First-in-human evaluation of [18F]CETO: a novel tracer for adrenocortical tumours

PURPOSE

[11C]Metomidate positron emission tomography (PET) is currently used for staging of adrenocortical carcinoma and for lateralization in primary aldosteronism (PA). Due to the short half-life of carbon-11 and a high non-specific liver uptake of [11C]metomidate there is a need for improved adrenal imaging methods. In a previous pre-clinical study para-chloro-2-[18F]fluoroethyletomidate has been proven to be a specific adrenal tracer. The objective is to perform a first evaluation of para-chloro-2-[18F]fluoroethyletomidate positron emission computed tomography ([18F]CETO-PET/CT) in patients with adrenal tumours and healthy volunteers.

METHODS

Fifteen patients underwent [18F]CETO-PET/CT. Five healthy volunteers were recruited for test-retest analysis and three out of the five underwent additional [15O]water PET/CT to measure adrenal blood flow. Arterial blood sampling and tracer metabolite analysis was performed. The kinetics of [18F]CETO were assessed and simplified quantitative methods were validated by comparison to outcome measures of tracer kinetic analysis.

RESULTS

Uptake of [18F]CETO was low in the liver and high in adrenals. Initial metabolization was rapid, followed by a plateau. The kinetics of [18F]CETO in healthy adrenals and all adrenal pathologies, except for adrenocortical carcinoma, were best described by an irreversible single-tissue compartment model. Standardized uptake values (SUV) correlated well with the uptake rate constant K1. Both K1 and SUV were highly correlated to adrenal blood flow in healthy controls. Repeatability coefficients of K1, SUV65-70, and SUV120 were 25, 22, and 17%.

CONCLUSIONS

High adrenal uptake combined with a low unspecific liver uptake suggests that 18F]CETO is a suitable tracer for adrenal imaging. Adrenal SUV, based on a whole-body scan at 1 h p.i., correlated well with the net uptake rate Ki.

TRIAL REGISTRATION

ClinicalTrials.gov , NCT05361083 Retrospectively registered 29 April 2022. at,  https://clinicaltrials.gov/ct2/show/NCT05361083.

Amilorides inhibit SARS-CoV-2 replication in vitro by targeting RNA structures

The SARS-CoV-2 pandemic, and the likelihood of future coronavirus pandemics, emphasized the urgent need for development of novel antivirals. Small-molecule chemical probes offer both to reveal aspects of virus replication and to serve as leads for antiviral therapeutic development. Here, we report on the identification of amiloride-based small molecules that potently inhibit OC43 and SARS-CoV-2 replication through targeting of conserved structured elements within the viral 5′-end. Nuclear magnetic resonance–based structural studies revealed specific amiloride interactions with stem loops containing bulge like structures and were predicted to be strongly bound by the lead amilorides in retrospective docking studies. Amilorides represent the first antiviral small molecules that target RNA structures within the 5′ untranslated regions and proximal region of the CoV genomes. These molecules will serve as chemical probes to further understand CoV RNA biology and can pave the way for the development of specific CoV RNA–targeted antivirals.

Knowledge, attitudes and practices regarding antimicrobial use and resistance among communities of Ilala, Kilosa and Kibaha districts of Tanzania

BACKGROUND

Antimicrobial resistance (AMR) represents one of the biggest threats to health globally. This cross-sectional study determined knowledge, attitudes and practices (KAP) regarding antimicrobial use (AMU) and AMR among communities of Ilala, Kilosa and Kibaha in Tanzania.

METHOD

A semi-structured questionnaire was used to collect socio-demographic and KAP data through face-to-face interviews. Responses related to the triad of KAP were assigned scores that were aggregated for each participant. Linear regression analysis was conducted to determine predictors of KAP scores.

RESULTS

The study enrolled 828 participants from the three districts. A total of 816 (98.6%) were aware of antimicrobials, and 808 (99%, n = 816) reported to have used them. Antimicrobials were mainly used to treat cough (68.0%), urinary tract infections (53.4%), diarrhoea (48.5%) and wounds (45.2%). The most frequent sources of antimicrobials were health facility (65.0%, n = 820) and pharmacies/basic drug shops (53.7%). The median AMU knowledge score was 5 (IQR = 4, 7) and that of AMR was 26 (IQR=23, 29). The median AMU attitudes score was 32 (IQR: 29, 35) and that of AMR was 19 (IQR=17, 22). The median AMU practice score was 3 (IQR: 3, 3). The KAP scores were significantly influenced by increased participant's age (βadj=0.10; 95% CI: 0.05, 0.15) and level of education, being lower among those with primary education (βadj=5.32; 95% CI: 3.27, 7.37) and highest among those with college/university education (βadj=9.85; 95% CI: 6.04, 13.67).

CONCLUSION

The study documented a moderate level of KAP regarding AMU and AMR in the study districts. The participant's age and level of education were significantly associated with participant's KAP scores. The observed inadequate knowledge, inappropriate attitude, and practices of AMU and AMR should be considered as alarming problems that require immediate actions including policy formulation and planning of community-based mitigation measures.

Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models

It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.

Disease-causing microorganisms, including viruses, bacteria, protozoa and fungi, form complex communities within animals and plants. These microorganisms can coexist harmoniously or even beneficially, or they may competitively interact for host resources. Well-studied examples include interactions between viruses and bacteria in the respiratory tract. Whilst ecological studies have revealed that some pathogens do interact within their hosts, identifying interactions from available population scale data from health authorities is challenging. This is exacerbated by a lack of large-scale data describing the infection patterns of multiple pathogens within single populations over long time frames. Furthermore, methods for evaluating whether infection frequencies of different pathogens fluctuate together or not over time cannot readily account for alternative explanations. For example, human pathogens may have related seasonal patterns depending on the age groups they infect and the weather conditions they survive in, and not because they are interacting. We developed a robust statistical framework to identify pathogen-pathogen interactions from population scale diagnostic data. This framework serves as a crucial step in identifying such important interactions and will guide new studies to elucidate their underpinning mechanisms. This will have important consequences for public health preparedness and the design of effective disease control interventions.

How patients' experiences of respiratory tract infections affect healthcare-seeking and antibiotic use: insights from a cross-sectional survey in rural Anhui, China

OBJECTIVE

To investigate the occurrence of reported respiratory tract infection (RTI) symptoms and their effects on use of self and professional care among patients in the community.

DESIGN

A cross-sectional retrospective household survey.

SETTING

12 administrative villages from rural Anhui, China.

PARTICIPANTS

2160 rural adult residents aged ≥18 years registered as rural residents and actually living in the sampled villages when this study was conducted.

METHOD

The respondents were recruited using stratified-clustered randomised sampling. A structured questionnaire was deployed to solicit information about social demographics, symptoms of last RTI and healthcare-seeking following the RTI. Descriptive analyses were performed to investigate the reported symptoms, and multivariate logistic regression models were developed to identify relationships between number of concurrent symptoms and healthcare-seeking and antibiotics use.

RESULTS

A total of 1968 residents completed the survey, resulting in a response rate of 91.1%. The number of concurrent symptoms showed a clear increasing trend with seeking help from clinics and being prescribed antibiotics. Multivariate regression revealed statistically significant associations between the following: (a) visiting clinics and education (OR=0.790), sore throat (OR=1.355), cough (OR=1.492), shortness of breath (OR=1.707) and fever (OR=2.142); (b) buying medicine from shops without prescription and education (OR=1.230) and cough (OR=1.452); (c) getting antibiotics at clinics and sore throat (OR=2.05) and earache and/or tinnitus (OR=4.884); and (d) obtaining antibiotics at medicine shops and productive cough (OR=1.971).

CONCLUSIONS

Reported RTI symptoms play an important role in shaping both patient- and doctor-led responses.