<Emphasis Type="Italic">Burkholderia</Emphasis> Hep_Hag autotransporter (BuHA) proteins elicit a strong antibody response during experimental glanders but not human melioidosis

Background  

The bacterial biothreat agents Burkholderia mallei and Burkholderia pseudomallei are the cause of glanders and melioidosis, respectively. Genomic and epidemiological studies have shown that B. mallei is a recently emerged, host restricted clone of B. pseudomallei.     

Disintegration of Dung Pats from Cattle Treated with the Ivermectin Anthelmintic Bolus,or the Biocontrol Agent Duddingtonia flagrans

An experiment was performed during the grazing seasons of 1998, 1999 and 2000 to study the influence of the antiparasitic drug ivermectin and the nematophagous fungus Duddingtonia flagrans on cattle dung disintegration. The faeces originated from groups of animals that were part of a separate grazing experiment where different control strategies for nematode parasite infections were investigated. Each group consisted of 10 first-season grazing cattle that were either untreated, treated with the ivermectin sustained-release bolus, or fed chlamydospores of D. flagrans. Faeces were collected monthly on 4 occasions and out of pooled faeces from each group, 4 artificial 1 kg dung pats were prepared and deposited on nylon mesh on an enclosed pasture and protected from birds. The position of the new set of pats was repeated throughout the 3 years of the study. Each year, the dung pats were weighed 4, 6, 8 and 10 weeks after deposition and immediately afterwards replaced to their initial positions.

Results showed that there was no difference in faecal pat disintegration between groups. However, the time-lag between deposition and complete disintegration of the faeces varied significantly between deposition occasions. Dung pats disappeared within 2 weeks (visual observation) when subjected to heavy rainfall early after deposition, whereas an extended dry period coincided with faeces still remaining 12 months after deposition.

     

Multivariate analysis of human immunodeficiency virus type 1 neutralization data.

We report on the use of spectral map analysis of the inter- and intraclade neutralization data of 14 sera of human immunodeficiency virus type 1 (HIV-1)-infected individuals and 16 primary isolates, representing genetic clades A to H in group M and group O. This multivariate analysis has been used previously to study the interaction between drugs and receptors and between viruses and antiviral compounds. The analysis reveals the existence of neutralization clusters, not correlated with the known genetic clades. The structural factors that have been identified may correlate with the most important neutralization epitopes. Three key primary HIV-1 isolates, which allow discrimination of sera that are likely or unlikely to neutralize primary isolates from most of the genetic clades, were identified. Our method of analysis will facilitate the evaluation as well as the design of suitable HIV-1 vaccines, which induce high-titer interclade cross-neutralizing antibodies.     

Effect of dibutyryl cyclic adenosine 3′5′-monophosphate on mitotic activity in the thyroid of hypophysectomized rats

Summary Effect of dibutyryl cyclic adenosine 35-monophosphate (dbcAMP) on mitotic activity in the thyroid of hypophysectomized rats has been examined. It has been demonstrated that dbcAMP stimulates the incidence of mitoses in the thyroid follicular cells. It is therefore suggested that cAMP may be a mediator of the proliferogenic effect of TSH on the thyroid in vivo. Cyclic AMP could also release some unidentified growth-promoting factors for the thyroid. A direct stimulating effect of dbcAMP on the proliferation of the thyroid follicular cells is assumed to be possible as well.     

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BackgroundPeople with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.Methods and findingsWe performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.ConclusionsIn this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

In an observational analysis of primary care data from the UK, Naomi Launders and colleagues study the prevalence and clustering of physical health conditions and multimorbidity in individuals with severe mental illnesses.