In-vitro Optimization of Nanoparticle-Cell Labeling Protocols for In-vivo Cell Tracking Applications.

Recent advances in theranostic nanomedicine can promote stem cell and immune cell-based therapy. Gold nanoparticles (GNPs) have been shown to be promising agents for in-vivo cell-tracking in cell-based therapy applications. Yet a crucial challenge is to develop a reliable protocol for cell upload with, on the one hand, sufficient nanoparticles to achieve maximum visibility of cells, while on the other hand, assuring minimal effect of particles on cell function and viability. Previous studies have demonstrated that the physicochemical parameters of GNPs have a critical impact on their efficient uptake by cells. In the current study we have examined possible variations in GNP uptake, resulting from different incubation period and concentrations in different cell-lines. We have found that GNPs effectively labeled three different cell-lines - stem, immune and cancer cells, with minimal impairment to cell viability and functionality. We further found that uptake efficiency of GNPs into cells stabilized after a short period of time, while GNP concentration had a significant impact on cellular uptake, revealing cell-dependent differences. Our results suggest that while heeding the slight variations within cell lines, modifying the loading time and concentration of GNPs, can promote cell visibility in various nanoparticle-dependent in-vivo cell tracking and imaging applications.Israel Cancer Research Fund (ICRF), Israel Science Foundation (grant #749/14), Christians for Israel Chair in Medical Researc

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK

Squatter settlements and slums and sustainable development

Squatter settlement is defined as a low residential area, which has developed without legal right to the land or permission from the concerned authorities to build, and as a result, of their illegal status, infrastructure and services are usually inadequate (UN-Habitat 2003). On the other hand, slums are contiguous settlements where inhabitants are characterized by insecure residential status, inadequate access to safe water, inadequate access to sanitation and other basic infrastructure and services, poor housing quality, and overcrowding (UN-Habitat 2003). Both are form of informal settlements that are not formally planned

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study

Off-label psychopharmacologic prescribing for children: History supports close clinical monitoring

The review presents pediatric adverse drug events from a historical perspective and focuses on selected safety issues associated with off-label use of medications for the psychiatric treatment of youth. Clinical monitoring procedures for major psychotropic drug classes are reviewed. Prior studies suggest that systematic treatment monitoring is warranted so as to both minimize risk of unexpected adverse events and exposures to ineffective treatments. Clinical trials to establish the efficacy and safety of drugs currently being used off-label in the pediatric population are needed. In the meantime, clinicians should consider the existing evidence-base for these drugs and institute close clinical monitoring