Controlling the structures of organic semiconductor–quantum dot nanocomposites through ligand shell chemistry

Nanocrystal quantum dots (QD) functionalised with active organic ligands hold significant promise as solar energy conversion materials, capable of multiexcitonic processes that could improve the efficiencies of single-junction photovoltaic devices. Small-angle X-ray and neutron scattering (SAXS and SANS) were used to characterize the structure of lead sulphide QDs post ligand-exchange with model acene-carboxylic acid ligands (benzoic acid, hydrocinnamic acid and naphthoic acid). Results demonstrate that hydrocinnamic acid and naphthoic acid ligated QDs form monolayer ligand shells, whilst benzoic acid ligated QDs possess ligand shells thicker than a monolayer. Further, the formation of a range of nanocomposite materials through the self-assembly of such acene-ligated QDs with an organic small-molecule semiconductor [5,12-bis((triisopropylsilyl)ethynyl)tetracene (TIPS-Tc)] is investigated. These materials are representative of a wider set of functional solar energy materials; here the focus is on structural studies, and their optoelectronic function is not investigated. As TIPS-Tc concentrations are increased, approaching the solubility limit, SANS data show that QD fractal-like features form, with structures possibly consistent with a diffusion limited aggregation mechanism. These, it is likely, act as heterogeneous nucleation agents for TIPS-Tc crystallization, generating agglomerates containing both QDs and TIPS-Tc. Within the TIPS-Tc crystals there seem to be three distinct QD morphologies: (i) at the crystallite centre (fractal-like QD aggregates acting as nucleating agents), (ii) trapped within the growing crystallite (giving rise to QD features ordered as sticky hard spheres), and (iii) a population of aggregate QDs at the periphery of the crystalline interface that were expelled from the growing TIPS-Tc crystal. Exposure of the QD:TIPS-Tc crystals to DMF vapour, a solvent known to be able to strip ligands from QDs, alters the spacing between PbS–hydrocinnamic acid and PbS–naphthoic acid ligated QD aggregate features. In contrast, for PbS–benzoic acid ligated QDs, DMF vapour exposure promotes the formation of ordered QD colloidal crystal type phases. This work thus demonstrates how different QD ligand chemistries control the interactions between QDs and an organic small molecule, leading to widely differing self-assembly processes. It highlights the unique capabilities of multiscale X-ray and neutron scattering in characterising such composite materials

Mixed small-molecule matrices improve nanoparticle dispersibility in organic semiconductor-nanoparticle films

Controlling the dispersibility of nanocrystalline inorganic quantum dots (QDs) within organic semiconductor (OSC):QD nanocomposite films is critical for a wide range of optoelectronic devices. This work demonstrates how small changes to the OSC host molecule can have a dramatic detrimental effect on QD dispersibility within the host organic semiconductor matrix as quantified by grazing incidence X-ray scattering. It is commonplace to modify QD surface chemistry to enhance QD dispersibility within an OSC host. Here, an alternative route toward optimizing QD dispersibilities is demonstrated, which dramatically improves QD dispersibilities through blending two different OSCs to form a fully mixed OSC matrix phase

Insights into the kinetics and self-assembly order of small-molecule organic semiconductor/quantum dot blends during blade coating

Organic–inorganic nanocomposite films formed from blends of small-molecule organic semiconductors and colloidal quantum dots are attractive candidates for high efficiency, low-cost solar energy harvesting devices. Understanding and controlling the self-assembly of the resulting organic–inorganic nanocomposite films is crucial in optimising device performance, not only at a lab-scale but for large-scale, high-throughput printing and coating methods. Here, in situ grazing incidence X-ray scattering (GIXS) gives direct insights into how small-molecule organic semiconductors and colloidal quantum dots self-assemble during blade coating. Results show that for two blends separated only by a small difference in the structure of the small molecule forming the organic phase, crystallisation may proceed down two distinct routes. It either occurs spontaneously or is mediated by the formation of quantum dot aggregates. Irrespective of the initial crystallisation route, the small-molecule crystallisation acts to exclude the quantum dot inclusions from the growing crystalline matrix phase. These results provide important fundamental understanding of structure formation in nanocomposite films of organic small molecules and colloidal quantum dots prepared via solution processing routes. It highlights the fundamental difference to structural evolution which can be made by seemingly small changes in system composition. It provides routes for the structural design and optimisation of solution-processed nanocomposites that are compatible with the large-scale deposition manufacturing techniques that are crucial in driving their wider adoption in energy harvesting applications

Alternative lengthening of telomeres in childhood neuroblastoma from genome to proteome

Telomere maintenance by telomerase activation or alternative lengthening of telomeres (ALT) is a major determinant of poor outcome in neuroblastoma. Here, we screen for ALT in primary and relapsed neuroblastomas (n = 760) and characterize its features using multi-omics profiling. ALT-positive tumors are molecularly distinct from other neuroblastoma subtypes and enriched in a population-based clinical sequencing study cohort for relapsed cases. They display reduced ATRX/DAXX complex abundance, due to either ATRX mutations (55%) or low protein expression. The heterochromatic histone mark H3K9me3 recognized by ATRX is enriched at the telomeres of ALT-positive tumors. Notably, we find a high frequency of telomeric repeat loci with a neuroblastoma ALT-specific hotspot on chr1q42.2 and loss of the adjacent chromosomal segment forming a neo-telomere. ALT-positive neuroblastomas proliferate slowly, which is reflected by a protracted clinical course of disease. Nevertheless, children with an ALT-positive neuroblastoma have dismal outcome

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs

Pilocytic astrocytoma: pathology, molecular mechanisms and markers

Pilocytic astrocytomas (PAs) were recognized as a discrete clinical entity over 70 years ago. They are relatively benign (WHO grade I) and have, as a group, a 10-year survival of over 90 %. Many require merely surgical removal and only very infrequently do they progress to more malignant gliomas. While most show classical morphology, they may present a spectrum of morphological patterns, and there are difficult cases that show similarities to other gliomas, some of which are malignant and require aggressive treatment. Until recently, almost nothing was known about the molecular mechanisms involved in their development. The use of high-throughput sequencing techniques interrogating the whole genome has shown that single abnormalities of the mitogen-activating protein kinase (MAPK) pathway are exclusively found in almost all cases, indicating that PA represents a one-pathway disease. The most common mechanism is a tandem duplication of a ≈2 Mb-fragment of #7q, giving rise to a fusion between two genes, resulting in a transforming fusion protein, consisting of the N-terminus of KIAA1549 and the kinase domain of BRAF. Additional infrequent fusion partners have been identified, along with other abnormalities of the MAP-K pathway, affecting tyrosine kinase growth factor receptors at the cell surface (e.g., FGFR1) as well as BRAF V600E, KRAS, and NF1 mutations among others. However, while the KIAA1549-BRAF fusion occurs in all areas, the incidence of the various other mutations identified differs in PAs that develop in different regions of the brain. Unfortunately, from a diagnostic standpoint, almost all mutations found have been reported in other brain tumor types, although some retain considerable utility. These molecular abnormalities will be reviewed, and the difficulties in their potential use in supporting a diagnosis of PA, when the histopathological findings are equivocal or in the choice of individualized therapy, will be discussed

Clinical implementation of integrated molecular-morphologic risk prediction for meningioma

Risk prediction for meningioma tumors was until recently almost exclusively based on morphological features of the tumor. To improve risk prediction, multiple models have been established that incorporate morphological and molecular features for an integrated risk prediction score. One such model is the integrated molecular-morphologic meningioma integrated score (IntS), which allocates points to the histological grade, epigenetic methylation family and specific copy-number variations. After publication of the IntS, questions arose in the neuropathological community about the practical and clinical implementation of the IntS, specifically regarding the calling of CNVs, the applicability of the newly available version (v12.5) of the brain tumor classifier and the need for incorporation of TERT-promoter and CDKN2A/B status analysis in the IntS calculation. To investigate and validate these questions additional analyses of the discovery (n = 514), retrospective validation (n = 184) and prospective validation (n = 287) cohorts used for IntS discovery and validation were performed. Our findings suggest that any loss over 5% of the chromosomal arm suffices for the calling of a CNV, that input from the v12.5 classifier is as good or better than the dedicated meningioma classifier (v2.4) and that there is most likely no need for additional testing for TERT-promoter mutations and/or homozygous losses of CDKN2A/B when defining the IntS for an individual patient. The findings from this study help facilitate the clinical implementation of IntS-based risk prediction for meningioma patients

Clinical implementation of integrated molecular-morphologic risk prediction for meningioma

Risk prediction for meningioma tumors was until recently almost exclusively based on morphological features of the tumor. To improve risk prediction, multiple models have been established that incorporate morphological and molecular features for an integrated risk prediction score. One such model is the integrated molecular-morphologic meningioma integrated score (IntS), which allocates points to the histological grade, epigenetic methylation family and specific copy-number variations. After publication of the IntS, questions arose in the neuropathological community about the practical and clinical implementation of the IntS, specifically regarding the calling of CNVs, the applicability of the newly available version (v12.5) of the brain tumor classifier and the need for incorporation of TERT-promoter and CDKN2A/B status analysis in the IntS calculation. To investigate and validate these questions additional analyses of the discovery (n = 514), retrospective validation (n = 184) and prospective validation (n = 287) cohorts used for IntS discovery and validation were performed. Our findings suggest that any loss over 5% of the chromosomal arm suffices for the calling of a CNV, that input from the v12.5 classifier is as good or better than the dedicated meningioma classifier (v2.4) and that there is most likely no need for additional testing for TERT-promoter mutations and/or homozygous losses of CDKN2A/B when defining the IntS for an individual patient. The findings from this study help facilitate the clinical implementation of IntS-based risk prediction for meningioma patients.NEUROPatholog