study, stepped gradient choice tests comparing soil moisture levels of 50–125% soil capacity showed slug preferences for levels in a range near to 125%. Activity became erratic, however, when given a choice of high moisture levels (125–370%), potentially because slugs searched for preferred conditions. Slug spatial aggregation was investigated in 21 commercial fields in 2023/24, a season of extreme rainfall, and then compared to years exhibiting typical rainfall (2015–2018). Slug patches occurred in 27.2% of assessment visits to fields during 2023/24 compared to 96.4% in typical years, suggesting weather conditions leading to abnormally high soil moisture are significantly associated with the breakdown of slug spatial aggregation behaviour. Random forest models identified the weather predictors (precipitation, relative humidity, temperature) with the highest impact on slug distribution and relative abundance, with the assessment date and region also related to relative abundance. However, a complex of environmental parameters affects soil moisture content, and no statistically significant effects of individual weather predictors emerged. The results are discussed in relation to slug behaviour in the context of their impact on targeted slug treatments.

Fungal infections are a significant global health challenge, causing approximately 3.8 million deaths annually, with immunocompromised populations particularly at risk. Traditional antifungal therapies, including azoles, echinocandins, and polyenes, face limitations due to rising antifungal resistance, toxicity, and inadequate treatment options. This review explores innovative strategies for preventing and managing fungal infections, such as vaccines, antifungal peptides, nanotechnology, probiotics, and immunotherapy. Vaccines offer promising avenues for long-term protection, despite difficulties in their development due to fungal complexity and immune evasion mechanisms. Antifungal peptides provide a novel class of agents with broad-spectrum activity and reduced resistance risk, whilst nanotechnology enables targeted, effective drug delivery systems. Probiotics show potential in preventing fungal infections, particularly vulvovaginal candidiasis, by maintaining microbial balance. Immunotherapy leverages immune system modulation to enhance antifungal defenses, and omics technologies deliver comprehensive insights into fungal biology, paving the way for novel therapeutic and vaccine targets. While these approaches hold immense promise, challenges such as cost, accessibility, and translational barriers remain. A coordinated effort among researchers, clinicians, and policymakers is critical to advancing these strategies and addressing the global burden of fungal infections effectively.

The cytochrome P450 CYP168A1 from Pseudomonas aeruginosa was cloned and expressed in Escherichia coli followed by purification and characterization of function. CYP168A1 is a fatty acid hydroxylase that hydroxylates saturated fatty acids, including myristic (0.30 min -1 ), palmitic (1.61 min -1 ) and stearic acids (1.24 min -1 ), at both the ω-1- and ω-2-positions. However, CYP168A1 only hydroxylates unsaturated fatty acids, including palmitoleic (0.38 min -1 ), oleic (1.28 min -1 ) and linoleic acids (0.35 min -1 ), at the ω-1-position. CYP168A1 exhibited a catalytic preference for palmitic, oleic and stearic acids as substrates in keeping with the phosphatidylcholine-rich environment deep in the lung that is colonized by P . aeruginosa .

Genes encoding cytochrome P450 (CYP; P450) enzymes occur widely in the Archaea, Bacteria, and Eukarya, where they play important roles in metabolism of endogenous regulatory molecules and exogenous chemicals. We now report that genes for multiple and unique P450s occur commonly in giant viruses in the Mimiviridae, Pandoraviridae, and other families in the proposed order Megavirales. P450 genes were also identified in a herpesvirus (Ranid herpesvirus 3) and a phage (Mycobacterium phage Adler). The Adler phage P450 was classified as CYP102L1, and the crystal structure of the open formwas solved at 2.5 Å. Genes encoding known redox partners for P450s (cytochrome P450 reductase, ferredoxin and ferredoxin reductase, and flavodoxin and flavodoxin reductase) were not found in any viral genome so far described, implying that host redox partners may drive viral P450 activities. Giant virus P450 proteins share no more than 25% identity with the P450 gene products we identified in Acanthamoeba castellanii, an amoeba host for many giant viruses. Thus, the origin of the unique P450 genes in giant viruses remains unknown. If giant virus P450 genes were acquired from a host, we suggest it could have been from an as yet unknown and possibly ancient host. These studies expand the horizon in the evolution and diversity of the enormously important P450 superfamily. Determining the origin and function of P450s in giant viruses may help to discern the origin of the giant viruses themselves.

Mollusks are the second most diverse animal phylum, yet little is known about their endocrinology or how they respond to endocrine disrupting compound (EDC) pollution. Characteristic effects of endocrine disruption are reproductive impairment, skewed sex ratios, development of opposite sex characteristics, and population decline. However, whether classical vertebrate EDCs, such as steroid hormone-like chemicals and inhibitors of steroidogenesis, exert effects on mollusks is controversial. In the blue mussel, Mytilus edulis , EDC exposure is correlated with feminized sex ratios in wild and laboratory mussels, but sex reversal has not been confirmed. Here, we describe a non-destructive qPCR assay to identify the sex of M. edulis allowing identification of males and females prior to experimentation. We exposed male mussels to 17α-ethinylestradiol and female mussels to ketoconazole, EDCs that mimic vertebrate steroid hormones or inhibit their biosynthesis. Both chemicals changed the sex of individual mussels, interfered with gonadal development, and disrupted gene expression of the sex differentiation pathway. Impacts from ketoconazole treatment, including changes in steroid levels, confirmed a role for steroidogenesis and steroid-like hormones in mollusk endocrinology. The present study expands the possibilities for laboratory and field monitoring of mollusk species and provides key insights into endocrine disruption and sexual differentiation in bivalves.

Cabbage stem flea beetle (CSFB) is an important pest of oilseed rape that was controlled by neonicotinoid seed treatments until they were banned for this use in 2013. Since then, CSFB has been a difficult pest to control, partly due to widespread resistance to pyrethroid insecticides. Alternate solutions are necessary. Here, four entomopathogenic nematode (EPN) species were tested against CSFB adults under laboratory conditions. In addition, a bioassay was completed to test for EPN compatibility with a range of adjuvants (glycerin, xanthan gum and flame retardant) to protect EPNs from UV radiation and desiccation. Results show that EPNs have the potential to control CSFB adults under laboratory conditions. Heterorhabditis bacteriophora caused 75% CSFB mortality at a concentration of 4000 nematodes/mL after six days, Steinernema feltiae caused 80% CSFB mortality when applied at a concentration of 40,000 nematodes/mL after two days, Steinernema carpocapsae caused 85% mortality at a concentration of 10,000 nematodes/mL after six days, and Steinernema kraussei caused no more than 70% CSFB mortality overall compared to the water control, which led to 23% mortality. Steinernema feltiae and H. bacteriophora survival was 100% when exposed to adjuvants, except S. feltiae with glycerin and H. bacteriophora with flame retardant. Further research to evaluate the efficacy of EPN and adjuvants under field conditions is necessary.

IntroductionWorldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients’ age, blood glucose and weight changes to provide pancreatic cancer risk scores. These values are routinely collected in primary care in the UK. Primary care’s central role in cancer diagnosis makes it an ideal setting to implement ENDPAC but it has yet to be used in clinical settings. This study aims to determine the feasibility of applying ENDPAC to data held by UK primary care practices.Methods and analysisThis will be a multicentre observational study with a cohort design, determining the feasibility of applying ENDPAC in UK primary care. We will develop software to search, extract and process anonymised data from 20 primary care providers’ electronic patient record management systems on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥48 mmol/mol (6.5%) and no previous abnormal HbA1c results. Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort’s demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC’s effectiveness for the early detection of pancreatic cancer.Ethics and disseminationThis project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating primary care practices, clinical leads and policy makers will be provided with summaries of the findings.

Abstract Lactic acid bacteria (LAB) are indigenous to food-related habitats as well as associated with the mucosal surfaces of animals. The LAB family Streptococcaceae consists of the genera Lactococcus and Streptococcus. Members of the family include the industrially important species Lactococcus lactis, which has a long history safe use in the fermentative food industry, and the disease-causing streptococci Streptococcus pneumoniae and Streptococcus pyogenes. The central metabolic pathways of the Streptococcaceae family have been extensively studied because of their relevance in the industrial use of some species, as well as their influence on virulence of others. Recent developments in high-throughput proteomic and DNA-microarray techniques, in in vivoNMR studies, and importantly in whole-genome sequencing have resulted in new insights into the metabolism of the Streptococcaceae family. The development of cost-effective high-throughput sequencing has resulted in the publication of numerous whole-genome sequences of lactococcal and streptococcal species. Comparative genomic analysis of these closely related but environmentally diverse species provides insight into the evolution of this family of LAB and shows that the relatively small genomes of members of the Streptococcaceae family have been largely shaped by the nutritionally rich environments they inhabit. The central metabolic pathways of the closely related genera Lactococcus and Streptococcus are reviewed with a focus on the adaptations to nutrient'rich environments.

Background A central theme in (micro)biology is understanding the molecular basis of fitness i.e. which strategies are successful under which conditions; how do organisms implement such strategies at the molecular level; and which constraints shape the trade-offs between alternative strategies. Highly standardized microbial laboratory evolution experiments are ideally suited to approach these questions. For example, prolonged chemostats provide a constant environment in which the growth rate can be set, and the adaptive process of the organism to such environment can be subsequently characterized. Results We performed parallel laboratory evolution of Lactococcus lactis in chemostats varying the quantitative value of the selective pressure by imposing two different growth rates. A mutation in one specific amino acid residue of the global transcriptional regulator of carbon metabolism, CcpA, was selected in all of the evolution experiments performed. We subsequently showed that this mutation confers predictable fitness improvements at other glucose-limited growth rates as well. In silico protein structural analysis of wild type and evolved CcpA, as well as biochemical and phenotypic assays, provided the underpinning molecular mechanisms that resulted in the specific reprogramming favored in constant environments. Conclusion This study provides a comprehensive understanding of a case of microbial evolution and hints at the wide dynamic range that a single fitness-enhancing mutation may display. It demonstrates how the modulation of a pleiotropic regulator can be used by cells to improve one trait while simultaneously work around other limiting constraints, by fine-tuning the expression of a wide range of cellular processes.