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PURPOSE Novel biomarkers are needed to differentiate outcomes in intermediate-risk rhabdomyosarcoma (IR RMS). We sought to evaluate strategies for identifying circulating tumor DNA (ctDNA) in IR RMS and to determine whether ctDNA detection before therapy is associated with outcome. PATIENTS AND METHODS Pretreatment serum and tumor samples were available from 124 patients with newly diagnosed IR RMS from the Children's Oncology Group biorepository, including 75 patients with fusion-negative rhabdomyosarcoma (FN-RMS) and 49 with fusion-positive rhabdomyosarcoma (FP-RMS) disease. We used ultralow passage whole-genome sequencing to detect copy number alterations and a new custom sequencing assay, Rhabdo-Seq, to detect rearrangements and single-nucleotide variants. RESULTS We found that ultralow passage whole-genome sequencing was a method applicable to ctDNA detection in all patients with FN-RMS and that ctDNA was detectable in 13 of 75 serum samples (17%). However, the use of Rhabdo-Seq in FN-RMS samples also identified single-nucleotide variants, such as MYOD1 L122R, previously associated with prognosis. Identification of pathognomonic translocations between PAX3 or PAX7 and FOXO1 by Rhabdo-Seq was the best method for measuring ctDNA in FP-RMS and detected ctDNA in 27 of 49 cases (55%). Patients with FN-RMS with detectable ctDNA at diagnosis had significantly worse outcomes than patients without detectable ctDNA (event-free survival, 33.3% v 68.9%; P = .0028; overall survival, 33.3% v 83.2%; P < .0001) as did patients with FP-RMS (event-free survival, 37% v 70%; P = .045; overall survival, 39.2% v 75%; P = .023). In multivariable analysis, ctDNA was independently associated with worse prognosis in FN-RMS but not in the smaller FP-RMS cohort. CONCLUSION Our study demonstrates that baseline ctDNA detection is feasible and is prognostic in IR RMS.

Introduction/Background Endocrine therapy remains the fundamental treatment for advanced HR+ breast cancer (BC). For those patients who become refractory to endocrine therapy, resistance may be associated with mutations, amplifications, and fusions in the ESR1-encoded estrogen receptor. Here we examine the frequency of ESR1 alterations and the associated genomic landscape. Methods HR+/HER2- BC samples were sequenced with the OncomapTM ExTra assay, which uses whole-exome DNA sequencing with germline subtraction to detect somatic single nucleotide substitutions, indels, and copy number alterations (CNAs), and uses RNA sequencing to detect gene fusions. Tumor mutational burden (TMB) and microsatellite instability (MSI) are also reported. For analysis, BC samples were grouped by site: local (primary breast or regional lymph node) versus metastatic. Prior treatment history was unknown. Testing for a possible association between ESR1 and other biomarkers (genes, MSI, and TMB) was done using Fisher’s Exact Test (p≤0.05). Results A total of 988 HR+HER2- breast cancer patient samples were included in the analysis. Of these, 821 (83.1%) were local samples and the remaining 167 were metastatic samples, with liver (63, 37.7%), bone (20, 12.0%), skin (16, 9.6%) and chest wall (15, 9.0%) being the most common locations. ESR1 alterations were present in 84 tumor samples, 37 local and 47 metastatic, representing 4.5% and 28.1% of samples, respectively. ESR1 alterations included missense mutations (54 samples), fusions (29 samples), and amplifications (8 samples). The most common missense mutations were Y537S (20 samples, 37.0%), D538Q (20 samples, 37.0%), and E380Q (6 samples, 11.1%), which were located in the ligand binding domain and included both clonal and subclonal events. There were 30 ESR1 fusions identified, 17 (2.1%) in local and 13 in metastatic (7.7%) samples. Most fusions (24 samples, 82.8%) involved the same partner, CCDC170, while the other 6 fusions had unique partners. Examination of the 143 other biomarkers altered among ESR1-altered samples revealed 15 genes and MSI-high status that appeared to be over-represented (Table 1). However, none of the associations were statistically significant after correcting for multiple comparisons. Further, there was no evidence that the prevalence of ERBB2, TP53, AKT1 and PIK3CA alterations differed by ESR1 status (Table 1). Conclusions ESR1 alterations were significantly more common in HR+/HER2- metastatic breast cancer samples compared to local samples. Comprehensive genomic profiling with RNA sequencing identified both common and rare ESR1 fusions, which were most frequent in the metastatic samples. No significant difference in the molecular profile of ESR1 altered vs ESR1 wildtype samples was found in this cohort. Clinical trials with novel selective ER degraders (SERDs) to target these ESR1 alterations are ongoing. Table 1. Biomarkers that showed the highest association with ESR1 and other notable breast cancer biomarkers. Citation Format: Gargi Basu, Sameer S. Udhane, Susan Dombrowski, Lenny Hong, Fadel Alyaqoub, Michelle Barbi de Moura, Thiruppavai Chandrasekaran, Turgut Dogruluk, David Driscoll, Aimee Jalkanen, Pawan Noel, Szabolcs Szelinger, Min Wang, David Hall, Jess Hoag, Janine Lobello, Frederick Baehner, Snehal Thakkar, Joyce O’Shaughnessy. ESR1-alterations in HR+HER2- breast cancer patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-14-12.

Understanding the regulation of photosynthetic light harvesting and electron transfer is of great importance to efforts to improve the ability of the electron transport chain to supply downstream metabolism. A central regulator of the electron transport chain is ATP synthase, the molecular motor that harnesses the chemiosmotic potential generated from proton-coupled electron transport to synthesize ATP. ATP synthase is regulated both thermodynamically and post-translationally, with proposed phosphorylation sites on multiple subunits. In this study we focused on two N-terminal serines on the catalytic subunit β in tobacco (Nicotiana tabacum), previously proposed to be important for dark inactivation of the complex to avoid ATP hydrolysis at night. Here we show that there is no clear role for phosphorylation in the dark inactivation of ATP synthase. Instead, mutation of one of the two phosphorylated serine residues to aspartate to mimic constitutive phosphorylation strongly decreased ATP synthase abundance. We propose that the loss of N-terminal phosphorylation of ATPβ may be involved in proper ATP synthase accumulation during complex assembly.

OBJECTIVE The pediatric sepsis literature lacks studies examining the inpatient setting, yet sepsis remains a leading cause of death in children’s hospitals. More information is needed about sepsis arising in patients already hospitalized to improve morbidity and mortality outcomes. This study describes the clinical characteristics, process measures, and outcomes of inpatient sepsis cases compared with emergency department (ED) sepsis cases within the Improving Pediatric Sepsis Outcomes data registry from 46 hospitals that care for children. METHODS This retrospective cohort study included Improving Pediatric Sepsis Outcomes sepsis cases from January 2017 to December 2019 with onset in inpatient or ED. We used descriptive statistics to compare inpatient and ED sepsis metrics and describe inpatient sepsis outcomes. RESULTS The cohort included 26 855 cases; 8.4% were inpatient and 91.6% were ED. Inpatient cases had higher sepsis-attributable mortality (2.0% vs 1.4%, P = .025), longer length of stay after sepsis recognition (9 vs 5 days, P 40% of cases had a time from arrival to recognition within 12 hours. In 21% of cases, this time was >96 hours. Improved adherence to sepsis treatment bundles over time was associated with improved 30-day sepsis-attributable mortality for inpatients with sepsis. CONCLUSIONS Inpatient sepsis cases had longer lengths of stay, more need for intensive care, and higher vasopressor use. Sepsis-attributable mortality was significantly higher in inpatient cases compared with ED cases and improved with improved sepsis bundle adherence.

We present a platform to foster research in active scene understanding, consisting of high-fidelity simulated environments and a simple yet powerful API that controls a mobile robot in simulation and reality. In contrast to static, pre-recorded datasets that focus on the perception aspect of scene understanding, agency is a top priority in our work. We provide three levels of robot agency, allowing users to control a robot at varying levels of difficulty and realism. While the most basic level provides pre-defined trajectories and ground-truth localisation, the more realistic levels allow us to evaluate integrated behaviours comprising perception, navigation, exploration and SLAM. In contrast to existing simulation environments, we focus on robust scene understanding research using our environment interface (BenchBot) that provides a simple API for seamless transition between the simulated environments and real robotic platforms. We believe this scaffolded design is an effective approach to bridge the gap between classical static datasets without any agency and the unique challenges of robotic evaluation in reality. Our BenchBot Environments for Active Robotics (BEAR) consist of 25 indoor environments under day and night lighting conditions, a total of 1443 objects to be identified and mapped, and ground-truth 3D bounding boxes for use in evaluation. BEAR website: https://qcr.github.io/dataset/benchbot-bear-data/ .

All units managing hypertensive pregnant women should maintain and review uniform departmental management protocols and conduct regular audits of maternal & fetal outcomes. The cause(s) of pre-eclampsia and the optimal clinical management of the hypertensive disorders of pregnancy remain uncertain; therefore, we recommend that every hypertensive pregnant woman be offered an opportunity to participate in research, clinical trials and follow-up studies.

High resolution in weather and climate was always a common and ongoing goal of the community. In this regards, machine learning techniques accompanied numerical and statistical methods in recent years. Here we demonstrate that artificial intelligence can skilfully downscale low resolution climate model data when combined with numerical climate model data. We show that recently developed image inpainting technique perform accurate super-resolution via transfer learning using the HighResMIP of CMIP6 (Coupled Model Intercomparison Project Phase 6) experiments. Its huge data base offers a unique training opportunity for machine learning approaches. The transfer learning purpose allows also to downscale other CMIP6 experiments and models, as well as observational data like HadCRUT5. Combined with the technology of Kadow et al. 2020 of infilling missing climate data, we gain a neural network which reconstructs and downscales the important observational data set (IPCC AR6) at the same time. We further investigate the application of our method to downscale quantities predicted from a numerical ocean model (ICON-O) to improve computation times. In this process we focus on the ability of the model to predict eddies from low-resolution data.An extension to:Kadow, C., Hall, D.M. & Ulbrich, U. Artificial intelligence reconstructs missing climate information. Nature Geoscience 13, 408–413 (2020). https://doi.org/10.1038/s41561-020-0582-5

Supplemental Figure S6. Graphical User Interface for tissue segmentation, MYOD1 mutation prediction, and risk prediction models.

Purpose:Rhabdomyosarcoma (RMS) is an aggressive soft-tissue sarcoma, which primarily occurs in children and young adults. We previously reported specific genomic alterations in RMS, which strongly correlated with survival; however, predicting these mutations or high-risk disease at diagnosis remains a significant challenge. In this study, we utilized convolutional neural networks (CNN) to learn histologic features associated with driver mutations and outcome using hematoxylin and eosin (H&E) images of RMS.Experimental Design:Digital whole slide H&E images were collected from clinically annotated diagnostic tumor samples from 321 patients with RMS enrolled in Children's Oncology Group (COG) trials (1998–2017). Patches were extracted and fed into deep learning CNNs to learn features associated with mutations and relative event-free survival risk. The performance of the trained models was evaluated against independent test sample data (n = 136) or holdout test data.Results:The trained CNN could accurately classify alveolar RMS, a high-risk subtype associated with PAX3/7-FOXO1 fusion genes, with an ROC of 0.85 on an independent test dataset. CNN models trained on mutationally-annotated samples identified tumors with RAS pathway with a ROC of 0.67, and high-risk mutations in MYOD1 or TP53 with a ROC of 0.97 and 0.63, respectively. Remarkably, CNN models were superior in predicting event-free and overall survival compared with current molecular-clinical risk stratification.Conclusions:This study demonstrates that high-risk features, including those associated with certain mutations, can be readily identified at diagnosis using deep learning. CNNs are a powerful tool for diagnostic and prognostic prediction of rhabdomyosarcoma, which will be tested in prospective COG clinical trials.

Supplemental Figure S2. Sample partitioning for training and testing a TP53 mutation predictive model using K-fold cross-validation.

supplementary table legend

Supplemental Description of the Rhabdomyosarcoma Web-based Application

Supplemental Table S1. Whole slide image tissue segmentation statistics by an expert pathologist and probability prediction using a trained convolutional neural network. Supplemental Table S2. Clinical and molecular characteristics of FN-RMS samples used for training models for mutation prediction. Yellow boxes indicate genes included in defining the RAS pathway. Supplemental Table S3. Clinical information with COG risk stratification of FN-RMS samples used for training a prognostication predictive CNN.

Supplemental Figure S5. Frequency of mutations in COG and A.I. designated risk groups.

Supplemental Figure S3. Sample partitioning for training and testing a RAS pathway mutation predictive model using K-fold cross-validation. Three independent experiments were trained on a random selection of samples for training, validation and testing.

Supplemental Figure S4. Sample partitioning for training a MYOD1 mutation predictive model using K-fold cross-validation.

Supplemental Figure S1. Performance of A.I. model in classifying multiple samples from the same patient.

Purpose:Aurora A kinase (AAK) plays an integral role in mitotic entry, DNA damage checkpoint recovery, and centrosome and spindle maturation. Alisertib (MLN8237) is a potent and selective AAK inhibitor. In pediatric preclinical models, antitumor activity was observed in neuroblastoma, acute lymphoblastic leukemia, and sarcoma xenografts. We conducted a phase 2 trial of alisertib in pediatric patients with refractory or recurrent solid tumors or acute leukemias (NCT01154816).Patients and Methods:Alisertib (80 mg/m2/dose) was administered orally, daily for 7 days every 21 days. Pharmacogenomic (PG) evaluation for polymorphisms in the AURK gene and drug metabolizing enzymes (UGT1A1*28), and plasma pharmacokinetic studies (PK) were performed. Using a 2-stage design, patients were enrolled to 12 disease strata (10 solid tumor and 2 acute leukemia). Response was assessed after cycle 1, then every other cycle.Results:A total of 139 children and adolescents (median age, 10 years) were enrolled, 137 were evaluable for response. Five objective responses were observed (2 complete responses and 3 partial responses). The most frequent toxicity was myelosuppression. The median alisertib trough concentration on day 4 was 1.3 μmol/L, exceeding the 1 μmol/L target trough concentration in 67% of patients. No correlations between PG or PK and toxicity were observed.Conclusions:Despite alisertib activity in pediatric xenograft models and cogent pharmacokinetic-pharmacodynamic relationships in preclinical models and adults, the objective response rate in children and adolescents receiving single-agent alisertib was less than 5%.

Figure S1. Percentage of huCD45+ cells in blood (cardiac bleed) of engrafted mice at treatment initiation, then on Days 7, 21 and 42 for control (light grey), mice treated with Schedule A (7 days, BID, dark grey) or Schedule B (5 days BID X 3, black). The hatched bar corresponds to day 0. Medians and ranges are depicted. Figure S2. Percentage of huCD45+ cells in spleens of engrafted mice at treatment initiation, then on Days 7, 21 and 42 for control (light grey), mice treated with Schedule A (7 days, BID, dark grey) or Schedule B (5 days BID X 3, black). The hatched bar corresponds to day 0. Medians and ranges are depicted. Figure S3. Percentage of huCD45+ cells in bone marrows of engrafted mice at treatment initiation, then on Days 7, 21 and 42 for control (light grey), mice treated with Schedule A (7 days, BID, dark grey) or Schedule B (5 days BID X 3, black). The hatched bar corresponds to day 0. Medians and ranges are depicted. Table S1. Alisertib Pharmacokinetic Parameters Table S2. Summary table of in vivo drug responses

Background Relative to other pediatric cancers, survival for rhabdomyosarcoma (RMS) has not improved in recent decades, suggesting the need to enhance risk stratification. Therefore, we conducted a genome-wide association study for event-free survival (EFS) and overall survival (OS) to identify genetic variants associated with outcomes in individuals with RMS. Methods The study included 920 individuals with newly diagnosed RMS who were enrolled in Children’s Oncology Group protocols. To assess the association of each single nucleotide polymorphism (SNP) with EFS and OS, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using multivariable Cox proportional hazards models, adjusted for clinical covariates. All statistical tests were two sided. We also performed stratified analyses by histological subtype (alveolar and embryonal RMS) and carried out sensitivity analyses of statistically significant SNPs by PAX3/7-FOXO1 fusion status and genetic ancestry group. Results We identified that rs17321084 was associated with worse EFS (HR = 2.01, 95% CI = 1.59 to 2.53, P = 5.39 × 10−9) and rs10094840 was associated with worse OS (HR = 1.84, 95% CI = 1.48 to 2.27, P = 2.13 × 10−8). Using publicly available data, we found that rs17321084 lies in a binding region for transcription factors GATA2 and GATA3, and rs10094840 is associated with SPAG1 and RNF19A expression. We also identified that CTNNA3 rs2135732 (HR = 3.75, 95% CI = 2.34 to 5.99, P = 3.54 × 10−8) and MED31 rs74504320 (HR = 3.21, 95% CI = 2.12 to 4.86, P = 3.60 × 10−8) were associated with worse OS among individuals with alveolar RMS. Conclusions We demonstrated that common germline variants are associated with EFS and OS among individuals with RMS. Additional replication and investigation of these SNP effects may further support their consideration in risk stratification protocols.

Commercially developed monoclonal antibodies (mAb) have been effective in the prevention or treatment of SARS-CoV-2 infection1-3 but the rapid antigenic evolution of the Omicron sub-lineages has reduced their activity4-8 and they are no longer licensed for use in many countries. Here, we isolate spike binding monoclonal antibodies from vaccinees who suffered vaccine break-through infections with Omicron sublineages BA.4/5. We find that it is possible for antibodies targeting highly mutated regions to recover broad activity through allosteric effects (mAb BA.4/5-35) and characterise a pair of potent mAbs with extremely broad neutralization against current and historical SARS-CoV-2 variants. One, mAb BA.4/5-2, binds at the back of the left shoulder of the receptor binding domain (RBD) in an area which has resisted mutational change to date. The second, mAb BA.4/5-5, binds a conserved epitope in sub-domain 1 (SD1). The isolation of this pair of antibodies with non-overlapping epitopes shows that potent and extremely broadly neutralizing antibodies are still generated following infection and SD1 directed mAbs may increase the resilience of mAb therapeutics/prophylactics against SARS-CoV-2.

Funding: Engineering and Physical Sciences Research Council - EP/P010482/1; Leverhulme Trust - RPG-2016-047; Royal Society - SRF\R1\201089; China Scholarship Council - 201603780001; Horizon 2020 Framework Programme - 838885; Fonds De La Recherche Scientifique - FNRS - 2.5020.11; Fonds De La Recherche Scientifique - FNRS - F.4534.21; Horizon 2020 Framework Programme - 101023743. The use of thermally activated delayed fluorescence (TADF) emitters and emitters that show preferential horizontal orientation of their transition dipole moment (TDM) are two emerging strategies to enhance the efficiency of OLEDs. We present the first example of a liquid crystalline multi-resonance TADF (MR-TADF) emitter, DiKTa-LC. The compound possesses a nematic liquid crystalline phase between 80 °C and 110 °C. Importantly, the TDM of the spin-coated film shows preferential horizontal orientation, with an anisotropy factor, a, of 0.28, which is preserved in doped poly(vinylcarbazole) films. Green-emitting (λEL = 492 nm) solution-processed OLEDs based on DiKTa-LC showed an EQEmax of 13.6%. We thus demonstrate for the first time how self-assembly of a liquid crystalline TADF emitter can lead to the so-far elusive control of the orientation of the transition dipole in solution-processed films, which will be of relevance for high-performance solution-processed OLEDs. Publisher PDF

This article explores whether emissions pricing is sufficient to achieve the low-emissions transition in Aotearoa New Zealand. It draws on a critical review of the international literature on emissions pricing, policy interactions and political economy to make three broad arguments. First, that emissions pricing alone cannot be expected to induce the necessary levels of behaviour change and technological transition in the urgent time frame required. Second, non-pricing policies can deliver emissions reductions, even within the context of emissions trading under a volume cap. Third, even if emissions pricing could induce sufficient change, there are political economy constraints on reaching the adequate price in a feasible and equitable way. Consequently, we argue that the weight of evidence lies with utilising emissions pricing as part of a policy mix.

Tree planting has long played a major role in the New Zealand Government’s approach to climate mitigation and is increasingly understood as important for climate adaptation. However, large-scale tree planting in Aotearoa New Zealand has been dominated by exotic species. Although there is growing public and expert support for using native species for forest revegetation in farm landscapes, there are two key barriers. First, the lack of ecological and economic data on native species performance in different environmental conditions. Second, policy and market-related mechanisms associated with carbon sequestration, such as the New Zealand Emissions Trading Scheme, favor the continuing use of exotic tree species, especially Pinus radiata, over native species. Consequently, there are strong incentives for exotic forests and insufficient financial support for natives, even when native forest re-establishment is often the preference of landowners, Indigenous peoples, and local communities. The AUT Living Laboratories Program is a long-term, transdisciplinary, experimental restoration research program aimed at addressing scientific, social, and economic knowledge gaps for native revegetation as a Nature-based Solution (NbS) on farmland soils. Here, we present the project design and establishment information from the three experimental restoration sites, which vary in native species composition, planting configuration, and environmental and socio-cultural context. Each site involves partnerships with Indigenous communities, specifically Ngāti Whātua Ōrākei, Ngāti Manuhiri, and Ngāti Pāoa, to value and embed mātauranga Māori as Indigenous knowledge. Monitoring carbon sequestration along with changes in ecological functions and outcomes, including native biodiversity, will be critical to ensure that large-scale tree-planting aligns with the government’s strategies for climate change, native biodiversity, and economic prosperity.

Planting trees is widely regarded as an important part of climate change mitigation and adaptation efforts. As a result, large-scale tree planting projects have been initiated around the world. However, a number of these initiatives have unintentionally opened up risks to native forests and biodiversity while increasing exotic tree cover. Using the Aotearoa New Zealand One Billion Trees programme as a case study we reflect on what trees are being incentivised by these projects and the downstream impacts of how these projects are realised. We suggest ten recommendations for how these initiatives could be adapted to avoid perverse outcomes for native species while jointly achieving our carbon and biodiversity goals: (1) Diversify strategies—protect first, restore second, plant third; (2) Consider net change in trees—do not just count trees planted; (3) Consider the co-benefits of carbon and biodiversity from the outset; (4) Consider the broader landscape; (5) Consider the carbon and biodiversity benefits of soil; (6) Consider the importance of existing carbon stocks; (7) Consider potential impacts to non-tree ecosystems; (8) Consider the longevity of the future forest; (9) Support landowners in planting and maintaining native trees; (10) Remember that climate goals cannot be achieved by planting trees alone. We believe these recommendations are critical for improving the outcomes of the One Billion Trees programme in Aotearoa New Zealand, while providing important insights relevant to other tree planting initiatives around the world.

PURPOSE Rhabdomyosarcoma is the most common soft tissue sarcoma of childhood. Despite aggressive therapy, the 5-year survival rate for patients with metastatic or recurrent disease remains poor, and beyond PAX-FOXO1 fusion status, no genomic markers are available for risk stratification. We present an international consortium study designed to determine the incidence of driver mutations and their association with clinical outcome. PATIENTS AND METHODS Tumor samples collected from patients enrolled on Children's Oncology Group trials (1998-2017) and UK patients enrolled on malignant mesenchymal tumor and RMS2005 (1995-2016) trials were subjected to custom-capture sequencing. Mutations, indels, gene deletions, and amplifications were identified, and survival analysis was performed. RESULTS DNA from 641 patients was suitable for analyses. A median of one mutation was found per tumor. In FOXO1 fusion-negative cases, mutation of any RAS pathway member was found in > 50% of cases, and 21% had no putative driver mutation identified. BCOR (15%), NF1 (15%), and TP53 (13%) mutations were found at a higher incidence than previously reported and TP53 mutations were associated with worse outcomes in both fusion-negative and FOXO1 fusion-positive cases. Interestingly, mutations in RAS isoforms predominated in infants < 1 year (64% of cases). Mutation of MYOD1 was associated with histologic patterns beyond those previously described, older age, head and neck primary site, and a dismal survival. Finally, we provide a searchable companion database ( ClinOmics ), containing all genomic variants, and clinical annotation including survival data. CONCLUSION This is the largest genomic characterization of clinically annotated rhabdomyosarcoma tumors to date and provides prognostic genetic features that refine risk stratification and will be incorporated into prospective trials.

A l’origine, les mecanismes de reglement des differends entre investisseurs et Etats (RDIE, ou ISDS en anglais pour Investor-State Dispute Settlement) etaient destines a proteger les entreprises des pays du Nord contre le risque d’expropriation par les pays du Sud. A partir des annees 2000, ces mecanismes ont ete de plus en plus souvent utilises contre les pays du Nord par des investisseurs qui reclamaient d’etre indemnises a la suite de la nationalisation ou de la remunicipalisation de certains services ou tentaient de peser sur ces decisions, ou qui s’opposaient a l’adoption de reglementations environnementales ou sociales plus strictes menacant leurs interets commerciaux. La resistance aux mecanismes de reglement des differends entre investisseurs et Etats est venue des mouvements sociaux autant que des gouvernements, et malgre le pouvoir exerce par les multinationales, la tendance mondiale consiste desormais a exclure ces mecanismes des nouveaux accords d’investissement. L’objectif de cet article est de proposer une analyse d’economie politique des processus de soutien ou de contestation du role joue par les mecanismes de RDIE dans les accords internationaux, processus qui renvoient a des actions menees a l’echelon national, local et international. Les conflits qui en resultent sont interpretes en termes de contradictions postcoloniales touchant a la souverainete des Etats dans le contexte de la mondialisation, en termes de contestation persistante du role du secteur public et en termes de politiques climatiques.Remarques a l’intention des praticiensLa probabilite pour les investisseurs de voir un differend tranche en leur faveur dans le cadre d’un mecanisme de RDIE ne devrait pas etre surestimee, et l’evaluation que font ces derniers du bien-fonde et des perspectives de remporter un tel differend devrait etre soumise a un examen critique. Les gouvernements devraient etre conscients qu’il existe dans la societe civile un large consensus a l’encontre des mecanismes de RDIE et que la tendance generale actuelle est a la suppression de ces clauses des accords internationaux. Ils devraient egalement passer en revue l’ensemble des traites bilateraux d’investissement et accords de libre-echange qu’ils ont conclus, ainsi que le traite sur la Charte de l’energie ratifie par leur pays, pour evaluer les avantages potentiels respectifs de leur maintien ou de leur denonciation.2

Until ten years ago, the UK’s approach to bribery and corruption, including at its borders, was fragmented, limited in scope and unsuccessful in tackling bribery across borders. This article focuses on the changes which the Bribery Act 2010 has brought about over the last decade which has elevated the UK’s anti-bribery regime to one which is highly regarded. One might expect the natural consequence of the Bribery Act’s international reach to be a dramatic increase in the number of prosecutions (particularly in relation to bribing public officials) – however that has not proved to be the case. This article shows that the Bribery Act has instead brought about a fundamental change of approach by lawmakers and businesses alike – which is not evident from the raw statistics. The Bribery Act’s power lies in the combination of its international reach and the obligations it places on commercial organizations to prevent bribery which have caused UK corporates (including those incorporated elsewhere but who carry on a business, or part of a business, in the UK) to significantly tighten their anti-bribery internal policies and procedures. The shift in focus from the individual to the corporate has also been reflected in the approach of UK law enforcement through their use of Deferred Prosecution Agreements which has resulted in corporate offenders being punished with unprecedented fines. The paper ends by asking whether Brexit and the re-establishment of a large number of hard borders with EU countries will lead to an increase in the number of prosecutions for bribing customs officials after all. Bribery Act 2010, bribery and corruption, corporate offence, commercial organization, failure to prevent, extra-territorial reach, strict liability, Deferred Prosecution Agreement

As we reflect on the disruptive impact that the pandemic has inflicted upon our personal and professional lives, I marvel at the resilience of our Motion Imaging Technology Council’s determination to continue addressing the rapidly evolving digital imaging technology challenges that are confronting filmmakers. Since its formation in 2002 as the ASC Technology Committee, our agenda over the years has consistently identified the critical technology developments driving the evolution of digital production workflows. The unique nature of our mission has always been the fusion of a solid scientific and engineering knowledge base with a laser focus on how these technologies can best benefit the cinematographer’s ability to utilize them to enhance their creative vision.

Funding: S. W. thanks the China Scholarship Council (201906250199). A. K. G. is grateful to the Royal Society for Newton International Fellowship NF171163. EZ-C and IDWS acknowledge support from EPSRC (EP/L017008, EP/P010482/1). We are also grateful for financial support from the University of St Andrews Restarting Research Funding Scheme (SARRF) which is funded through the Scottish Funding Council grant reference SFC/AN/08/020. EZ-C is a Royal Society Leverhulme Trust Senior Research fellow (SRF\R1\201089). We would also like to thank the Leverhulme Trust (RPG-2016-047) for financial support. Herein, we demonstrate how judicious selection of donor decorating a central multi-resonant thermally activated delayed fluorescence (MR-TADF) core based on DiKTa can lead to very high-performance OLEDs. Decorating the DiKTa core with triphenylamine (TPA) and diphenylamine (DPA), 3TPA-DiKTa and 3DPA-DiKTa exhibit bright, narrowband green and red emission in doped films, respectively. The OLEDs based on these emitters showed record-high performance with maximum external quantum efficiencies (EQEmax) for this family of emitters, with a EQEmax of 30.8% for 3TPA-DiKTa at λEL of 551 nm and 16.7% for 3DPA-DiKTa at λEL of 613 nm. The efficiency roll-off in the OLEDs was improved significantly by using 4CzIPN as an assistant dopant in hyperfluorescence (HF) devices. The outstanding device performance has been attributed to preferential horizontal orientation of the transition dipole moments of 3TPA-DiKTa and 3DPA-DiKTa. Publisher PDF

The importance of intermediate triplet states and the nature of excited states has gained interest in recent years for the thermally activated delayed fluorescence (TADF) mechanism. It is widely accepted that simple conversion between charge transfer (CT) triplet and singlet excited states is too crude, and a more complex route involving higher-lying locally excited triplet excited states has to be invoked to witness the magnitude of the rate of reverse intersystem crossing (RISC) rates. The increased complexity has challenged the reliability of computational methods to accurately predict the relative energy between excited states as well as their nature. Here we compare the results of widely used DFT functionals, CAM-B3LYP, LC-ꞷPBE, LC-ꞷ*PBE, LC-ꞷ*HPBE, B3LYP, PBE0 and M06-2X against a wavefunction-based reference method, Spin-Component Scaling second-order approximate Coupled-Cluster (SCS-CC2) in fourteen known TADF emitters possessing a diversity of chemical structures. Overall, the use of the Tamm-Dancoff Approximation (TDA) together with the CAM-B3LYP, M06-2X and the two ꞷ-tuned range-separated functionals LC-ꞷ*PBE and LC-ꞷ*HPBE demonstrated the best agreement with SCS-CC2 calculations in predicting the absolute energy of the singlet S1, and triplet T1 and T2 excited states and their energy differences. However, consistently across the series and irrespective of the functional or the use of TDA, the nature of T1 and T2 is not as accurately captured as compared to S1. The presented work highlights that despite good agreement of energies, the description of the exact nature of the triplet states should be undertaken with caution.

The environments in which plant species evolved are now generally understood to be dynamic rather than static. Photosynthesis has to operate within these dynamic environments, such as sudden changes to light intensities. Plants have evolved photoprotection mechanisms that prevent damage caused by sudden changes to high light intensities. The extent of genetic variation within plants species to deal with these dynamic light conditions remains largely unexplored. Here we show that one accession ofA. thalianahas a more efficient photoprotection mechanism in dynamic light conditions, compared to six other accessions. The construction of a doubled haploid population and subsequent phenotyping in a dynamically controlled high-throughput system reveals up to 15 QTLs for photoprotection. Identifying the causal gene underlying one of the major QTLs shows that an allelic variant ofcpFtsYresults in more efficient photoprotection under high and fluctuating light intensities. Further analyses reveal this allelic variant to be overprotecting, reducing biomass in a range of dynamic environmental conditions. This suggests that within nature, adaptation can occur to more stressful environments and that revealing the causal genes and mechanisms can help improve the general understanding of photosynthetic functioning. The other QTLs possess different photosynthetic properties, and thus together they show how there is ample intraspecific genetic variation for photosynthetic functioning in dynamic environments. With photosynthesis being one of the last unimproved components of crop yield, this amount of genetic variation for photosynthesis forms excellent input for breeding approaches. In these breeding approaches, the interactions with the environmental conditions should however be precisely assessed. Doing so correctly, allows us to tap into nature’s solution to challenging environmental conditions.

Purpose: Rhabdomyosarcoma (RMS) is an aggressive soft-tissue sarcoma, which primarily occurs in children and young adults. We previously reported specific genomic alterations in RMS, which strongly correlated with survival; however, predicting these mutations or high-risk disease at diagnosis remains a significant challenge. In this study, we utilized convolutional neural networks (CNN) to learn histologic features associated with driver mutations and outcome using hematoxylin and eosin (H&E) images of RMS. Experimental Design: Digital whole slide H&E images were collected from clinically annotated diagnostic tumor samples from 321 patients with RMS enrolled in Children's Oncology Group (COG) trials (1998–2017). Patches were extracted and fed into deep learning CNNs to learn features associated with mutations and relative event-free survival risk. The performance of the trained models was evaluated against independent test sample data (n = 136) or holdout test data. Results: The trained CNN could accurately classify alveolar RMS, a high-risk subtype associated with PAX3/7-FOXO1 fusion genes, with an ROC of 0.85 on an independent test dataset. CNN models trained on mutationally-annotated samples identified tumors with RAS pathway with a ROC of 0.67, and high-risk mutations in MYOD1 or TP53 with a ROC of 0.97 and 0.63, respectively. Remarkably, CNN models were superior in predicting event-free and overall survival compared with current molecular-clinical risk stratification. Conclusions: This study demonstrates that high-risk features, including those associated with certain mutations, can be readily identified at diagnosis using deep learning. CNNs are a powerful tool for diagnostic and prognostic prediction of rhabdomyosarcoma, which will be tested in prospective COG clinical trials.

We present a p- and n-doped nonacene compound, NOBNacene, that represents a rare example of a linearly extended ladder-type multiresonant thermally activated delayed fluorescence (MR-TADF) emitter. This compound shows efficient narrow deep blue emission (PL = 410 nm, FWHM = 38 nm, ФPL = 71%, d = 1.18 ms) in 1.5 wt% TSPO1 thin film. The organic light-emitting diode (OLED) using this compound as the emitter shows a comparable electrolumines-cence spectrum (EL = 409 nm, FWHM = 37 nm) and a maximum external quantum efficiency (EQEmax) of 8.5% at CIE coordinates of (0.173, 0.055). The EQEmax values were increased to 11.2% at 3 wt% doping of the emitter within the emissive layer of the device. At this concentra-tion, the electroluminescence spectrum broadened slightly, leading to CIE coordinates of (0.176, 0.068).

We show how borylation of an acceptor-donor-acceptor (A-D-A) thermally activated delayed fluorescence (TADF) emitter, DIDOBNA-N, transforms the compound into a multi-resonant TADF (MR-TADF) emitter, MesB-DIDOBNA-N. DIDOBNA-N emits bright blue light (𝜆PL = 444 nm, FWHM = 64 nm, 𝛷PL = 81%, 𝜏d = 23 𝜇s, 1.5 wt% in TSPO1). The deep blue organic light-emitting diode (OLED) based on this compound shows a very high maximum external quantum efficiency (EQEmax) of 15.3% for a device with CIEy of 0.073. The MR-TADF emitter, MesB-DIDOBNA-N shows efficient and narrowband violet emission (𝜆PL = 402 nm, FWHM = 19 nm, 𝛷PL = 74.7%, 𝜏d = 133 𝜇s, 1.5 wt% in TSPO1). The OLED with MesB-DIDOBNA-N shows out-standing efficiency for a violet OLED at 9.3% and CIEy = 0.044, which is the bluest EL reported for a MR-TADF OLED to date. Noteworthy are the CIE coordinates of (0.166, 0.045), which are very close to the Rec.2020 standard for blue (0.131, 0.046). The EQEmax values were improved from 9.3% to 13.6% by increasing the concentration of the emitter in the host from 1.5 wt% to 5 wt%.