julilili42/papers huggingface dataset:
Molecular signatures define BAP1-altered meningioma as a distinct CNS tumor with deregulation of Polycomb repressive complex target genes
2025-04-18

Abstract Background Meningiomas are the most common primary intracranial neoplasms, with highly variable patient outcomes. While most meningiomas are benign, a significant subset recurs postoperatively, presenting substantial treatment challenges. BAP1 gene inactivation has been suggested as a marker for aggressive meningiomas, although its precise molecular and clinical roles remain poorly understood. Methods To comprehensively investigate BAP1-altered meningiomas, we used six meningiomas with known BAP1 alterations as a discovery set. Genome-wide DNA methylation profiling of these samples, along 11 151 reference meningiomas, identified a distinct molecular cluster (n = 42) using unsupervised visualization approaches. These tumors were further characterized by DNA/RNA sequencing, histopathological examination, and a retrospective review of clinical data, compared to reference meningioma cohorts, providing a thorough characterization of this rare tumor subtype. Results Our integrative analysis revealed BAP1-altered meningiomas as a distinct CNS tumor subtype, characterized by recurrent loss of chromosome 3p21 and driven by various BAP1-inactivating alterations. Although rhabdoid morphology is present in some cases, it is not exclusive and should not be used as a grading criterion. Progression-free survival analysis showed a median of 21 months (95% CI: 12-NA), with a 2-year overall survival rate of 79% (95% CI: 60%-100%), highlighting the aggressive nature of these tumors. Gene expression profiling revealed upregulation of PRC target genes, dysregulated Polycomb signaling, and elevated expression in several cellular and growth factor pathways. Conclusions BAP1-altered meningiomas represent a distinct and aggressive CNS tumor subtype associated with PRC dysregulation and recurrent 3p chromosome loss. These findings support the designation “meningioma, BAP1-altered.”
To be or not to be: navigating the influence of MicroRNAs on cervical cancer cell death
2025-04-18

With all diagnostic and therapeutic advances, such as surgery, radiation- and chemo-therapy, cervical cancer (CC) is still ranked fourth among the most frequent cancers in women globally. New biomarkers and therapeutic targets are warranted to be discovered for the early detection, treatment, and prognosis of CC. As component of the non-coding RNA's family, microRNAs (miRNAs) participate in several cellular functions such as cell proliferation, gene expression, many signaling cascades, apoptosis, angiogenesis, etc. MiRNAs can suppress or induce programmed cell death (PCD) pathways by altering their regulatory genes. Besides, abnormal expression of miRNAs weakens or promotes various signaling pathways associated with PCD, resulting in the development of human diseases such as CC. For that reason, understanding the effects that miRNAs exert on the various modes of tumor PCD, and evaluating the potential of miRNAs to serve as targets for induction of cell death and reappearance of chemotherapy. The current study aims to define the effect that miRNAs exert on cell apoptosis, autophagy, pyroptosis, ferroptosis, and anoikis in cervical cancer to investigate possible targets for cervical cancer therapy. Manipulating the PCD pathways by miRNAs could be considered a primary therapeutic strategy for cervical cancer.
The fNIRS glossary project: a consensus-based resource for functional near-infrared spectroscopy terminology
2025-04-18

The fNIRS glossary provides a community-sourced resource that facilitates education and effective scientific communication within the fNIRS community and related fields. By lowering barriers to learning and engaging with fNIRS, the glossary is poised to benefit a broad spectrum of researchers, including those with limited access to educational resources.
A look in the mirror - body exposure in clinical practice
2025-04-18

Abstract Background The dissemination of evidence-based techniques is critical for the successful treatment of eating disorders in clinical practice. A growing number of studies suggests that body exposure is an effective technique to treat body image disturbance in eating disorders. However, the dissemination of body exposure among psychotherapists in clinical practice remains unclear. Methods An online survey was conducted among licensed psychotherapists in Germany. The dissemination of body exposure in clinical practice, psychotherapists’ characteristics (such as clinical training, attitudes towards exposure, confidence), and therapists’ experiences with benefits and side-effects of body exposure were assessed. Results Data of 230 psychotherapists were analysed. More than half of them (58.3%) applied body exposure in their clinical practice. Yet, body exposure was only offered to 37.3% of their eating disorder patients. Moreover, 56.7% of psychotherapists delivering body exposure indicated that they have not received any training in this technique. Self-reported confidence in delivering body exposure correlated significantly with the number of patients treated with body exposure. Psychotherapists who applied body exposure reported minor side-effects and that the majority of their patients profited from this technique. Conclusions Our results offer insights into the dissemination of body exposure in clinical practice in Germany. Overall, body exposure is still underused considering the empirical evidence demonstrating the potential of body exposure to treat body image disturbances effectively. Moreover, with regard to potential barriers of using body exposure, our data suggest that training opportunities for clinicians may facilitate the dissemination of this technique in clinical practice.
“Football Still Puts Food on My Table”: Exploring the Positive Narratives of Former Amateur and Semi-Professional Footballers in Nigeria
2025-04-18

Pre-professional career termination has attracted considerable interest in football research. Research attention has mostly been on the difficulties that players may face in navigating the transition to a post-football life. However, “the excessive focus on the pathologies” may obscure the many different ways that the aspired career may contribute to the athlete's post-football well-being. Through a positive psychology approach, this paper explored the narrative frames through which former amateur and semi-professional players in Nigeria articulate a positive experience of their pursuit of a professional career, irrespective of the unrealized objective of becoming professional footballers. The findings reveal three positive narrative frames arising from connections that study participants made between their football pursuits and their post-football well-being. These include the narrative of livelihood, the narrative of purpose and the narrative of recognition. The implication of the findings is that amateur and semi-professional clubs need to be more deliberate in providing players with a range of experiences that may support a more positive post-football life narrative.
Mental disorders in people with undiagnosed diseases presenting to German centres for rare diseases – prevalence, type and relevance
2025-04-19

People presenting to centres for rare diseases (CRD) for diagnostic work-up often suffer from mental disorders. The prevalence and distribution of these mental disorders and their relevance for care remain largely unclear and well-controlled multicentre studies are missing. The ZSE-DUO study was a multicentre, prospective, controlled cohort study involving 11 German CRD. In total, 662 adult patients with an unclear diagnosis were evaluated by an additional mental health specialist along with their usual CRD care. Mental disorders were assessed through a standardized clinical examination, including the Mini-DIPS interview. Prevalence of diagnosed mental disorders (ICD-10 coding) was assessed and compared to population prevalence. A total of 54.5 % (361 patients) of adults with unexplained symptoms presenting to a CRD had current mental disorders. Mental disorders were deemed the sole explanation for the entire symptomatology in 53.5 % of cases. In 36.2 % of cases, a combination of a mental disorder with a somatic disease was considered to explain the unexplained symptoms. In 8.3 % of cases, it was assessed that the mental disorder was not involved in explaining the unexplained symptoms. Assessing whether a mental disorder contributes to the patient's symptom complex is crucial for determining suitable treatment strategies in terms of a bio-psycho-social approach.
Uncertainty mapping and probabilistic tractography using Simulation-based Inference in diffusion MRI: A comparison with classical Bayes
2025-04-20

Simulation-Based Inference (SBI) has recently emerged as a powerful framework for Bayesian inference: Neural networks are trained on simulations from a forward model, and learn to rapidly estimate posterior distributions. We here present an SBI framework for parametric spherical deconvolution of diffusion MRI data of the brain. We demonstrate its utility for estimating white matter fibre orientations, mapping uncertainty of voxel-based estimates and performing probabilistic tractography by spatially propagating fibre orientation uncertainty. We conduct an extensive comparison against established Bayesian methods based on Markov-Chain Monte-Carlo (MCMC) and find that: a) in-silico training can lead to calibrated SBI networks with accurate parameter estimates and uncertainty mapping for both single- and multi-shell diffusion MRI, b) SBI allows amortised inference of the posterior distribution of model parameters given unseen observations, which is orders of magnitude faster than MCMC, c) SBI-based tractography yields reconstructions that have a high level of agreement with their MCMC-based counterparts, equal to or higher than scan-rescan reproducibility of estimates. We further demonstrate how SBI design considerations (such as dealing with noise, defining priors and handling model selection) can affect performance, allowing us to identify optimal practices. Taken together, our results show that SBI provides a powerful alternative to classical Bayesian inference approaches for fast and accurate model estimation and uncertainty mapping in MRI.
A computational ontology framework for the synthesis of multi-level pathology reports from brain MRI scans
2025-04-21

Background Convolutional neural network (CNN) based volumetry of MRI data can help differentiate Alzheimer's disease (AD) and the behavioral variant of frontotemporal dementia (bvFTD) as causes of cognitive decline and dementia. However, existing CNN-based MRI volumetry tools lack a structured hierarchical representation of brain anatomy, which would allow for aggregating regional pathological information and automated computational inference. Objective Develop a computational ontology pipeline for quantifying hierarchical pathological abnormalities and visualize summary charts for brain atrophy findings, aiding differential diagnosis. Methods Using FastSurfer, we segmented brain regions and measured volume and cortical thickness from MRI scans pooled across multiple cohorts (N = 3433; ADNI, AIBL, DELCODE, DESCRIBE, EDSD, and NIFD), including healthy controls, prodromal and clinical AD cases, and bvFTD cases. Employing the Web Ontology Language (OWL), we built a semantic model encoding hierarchical anatomical information. Additionally, we created summary visualizations based on sunburst plots for visual inspection of the information stored in the ontology. Results Our computational framework dynamically estimated and aggregated regional pathological deviations across different levels of neuroanatomy abstraction. The disease similarity index derived from the volumetric and cortical thickness deviations achieved an AUC of 0.88 for separating AD and bvFTD, which was also reflected by distinct atrophy profile visualizations. Conclusions The proposed automated pipeline facilitates visual comparison of atrophy profiles across various disease types and stages. It provides a generalizable computational framework for summarizing pathologic findings, potentially enhancing the physicians’ ability to evaluate brain pathologies robustly and interpretably.
Ibaqpy: A scalable Python package for baseline quantification in proteomics leveraging SDRF metadata
2025-04-21

Intensity-based absolute quantification (iBAQ) is essential in proteomics as it allows for the assessment of a protein's absolute abundance in various samples or conditions. However, the computation of these values for increasingly large-scale and high-throughput experiments, such as those using DIA, TMT, or LFQ workflows, poses significant challenges in scalability and reproducibility. Here, we present ibaqpy (https://github.com/bigbio/ibaqpy), a Python package designed to compute iBAQ values efficiently for experiments of any scale. Ibaqpy leverages the Sample and Data Relationship Format (SDRF) metadata standard to incorporate experimental metadata into the quantification workflow. This allows for automatic normalization and batch correction while accounting for key aspects of the experimental design, such as technical and biological replicates, fractionation strategies, and sample conditions. Designed for large-scale proteomics datasets, ibaqpy can also recompute iBAQ values for existing experiments when an SDRF is available. We showcased ibaqpy's capabilities by reanalyzing 17 public proteomics datasets from ProteomeXchange, covering HeLa cell lines with 4921 samples and 5766 MS runs, quantifying a total of 11,014 proteins. In our reanalysis, ibaqpy is a key component in automating reproducible quantification, reducing manual effort and making quantitative proteomics more accessible while supporting FAIR principles for data reuse. SIGNIFICANCE: Proteomics studies often rely on intensity-based absolute quantification (iBAQ) to assess protein abundance across various biological conditions. Despite its widespread use, computing iBAQ values at scale remains challenging due to the increasing complexity and volume of proteomics experiments. Existing tools frequently lack metadata integration, limiting their ability to handle experimental design intricacies such as replicates, fractions, and batch effects. Our work introduces ibaqpy, a scalable Python package that leverages the Sample and Data Relationship Format (SDRF) to compute iBAQ values efficiently while incorporating critical experimental metadata. By enabling automated normalization and batch correction, ibaqpy ensures reproducible and comparable quantification across large-scale datasets. We validated the utility of ibaqpy through the reanalysis of 17 public HeLa datasets, comprising over 200 million peptide features and quantifying 11,000 proteins across thousands of samples. This comprehensive reanalysis highlights the robustness and scalability of ibaqpy, making it an essential tool for researchers conducting large-scale proteomics experiments. Moreover, by promoting FAIR principles for data reuse and interoperability, ibaqpy offers a transformative approach to baseline protein quantification, supporting reproducible research and data integration within the proteomics community.
Au 147 (SPh) 30 (PPh 3 ) 12 : A Geometrically Closed, but Electronically Open Triple‐Shell Icosahedral Gold Cluster and its Geometrically Open Counterpart
2025-04-21

Abstract The aesthetic platonic solids have been known since ancient times, and the structure of all five platonic solids is also found in chemical compounds. While gold sub‐nanometer clusters and gold nanoparticles with an icosahedral structure have been known for a long time to exist, a multi‐shell icosahedral gold cluster at the intermediate size between 13 and thousands of atoms has been elusive. Here we present the synthesis and crystallographic characterization of the first triple‐shell icosahedral metal cluster, Au 147 (SPh) 30 (PPh 3 ) 12 1 . The gold core in 1 is stabilized by phosphines and thiolates, but surprisingly no staple motifs are formed. A second cluster, Au 146 (SPh) 30 (PPh 3 ) 12 2 , cocrystallizes and is identified as having a closed electronic shell but can be considered as a geometrically open pendant of 1 . The unique clusters are characterized experimentally by EDX, UV/vis, DLS, and EPR and theoretically by quantum chemical calculations.
Time-Resolved Intrinsic and Extrinsic Photoresponse of Colloidal SWIR-Active Indium Antimonide Quantum Dot Photodetectors
2025-04-21

Colloidal indium antimonide (InSb) quantum dots (QDs) are highly promising nanomaterials for SWIR photodetectors due to their optical properties, solution processability, and low toxicity. Here, we present surface engineering of colloidal InSb QDs and an investigation of the intrinsic and extrinsic photoresponse time (τIn and tEx) of InSb QD photodetectors. Chloride (Cl-) ligands are chosen for surface engineering and their effects are studied by X-ray photoelectron spectroscopy. Using a pump-probe technique based on asynchronous optical sampling (ASOPS), we find that τIn of Cl-capped InSb QDs can be described by two components of 1.5 ns and 200 ps. By studying the dependence of these components on the voltage, the excitation power, and the temperature, we assign them to trap-assisted Auger recombination and carrier trapping. For tEx, we obtain much faster rise times (9.77 μs) than fall times (635 μs), indicating prolonged recovery due to slow release of trapped carriers. We devise measures to partially mitigate this drawback, enabling sub-microsecond photo switching and a 3 dB bandwidth of 5 MHz. Our findings highlight the potential of colloidal InSb QDs for environmentally benign and high-speed SWIR photodetectors.
Translation, Linguistic Validation, and Reliability of the CLEFT-Q in a German Context
2025-04-21

The aim of this study was to translate and culturally adapt the CLEFT-Q questionnaire into German and evaluate its reliability as an instrument for Patient Reported Outcome Measures (PROMs). The translation followed the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) guidelines. Applicability was tested through cognitive debriefings with 7 patients. Adjustments were made during the process to achieve a conceptually equivalent translation. Reliability was assessed by conducting retest interviews with 50 patients at 4-week intervals. Translation challenges included difficulties in 8.4% of items during forward translation, 31.1% of items when comparing the 2 forward translations, and 10.1% of items during back-translation review. Cognitive debriefings revealed comprehension issues with 4 items (3.4%). Internal consistency and stability were evaluated using Cronbach alpha and the intraclass correlation coefficient, both yielding values of 0.909, considered excellent. PROMs play a growing role in quality assurance for medical care. The CLEFT-Q is currently the only international tool specifically available for cleft lip and palate patients. Its German translation provides a reliable and valid instrument to assess outcomes in German-speaking regions, covering key aspects of patient experience, including satisfaction, functional outcomes, and health-related quality of life.
Unlocking the potential of the terrestrial gastropod species Zootecus insularis as a climate archive for arid regions
2025-04-21

Local-scale climate reconstruction in arid regions is challenging due to the scarcity of suitably preserved archives. While several well-studied climate proxy datasets exist for southeastern Arabia, including those preserved in speleothems, sedimentary deposits and paleosoils, and occasionally sediment cores collected for pollen analysis, snails have not yet been explored as a potential archive. This study investigates the potential of the terrestrial gastropod Zootecus insularis collected from geoarchaeological sections as new climate archive for arid environments. Isotope analysis was conducted on specimens from Holocene contexts in Oman to reconstruct long-term climate trends. Previously published water temperatures calculated from oxygen isotope data of Melanoides tuberculata, a freshwater gastropod species found in the same geoarchaeological sections as the terrestrial Zootecus shells, were interpolated to the age of the terrestrial snails, allowing for the recalculation of an oxygen isotope signal used to identify wet or dry periods. The resulting dataset showed a strong correlation with existing paleoclimate datasets from speleothems and paleolakes. Additionally, the δ<sup>13</sup>C values of Z. insularis indicated a significant shift towards more negative values over time, which probably suggests a transition from C4 grass-dominated vegetation to mixed C4/C3 xerophilic vegetation. This integrated approach suggests that snails could provide a valuable new archive for paleoclimate studies in arid regions.
Abstract 4591: Development and validation of a molecular classifier of meningiomas
2025-04-21

Abstract Background: Meningiomas exhibit considerable clinical and biological heterogeneity. We previously identified four distinct molecular groups (immunogenic, NF2-wildtype, hypermetabolic, proliferative) that address much of this heterogeneity. Despite the utility of these groups, the stochasticity of clustering methods and the use of multi-omics data for discovery limits the potential for classifying prospective cases. We sought to address this with a dedicated classifier. Methods: Using an international cohort of 1698 meningiomas, we constructed and rigorously validated a machine learning-based molecular classifier using only DNA methylation data as input. Original and newly-predicted molecular groups were compared using DNA methylation, RNA sequencing, copy number profiles, whole exome sequencing, and clinical outcomes. Results: We show that group-specific outcomes in the validation cohort are nearly identical to those originally described, with median PFS of 7.4 (4.9-Inf) years in hypermetabolic tumors and 2.5 (2.3-5.3) years in proliferative tumors (not reached in the other groups). Tumors classified as NF2-wildtype had no NF2 mutations, and 51.4% had canonical mutations previously described in this group. RNA pathway analysis revealed upregulation of immune-related pathways in the immunogenic group, metabolic pathways in the hypermetabolic group and cell-cycle programs in the proliferative group. Bulk deconvolution similarly revealed enrichment of macrophages in immunogenic tumors and neoplastic cells in hypermetabolic and proliferative tumors with similar proportions to those originally described. Conclusions: Our DNA methylation-based classifier, which is publicly available for immediate clinical use, recapitulates the biology and outcomes of the original molecular groups as assessed using multiple metrics/platforms that were not used in its training. Citation Format: Alex Landry, Justin Wang, Jeff Liu, Vikas Patil, Chloe Gui, Andrew Ajisebutu, Yosef Ellenbogen, Qingxia Wei, Olivia Singh, Julio Sosa, Sheila Mansouri, Aaron Cohen-Gadol, Ghazaleh Tabatabai, Marcos Tatagiba, Felix Behling, Jill Banholtz-Sloan, Andrew Sloan, Lola Chambless, Serge Makarenko, Stephen Yip, Alireza Mansouri, Derek Tsang, Kenneth Aldape, Andrew Gao, Farshad Nassiri, Gelareh Zadeh. Development and validation of a molecular classifier of meningiomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4591.