A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as ‘chemo fog’. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning.

This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research.

     

Effect of therapeutic administration of β-lactam antibiotics on the bacterial community and antibiotic resistance patterns in milk

Dairy cows with mastitis are frequently treated with antibiotics. The potential effect of antibiotics on the milk microbiome is still not clear. Therefore, the objective of this research was to investigate the effect of 2 commonly used cephalosporins on the milk microbiota of dairy cows and the antibiotic resistance genes in the milk. The milk samples were collected from 7 dairy cows at the period before medication (d 0), medication (d 1, 2, 3), withdrawal period (d 4, 6, 8), and the period after withdrawal (d 9, 11, 13, 15). We applied 16S rRNA sequencing to explore the microbiota changes, and antibiotic resistance patterns were investigated by quantitative PCR. The microbiota richness and diversity in each sample were calculated using the Chao 1 (richness), Shannon (diversity), and Simpson (diversity) indices. The cephalosporins treatment lowered the Simpson diversity value at the period of withdrawal. Members of the Enterobacter genera were the most affected bacteria associated with mastitis. Meanwhile, antibiotic resistance genes in the milk were also influenced by antibiotic treatment. The cephalosporins treatment raised the proportion of bla_TEM in milk samples at the period of withdrawal. Therefore, the treatment of cephalosporins led to change in the milk microbiota and increase of β-lactam resistance gene in the milk at the time of withdrawal period.     

Thin reference layers available for calibration purposes in ion beam analysis

Evaporated standard layers of metals deposited on light substrates (mainly vitreous carbon) are available which can be employed to reduce some of the key uncertainties in ion beam analysis. Their preparation and the determination of their accurate areal density by a unique in-vacuum weighing procedure are described. Examples of our own application of such reference layers in Rutherford backscattering spectrometry (RBS) and particle-induced X-ray emission (PIXE) analysis are presented, all serving to improve the analytical accuracy.