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Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Childrens Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

Pediatric brain tumors are the leading cause of cancer-related death in children in the United States and contribute a disproportionate number of potential years of life lost compared to adult cancers. Moreover, survivors frequently suffer long-term side effects, including secondary cancers. The Children's Brain Tumor Network (CBTN) is a multi-institutional international clinical research consortium created to advance therapeutic development through the collection and rapid distribution of biospecimens and data via open-science research platforms for real-time access and use by the global research community. The CBTN's 32 member institutions utilize a shared regulatory governance architecture at the Children's Hospital of Philadelphia to accelerate and maximize the use of biospecimens and data. As of August 2022, CBTN has enrolled over 4700 subjects, over 1500 parents, and collected over 65,000 biospecimen aliquots for research. Additionally, over 80 preclinical models have been developed from collected tumors. Multi-omic data for over 1000 tumors and germline material are currently available with data generation for > 5000 samples underway. To our knowledge, CBTN provides the largest open-access pediatric brain tumor multi-omic dataset annotated with longitudinal clinical and outcome data, imaging, associated biospecimens, child-parent genomic pedigrees, and in vivo and in vitro preclinical models. Empowered by NIH-supported platforms such as the Kids First Data Resource and the Childhood Cancer Data Initiative, the CBTN continues to expand the resources needed for scientists to accelerate translational impact for improved outcomes and quality of life for children with brain and spinal cord tumors.

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

RNA structural elements occur in numerous single-stranded positive-sense RNA viruses. The stem-loop 2 motif (s2m) is one such element with an unusually high degree of sequence conservation, being found in the 3' untranslated region (UTR) in the genomes of many astroviruses, some picornaviruses and noroviruses, and a variety of coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2. The evolutionary conservation and its occurrence in all viral subgenomic transcripts imply a key role for s2m in the viral infection cycle. Our findings indicate that the element, while stably folded, can nonetheless be invaded and remodeled spontaneously by antisense oligonucleotides (ASOs) that initiate pairing in exposed loops and trigger efficient sequence-specific RNA cleavage in reporter assays. ASOs also act to inhibit replication in an astrovirus replicon model system in a sequence-specific, dose-dependent manner and inhibit SARS-CoV-2 replication in cell culture. Our results thus permit us to suggest that the s2m element is readily targeted by ASOs, which show promise as antiviral agents. IMPORTANCE The highly conserved stem-loop 2 motif (s2m) is found in the genomes of many RNA viruses, including SARS-CoV-2. Our findings indicate that the s2m element can be targeted by antisense oligonucleotides. The antiviral potential of this element represents a promising start for further research into targeting conserved elements in RNA viruses.

Layered crystals are known to be good candidates for bulk thermoelectric applications as they open new ways to realise highly efficient devices. Two dimensional materials, isolated from layered materials, and their stacking into heterostructures have attracted intense research attention for nanoscale applications due to their high Seebeck coefficient and possibilities to engineer their thermoelectric properties. However, integration to thermoelectric devices is problematic due to their usually high thermal conductivities. Reporting on thermal transport studies between 150 and 300 K, we show that franckeite, a naturally occurring 2D heterostructure, exhibits a very low thermal conductivity which combined with its previously reported high Seebeck coefficient and electrical conductance make it a promising candidate for low dimensional thermoelectric applications. We find cross- and in-plane thermal conductivity values at room temperature of 0.70 and 0.88 W m−1 K−1, respectively, which is one of the lowest values reported today for 2D-materials. Interestingly, a 1.77 nm thick layer of franckeite shows very low thermal conductivity similar to one of the most widely used thermoelectric material Bi2Te3 with the thickness of 10–20 nm. We show that this is due to the low Debye frequency of franckeite and scattering of phonon transport through van der Waals interface between different layers. This observation open new routes for high efficient ultra-thin thermoelectric applications.

Liver pyruvate kinase (PKL) is a major regulator of metabolic flux and ATP production during liver cell glycolysis and is considered a potential drug target for the treatment of non-alcoholic fatty liver disease (NAFLD). In this study, we report the first ADP-competitive PKL inhibitors and identify several starting points for the further optimization of these inhibitors. Modeling and structural biology guided the optimization of a PKL-specific anthraquinone-based compound. A structure-activity relationship study of 47 novel synthetic derivatives revealed PKL inhibitors with half-maximal inhibitory concentration (IC50) values in the 200 nM range. Despite the difficulty involved in studying a binding site as exposed as the ADP site, these derivatives feature expanded structural diversity and chemical spaces that may be used to improve their inhibitory activities against PKL. The obtained results expand the knowledge of the structural requirements for interactions with the ADP-binding site of PKL., QC 20220530

Allogeneic transplant (alloHCT) and chimeric antigen receptor modified (CAR)-T cell therapy are potentially cuarative options of diffuse large B-cell lymphoma (DLBCL) relapsing after an autologous (auto)HCT. Although the Center for International Blood and Marrow Transplant Research (CIBMTR) prognostic model can predict outcomes of alloHCT in DLBCL after autoHCT failure, corresponding models of CAR-T treatment in similar patient populations are not available. In this noncomparative registry analysis, we report outcomes of patients with DLBCL (≥18 years) undergoing a reduced intensity alloHCT or CAR-T therapy with axicabtagene ciloleucel during 2012 to 2019 after a prior auto-HCT failure and apply the CIBMTR prognostic model to CAR-T recipients. A total of 584 patients were included. The 1-year relapse, nonrelapse mortality, overall survival (OS), and progression-free survival for CAR-T treatment after autoHCT failure were 39.5%, 4.8%, 73.4%, and 55.7%, respectively. The corresponding rates in the alloHCT cohort were 26.2%, 20.0%, 65.6%, and 53.8%, respectively. The 1-year OS of alloHCT recipients classified as low-, intermediate- and high/very high-risk groups according to the CIBMTR prognostic score was 73.3%, 59.9%, and 46.3%, respectively (P = .002). The corresponding rates for low-, intermediate-, and high/very high-risk CAR-T patients were 88.4%, 76.4%, and 52.8%, respectively (P < .001). This registry analysis shows that both CAR-T and alloHCT can provide durable remissions in a subset of patients with DLBCL relapsing after a prior autoHCT. The simple CIBMTR prognostic score can be used to identify patients at high risk of treatment failure after either procedure. Evaluation of novel relapse mitigations strategies after cellular immunotherapies are warranted in these high-risk patients.

Layered crystals are known to be good candidates for bulk thermoelectric applications as they open new ways to realise highly efficient devices. Two dimensional materials, isolated from layered materials, and their stacking into heterostructures have attracted intense research attention for nanoscale applications due to their high Seebeck coefficient and possibilities to engineer their thermoelectric properties. However, integration to thermoelectric devices is problematic due to their usually high thermal conductivities. Reporting on thermal transport studies between 150 and 300 K, we show that franckeite, a naturally occurring 2D heterostructure, exhibits a very low thermal conductivity which combined with its previously reported high Seebeck coefficient and electrical conductance make it a promising candidate for low dimensional thermoelectric applications. We find cross- and in-plane thermal conductivity values at room temperature of 0.70 and 0.88 W m−1 K−1, respectively, which is one of the lowest values reported today for 2D-materials. Interestingly, a 1.77 nm thick layer of franckeite shows very low thermal conductivity similar to one of the most widely used thermoelectric material Bi2Te3 with the thickness of 10–20 nm. We show that this is due to the low Debye frequency of franckeite and scattering of phonon transport through van der Waals interface between different layers. This observation open new routes for high efficient ultra-thin thermoelectric applications.

During the 21st century, human-environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human-environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.

During the 21st century, human-environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human-environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.

During the 21st century, human-environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human-environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.

During the 21st century, human-environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human-environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.

During the 21st century, human-environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human-environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.

Diffuse midline glioma (DMG) is a highly morbid pediatric brain tumor. Up to 80% of DMGs harbor mutations in histone H3-encoding genes, associated with poor prognosis. We previously showed the feasibility of detecting H3 mutations in circulating tumor DNA (ctDNA) in the liquid biome of children diagnosed with DMG. However, detection of low levels of ctDNA is highly dependent on platform sensitivity and sample type. To address this, we optimized ctDNA detection sensitivity and specificity across two commonly used digital droplet PCR (ddPCR) platforms (RainDance and BioRad), and validated methods for detecting H3F3A c.83A > T (H3.3K27M) mutations in DMG CSF, plasma, and primary tumor specimens across three different institutions. DNA was extracted from H3.3K27M mutant and H3 wildtype (H3WT) specimens, including H3.3K27M tumor tissue (n = 4), CSF (n = 6), plasma (n = 4), and human primary pediatric glioma cells (H3.3K27M, n = 2; H3WT, n = 1). ctDNA detection was enhanced via PCR pre-amplification and use of distinct custom primers and fluorescent LNA probes for c.83 A > T H3F3A mutation detection. Mutation allelic frequency (MAF) was determined and validated through parallel analysis of matched H3.3K27M tissue specimens (n = 3). We determined technical nuances between ddPCR instruments, and optimized sample preparation and sequencing protocols for H3.3K27M mutation detection and quantification. We observed 100% sensitivity and specificity for mutation detection in matched DMG tissue and CSF across assays, platforms and institutions. ctDNA is reliably and reproducibly detected in the liquid biome using ddPCR, representing a clinically feasible, reproducible, and minimally invasive approach for DMG diagnosis, molecular subtyping and therapeutic monitoring.

Graphene's (GR) remarkable mechanical and electrical properties - such as its Young's modulus, lowmass per unit area, natural atomic flatness and electrical conductance - would make it an ideal material for micro and nanoelectromechanical systems (MEMS and NEMS). However, the difficulty of attaching GR to supports coupled with naturally occurring internal defects in a few layer GR can significantly adversely affect the performance of such devices. Here, we have used a combined contact resonance atomic force microscopy (CR-AFM) and ultrasonic force microscopy (UFM) approach to characterise and map with nanoscale spatial resolution GR membrane properties inaccessible to most conventional scanning probe characterisation techniques. Using a multi-layer GR plate (membrane) suspended over a round hole we show that this combined approach allows access to the mechanical properties, internal structure and attachment geometry of the membrane providing information about both the supported and suspended regions of the system. We show that UFM allows the precise geometrical position of the supported membrane-substrate contact to be located and provides indication of the local variation of its quality in the contact areas. At the same time, we show that by mapping the position sensitive frequency and phase response of CR-AFM response, one can reliably quantify the membrane stiffness, and image the defects in the suspended area of the membrane. The phase and amplitude of experimental CR-AFM measurements show excellent agreement with an analytical model accounting for the resonance of the combined CR-AFM probe-membrane system. The combination of UFM and CR-AFM provide an beneficial combination for investigation of few-layer NEMS systems based on two dimensional materials.

BACKGROUNDPatients with diffuse midline gliomas (DMGs), including diffuse intrinsic pontine glioma (DIPG), have dismal outcomes. We previously described the H3.3K27M mutation as a shared neoantigen in HLA-A*02.01+, H3.3K27M+ DMGs. Within the Pacific Pediatric Neuro-Oncology Consortium, we assessed the safety and efficacy of an H3.3K27M-targeted peptide vaccine.METHODSNewly diagnosed patients, aged 3-21 years, with HLA-A*02.01+ and H3.3K27M+ status were enrolled in stratum A (DIPG) or stratum B (nonpontine DMG). Vaccine was administered in combination with polyinosinic-polycytidylic acid-poly-I-lysine carboxymethylcellulose (poly-ICLC) every 3 weeks for 8 cycles, followed by once every 6 weeks. Immunomonitoring and imaging were performed every 3 months. Imaging was centrally reviewed. Immunological responses were assessed in PBMCs using mass cytometry.RESULTSA total of 19 patients were enrolled in stratum A (median age,11 years) and 10 in stratum B (median age, 13 years). There were no grade-4 treatment-related adverse events (TRAEs). Injection site reaction was the most commonly reported TRAE. Overall survival (OS) at 12 months was 40% (95% CI, 22%-73%) for patients in stratum A and 39% (95% CI, 16%-93%) for patients in stratum B. The median OS was 16.1 months for patients who had an expansion of H3.3K27M-reactive CD8+ T cells compared with 9.8 months for their counterparts (P = 0.05). Patients with DIPG with below-median baseline levels of myeloid-derived suppressor cells had prolonged OS compared with their counterparts (P < 0.01). Immediate pretreatment dexamethasone administration was inversely associated with H3.3K27M-reactive CD8+ T cell responses.CONCLUSIONAdministration of the H3.3K27M-specific vaccine was well tolerated. Patients with H3.3K27M-specific CD8+ immunological responses demonstrated prolonged OS compared with nonresponders.TRIAL REGISTRATIONClinicalTrials.gov NCT02960230.FUNDINGThe V Foundation, the Pacific Pediatric Neuro-Oncology Consortium

Graphene's (GR) remarkable mechanical and electrical properties - such as its Young's modulus, lowmass per unit area, natural atomic flatness and electrical conductance - would make it an ideal material for micro and nanoelectromechanical systems (MEMS and NEMS). However, the difficulty of attaching GR to supports coupled with naturally occurring internal defects in a few layer GR can significantly adversely affect the performance of such devices. Here, we have used a combined contact resonance atomic force microscopy (CR-AFM) and ultrasonic force microscopy (UFM) approach to characterise and map with nanoscale spatial resolution GR membrane properties inaccessible to most conventional scanning probe characterisation techniques. Using a multi-layer GR plate (membrane) suspended over a round hole we show that this combined approach allows access to the mechanical properties, internal structure and attachment geometry of the membrane providing information about both the supported and suspended regions of the system. We show that UFM allows the precise geometrical position of the supported membrane-substrate contact to be located and provides indication of the local variation of its quality in the contact areas. At the same time, we show that by mapping the position sensitive frequency and phase response of CR-AFM response, one can reliably quantify the membrane stiffness, and image the defects in the suspended area of the membrane. The phase and amplitude of experimental CR-AFM measurements show excellent agreement with an analytical model accounting for the resonance of the combined CR-AFM probe-membrane system. The combination of UFM and CR-AFM provide an beneficial combination for investigation of few-layer NEMS systems based on two dimensional materials.

Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. Unfortunately, medical staff does not always follow the World Health Organization (WHO) hand washing guidelines in their everyday work. To this end, we present neural networks for automatically recognizing the different washing movements defined by the WHO. We train the neural network on a part of a large (2000+ videos) real-world labeled dataset with the different washing movements. The preliminary results show that using pre-trained neural network models such as MobileNetV2 and Xception for the task, it is possible to achieve >64 % accuracy in recognizing the different washing movements. We also describe the collection and the structure of the above open-access dataset created as part of this work. Finally, we describe how the neural network can be used to construct a mobile phone application for automatic quality control and real-time feedback for medical professionals.

BACKGROUNDPatients with diffuse midline gliomas (DMGs), including diffuse intrinsic pontine glioma (DIPG), have dismal outcomes. We previously described the H3.3K27M mutation as a shared neoantigen in HLA-A*02.01+, H3.3K27M+ DMGs. Within the Pacific Pediatric Neuro-Oncology Consortium, we assessed the safety and efficacy of an H3.3K27M-targeted peptide vaccine.METHODSNewly diagnosed patients, aged 3-21 years, with HLA-A*02.01+ and H3.3K27M+ status were enrolled in stratum A (DIPG) or stratum B (nonpontine DMG). Vaccine was administered in combination with polyinosinic-polycytidylic acid-poly-I-lysine carboxymethylcellulose (poly-ICLC) every 3 weeks for 8 cycles, followed by once every 6 weeks. Immunomonitoring and imaging were performed every 3 months. Imaging was centrally reviewed. Immunological responses were assessed in PBMCs using mass cytometry.RESULTSA total of 19 patients were enrolled in stratum A (median age,11 years) and 10 in stratum B (median age, 13 years). There were no grade-4 treatment-related adverse events (TRAEs). Injection site reaction was the most commonly reported TRAE. Overall survival (OS) at 12 months was 40% (95% CI, 22%-73%) for patients in stratum A and 39% (95% CI, 16%-93%) for patients in stratum B. The median OS was 16.1 months for patients who had an expansion of H3.3K27M-reactive CD8+ T cells compared with 9.8 months for their counterparts (P = 0.05). Patients with DIPG with below-median baseline levels of myeloid-derived suppressor cells had prolonged OS compared with their counterparts (P < 0.01). Immediate pretreatment dexamethasone administration was inversely associated with H3.3K27M-reactive CD8+ T cell responses.CONCLUSIONAdministration of the H3.3K27M-specific vaccine was well tolerated. Patients with H3.3K27M-specific CD8+ immunological responses demonstrated prolonged OS compared with nonresponders.TRIAL REGISTRATIONClinicalTrials.gov NCT02960230.FUNDINGThe V Foundation, the Pacific Pediatric Neuro-Oncology Consortium Fou

PURPOSE: Glioblastoma multiforme (GBM) and high-risk neuroblastoma are cancers with poor outcome. Immunotherapy in the form of neurotropic oncolytic viruses is a promising therapeutic strategy for these malignancies. Here we evaluate the oncolytic potential of the neurovirulent and partly interferon (IFN)-β-resistant Semliki Forest virus (SFV)-4 in GBMs and neuroblastomas. To reduce neurovirulence we constructed SFV4miRT, which is attenuated in normal CNS cells through insertion of microRNA target sequences for miR124, miR125, miR134 Experimental Design:Oncolytic activity of SFV4miRT was examined in mouse neuroblastoma and GBM cell lines and in patient-derived human glioblastoma cell cultures (HGCC). In vivo neurovirulence and therapeutic efficacy was evaluated in two syngeneic orthotopic glioma models (CT-2A, GL261) and syngeneic subcutaneous neuroblastoma model (NXS2). The role of IFN-β in inhibiting therapeutic efficacy was investigated. RESULTS: The introduction of microRNA target sequences reduced neurovirulence of SFV4 in terms of attenuated replication in mouse CNS cells and ability to cause encephalitis when administered intravenously. A single intravenous injection of SFV4miRT prolonged survival and cured 4 of 8 mice (50%) with NXS2 and 3 of 11 mice (27%) with CT-2A, but not for GL261 tumor bearing mice. In vivo therapeutic efficacy in different tumor models inversely correlated to secretion of IFN-β by respective cells upon SFV4 infection in vitro Similarly, killing efficacy of HGCC lines inversely correlated to IFN-β response and interferon-α⁄β receptor (IFNAR)-1 expression. CONCLUSIONS: SFV4miRT has reduced neurovirulence, while retaining its oncolytic potential. SFV4miRT is an excellent candidate for treatment of GBMs and neuroblastomas with low IFN-β secretion.

The primary objective of this thesis is to understand the behaviour of extreme events taking place in the foreign exchange (FX) and stock exchange (SX) markets around the Global Financial Crisis using parametric and non-parametric methods. Specifically, it models the evolution of the extreme values and Black Swans measures of daily stock returns and volatility proxies from a set of more than thirty SX and FX markets and compares their statistical properties in the pre- and post-crisis periods.My findings suggest that irrespective of the modelling approach followed, there are substantial differences in the tail-behaviour of the two periods that cannot be accounted for by the mainstream mean-variance model although the identification of latent Non-linearities in the underlying mean and/or variance dynamics does indeed lead to a significant reduction in tail asymmetry and kurtosis. Moreover, the mainstream parametric models prove insufficient in encompassing the volatility tails. Consequently, this study demonstrates that during times of extreme financial turbulence in financial markets the existing financial risk models are inadequate to provide guidance for the probability of extreme events taking place and subsequently underlines the need for additional research on parsimonious models and for the use of encyclopaedic exercise of judgment in the real-world risk management.

The primary objective of this thesis is to understand the behaviour of extreme events taking place in the foreign exchange (FX) and stock exchange (SX) markets around the Global Financial Crisis using parametric and non-parametric methods. Specifically, it models the evolution of the extreme values and Black Swans measures of daily stock returns and volatility proxies from a set of more than thirty SX and FX markets and compares their statistical properties in the pre- and post-crisis periods.My findings suggest that irrespective of the modelling approach followed, there are substantial differences in the tail-behaviour of the two periods that cannot be accounted for by the mainstream mean-variance model although the identification of latent Non-linearities in the underlying mean and/or variance dynamics does indeed lead to a significant reduction in tail asymmetry and kurtosis. Moreover, the mainstream parametric models prove insufficient in encompassing the volatility tails. Consequently, this study demonstrates that during times of extreme financial turbulence in financial markets the existing financial risk models are inadequate to provide guidance for the probability of extreme events taking place and subsequently underlines the need for additional research on parsimonious models and for the use of encyclopaedic exercise of judgment in the real-world risk management.

Merging unique performance of compound semiconductor (CS) III-V materials in optoelectronics, high frequency and power devices with mature Si manufacturing is a holy grail of modern semiconductor technology. The difference between lattice constants, processing, and chemistry are just a few major challenges to be resolved. With practically non-existing methods for studying nanoscale physical properties of these buried structures, we developed a new concept for fast and efficient 3D nanoscale resolution quantitative mapping of physical properties of CS materials and devices. We combine novel nano-sectioning using variable energy Ar ion beam targeted at the edge of the sample to create a perfectly flat oblique near-atomic flat section through all layers of interest, and the material sensitive scanning probe microscopy (SPM), to reveal 3D morphology, composition, strain and crystalline quality via local physical properties – mechanical and piezoelectric moduli, nanoscale heat conductance, workfunction and electrical conductivity. We can observe the propagation of antiphase domains (APD) from the GaAs-Si interface through the 3D structure, reporting for the first time APD effect on electronic properties of multiple quantum wells that are electrically short the structure evident on charge distribution nanomaps. In GaN nanowires, we directly observe NW/Si substrate interface, and unexpectedly find the in-NWs domains of the opposite polarity via piezoelectric moduli maps. The novel paradigm will make a disruptive change on how 3D structure and physical properties of CS and microelectronics materials and devices are currently studied.

Merging unique performance of compound semiconductor (CS) III-V materials in optoelectronics, high frequency and power devices with mature Si manufacturing is a holy grail of modern semiconductor technology. The difference between lattice constants, processing, and chemistry are just a few major challenges to be resolved. With practically non-existing methods for studying nanoscale physical properties of these buried structures, we developed a new concept for fast and efficient 3D nanoscale resolution quantitative mapping of physical properties of CS materials and devices. We combine novel nano-sectioning using variable energy Ar ion beam targeted at the edge of the sample to create a perfectly flat oblique near-atomic flat section through all layers of interest, and the material sensitive scanning probe microscopy (SPM), to reveal 3D morphology, composition, strain and crystalline quality via local physical properties – mechanical and piezoelectric moduli, nanoscale heat conductance, workfunction and electrical conductivity. We can observe the propagation of antiphase domains (APD) from the GaAs-Si interface through the 3D structure, reporting for the first time APD effect on electronic properties of multiple quantum wells that are electrically short the structure evident on charge distribution nanomaps. In GaN nanowires, we directly observe NW/Si substrate interface, and unexpectedly find the in-NWs domains of the opposite polarity via piezoelectric moduli maps. The novel paradigm will make a disruptive change on how 3D structure and physical properties of CS and microelectronics materials and devices are currently studied.

The primary objective of this thesis is to understand the behaviour of extreme events taking place in the foreign exchange (FX) and stock exchange (SX) markets around the Global Financial Crisis using parametric and non-parametric methods. Specifically, it models the evolution of the extreme values and Black Swans measures of daily stock returns and volatility proxies from a set of more than thirty SX and FX markets and compares their statistical properties in the pre- and post-crisis periods.My findings suggest that irrespective of the modelling approach followed, there are substantial differences in the tail-behaviour of the two periods that cannot be accounted for by the mainstream mean-variance model although the identification of latent Non-linearities in the underlying mean and/or variance dynamics does indeed lead to a significant reduction in tail asymmetry and kurtosis. Moreover, the mainstream parametric models prove insufficient in encompassing the volatility tails. Consequently, this study demonstrates that during times of extreme financial turbulence in financial markets the existing financial risk models are inadequate to provide guidance for the probability of extreme events taking place and subsequently underlines the need for additional research on parsimonious models and for the use of encyclopaedic exercise of judgment in the real-world risk management.

Identification and retrieval of soft tissue foreign bodies (STFBs) poses significant challenges in the emergency department. Prior studies have demonstrated the utility of ultrasound in identification and retrieval of STFBs, including radiolucent objects such as wood. We present a case of STFB extraction that utilizes ultrasound to identify the longitudinal axis of the object. With the longitudinal axis identified, the foreign body can be excised by making an incision where the foreign body is closest to the skin. The importance of this technique as it pertains to minimizing surrounding tissue destruction and discomfort for patients has not been previously reported.

Identification and retrieval of soft tissue foreign bodies (STFBs) poses significant challenges in the emergency department. Prior studies have demonstrated the utility of ultrasound in identification and retrieval of STFBs, including radiolucent objects such as wood. We present a case of STFB extraction that utilizes ultrasound to identify the longitudinal axis of the object. With the longitudinal axis identified, the foreign body can be excised by making an incision where the foreign body is closest to the skin. The importance of this technique as it pertains to minimizing surrounding tissue destruction and discomfort for patients has not been previously reported.

Development of novel high frequency Si, Si3N4, and graphene based micro-and nano-electromechanical systems (MEMS and NEMS) requires suitable characterization methods with nanoscale spatial resolution, high frequency (HF) response and high sensitivity. As spatial resolution of existing methods such as Laser Doppler Vibrometry (LDV) is limited by the light wavelength to the micrometre scale [1], it is tempting to use atomic force microscope (AFM) techniques offering nanoscale resolution. Here we use AFM to analyse the vibrations of nanoscale thin membranes over the frequency range from kHz to several MHz using both linear and nonlinear mechanisms for their excitation and detection. Our model system is a Si3N4 membrane (200 nm thickness, 500x500 um2, Agar Scientific) on a Si substrate. The AFM (Multimode, Nanoscope 8, Bruker) was modified with a piezoceramic transducer driven by the function generator to excite sample vibrations from kHz to about 10 MHz, with the resulting cantilever deflection detected by a standard lock-in-amplifier. The reference optical vibrometry (OFV-2670 and UHF-120, Polytec) found the membrane fundamental vibrational mode at ~250 KHz suggesting it to be under high tensile stress. The core idea of our study was to explore the possibility of detection HF membrane vibrations via AFM and effect of the probing tip contact on the resonance frequency. We used three AFM modes: 1) Force Modulation Microscopy (FMM) with tip vibrations detected at the excitation frequency, 2) nonlinear off-resonance regime where HF sample vibration is modulated at low frequency, and cantilever response measured at the modulation frequency (Ultrasonic Force Microscopy, UFM [2]), 3) UFM resonance regime, where the modulation frequency was around the membrane resonance (M-UFM). While the edge of a membrane was not detectable via topography, it was clearly visible in all ultrasonic modes. FMM mapping at swept excitation frequency showed that the cantilever-tip loading of the

Emerging quantum technologies require mastering thermal management, especially at the nanoscale. It is now accepted that thermal metamaterial-based phonon manipulation is possible, especially at sub-kelvin temperatures. In these extreme limits of low temperatures and dimensions, heat conduction enters a quantum regime where phonon exchange obeys the Landauer formalism. Phonon transport is then governed by the transmission coefficients between the ballistic conductor and the thermal reservoirs. Here we report on ultra-sensitive thermal experiments made on ballistic 1D phonon conductors using a micro-platform suspended sensor. Our thermal conductance measurements attain a power sensitivity of 15 attoWatts Hz−−−√−1 around 100 mK. Ballistic thermal transport is dominated by non-ideal transmission coefficients and not by the quantized thermal conductance of the nanowire itself. This limitation of heat transport in the quantum regime may have a significant impact on modern thermal management and thermal circuit design.

Advances in material design and device miniaturization lead to physical properties that may significantly differ from the bulk ones. In particular, thermal transport is strongly affected when the device dimensions approach the mean free path of heat carriers. Scanning Thermal Microscopy (SThM) is arguably the best approach for probing nanoscale thermal properties with few tens of nm lateral resolution. Typical SThM probes based on microfabricated Pd resistive probes (PdRP) using a spatially distributed heater and a nanoscale tip in contact with the sample provide high sensitivity and operation in ambient, vacuum, and liquid environments. Although some aspects of the response of this sensor have been studied, both for static and dynamic measurements, here we build an analytical model of the PdRP sensor taking into account finite dimensions of the heater that improves the precision and stability of the quantitative measurements. In particular, we analyse the probe response for heat flowing through a tip to the sample and due to probe selfheating and theoretically and experimentally demonstrate that they can differ by more than 50%, hence introducing significant correction in the SThM measurements. Furthermore, we analyzed the effect of environmental parameters such as sample and microscope stage temperatures and laser illumination, which allowed reducing the experimental scatter by a factor of 10. Finally, varying these parameters, we measured absolute values of heat resistances and compared these to the model for both ambient and vacuum SThM operations, providing a comprehensive pathway improving the precision of the nanothermal measurements in SThM.

Development of novel high frequency Si, Si3N4, and graphene based micro-and nano-electromechanical systems (MEMS and NEMS) requires suitable characterization methods with nanoscale spatial resolution, high frequency (HF) response and high sensitivity. As spatial resolution of existing methods such as Laser Doppler Vibrometry (LDV) is limited by the light wavelength to the micrometre scale [1], it is tempting to use atomic force microscope (AFM) techniques offering nanoscale resolution. Here we use AFM to analyse the vibrations of nanoscale thin membranes over the frequency range from kHz to several MHz using both linear and nonlinear mechanisms for their excitation and detection. Our model system is a Si3N4 membrane (200 nm thickness, 500x500 um2, Agar Scientific) on a Si substrate. The AFM (Multimode, Nanoscope 8, Bruker) was modified with a piezoceramic transducer driven by the function generator to excite sample vibrations from kHz to about 10 MHz, with the resulting cantilever deflection detected by a standard lock-in-amplifier. The reference optical vibrometry (OFV-2670 and UHF-120, Polytec) found the membrane fundamental vibrational mode at ~250 KHz suggesting it to be under high tensile stress. The core idea of our study was to explore the possibility of detection HF membrane vibrations via AFM and effect of the probing tip contact on the resonance frequency. We used three AFM modes: 1) Force Modulation Microscopy (FMM) with tip vibrations detected at the excitation frequency, 2) nonlinear off-resonance regime where HF sample vibration is modulated at low frequency, and cantilever response measured at the modulation frequency (Ultrasonic Force Microscopy, UFM [2]), 3) UFM resonance regime, where the modulation frequency was around the membrane resonance (M-UFM). While the edge of a membrane was not detectable via topography, it was clearly visible in all ultrasonic modes. FMM mapping at swept excitation frequency showed that the cantilever-tip loading of the

Development of novel high frequency Si, Si3N4, and graphene based micro-and nano-electromechanical systems (MEMS and NEMS) requires suitable characterization methods with nanoscale spatial resolution, high frequency (HF) response and high sensitivity. As spatial resolution of existing methods such as Laser Doppler Vibrometry (LDV) is limited by the light wavelength to the micrometre scale [1], it is tempting to use atomic force microscope (AFM) techniques offering nanoscale resolution. Here we use AFM to analyse the vibrations of nanoscale thin membranes over the frequency range from kHz to several MHz using both linear and nonlinear mechanisms for their excitation and detection. Our model system is a Si3N4 membrane (200 nm thickness, 500x500 um2, Agar Scientific) on a Si substrate. The AFM (Multimode, Nanoscope 8, Bruker) was modified with a piezoceramic transducer driven by the function generator to excite sample vibrations from kHz to about 10 MHz, with the resulting cantilever deflection detected by a standard lock-in-amplifier. The reference optical vibrometry (OFV-2670 and UHF-120, Polytec) found the membrane fundamental vibrational mode at ~250 KHz suggesting it to be under high tensile stress. The core idea of our study was to explore the possibility of detection HF membrane vibrations via AFM and effect of the probing tip contact on the resonance frequency. We used three AFM modes: 1) Force Modulation Microscopy (FMM) with tip vibrations detected at the excitation frequency, 2) nonlinear off-resonance regime where HF sample vibration is modulated at low frequency, and cantilever response measured at the modulation frequency (Ultrasonic Force Microscopy, UFM [2]), 3) UFM resonance regime, where the modulation frequency was around the membrane resonance (M-UFM). While the edge of a membrane was not detectable via topography, it was clearly visible in all ultrasonic modes. FMM mapping at swept excitation frequency showed that the cantilever-tip loading of the

Emerging quantum technologies require mastering thermal management, especially at the nanoscale. It is now accepted that thermal metamaterial-based phonon manipulation is possible, especially at sub-kelvin temperatures. In these extreme limits of low temperatures and dimensions, heat conduction enters a quantum regime where phonon exchange obeys the Landauer formalism. Phonon transport is then governed by the transmission coefficients between the ballistic conductor and the thermal reservoirs. Here we report on ultra-sensitive thermal experiments made on ballistic 1D phonon conductors using a micro-platform suspended sensor. Our thermal conductance measurements attain a power sensitivity of 15 attoWatts Hz−−−√−1 around 100 mK. Ballistic thermal transport is dominated by non-ideal transmission coefficients and not by the quantized thermal conductance of the nanowire itself. This limitation of heat transport in the quantum regime may have a significant impact on modern thermal management and thermal circuit design.

Advances in material design and device miniaturization lead to physical properties that may significantly differ from the bulk ones. In particular, thermal transport is strongly affected when the device dimensions approach the mean free path of heat carriers. Scanning Thermal Microscopy (SThM) is arguably the best approach for probing nanoscale thermal properties with few tens of nm lateral resolution. Typical SThM probes based on microfabricated Pd resistive probes (PdRP) using a spatially distributed heater and a nanoscale tip in contact with the sample provide high sensitivity and operation in ambient, vacuum, and liquid environments. Although some aspects of the response of this sensor have been studied, both for static and dynamic measurements, here we build an analytical model of the PdRP sensor taking into account finite dimensions of the heater that improves the precision and stability of the quantitative measurements. In particular, we analyse the probe response for heat flowing through a tip to the sample and due to probe selfheating and theoretically and experimentally demonstrate that they can differ by more than 50%, hence introducing significant correction in the SThM measurements. Furthermore, we analyzed the effect of environmental parameters such as sample and microscope stage temperatures and laser illumination, which allowed reducing the experimental scatter by a factor of 10. Finally, varying these parameters, we measured absolute values of heat resistances and compared these to the model for both ambient and vacuum SThM operations, providing a comprehensive pathway improving the precision of the nanothermal measurements in SThM.

Development of novel high frequency Si, Si3N4, and graphene based micro-and nano-electromechanical systems (MEMS and NEMS) requires suitable characterization methods with nanoscale spatial resolution, high frequency (HF) response and high sensitivity. As spatial resolution of existing methods such as Laser Doppler Vibrometry (LDV) is limited by the light wavelength to the micrometre scale [1], it is tempting to use atomic force microscope (AFM) techniques offering nanoscale resolution. Here we use AFM to analyse the vibrations of nanoscale thin membranes over the frequency range from kHz to several MHz using both linear and nonlinear mechanisms for their excitation and detection. Our model system is a Si3N4 membrane (200 nm thickness, 500x500 um2, Agar Scientific) on a Si substrate. The AFM (Multimode, Nanoscope 8, Bruker) was modified with a piezoceramic transducer driven by the function generator to excite sample vibrations from kHz to about 10 MHz, with the resulting cantilever deflection detected by a standard lock-in-amplifier. The reference optical vibrometry (OFV-2670 and UHF-120, Polytec) found the membrane fundamental vibrational mode at ~250 KHz suggesting it to be under high tensile stress. The core idea of our study was to explore the possibility of detection HF membrane vibrations via AFM and effect of the probing tip contact on the resonance frequency. We used three AFM modes: 1) Force Modulation Microscopy (FMM) with tip vibrations detected at the excitation frequency, 2) nonlinear off-resonance regime where HF sample vibration is modulated at low frequency, and cantilever response measured at the modulation frequency (Ultrasonic Force Microscopy, UFM [2]), 3) UFM resonance regime, where the modulation frequency was around the membrane resonance (M-UFM). While the edge of a membrane was not detectable via topography, it was clearly visible in all ultrasonic modes. FMM mapping at swept excitation frequency showed that the cantilever-tip loading of the

Thermal transport properties of amorphous materials at low temperatures are governed by the interaction between phonons and localized excitations referred to as tunneling two-level systems (TLSs). The temperature variation of the thermal conductivity of these amorphous materials is considered as universal and is characterized by a quadratic power law. This is well described by the phenomenological TLS model even though its microscopic explanation is still elusive. Here, by scaling down to the nanometer-scale amorphous systems much below the bulk phonon-TLS mean free path, we probe the robustness of that model in restricted geometry systems. Using very sensitive thermal conductance measurements, we demonstrate that the temperature dependence of the thermal conductance of silicon nitride nanostructures remains mostly quadratic independently of the nanowire section. It does not follow the cubic power law in temperature as expected in a Casimir-Ziman regime of boundary-limited thermal transport. This shows a thermal transport counterintuitively dominated by phonon-TLS interactions and not by phonon boundary scattering in the nanowires. This could be ascribed to an unexpected high density of TLSs on the surfaces which still dominates the phonon diffusion processes at low temperatures and explains why the universal quadratic temperature dependence of thermal conductance still holds for amorphous nanowires.

Thermal transport properties of amorphous materials at low temperatures are governed by the interaction between phonons and localized excitations referred to as tunneling two-level systems (TLSs). The temperature variation of the thermal conductivity of these amorphous materials is considered as universal and is characterized by a quadratic power law. This is well described by the phenomenological TLS model even though its microscopic explanation is still elusive. Here, by scaling down to the nanometer-scale amorphous systems much below the bulk phonon-TLS mean free path, we probe the robustness of that model in restricted geometry systems. Using very sensitive thermal conductance measurements, we demonstrate that the temperature dependence of the thermal conductance of silicon nitride nanostructures remains mostly quadratic independently of the nanowire section. It does not follow the cubic power law in temperature as expected in a Casimir-Ziman regime of boundary-limited thermal transport. This shows a thermal transport counterintuitively dominated by phonon-TLS interactions and not by phonon boundary scattering in the nanowires. This could be ascribed to an unexpected high density of TLSs on the surfaces which still dominates the phonon diffusion processes at low temperatures and explains why the universal quadratic temperature dependence of thermal conductance still holds for amorphous nanowires.

Alphavirus-based vector and replicon systems have been extensively used experimentally and are likely to be used in human and animal medicine. Whilst marker genes can be inserted easily under the control of a duplicated subgenomic promoter, these constructs are often genetically unstable. Here, a novel alphavirus construct is described in which an enhanced green fluorescent protein (EGFP) marker gene is inserted into the virus replicase open reading frame between nsP3 and nsP4, flanked by nsP2 protease-recognition sites. This construct has correct processing of the replicase polyprotein, produces viable virus and expresses detectable EGFP fluorescence upon infection of cultured cells and cells of the mouse brain. In comparison to parental virus, the marker virus has an approximately 1 h delay in virus RNA and infectious virus production. Passage of the marker virus in vitro and in vivo demonstrates good genetic stability. Insertion of different markers into this novel construct has potential for various applications.

BackgroundRadiation therapy is the most commonly used postsurgical treatment for primary malignant brain tumors. Consequently, investigating the efficacy of chemotherapeutics combined with radiation for treating malignant brain tumors is of high clinical relevance. In this study, we examined the cyclin-dependent kinase 4/6 inhibitor palbociclib, when used in combination with radiation for treating human atypical teratoid rhabdoid tumor (ATRT) as well as glioblastoma (GBM).MethodsEvaluation of treatment antitumor activity in vitro was based upon results from cell proliferation assays, clonogenicity assays, flow cytometry, and immunocytochemistry for DNA double-strand break repair. Interpretation of treatment antitumor activity in vivo was based upon bioluminescence imaging, animal subject survival analysis, and staining of tumor sections for markers of proliferation and apoptosis.ResultsFor each of the retinoblastoma protein (RB)-proficient tumor models examined (2 ATRTs and 2 GBMs), one or more of the combination therapy regimens significantly (P < .05) outperformed both monotherapies with respect to animal subject survival benefit. Among the combination therapy regimens, concurrent palbociclib and radiation treatment and palbociclib treatment following radiation consistently outperformed the sequence in which radiation followed palbociclib treatment. In vitro investigation revealed that the concurrent use of palbociclib with radiation, as well as palbociclib following radiation, inhibited DNA double-strand break repair and promoted increased tumor cell apoptosis.ConclusionsOur results support further investigation and possible clinical translation of palbociclib as an adjuvant to radiation therapy for patients with malignant brain tumors that retain RB expression.