Abstract: The leaf area index (LAI) is a key dynamic parameter in Vertical Greening Systems (VGS). It quantifies the total amount of leaf area in the canopy and largely determines the extent of co-benefits of VGS. Whereas many studies on VGS discuss the importance of the LAI, only few elaborate on the parameter itself, how it is determined and what the current limitations are in VGS. Moreover, although there is scientific consensus on the importance of LAI in VGS, specific non-destructive monitoring techniques for continuous LAI monitoring appear to be absent, which results in limited overall data on the LAI of VGS under different spatial and temporal conditions and problems in quantifying the benefits of VGS in practice. To fill these gaps, this paper specifically focuses on the LAI of VGS and its monitoring techniques. An overview of existing LAI monitoring techniques in the field of VGS is presented. To arrive at dedicated techniques, this is complemented by a thorough analysis of LAI monitoring techniques used in other research fields, e.g. agriculture and forestry. It is established that two indirect techniques for LAI monitoring are currently available in the VGS sector, but a proper standardized sampling methodology currently lacks. Monitoring techniques used in other sectors offer opportunities for developing dedicated monitoring methods for VGS, but require further research due to the specific features of VGS systems. Furthermore, guidelines are proposed for a more standardized LAI determination of reporting of LAI values in VGS.

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: Melanoma remains a deadly cancer despite significant advances in immune checkpoint blockade and targeted therapies. The incidence of melanoma is also growing worldwide, which highlights the need for novel treatment options and strategic combination of therapies. Here, we investigate non-thermal plasma (NTP), an ionized gas, as a promising, therapeutic option. In a melanoma mouse model, direct treatment of tumors with NTP results in reduced tumor burden and prolonged survival. Physical characterization of NTP treatment in situ reveals the deposited NTP energy and temperature associated with therapy response, and whole transcriptome analysis of the tumor identified several modulated pathways. NTP treatment also enhances the cancer-immunity cycle, as immune cells in both the tumor and tumor-draining lymph nodes appear more stimulated to perform their anti-cancer functions. Thus, our data suggest that local NTP therapy stimulates systemic, anti-cancer immunity. We discuss, in detail, how these fundamental insights will help direct the translation of NTP technology into the clinic and inform rational combination strategies to address the challenges in melanoma therapy.

Abstract: Road traffic is the most widespread environmental noise source in Europe, proven to affect human health and well-being adversely. Noise barriers can be a very effective way to objectively reduce the noise levels to which the population is exposed, leading to positive effects on noise perception and quality of life. In this paper, surveys were used to assess subjective noise level indicators (annoyance and quality of life) from residents of the vicinity of a highway where obsolete noise barriers were to be replaced. %HA before the barrier replacement was measured from the surveys (26.8%) and estimated based on the acoustic simulation and two existing exposure/response relationships (14.6 and 18.8% before and 13.6 and 8.3% after). The difference in the measured %HA to those calculated from the ERRs shows that those models might not estimate %HA fairly for small samples or particular situations where high Lden is reported. Noise annoyance correlated differently with the quality of life indicators: a weak link was observed with health problems, while a strong correlation was found with the comfort level to perform activities outdoors. Objective noise measurements gave LA,eq,(15 min.) reductions of 4.1dB(A) due to the new barrier, while in acoustics models, calculated as Lday, expected this reduction to be 5.2 dB(A). After replacing the noise barriers, a second survey could still not be distributed due to the unknown effect of the COVID-19 measures that are still active