A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases.

While the preponderance of morbidity and mortality in medulloblastoma patients are due to metastatic disease, most research focuses on the primary tumor due to a dearth of metastatic tissue samples and model systems. Medulloblastoma metastases are found almost exclusively on the leptomeningeal surface of the brain and spinal cord; dissemination is therefore thought to occur through shedding of primary tumor cells into the cerebrospinal fluid followed by distal re-implantation on the leptomeninges. We present evidence for medulloblastoma circulating tumor cells (CTCs) in therapy-naive patients and demonstrate in vivo, through flank xenografting and parabiosis, that medulloblastoma CTCs can spread through the blood to the leptomeningeal space to form leptomeningeal metastases. Medulloblastoma leptomeningeal metastases express high levels of the chemokine CCL2, and expression of CCL2 in medulloblastoma in vivo is sufficient to drive leptomeningeal dissemination. Hematogenous dissemination of medulloblastoma offers a new opportunity to diagnose and treat lethal disseminated medulloblastoma.

Megastudies improve the impact of applied behavioural science.

Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens' decisions and outcomes1. Typically, different scientists test different intervention ideas in different samples using different outcomes over different time intervals2. The lack of comparability of such individual investigations limits their potential to inform policy. Here, to address this limitation and accelerate the pace of discovery, we introduce the megastudy-a massive field experiment in which the effects of many different interventions are compared in the same population on the same objectively measured outcome for the same duration. In a megastudy targeting physical exercise among 61,293 members of an American fitness chain, 30 scientists from 15 different US universities worked in small independent teams to design a total of 54 different four-week digital programmes (or interventions) encouraging exercise. We show that 45% of these interventions significantly increased weekly gym visits by 9% to 27%; the top-performing intervention offered microrewards for returning to the gym after a missed workout. Only 8% of interventions induced behaviour change that was significant and measurable after the four-week intervention. Conditioning on the 45% of interventions that increased exercise during the intervention, we detected carry-over effects that were proportionally similar to those measured in previous research3-6. Forecasts by impartial judges failed to predict which interventions would be most effective, underscoring the value of testing many ideas at once and, therefore, the potential for megastudies to improve the evidentiary value of behavioural science.

Canadian COVID-19 host genetics cohort replicates known severity associations.

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.

Enhancing clinical genomic accuracy with panelGC: a novel metric and tool for quantifying and monitoring GC biases in hybridization capture panel sequencing.

Accurate assessment of fragment abundance within a genome is crucial in clinical genomics applications such as the analysis of copy number variation (CNV). However, this task is often hindered by biased coverage in regions with varying guanine-cytosine (GC) content. These biases are particularly exacerbated in hybridization capture sequencing due to GC effects on probe hybridization and polymerase chain reaction (PCR) amplification efficiency. Such GC content-associated variations can exert a negative impact on the fidelity of CNV calling within hybridization capture panels. In this report, we present panelGC, a novel metric, to quantify and monitor GC biases in hybridization capture sequencing data. We establish the efficacy of panelGC, demonstrating its proficiency in identifying and flagging potential procedural anomalies, even in situations where instrument and experimental monitoring data may not be readily accessible. Validation using real-world datasets demonstrates that panelGC enhances the quality control and reliability of hybridization capture panel sequencing.

A Deep Learning Approach for the Identification of the Molecular Subtypes of Pancreatic Ductal Adenocarcinoma Based on Whole Slide Pathology Images.

Delayed diagnosis and treatment resistance make pancreatic ductal adenocarcinoma (PDAC) mortality rates high. Identifying molecular subtypes can improve treatment, but current methods are costly and time-consuming. In this study, deep learning models were used to identify histologic features that classify PDAC molecular subtypes based on routine hematoxylin-eosin-stained histopathologic slides. A total of 97 histopathology slides associated with resectable PDAC from The Cancer Genome Atlas project were used to train a deep learning model and tested the performance on 44 needle biopsy material (110 slides) from a local annotated patient cohort. The model achieved balanced accuracy of 96.19% and 83.03% in identifying the classical and basal subtypes of PDAC in The Cancer Genome Atlas and the local cohort, respectively. This study provides a promising method to cost-effectively and rapidly classifying PDAC molecular subtypes based on routine hematoxylin-eosin-stained slides, potentially leading to more effective clinical management of this disease.

ATR-X syndrome protein targets tandem repeats and influences allele-specific expression in a size-dependent manner.

ATRX is an X-linked gene of the SWI/SNF family, mutations in which cause syndromal mental retardation and downregulation of α-globin expression. Here we show that ATRX binds to tandem repeat (TR) sequences in both telomeres and euchromatin. Genes associated with these TRs can be dysregulated when ATRX is mutated, and the change in expression is determined by the size of the TR, producing skewed allelic expression. This reveals the characteristics of the affected genes, explains the variable phenotypes seen with identical ATRX mutations, and illustrates a new mechanism underlying variable penetrance. Many of the TRs are G rich and predicted to form non-B DNA structures (including G-quadruplex) in vivo. We show that ATRX binds G-quadruplex structures in vitro, suggesting a mechanism by which ATRX may play a role in various nuclear processes and how this is perturbed when ATRX is mutated.

Diagnostic and Therapeutic Implications of a FUS::TFCP2 Fusion and ALK Activation in a Metastatic Rhabdomyosarcoma.

The identification of gene fusions in rare sarcoma subtypes can have diagnostic, prognostic, and therapeutic impacts for advanced cancer patients. Here, we present a case of a 31-year-old male with a lytic lesion of the left mandible initially diagnosed as an osteosarcoma but found to have a TFCP2 fusion and ALK alteration, redefining the diagnosis and providing rationale for a novel treatment strategy. Histologically, the tumor displayed hypercellular, spindled to epithelioid neoplasm and nuclear pleomorphism, while immunohistochemistry showed diffuse SATB2 and focal desmin staining. Whole genome and transcriptome analysis revealed a FUS::TFCP2 fusion, the defining alteration of a rare molecularly characterized subtype of soft tissue sarcoma termed intraosseous rhabdomyosarcoma. An internal ALK deletion and extremely high ALK RNA expression were also identified, suggesting potential benefit of an ALK inhibitor. This patient displayed a rapid and dramatic clinical and radiographic response to an ALK inhibitor, alectinib. Unfortunately, the response was short-lived, likely due to the advanced stage and aggressiveness of the disease. This report describes genome and transcriptome characterization of an intraosseous rhabdomyosarcoma, few of which exist in the literature, as well as providing evidence that inhibition of ALK may be a rational treatment strategy for patients with this exceedingly rare soft tissue sarcoma subtype characterized by TFCP2 fusions and ALK activation.

cSurvival: a web resource for biomarker interactions in cancer outcomes and in cell lines.

Survival analysis is a technique for identifying prognostic biomarkers and genetic vulnerabilities in cancer studies. Large-scale consortium-based projects have profiled >11 000 adult and >4000 pediatric tumor cases with clinical outcomes and multiomics approaches. This provides a resource for investigating molecular-level cancer etiologies using clinical correlations. Although cancers often arise from multiple genetic vulnerabilities and have deregulated gene sets (GSs), existing survival analysis protocols can report only on individual genes. Additionally, there is no systematic method to connect clinical outcomes with experimental (cell line) data. To address these gaps, we developed cSurvival (https://tau.cmmt.ubc.ca/cSurvival). cSurvival provides a user-adjustable analytical pipeline with a curated, integrated database and offers three main advances: (i) joint analysis with two genomic predictors to identify interacting biomarkers, including new algorithms to identify optimal cutoffs for two continuous predictors; (ii) survival analysis not only at the gene, but also the GS level; and (iii) integration of clinical and experimental cell line studies to generate synergistic biological insights. To demonstrate these advances, we report three case studies. We confirmed findings of autophagy-dependent survival in colorectal cancers and of synergistic negative effects between high expression of SLC7A11 and SLC2A1 on outcomes in several cancers. We further used cSurvival to identify high expression of the Nrf2-antioxidant response element pathway as a main indicator for lung cancer prognosis and for cellular resistance to oxidative stress-inducing drugs. Altogether, these analyses demonstrate cSurvival's ability to support biomarker prognosis and interaction analysis via gene- and GS-level approaches and to integrate clinical and experimental biomedical studies.

CoDesign of a digital intervention for parents with bipolar disorder informed by integrated knowledge translation principles.

OBJECTIVES: To provide detailed information on the codesign of a digital intervention to support parents with bipolar disorder (BD) who have young children. Each step of this process is reported, as well as a detailed description of the final version of the intervention in line with the TIDieR framework. METHODS: Clinical experience and lived experience experts participated in online workshops, meetings, and remote feedback requests, informed by Integrated Knowledge Translation (IKT) principles. The IKT research group responded to each phase of recommendations from the knowledge users. RESULTS: Five clinical experience experts and six lived experience experts engaged with the codesign process. Their recommendations for principles, content, look, and feel, and functionality of the digital intervention were structured over five iterative phases. This led to a final implemented design that was identified by the clinical and lived experience experts (referred to together as the knowledge users group) as genuinely reflecting their input. CONCLUSIONS: The IKT principles offer an accessible structure for engaging with clinical and lived experience experts throughout a codesign process, in this case for a digital intervention for parents with BD. The resulting intervention is described in detail for transparency to aid further evaluation and development and to help other teams planning codesign approaches to intervention development.

The genetic basis and cell of origin of mixed phenotype acute leukaemia.

Mixed phenotype acute leukaemia (MPAL) is a high-risk subtype of leukaemia with myeloid and lymphoid features, limited genetic characterization, and a lack of consensus regarding appropriate therapy. Here we show that the two principal subtypes of MPAL, T/myeloid (T/M) and B/myeloid (B/M), are genetically distinct. Rearrangement of ZNF384 is common in B/M MPAL, and biallelic WT1 alterations are common in T/M MPAL, which shares genomic features with early T-cell precursor acute lymphoblastic leukaemia. We show that the intratumoral immunophenotypic heterogeneity characteristic of MPAL is independent of somatic genetic variation, that founding lesions arise in primitive haematopoietic progenitors, and that individual phenotypic subpopulations can reconstitute the immunophenotypic diversity in vivo. These findings indicate that the cell of origin and founding lesions, rather than an accumulation of distinct genomic alterations, prime tumour cells for lineage promiscuity. Moreover, these findings position MPAL in the spectrum of immature leukaemias and provide a genetically informed framework for future clinical trials of potential treatments for MPAL.

It is time to reconsider the use of naturally-occurring endotoxins in endotoxin recovery studies: Part 2 of a BioPhorum harmonized endotoxin recovery study.

The evaluation of Naturally Occurring Endotoxins (NOEs) for Low Endotoxin Recovery (LER) studies has been a topic in the industry and regulatory agencies have been hesitant to endorse NOE use in LER studies over purified Lipopolysaccharide (LPS) standards such as Control Standard Endotoxin (CSE) or Reference Standard Endotoxin (RSE). In a recent study involving 11 BioPhorum member companies across 13 sites, NOEs prepared in high and low nutrient conditions were evaluated in two common monoclonal antibody buffer formulations: 10 mM Sodium Citrate, 0.05 % Polysorbate 80, pH 6.0 and 20 mM Histidine, 0.05 % Polysorbate 80, pH 6.0. 12 g-negative bacterial isolates were used to prepare NOE analytes, which were spiked into the formulation buffers. Additionally, the NOEs were spiked into Limulus Amebocyte Lysate (LAL) reagent water as controls and purified LPS into the citrate/polysorbate buffer as the LER control. Results showed the average of three runs per organism was >50 % recovery, at the conclusion of the 7-day period, regardless of nutrient culture preparation conditions. Furthermore, purified LPS controls became undetectable (<50 % recovery) in the citrate/polysorbate buffer, highlighting the presence of LER. These findings highlight the potential value of using NOEs from relevant manufacturing facilities to assess overall risk when purified LPS recovery is insufficient.

Current concepts: the hip, core and kinetic chain in the overhead athlete.

BACKGROUND: As overhead sports continue to grow in popularity, there has been increased interest in optimizing sports performance and injury prevention in these athletes. The hip, core, and kinetic chain have become a focus of research in recent decades, and their importance in upper extremity mechanics is now being recognized. METHODS: An extensive review was carried out to identify papers correlating the hip, core and/or kinetic chain in overhead athletic performance and injury. RESULTS: Recent literature has shown that efficiency and synchrony of the hips and core during an overhead movement (such as in baseball, golf, tennis, or volleyball) is essential for a powerful and precise execution of the task. Impairments of the hip and core, particularly abnormal joint mobility or weakness, can limit efficient energy transfer through the kinetic chain and may negatively impact performance. Recent epidemiologic studies have found hip pain to be common in adolescent, collegiate, and adult athletes. Moreover, hip pain in overhead athletes specifically has also been found to occur at a high rate. Abnormalities in hip range of motion, hip morphology, and core strength can lead to abnormal mechanics upstream in the kinetic chain, which may place athletes at risk of injuries. CONCLUSION: In this review, the complex and multifaceted relationship between the hip, core, and kinetic chain is highlighted with an emphasis on recent literature and relevant findings.

Personal Recovery With Bipolar Disorder: A Network Analysis.

BACKGROUND: Personal recovery is valued by people with bipolar disorder (BD), yet its conceptualisation is unclear. Prior work conceptualising personal recovery has focussed on qualitative evidence or clinical factors without considering broader psychosocial factors. This study used a network analysis of Bipolar Recovery Questionnaire (BRQ) responses, aiming to identify (1) independent relationships between items to identify those most "central" to personal recovery and (2) how the relationships between items reflect themes of personal recovery. METHODS: The model was developed from BRQ responses (36 items) from 394 people diagnosed with bipolar disorder. The undirected network was based on a partial correlation matrix and was weighted. Strength scores were calculated for each node. Community detection analysis identified potential themes. The accuracy of the network was assessed using bootstrapping. RESULTS: Two consistent communities were identified: "Access to meaningful activity" and "Learning from experiences." "I feel confident enough to get involved in things in life that interest me" was the strongest item, although the strength stability coefficient (0.36) suggested strength should be interpreted with caution. The average edge weight was 0.02; however, stronger edges were identified. LIMITATIONS: The network showed low stability, possibly due to sample heterogeneity. Future work could incorporate demographic variables, such as time since BD diagnosis or stage of personal recovery, into network estimation. CONCLUSIONS: Network analysis can be applied to personal recovery, not only clinical symptoms of BD. Clinical applications could include tailoring recovery-focussed therapies towards encouraging important aspects of recovery, such as feeling confident to get involved with life.

Exploring the lived experiences and care challenges of formal paid caregivers for people with intellectual disability and dementia.

A greater number of people with intellectual disability are living into older age and are at increased risk of developing conditions such as dementia. Caring for a person with dementia presents several challenges for formal caregivers due to the progressive nature of the disease. An interpretive phenomenological analysis was used to understand the lived experiences of a purposive sample of formal caregivers in caring for people with intellectual disability and dementia. Discussions from 14 individual interviews generated data were analysed. Four key super-ordinate themes emerged which were: (1) recognising early indicators and diagnosis, (2) post diagnostic support, (3) coping with change and (4) need for future development. Themes reflected the experiences, barriers to dementia diagnosis and provide a valuable insight into the challenges faced by formal caregivers in providing aged care services.

Spruce giga-genomes: structurally similar yet distinctive with differentially expanding gene families and rapidly evolving genes.

Spruces (Picea spp.) are coniferous trees widespread in boreal and mountainous forests of the northern hemisphere, with large economic significance and enormous contributions to global carbon sequestration. Spruces harbor very large genomes with high repetitiveness, hampering their comparative analysis. Here, we present and compare the genomes of four different North American spruces: the genome assemblies for Engelmann spruce (Picea engelmannii) and Sitka spruce (Picea sitchensis) together with improved and more contiguous genome assemblies for white spruce (Picea glauca) and for a naturally occurring introgress of these three species known as interior spruce (P. engelmannii × glauca × sitchensis). The genomes were structurally similar, and a large part of scaffolds could be anchored to a genetic map. The composition of the interior spruce genome indicated asymmetric contributions from the three ancestral genomes. Phylogenetic analysis of the nuclear and organelle genomes revealed a topology indicative of ancient reticulation. Different patterns of expansion of gene families among genomes were observed and related with presumed diversifying ecological adaptations. We identified rapidly evolving genes that harbored high rates of non-synonymous polymorphisms relative to synonymous ones, indicative of positive selection and its hitchhiking effects. These gene sets were mostly distinct between the genomes of ecologically contrasted species, and signatures of convergent balancing selection were detected. Stress and stimulus response was identified as the most frequent function assigned to expanding gene families and rapidly evolving genes. These two aspects of genomic evolution were complementary in their contribution to divergent evolution of presumed adaptive nature. These more contiguous spruce giga-genome sequences should strengthen our understanding of conifer genome structure and evolution, as their comparison offers clues into the genetic basis of adaptation and ecology of conifers at the genomic level. They will also provide tools to better monitor natural genetic diversity and improve the management of conifer forests. The genomes of four closely related North American spruces indicate that their high similarity at the morphological level is paralleled by the high conservation of their physical genome structure. Yet, the evidence of divergent evolution is apparent in their rapidly evolving genomes, supported by differential expansion of key gene families and large sets of genes under positive selection, largely in relation to stimulus and environmental stress response.

The utility of color normalization for AI-based diagnosis of hematoxylin and eosin-stained pathology images.

The color variation of hematoxylin and eosin (H&E)-stained tissues has presented a challenge for applications of artificial intelligence (AI) in digital pathology. Many color normalization algorithms have been developed in recent years in order to reduce the color variation between H&E images. However, previous efforts in benchmarking these algorithms have produced conflicting results and none have sufficiently assessed the efficacy of the various color normalization methods for improving diagnostic performance of AI systems. In this study, we systematically investigated eight color normalization algorithms for AI-based classification of H&E-stained histopathology slides, in the context of using images both from one center and from multiple centers. Our results show that color normalization does not consistently improve classification performance when both training and testing data are from a single center. However, using four multi-center datasets of two cancer types (ovarian and pleural) and objective functions, we show that color normalization can significantly improve the classification accuracy of images from external datasets (ovarian cancer: 0.25 AUC increase, p = 1.6 e-05; pleural cancer: 0.21 AUC increase, p = 1.4 e-10). Furthermore, we introduce a novel augmentation strategy by mixing color-normalized images using three easily accessible algorithms that consistently improves the diagnosis of test images from external centers, even when the individual normalization methods had varied results. We anticipate our study to be a starting point for reliable use of color normalization to improve AI-based, digital pathology-empowered diagnosis of cancers sourced from multiple centers. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The interplay between suicidal experiences, psychotic experiences and interpersonal relationships: a qualitative study.

BACKGROUND: Suicidal thoughts, acts, plans and deaths are considerably more prevalent in people with non-affective psychosis, including schizophrenia, compared to the general population. Social isolation and interpersonal difficulties have been implicated in pathways which underpin suicidal experiences in people with severe mental health problems. However, the interactions between psychotic experiences, such as hallucinations and paranoia, suicidal experiences, and the presence, and indeed, absence of interpersonal relationships is poorly understood and insufficiently explored. The current study sought to contribute to this understanding. METHODS: An inductive thematic analysis was conducted on transcripts of 22, individual, semi-structured interviews with adult participants who had both non-affective psychosis and recent suicidal experiences. A purposive sampling strategy was used. Trustworthiness of the analysis was assured with researcher triangulation. RESULTS: Participants relayed both positive and negative experiences of interpersonal relationships. A novel conceptual model is presented reflecting a highly complex interplay between a range of different suicidal experiences, psychosis, and aspects of interpersonal relationships. Three themes fed into this interplay, depicting dynamics between perceptions of i. not mattering and mattering, ii. becoming disconnected from other people, and iii. constraints versus freedom associated with sharing suicidal and psychotic experiences with others. CONCLUSION: This study revealed a detailed insight into ways in which interpersonal relationships are perceived to interact with psychotic and suicidal experiences in ways that can be both beneficial and challenging. This is important from scientific and clinical perspectives for understanding the complex pathways involved in suicidal experiences. TRIAL REGISTRATION: ClinicalTrials.gov (NCT03114917), 14th April 2017. ISRCTN (reference ISRCTN17776666 .); 5th June 2017). Registration was recorded prior to participant recruitment commencing.

Impact of Ivermectin on the Gut Microbial Ecosystem.

Ivermectin is a an anti-helminthic that is critical globally for both human and veterinary care. To the best of our knowledge, information available regarding the influence of ivermectin (IVM) on the gut microbiota has only been collected from diseased donors, who were treated with IVM alone or in combination with other medicines. Results thus obtained were influenced by multiple elements beyond IVM, such as disease, and other medical treatments. The research presented here investigated the impact of IVM on the gut microbial structure established in a Triple-SHIME® (simulator of the human intestinal microbial ecosystem), using fecal material from three healthy adults. The microbial communities were grown using three different culture media: standard SHIME media and SHIME media with either soluble or insoluble fiber added (control, SF, ISF). IVM introduced minor and temporary changes to the gut microbial community in terms of composition and metabolite production, as revealed by 16S rRNA amplicon sequencing analysis, flow cytometry, and GC-MS. Thus, it was concluded that IVM is not expected to induce dysbiosis or yield adverse effects if administered to healthy adults. In addition, the donor's starting community influences the relationship between IVM and the gut microbiome, and the soluble fiber component in feed could protect the gut microbiota from IVM; an increase in short-chain fatty acid production was predicted by PICRUSt2 and detected with IVM treatment.

A rational analysis and computational modeling perspective on IAM and déjà vu.

The proposed memory architecture by Barzykowski and Moulin is compelling, and could be improved by incorporating a rational analysis of the functional roles of involuntary autobiographical memory and déjà vu. Additionally, modeling these phenomena computationally would remove ambiguities from the proposal. We provide examples of past work that illustrate how the phenomena may be described more precisely.