A social network analysis approach to assess COVID19-related disruption to substance use treatment and informal social interactions among people who use drugs in Scotland.

AIMS: To assess the extent of Coronavirus-related disruption to health and social care treatment and social interactions among people with lived or living experience of substance use in Scotland, and explore potential reasons for variations in disruption. DESIGN: Cross sectional mixed methods interview, incorporating a social network 'egonet interview' approach asking about whether participants had interactions with a range of substance use, health, social care or third sector organisations, or informal social interactions. SETTING: Five Alcohol and Drug Partnership Areas in Scotland. PARTICIPANTS: 57 (42% women) participants were involved in the study, on average 42 years old. MEASUREMENTS: Five-point Likert scale reporting whether interactions with a range of services and people had gotten much better, better, no different (or no change), worse, or much worse since COVID19 and lockdown. Ratings were nested within participants (Individuals provided multiple ratings) and some ratings were also nested within treatment service (services received multiple ratings). The nested structure was accounted for using cross classified ordinal logistic multilevel models. FINDINGS: While the overall average suggested only a slight negative change in interactions (mean rating 2.93), there were substantial variations according to type of interaction, and between individuals. Reported change was more often negative for mental health services (Adjusted OR = 0.93 95% CI 0.17,0.90), and positive for pharmacies (3.03 95% CI 1.36, 5.93). The models found between-participant variation of around 10%, and negligible between-service variation of around 1% in ratings. Ratings didn't vary by individual age or gender but there was variation between areas. CONCLUSIONS: Substance use treatment service adaptations due to COVID19 lockdown led to both positive and negative service user experiences. Social network methods provide an effective way to describe complex system-wide interaction patterns, and to measure variations at the individual, service, and area level.

The Influence of Computed Tomography Contrast Agent on Radiation-Induced Gene Expression and Double-Strand Breaks.

After nuclear scenarios, combined injuries of acute radiation syndrome (ARS) with, e.g., abdominal trauma, will occur and may require contrast-enhanced computed tomography (CT) scans for diagnostic purposes. Here, we investigated the effect of iodinated contrast agents on radiation-induced gene expression (GE) changes used for biodosimetry (AEN, BAX, CDKN1A, EDA2R, APOBEC3H) and for hematologic ARS severity prediction (FDXR, DDB2, WNT3, POU2AF1), and on the induction of double-strand breaks (DSBs) used for biodosimetry. Whole blood samples from 10 healthy donors (5 males, 5 females, mean age: 28 ± 2 years) were irradiated with X rays (0, 1 and 4 Gy) with and without the addition of iodinated contrast agent (0.016 ml contrast agent/ml blood) to the blood prior to the exposure. The amount of contrast agent was set to be equivalent to the blood concentration of an average patient (80 kg) during a contrast-enhanced CT scan. After irradiation, blood samples were incubated at 37°C for 20 min (DSB) and 8 h (GE, DSB). GE was measured employing quantitative real-time polymerase chain reaction. DSB foci were revealed by γH2AX + 53BP1 immunostaining and quantified automatically in >927 cells/sample. Radiation-induced differential gene expression (DGE) and DSB foci were calculated using the respective unexposed sample without supplementation of contrast agent as the reference. Neither the GE nor the number of DSB foci was significantly (P = 0.07-0.94) altered by the contrast agent application. However, for some GE and DSB comparisons with/without contrast agent, there were weakly significant differences (P = 0.03-0.04) without an inherent logic and thus are likely due to inter-individual variation. In nuclear events, the diagnostics of combined injuries can require the use of an iodinated contrast agent, which, according to our results, does not alter or influence radiation-induced GE changes and the quantity of DSB foci. Therefore, the gene expression and γH2AX focus assay can still be applied for biodosimetry and/or hematologic ARS severity prediction in such scenarios.

Validation of genes for H-ARS severity prediction in leukemia patients - interspecies comparison, challenges, and promises.

PURPOSE: In a previous baboon-study, a total of 29 genes were identified for clinical outcome prediction of the hematologic, acute, radiation, syndrome (H-ARS) severity. Among them, four genes (FDXR, DDB2, POU2AF1, WNT3) appeared promising and were validated in five leukemia patients. Within this study, we sought further in-vivo validation in a larger number of whole-body irradiated patients. MATERIAL AND METHODS: Peripheral blood was drawn from 10 leukemia patients before and up to 3 days during a fractionated (2 Gy/day) total-body irradiation (TBI) with 2-12Gy. After RNA-isolation, gene expression (GE) was evaluated on 31 genes widely used in biodosimetry and H-ARS prediction employing qRT-PCR. A customized low-density-array (LDA) allowed simultanously analyzing all genes, the 96-well format further examined the four most promising genes. Fold-changes (FC) in GE relative to pre-irradiation were calculated. RESULTS: Five patients suffering from acute-lymphoblastic-leukemia (ALL) respectively non-Hodgkin-lymphoma (NHL) revealed sufficient RNA-amounts and corresponding lymphocyte and neutrophile counts for running qRT-PCR, while acute-myeloid-leukemia (AML) and one myelofibrosis patient could not supply enough RNA. Generally, 1-2µg total RNA was isolated, whereas up to 10-fold differences in RNA-quantities (associated suppressed GE-changes) were identified among pre-exposure and exposure samples. From 31 genes, 23 were expressed in at least one of the pre-exposure samples. Relative to pre-exposure, the number of expressed genes could halve at 48 and 72h after irradiation. Using the LDA, 13 genes were validated in human samples. The four most promising genes (vid. sup.) were either undetermined or too close to pre-exposure. However, they were measured using the more sensitive 96-well format, except WNT3, which wasn´t detectable. As in previous studies, an opposite regulation in GE for FDXR in leukemia patients (up-regulated) relative to baboons (down-regulated) was reconfirmed. Radiation-induced GE-changes of DDB2 (up-regulated) and POU2AF1 (down-regulated) behaved similarly in both species. Hence, 16 out of 23 genes of two species showed GE-changes in the same direction, and up-regulated FDXR as in human studies were revalidated. CONCLUSION: Identified genes for H-ARS severity prediction, previously detected in baboons, were validated in ALL but not in AML patients. Limitations related to leukemia type, associated reduced RNA amounts, suppressed GE changes, and methodological challenges must be considered as factors negatively affecting the total number of validated genes. Based on that, we propose additional controls including blood cell counts and preferably fluorescence-based RNA quantity measurements for selecting promising samples and using a more sensitive 96-well format for candidate genes with low baseline copy numbers.

Liquid Biopsy in Whole Blood for Identification of Gene Expression Patterns (mRNA and miRNA) Associated with Recurrence of Glioblastoma WHO CNS Grade 4.

GBM WHO CNS Grade 4 represents a major challenge for oncology due to its aggressive behavior. Conventional imaging has restrictions in detecting tumor recurrence. This prospective study aims to identify gene-based biomarkers in whole blood instead of isolating exosomes for the early detection of tumor recurrence. Blood samples (n = 33) were collected from seven GBM patients at time points before and after surgery as well as upon tumor recurrence. Four tumor tissue samples were assessed in parallel. Next-generation sequencing (NGS), including mRNA-seq and small RNA-seq, was used to analyze gene expression profiles in blood samples and tumor tissues. A novel filtering pipeline was invented to narrow down potential candidate genes. In total, between 6-93 mRNA and 1-19 small RNA candidates could be identified among the seven patients. The overlap of genes between the patients was minimal, indicating significant inter-individual variance among GBM patients. In summary, this prospective study supports the applicability of gene expression measurements in whole blood for the detection of tumor recurrence. It might provide an alternative to the challenging workflow of liquid biopsy after laborious exosome isolation from whole blood.