An AI-based segmentation and analysis pipeline for high-field MR monitoring of cerebral organoids.

Cerebral organoids recapitulate the structure and function of the developing human brain in vitro, offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desirable. This work presents a novel non-invasive approach to monitor and analyze cerebral organoids over time using high-field magnetic resonance imaging and state-of-the-art tools for automated image analysis. Three specific objectives are addressed, (I) organoid segmentation to investigate organoid development over time, (II) global cysticity classification and (III) local cyst segmentation for organoid quality assessment. We show that organoid growth can be monitored reliably over time and cystic and non-cystic organoids can be separated with high accuracy, with on par or better performance compared to state-of-the-art tools applied to brightfield imaging. Local cyst segmentation is feasible but could be further improved in the future. Overall, these results highlight the potential of the pipeline for clinical application to larger-scale comparative organoid analysis.

In vivo nanoparticle-based T cell imaging can predict therapy response towards adoptive T cell therapy in experimental glioma.

Rationale: Intrinsic brain tumors, such as gliomas are largely resistant to immunotherapies including immune checkpoint blockade. Adoptive cell therapies (ACT) including chimeric antigen receptor (CAR) or T cell receptor (TCR)-transgenic T cell therapy targeting glioma-associated antigens are an emerging field in glioma immunotherapy. However, imaging techniques for non-invasive monitoring of adoptively transferred T cells homing to the glioma microenvironment are currently lacking. Methods: Ultrasmall iron oxide nanoparticles (NP) can be visualized non-invasively by magnetic resonance imaging (MRI) and dedicated MRI sequences such as T2* mapping. Here, we develop a protocol for efficient ex vivo labeling of murine and human TCR-transgenic and CAR T cells with iron oxide NPs. We assess labeling efficiency and T cell functionality by flow cytometry and transmission electron microscopy (TEM). NP labeled T cells are visualized by MRI at 9.4 T in vivo after adoptive T cell transfer and correlated with 3D models of cleared brains obtained by light sheet microscopy (LSM). Results: NP are incorporated into T cells in subcellular cytoplasmic vesicles with high labeling efficiency without interfering with T cell viability, proliferation and effector function as assessed by cytokine secretion and antigen-specific killing assays in vitro. We further demonstrate that adoptively transferred T cells can be longitudinally monitored intratumorally by high field MRI at 9.4 Tesla in a murine glioma model with high sensitivity. We find that T cell influx and homogenous spatial distribution of T cells within the TME as assessed by T2* imaging predicts tumor response to ACT whereas incomplete T cell coverage results in treatment resistance. Conclusion: This study showcases a rational for monitoring adoptive T cell therapies non-invasively by iron oxide NP in gliomas to track intratumoral T cell influx and ultimately predict treatment outcome.

MR microscopy to assess clot composition following mechanical thrombectomy predicts recanalization and clinical outcome.

BACKGROUND: Mechanical thrombectomy (MT) is the standard of care for patients with a stroke and large vessel occlusion. Clot composition is not routinely assessed in clinical practice as no specific diagnostic value is attributed to it, and MT is performed in a standardized 'non-personalized' approach. Whether different clot compositions are associated with intrinsic likelihoods of recanalization success or treatment outcome is unknown. METHODS: We performed a prospective, non-randomized, single-center study and analyzed the clot composition in 60 consecutive patients with ischemic stroke undergoing MT. Clots were assessed by ex vivo multiparametric MRI at 9.4 T (MR microscopy), cone beam CT, and histopathology. Clot imaging was correlated with preinterventional CT and clinical data. RESULTS: MR microscopy showed red blood cell (RBC)-rich (21.7%), platelet-rich (white,38.3%) or mixed clots (40.0%) as distinct morphological entities, and MR microscopy had high accuracy of 95.4% to differentiate clots. Clot composition could be further stratified on preinterventional non-contrast head CT by quantification of the hyperdense artery sign. During MT, white clots required more passes to achieve final recanalization and were not amenable to contact aspiration compared with mixed and RBC-rich clots (maneuvers: 4.7 vs 3.1 and 1.2 passes, P<0.05 and P<0.001, respectively), whereas RBC-rich clots showed higher probability of first pass recanalization (76.9%) compared with white clots (17.4%). White clots were associated with poorer clinical outcome at discharge and 90 days after MT. CONCLUSION: Our study introduces MR microscopy to show that the hyperdense artery sign or MR relaxometry could guide interventional strategy. This could enable a personalized treatment approach to improve outcome of patients undergoing MT.

A Cellular Ground Truth to Develop MRI Signatures in Glioma Models by Correlative Light Sheet Microscopy and Atlas-Based Coregistration.

Glioblastoma is the most common malignant primary brain tumor with poor overall survival. Magnetic resonance imaging (MRI) is the main imaging modality for glioblastoma but has inherent shortcomings. The molecular and cellular basis of MR signals is incompletely understood. We established a ground truth-based image analysis platform to coregister MRI and light sheet microscopy (LSM) data to each other and to an anatomic reference atlas for quantification of 20 predefined anatomic subregions. Our pipeline also includes a segmentation and quantification approach for single myeloid cells in entire LSM datasets. This method was applied to three preclinical glioma models in male and female mice (GL261, U87MG, and S24), which exhibit different key features of the human glioma. Multiparametric MR data including T2-weighted sequences, diffusion tensor imaging, T2 and T2* relaxometry were acquired. Following tissue clearing, LSM focused on the analysis of tumor cell density, microvasculature, and innate immune cell infiltration. Correlated analysis revealed differences in quantitative MRI metrics between the tumor-bearing and the contralateral hemisphere. LSM identified tumor subregions that differed in their MRI characteristics, indicating tumor heterogeneity. Interestingly, MRI signatures, defined as unique combinations of different MRI parameters, differed greatly between the models. The direct correlation of MRI and LSM allows an in-depth characterization of preclinical glioma and can be used to decipher the structural, cellular, and, likely, molecular basis of tumoral MRI biomarkers. Our approach may be applied in other preclinical brain tumor or neurologic disease models, and the derived MRI signatures could ultimately inform image interpretation in a clinical setting.SIGNIFICANCE STATEMENT We established a histologic ground truth-based approach for MR image analyses and tested this method in three preclinical glioma models exhibiting different features of glioblastoma. Coregistration of light sheet microscopy to MRI allowed for an evaluation of quantitative MRI data in histologically distinct tumor subregions. Coregistration to a mouse brain atlas enabled a regional comparison of MRI parameters with a histologically informed interpretation of the results. Our approach is transferable to other preclinical models of brain tumors and further neurologic disorders. The method can be used to decipher the structural, cellular, and molecular basis of MRI signal characteristics. Ultimately, information derived from such analyses could strengthen the neuroradiological evaluation of glioblastoma as they enhance the interpretation of MRI data.

Supporting the planning of urban blue-green infrastructure for biodiversity: A multi-scale prioritisation framework.

Primary considerations for urban blue-green infrastructure (BGI) encompass sustainable stormwater/urban heat management while biodiversity conservation is often considered an inherent benefit rather than a core planning requirement. However, ecological function of BGI as 'stepping stones' or linear corridors for otherwise fragmented habitats is undisputed. While quantitative approaches for modelling ecological connectivity in conservation planning are well established, mismatches in scope and scale with models that support the planning of BGI makes their adoption and integration difficult across disciplines. Technical complexities have led to ambiguity around circuit and network-based approaches, focal node placement, spatial extents, and resolution. Furthermore, these approaches are often computationally intensive, and considerable gaps remain in their use for identifying local-scale critical "pinch-points" that urban planners may respond to with the integration of BGI interventions that address biodiversity enhancement among other ecosystem services. Here, we present a framework that simplifies and integrates the merits of regional connectivity assessments with a focus on urban areas to prioritise BGI planning interventions while reducing computational demands. Our framework facilitates: (1) modelling potential ecological corridors at a coarse regional scale, (2) prioritising local-scale BGI interventions based on the relative contribution of individual nodes in this regional network, and (3) inferring connectivity hot- and cold-spots for local-scale BGI interventions. We illustrate this in the Swiss lowlands, demonstrating how, compared to previous work, we are able to identify and rank different priority locations across the region for BGI interventions in support of biodiversity enhancement and how their local-scale functional design may be benefited by addressing specific environmental variables.

T cell-independent eradication of experimental glioma by intravenous TLR7/8-agonist-loaded nanoparticles.

Glioblastoma, the most common and aggressive primary brain tumor type, is considered an immunologically "cold" tumor with sparse infiltration by adaptive immune cells. Immunosuppressive tumor-associated myeloid cells are drivers of tumor progression. Therefore, targeting and reprogramming intratumoral myeloid cells is an appealing therapeutic strategy. Here, we investigate a ß-cyclodextrin nanoparticle (CDNP) formulation encapsulating the Toll-like receptor 7 and 8 (TLR7/8) agonist R848 (CDNP-R848) to reprogram myeloid cells in the glioma microenvironment. We show that intravenous monotherapy with CDNP-R848 induces regression of established syngeneic experimental glioma, resulting in increased survival rates compared with unloaded CDNP controls. Mechanistically, CDNP-R848 treatment reshapes the immunosuppressive tumor microenvironment and orchestrates tumor clearing by pro-inflammatory tumor-associated myeloid cells, independently of T cells and NK cells. Using serial magnetic resonance imaging, we identify a radiomic signature in response to CDNP-R848 treatment and ultrasmall superparamagnetic iron oxide (USPIO) imaging reveals that immunosuppressive macrophage recruitment is reduced by CDNP-R848. In conclusion, CDNP-R848 induces tumor regression in experimental glioma by targeting blood-borne macrophages without requiring adaptive immunity.

Use of pulsatile gonadotropin-releasing hormone (GnRH) in patients with functional hypothalamic amenorrhea (FHA) results in monofollicular ovulation and high cumulative live birth rates: a 25-year cohort.

PURPOSE: To analyze outcomes of pulsatile administration of gonadotropin-releasing hormone (GnRH) in infertile women diagnosed with functional hypothalamic amenorrhea (FHA). METHODS: A single-center retrospective cohort study was conducted from 1996 to 2020. Sixty-six patients with the diagnosis FHA that underwent therapy using the pulsatile GnRH pump for conception were included and analyzed. The primary outcome was the live birth rate (LBR). Secondary outcomes were the number of dominant follicles, ovulation rate, biochemical pregnancy rate (BPR), clinical pregnancy rate (CPR), miscarriage rate, and multiple pregnancy rate. A matched control group was selected to compare the birth weight of newborn children. RESULTS: During the study period, 66 patients with FHA underwent 82 treatments (14 of 66 patients had more than one treatment) and a total of 212 cycles (ovulation induction attempts) using pulsatile GnRH. The LBR per treatment was 65.9%. The ovulation rate per cycle was 96%, and monofollicular ovulation was observed in 75% of cycles. The BPR per treatment was 80.5%, and the cumulative CPR per treatment was 74.4%. The miscarriage rate was 11.5%. One dizygotic twin pregnancy was observed (1.6%). Average newborn birth weight (NBW) from patients with FHA was comparable to the control group. CONCLUSION(S): In patients with FHA, excellent pregnancy rates were achieved using the subcutaneous GnRH pump. The high cumulative LBR with normal NBW as well as low rates of multiple gestation indicate that the pulsatile GnRH pump represents a safer and more physiologic alternative to ovulation induction with injectable gonadotropins. TRIAL REGISTRATION: Ethics Committee Northwest and Central Switzerland (Ethikkommission Nordwest- und Zentralschweiz - EKNZ) - Project-ID 2020-01612.

Socio-technical networks of infrastructure management: Network concepts and motifs for studying digitalization, decentralization, and integrated management.

Networked infrastructure systems - including energy, transportation, water, and wastewater systems - provide essential services to society. Globally, these services are undergoing major transformative processes such as digitalization, decentralization, or integrated management. Such processes not only depend on technical changes in infrastructure systems but also include important social and socio-technical dimensions. In this article, we propose a socio-technical network perspective to study the ensemble of social actors and technical elements involved in an infrastructure system, and their complex relations. We conceptualize structurally explicit socio-technical networks of networked infrastructure systems based on methodological considerations from network analysis and draw on concepts from socio-technical system theories and social-ecological network studies. Based on these considerations, we suggest analytical methods to study basic network concepts such as density, reciprocity, and centrality in a socio-technical network. We illustrate socio-technical motifs, i.e., meaningful sub-structures in socio-technical networks of infrastructure management. Drawing on these, we describe how infrastructure systems can be analyzed in terms of digitalization, decentralization, and integrated management from a socio-technical network perspective. Using the example of urban wastewater systems, we illustrate an empirical application of our approach. The results of an empirical case study in Switzerland demonstrate the potential of socio-technical networks to promote a deeper understanding of complex socio-technical relations in networked infrastructure systems. We contend that such a deeper understanding could improve management practices of infrastructure systems and is becoming even more important for enabling future data-driven, decentralized, and more integrated infrastructure management.

Multi-level network dataset of ten Swiss wetlands governance cases based on qualitative interviews and quantitative surveys.

The dataset of this paper originated from quantitative online surveys and qualitative expert interviews with organizational actors relevant to the governance of ten Swiss wetlands from 2019 till 2021. Multi-level networks represent the wetlands governance for each of the ten cases. The collaboration networks of actors form the first level of the multi-level networks and are connected to multiple other network levels that account for the social and ecological systems those actors are active in. 521 actors relevant to the management of the ten wetlands are included in the collaboration networks; quantitative survey data exists for 71% of them. A unique feature of the collaboration networks is that it differentiates between positive and negative forms of collaboration specified based on actors' activity areas. Therefore, the data describes not only if actors collaborate but also how and where actors collaborate. Further additional two-mode networks (actor participation in forums and involvement in other regions outside the case area) are elicited in the survey and connected to the collaboration network. Finally, the dataset also contains data on ecological system interdependencies in the form of conceptual maps derived from 34 expert interviews (3-4 experts per case).

Transcellular blood-brain barrier disruption in malaria-induced reversible brain edema.

Brain swelling occurs in cerebral malaria (CM) and may either reverse or result in fatal outcome. It is currently unknown how brain swelling in CM reverses, as brain swelling at the acute stage is difficult to study in humans and animal models with reliable induction of reversible edema are not known. In this study, we show that reversible brain swelling in experimental murine CM can be induced reliably after single vaccination with radiation-attenuated sporozoites as proven by in vivo high-field magnetic resonance imaging. Our results provide evidence that brain swelling results from transcellular blood-brain barrier disruption (BBBD), as revealed by electron microscopy. This mechanism enables reversal of brain swelling but does not prevent persistent focal brain damage, evidenced by microhemorrhages, in areas of most severe BBBD. In adult CM patients magnetic resonance imaging demonstrate microhemorrhages in more than one third of patients with reversible edema, emphasizing similarities of the experimental model and human disease. Our data suggest that targeting transcellular BBBD may represent a promising adjunct therapeutic approach to reduce edema and may improve neurological outcome.

Kinetics of Heterogeneous Background in Stargardt's Disease over Time.

Stargardt's disease (STGD1) is caused by mutations in the ABCA4 gene. Different lesions characterised by decreased autofluorescence levels are found in fundus autofluorescence (FAF) from STGD1 patients and could be used as outcome indicators for disease progression. We investigated the fate of foci with reduced autofluorescence (FRA) within the heterogeneous background of STGD1 patients using FAF imaging. Genetically confirmed STGD1 patients presenting heterogeneous background autofluorescence on high-quality FAF images at a minimum of two visits at least 12 months apart were chosen. A grid centred on the fovea was used to define five different zones. Within each zone, five FRA were randomly selected for each eye. The eccentricity of foci was determined at different time points for each patient. Analysis of 175 randomly chosen FRA showed consistent centrifugal displacement over time, most notably in eyes showing areas with definitely decreased autofluorescence. Interestingly, FRA did not leave an area of hypo-autofluorescence on FAF in locations where they were previously located. These findings may help to better understand STGD1 progression, improve FAF interpretation, and shed light on the nature of heterogeneous background.

In Silico Analysis of Pathogenic CRB1 Single Nucleotide Variants and Their Amenability to Base Editing as a Potential Lead for Therapeutic Intervention.

Mutations in the Crumbs homolog 1 (CRB1) gene cause both autosomal recessive retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA). Since three separate CRB1 isoforms are expressed at meaningful levels in the human retina, base editing shows promise as a therapeutic approach. This retrospective analysis aims to summarise the reported pathogenic CRB1 variants and investigate their amenability to treatment with currently available DNA base editors. Pathogenic single nucleotide variants (SNVs) were extracted from the Leiden open-source variation database (LOVD) and ClinVar database and coded by mutational consequence. They were then analyzed for their amenability to currently available DNA base editors and available PAM sites from a selection of different Cas proteins. Of a total of 1115 unique CRB1 variants, 69% were classified as pathogenic SNVs. Of these, 62% were amenable to currently available DNA BEs. Adenine base editors (ABEs) alone have the potential of targeting 34% of pathogenic SNVs; 19% were amenable to a CBE while GBEs could target an additional 9%. Of the pathogenic SNVs targetable with a DNA BE, 87% had a PAM site for a Cas protein. Of the 33 most frequently reported pathogenic SNVs, 70% were targetable with a base editor. The most common pathogenic variant was c.2843G>A, p.Cys948Arg, which is targetable with an ABE. Since 62% of pathogenic CRB1 SNVs are amenable to correction with a base editor and 87% of these mutations had a suitable PAM site, gene editing represents a promising therapeutic avenue for CRB1-associated retinal degenerations.

Comparative evaluation of T-cell receptors in experimental glioma-draining lymph nodes.

BACKGROUND: Glioblastomas, the most common primary malignant brain tumors, are considered immunologically cold malignancies due to growth in an immune sanctuary site. While peptide vaccines have shown to generate intra-tumoral antigen-specific T cells, the identification of these tumor-specific T cells is challenging and requires detailed analyses of tumor tissue. Several studies have shown that CNS antigens may be transported via lymphatic drainage to cervical lymph nodes, where antigen-specific T-cell responses can be generated. Therefore, we investigated whether glioma-draining lymph nodes (TDLN) may constitute a reservoir of tumor-reactive T cells. METHODS: We addressed our hypothesis by flow cytometric analyses of chicken ovalbumin (OVA)-specific CD8+ T cells as well as T-cell receptor beta (TCRß) next-generation-sequencing (TCRß-NGS) of T cells from tumor tissue, TDLN, spleen, and inguinal lymph nodes harvested from experimental mouse GL261 glioma models. RESULTS: Longitudinal dextramer-based assessment of specific CD8+ T cells from TDLN did not show tumor model antigen reactivity. Unbiased immunogenomic analysis revealed a low overlap of TCRß sequences from glioma-infiltrating CD8+ T cells between mice. Enrichment scores, calculated by the ratio of productive frequencies of the different TCRß-CDR3 amino-acid (aa) rearrangements of CD8+ T cells derived from tumor, TDLN, inguinal lymph nodes, and spleen demonstrated a higher proportion of tumor-associated TCR in the spleen compared to TDLN. CONCLUSIONS: In experimental glioblastoma, our data did not provide evidence that glioma-draining cervical lymph nodes are a robust reservoir for spontaneous glioma-specific T cells highlighting the requirement for detailed analyses of glioma-infiltrating T cells for the discovery of tumor-specific TCR.

Barriers to the digital transformation of infrastructure sectors.

Digital technologies can be important to policy-makers and public servants, as these technologies can increase infrastructure performance and reduce environmental impacts. For example, utilizing data from sensors in sewer systems can improve their management, which in turn may result in better surface water quality. Whether such big data from sensors is utilized is, however, not only a technical issue, but also depends on different types of social and institutional conditions. Our article identifies individual, organizational, and institutional barriers at the level of sub-states that hinder the evaluation of data from sewer systems. We employ fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare 23 Swiss sub-states and find that two barriers at different levels can each hinder data evaluation on their own. More specifically, either a lack of vision at the individual level or a lack of resources at the organizational level hinder the evaluation of data. Findings suggest that taking into account different levels is crucial for understanding digital transformation in public organizations.

Local blood coagulation drives cancer cell arrest and brain metastasis in a mouse model.

Clinically relevant brain metastases (BMs) frequently form in cancer patients, with limited options for effective treatment. Circulating cancer cells must first permanently arrest in brain microvessels to colonize the brain, but the critical factors in this process are not well understood. Here, in vivo multiphoton laser-scanning microscopy of the entire brain metastatic cascade allowed unprecedented insights into how blood clot formation and von Willebrand factor (VWF) deposition determine the arrest of circulating cancer cells and subsequent brain colonization in mice. Clot formation in brain microvessels occurred frequently (>95%) and specifically at intravascularly arrested cancer cells, allowing their long-term arrest. An extensive clot embedded ∼20% of brain-arrested cancer cells, and those were more likely to successfully extravasate and form a macrometastasis. Mechanistically, the generation of tissue factor-mediated thrombin by cancer cells accounted for local activation of plasmatic coagulation in the brain. Thrombin inhibition by treatment with low molecular weight heparin or dabigatran and an anti-VWF antibody prevented clot formation, cancer cell arrest, extravasation, and the formation of brain macrometastases. In contrast, tumor cells were not able to directly activate platelets, and antiplatelet treatments did reduce platelet dispositions at intravascular cancer cells but did not reduce overall formation of BMs. In conclusion, our data show that plasmatic coagulation is activated early by intravascular tumor cells in the brain with subsequent clot formation, which led us to discover a novel and specific mechanism that is crucial for brain colonization. Direct or indirect thrombin and VWF inhibitors emerge as promising drug candidates for trials on prevention of BMs.

Nintedanib and a bi-specific anti-VEGF/Ang2 nanobody selectively prevent brain metastases of lung adenocarcinoma cells.

Brain metastases (BM) are an ever-increasing challenge in oncology, threatening quality of life and survival of many cancer patients. The majority of BM originate from lung adenocarcinoma, and stage III patients have a risk of 40-50% to develop BM in the first years of disease onset. As therapeutic options are limited, prevention of their occurrence is an attractive concept. Here we investigated whether Nintedanib (BIBF 1120), a tyrosine kinase inhibitor (TKI) targeting the VEGF pathway approved for lung adenocarcinoma, and the dual anti-VEGF-A/Ang2 nanobody BI836880 have the potential to prevent BM formation. A mouse model of brain metastasis from lung adenocarcinoma was used in which tumor cells were injected intracardially. Metastases formation occurred inside and outside of the brain and was followed by MRI, IVIS, and immunohistochemistry. BM were reduced in volume and number by both Nintedanib and the dual anti-VEGF-A/Ang2 nanobody, which translated into improved survival. Both compounds were able to normalize cerebral blood vessels at the site of brain metastatic lesions. Extracranial metastases, however, were not reduced, and meningeal metastases only partially. Interestingly, unspecific control IgG also lead to brain vessel normalization and reduction of brain and meningeal metastases. This data indicates a brain-specific group effect of antiangiogenic compounds with respect to metastasis prevention, most likely by preventing an early angiogenic switch. Thus, Nintedanib and BI836880 are promising candidates for future BM preventive study concepts in lung adenocarcinoma patients.

Characterization of experimental diabetic neuropathy using multicontrast magnetic resonance neurography at ultra high field strength.

In light of the limited treatment options of diabetic polyneuropathy (DPN) available, suitable animal models are essential to investigate pathophysiological mechanisms and to identify potential therapeutic targets. In vivo evaluation with current techniques, however, often provides only restricted information about disease evolution. In the study of patients with DPN, magnetic resonance neurography (MRN) has been introduced as an innovative diagnostic tool detecting characteristic lesions within peripheral nerves. We developed a novel multicontrast ultra high field MRN strategy to examine major peripheral nerve segments in diabetic mice non-invasively. It was first validated in a cross-platform approach on human nerve tissue and then applied to the popular streptozotocin(STZ)-induced mouse model of DPN. In the absence of gross morphologic alterations, a distinct MR-signature within the sciatic nerve was observed mirroring subtle changes of the nerves' fibre composition and ultrastructure, potentially indicating early re-arrangements of DPN. Interestingly, these signal alterations differed from previously reported typical nerve lesions of patients with DPN. The capacity of our approach to non-invasively assess sciatic nerve tissue structure and function within a given mouse model provides a powerful tool for direct translational comparison to human disease hallmarks not only in diabetes but also in other peripheral neuropathic conditions.

Heterogeneity of response to immune checkpoint blockade in hypermutated experimental gliomas.

Intrinsic malignant brain tumors, such as glioblastomas are frequently resistant to immune checkpoint blockade (ICB) with few hypermutated glioblastomas showing response. Modeling patient-individual resistance is challenging due to the lack of predictive biomarkers and limited accessibility of tissue for serial biopsies. Here, we investigate resistance mechanisms to anti-PD-1 and anti-CTLA-4 therapy in syngeneic hypermutated experimental gliomas and show a clear dichotomy and acquired immune heterogeneity in ICB-responder and non-responder tumors. We made use of this dichotomy to establish a radiomic signature predicting tumor regression after pseudoprogression induced by ICB therapy based on serial magnetic resonance imaging. We provide evidence that macrophage-driven ICB resistance is established by CD4 T cell suppression and Treg expansion in the tumor microenvironment via the PD-L1/PD-1/CD80 axis. These findings uncover an unexpected heterogeneity of response to ICB in strictly syngeneic tumors and provide a rationale for targeting PD-L1-expressing tumor-associated macrophages to overcome resistance to ICB.

Monitoring innate immune cell dynamics in the glioma microenvironment by magnetic resonance imaging and multiphoton microscopy (MR-MPM).

Rationale: Glioblastoma is the most frequent, primary brain tumor that is characterized by a highly immunosuppressive tumor microenvironment (TME). The TME plays a key role for tumor biology and the effectiveness of immunotherapies. Composition of the TME correlates with overall survival and governs therapy response. Non invasive assessment of the TME has been notoriously difficult. Methods: We have designed an in vivo imaging approach to non invasively visualize innate immune cell dynamics in the TME in a mouse glioma model by correlated MRI and multiphoton microscopy (MR-MPM) using a bimodal, fluorescently labeled iron oxide nanoparticle (NP). The introduction of Teflon cranial windows instead of conventional Titanium rings dramatically reduced susceptibility artifacts on MRI and allowed longitudinal MR-MPM imaging for innate immune cell tracking in the same animal. Results: We visualized tumor associated macrophage and microglia (TAM) dynamics in the TME and dissect the single steps of NP uptake by blood-born monocytes that give rise to tumor-associated macrophages. Next to peripheral NP-loading, we identified a second route of direct nanoparticle uptake via the disrupted blood-brain barrier to directly label tissue resident TAMs. Conclusion: Our approach allows innate immune cell tracking by MRI and multiphoton microscopy in the same animal to longitudinally investigate innate immune cell dynamics in the TME.

Retinal oedema in central retinal artery occlusion develops as a function of time.

PURPOSE: Time is the key criterion in the management of non-arteritic central retinal artery occlusion (NA-CRAO). However, the precise onset of vision loss is often difficult to determine. This study aimed to evaluate the temporal changes of retinal thickness in acute NA-CRAO and the potential of this parameter to be used as a surrogate marker to estimate the onset of retinal ischaemia. METHODS: Optical coherence tomography was used to continuously assess retinal thickness and oedema progression rate in six porcine eyes. Additionally, a retrospective analysis of 12 patients with acute NA-CRAO was performed to determine association strength and progression rate between retinal thickness and onset of ischaemia. All Optical coherence tomography (OCT) scans (pigs and NA-CRAO patients) were performed within an ischaemic time frame of up to 9 hr. RESULTS: Retinal oedema progression rate in pigs was 25.32 µm/hr [CI 95%: 24.24-26.40 µm/hr]. Retrospective analysis of the patients revealed a strong correlation between retinal oedema and duration of ischaemia (Spearman's rho = 0.77, p = 0.004) with an estimated progression rate of 10.02 µm/hr [CI 95%: 3.30-16.74 µm/hr]. CONCLUSION: Retinal thickness increases with oedema formation, and ischaemia onset is strongly correlated with this structural biomarker in both, pigs and NA-CRAO patients. Prospective clinical trials will have to determine the clinical feasibility of retinal thickness measurements as a biomarker to support clinical management of NA-CRAO.