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Non-thermal plasma (NTP) shows promise as a potent anti-cancer therapy with both cytotoxic and immunomodulatory effects. In this study, we investigate the chemical and biological effects of NTP-induced oxidation on several key, determinant immune checkpoints of natural killer (NK) cell function. We used molecular dynamics (MD) and umbrella sampling simulations to investigate the effect of NTP-induced oxidative changes on the MHC-I complexes HLA-Cw4 and HLA-E. Our simulations indicate that these chemical alterations do not significantly affect the binding affinity of these markers to their corresponding NK cell receptor, which is supported with experimental read-outs of ligand expression on human head and neck squamous cell carcinoma cells after NTP application. Broadening our scope to other key ligands for NK cell reactivity, we demonstrate rapid reduction in CD155 and CD112, target ligands of the inhibitory TIGIT axis, and in immune checkpoint CD73 immediately after treatment. Besides these transient chemical alterations, the reactive species in NTP cause a cascade of downstream cellular reactions. This is underlined by the upregulation of the stress proteins MICA/B, potent ligands for NK cell activation, 24 h post treatment. Taken together, this work corroborates the immunomodulatory potential of NTP, and sheds light on the interaction mechanisms between NTP and cancer cells.

IntroductionImmune dysregulation plays a major role in cancer progression. The quantification of lymphocytic spatial inflammation may enable spatial system biology, improve understanding of therapeutic resistance, and contribute to prognostic imaging biomarkers.MethodsIn this paper, we propose a knowledge-guided deep learning framework to measure the lymphocytic spatial architecture on human H&E tissue, where the fidelity of training labels is maximized through single-cell resolution image registration of H&E to IHC. We demonstrate that such an approach enables pixel-perfect ground-truth labeling of lymphocytes on H&E as measured by IHC. We then experimentally validate our technique in a genetically engineered, immune-compromised Rag2 mouse model, where Rag2 knockout mice lacking mature lymphocytes are used as a negative experimental control. Such experimental validation moves beyond the classical statistical testing of deep learning models and demonstrates feasibility of more rigorous validation strategies that integrate computational science and basic science.ResultsUsing our developed approach, we automatically annotated more than 111,000 human nuclei (45,611 CD3/CD20 positive lymphocytes) on H&E images to develop our model, which achieved an AUC of 0.78 and 0.71 on internal hold-out testing data and external testing on an independent dataset, respectively. As a measure of the global spatial architecture of the lymphocytic microenvironment, the average structural similarity between predicted lymphocytic density maps and ground truth lymphocytic density maps was 0.86 ± 0.06 on testing data. On experimental mouse model validation, we measured a lymphocytic density of 96.5 ± %1% in a Rag2+/- control mouse, compared to an average of 16.2 ± %5% in Rag2-/- immune knockout mice (p

Rural areas are regaining attention as key resource holders. This includes the attractiveness of intact and traditional cultural elements and heritage which helps to create new opportunities. However, renewal is needed for rural areas to be competitive beyond tourism. Knowledge exchange and transfer is seen as an enabling tool for regeneration and heritage valorization, although it has mostly been applied in an urban context. The aim of this paper is to explore the role of capacity building and knowledge exchange at different levels in promoting rural regeneration through heritage-led initiatives. The article describes a multi-directional knowledge transfer and exchange in 19 rural areas. The applied knowledge exchange methodology was designed to be a dynamic and vibrant exchange of capacity building and mutual learning. This exchange of knowledge enabled the local communities involved to explore new ideas and viable solutions for the regeneration of rural areas through the valorization of cultural and natural heritage. The research findings show that structuring a knowledge transfer and capacity building process that also involves key local stakeholders and the rural communities is an important milestone in the regeneration process. In addition, it can be a unique opportunity to start and build new professional long-term relationships.

Chan before Chan: Meditation, Repentance, and Visionary Experience in Chinese Buddhism. By ERIC M. GREENE. Honolulu: UNIVERSITY OF HAWAI'I PRESS, 2021. Pp. xiv + 313. $68 (cloth); $20 (paper) Chan [...]

There appears to be no “one-size-fits-all” strategy for evolving from a car-dependent urban environment towards a well-balanced modal split. The search for a suitable mobility strategy for a particular setting can be framed as seeking a suitable governance strategy. This article explores the opportunities of design-driven participatory action research (DD-PAR) as a governance strategy for improving mobility within a context of weak governance by investigating a single case study conducted in Paramaribo North, Suriname. Despite available plans, designs, and policy proposals, Surinamese public authorities are struggling to improve mobility. Notwithstanding many efforts, clientelism and patronage are weakening the power of the government, resulting in unimplemented public initiatives. Moreover, there are few civil society organisations to advocate for this weak public power. This creates a context in which neither the government nor civil society is sufficiently equipped to realise the modal shift in Paramaribo. Governance strategies depending on strong government or proactive civil society (e.g., actor-based strategies) are thus not suitable. In contrast, DD-PAR appears to have potential as a governance strategy, as it uses research and academics as forces to create societal enthusiasm, establish actor networks, and generate action. The current case study identifies key actors and preconditions for building a network of actors. It also provides tentative insights into urban tactics for increasing pressure on the government to provide adequate infrastructure and policy to accommodate newly developed action that supports a more diverse modal split.

Objectives: A phase 1, double-blind, placebo-controlled trial was conducted to evaluate the safety, tolerability, and exploratory efficacy of repeat monthly doses of subcutaneous (SC) casirivimab and imdevimab (CAS+IMD) in uninfected adult volunteers. Methods: Participants were randomized (3:1) to SC CAS+IMD 1200 mg or placebo every 4 weeks for up to six doses. Primary and secondary end points evaluated safety, pharmacokinetics, and immunogenicity. Exploratory efficacy was evaluated by the incidence of COVID-19 or SARS-CoV-2 seroconversion. Results: In total, 969 participants received CAS+IMD. Repeat monthly dosing of SC CAS+IMD led to a 92.4% relative risk reduction in clinically defined COVID-19 compared with placebo (3/729 [0.4%] vs 13/240 [5.4%]; odds ratio 0.07 [95% CI 0.01-0.27]), and a 100% reduction in laboratory-confirmed COVID-19 (0/729 vs 10/240 [4.2%]; odds ratio 0.00). Development of anti-drug antibodies occurred in a small proportion of participants (

Introduction: Immune dysregulation plays a major role in cancer progression. The quantification of lymphocytic spatial inflammation may enable spatial system biology, improve understanding of therapeutic resistance, and contribute to prognostic imaging biomarkers. Methods: In this paper, we propose a knowledge-guided deep learning framework to measure the lymphocytic spatial architecture on human H&E tissue, where the fidelity of training labels is maximized through single-cell resolution image registration of H&E to IHC. We demonstrate that such an approach enables pixel-perfect ground-truth labeling of lymphocytes on H&E as measured by IHC. We then experimentally validate our technique in a genetically engineered, immune-compromised Rag2 mouse model, where Rag2 knockout mice lacking mature lymphocytes are used as a negative experimental control. Such experimental validation moves beyond the classical statistical testing of deep learning models and demonstrates feasibility of more rigorous validation strategies that integrate computational science and basic science. Results: Using our developed approach, we automatically annotated more than 111,000 human nuclei (45,611 CD3/CD20 positive lymphocytes) on H&E images to develop our model, which achieved an AUC of 0.78 and 0.71 on internal hold-out testing data and external testing on an independent dataset, respectively. As a measure of the global spatial architecture of the lymphocytic microenvironment, the average structural similarity between predicted lymphocytic density maps and ground truth lymphocytic density maps was 0.86 ± 0.06 on testing data. On experimental mouse model validation, we measured a lymphocytic density of 96.5 ± %1% in a Rag2+/- control mouse, compared to an average of 16.2 ± %5% in Rag2-/- immune knockout mice (p<0.0001, ANOVA-test). Discussion: These results demonstrate that CD3/CD20 positive lymphocytes can be accurately detected and characterized on H&E by deep learning and generalized across species. Collectively, these data suggest that our understanding of complex biological systems may benefit from computationally-derived spatial analysis, as well as integration of computational science and basic science. [ABSTRACT FROM AUTHOR]

Objectives: Decision‐making for patients with a locally advanced laryngeal carcinoma (T3 and T4) is challenging due to the treatment choice between organ preservation and laryngectomy, both with different and high impact on function and quality of life (QoL). The complexity of these treatment decisions and their possible consequences might lead to decisional conflict (DC). This study aimed to explore the level of DC in locally advanced laryngeal carcinoma patients facing curative decision‐making, and to identify possible associated factors. Methods: In this multicenter prospective cohort study, participants completed questionnaires on DC, level of shared decision‐making (SDM), and a knowledge test directly after counseling and 6 months after treatment. Descriptive statistics and Spearman correlation tests were used to analyze the data. Results: Directly after counseling, almost all participants (44/45; 98%) experienced Clinically Significant DC score (CSDC >25, scale 0–100). On average, patients scored 47% (SD 20%) correct on the knowledge test. Questions related to radiotherapy were answered best (69%, SD 29%), whilst only 35% (SD 29%) of the questions related to laryngectomy were answered correctly. Patients' perceived level of SDM (scale 0–100) was 70 (mean, SD 16.2), and for physicians this was 70 (SD 1.7). Conclusion: Most patients with advanced larynx cancer experience high levels of DC. Low knowledge levels regarding treatment aspects indicate a need for better patient counseling. Level of Evidence: 4 Laryngoscope, 134:3604–3610, 2024 [ABSTRACT FROM AUTHOR]