Publications by authors named "Poisson L"

We present the design of a VMI spectrometer optimized for attosecond spectroscopy in the 0-40 eV energy range. It is based on a compact three-electrode configuration where the lens shape, size, and material have been optimized using numerical simulations to improve the spectral resolution by a factor of ∼5 relative to the initial design [Eppink and Parker, Rev. Sci.

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Background: Glioblastoma is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification.

Methods: We developed a highly reproducible, personalized prognostication and clinical subgrouping system using machine learning (ML) on routine clinical data, MRI, and molecular measures from 2,838 demographically diverse patients across 22 institutions and 3 continents. Patients were stratified into favorable, intermediate, and poor prognostic subgroups (I, II, III) using Kaplan-Meier analysis (Cox proportional model and hazard ratios [HR]).

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CD19-targeted chimeric antigen receptor-modified T (CAR-T) cells have shown success in clinical studies, with several CD19 CAR-T cell products now having been approved for market use. However, this cell therapy can be associated with side effects such as cytokine release syndrome (CRS). Therefore, pre-clinical test systems are highly desired to permit the evaluation of these unwanted effects before clinical trials begin.

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Although medical mistrust is associated with lower cancer screening uptake among racial minorities, such as African Americans, potential impacts on cancer screening among White Americans are generally understudied. In this study, we examined links from medical mistrust to lung cancer screening among African American ( = 203) and White American ( = 201) smokers. Participants completed the Group-Based Medical Mistrust Scale and viewed a brief online educational module about lung cancer risks, etiology, and screening.

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  • Multiple sclerosis (MS) is difficult to diagnose and manage, often leading to late treatment; however, artificial intelligence (AI) shows promise in analyzing patient data to improve diagnosis.* -
  • This study employed a machine-learning approach to analyze metabolite profiles in MS patients and healthy controls, uncovering unique biochemical changes linked to disease severity.* -
  • A trained AI model achieved high accuracy rates (87% overall, with good sensitivity, specificity, and precision), indicating potential for clinical use, but further validation with larger studies is required.*
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  • Glioblastoma (GBM) tumors show diverse genetic and transcriptional profiles, leading to significant variations in how cancer stem cells (CSCs) respond to standard treatments like radiation and temozolomide (TMZ).
  • Through targeted proteomics and RNA sequencing, the study found that while differentiating CSCs to an astrocytic state activates certain oncogenic pathways and retains some "stemness," it also increases resistance to TMZ treatment.
  • The transcriptional response to treatments was largely influenced by the p53 status of the cells, revealing that both mutant and wild-type p53 models activated a DNA-damage related immune response, indicating potential pathways for improving GBM treatment strategies.
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  • Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease affecting young adults, manifesting primarily as relapsing-remitting MS (RRMS) and progressing to secondary progressive MS (SPMS) or existing as primary progressive MS (PPMS), which has a steady decline without remission.
  • Researchers conducted a study using global untargeted metabolomics to identify specific altered metabolites in the serum of patients with RRMS, PPMS, and healthy subjects (HS), analyzing a total of 235 metabolites.
  • The study found significant differences in metabolite profiles between RRMS and HS (22 metabolites) as well as PPMS and HS (28 metabolites), and identified key metabolic pathways involved, suggesting that these unique altered metabolites could help differentiate
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Purpose: Patient-reported outcome measures (PROMs) provide a direct report of the patient's perspective, complementary to clinician assessment. Currently, understanding the real-time changes in PROM scores near the end of life remains limited. This study evaluated differences in mean PROM scores between patients with cancer within 6 months before death compared with surviving patients with cancer.

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Background Recent advancements, including image processing capabilities, present new potential applications of large language models such as ChatGPT (OpenAI), a generative pretrained transformer, in radiology. However, baseline performance of ChatGPT in radiology-related tasks is understudied. Purpose To evaluate the performance of GPT-4 with vision (GPT-4V) on radiology in-training examination questions, including those with images, to gauge the model's baseline knowledge in radiology.

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  • Data-intensive research seeks to enhance healthcare delivery, decision-making, and patient outcomes, relying on quantitative scientists like biostatisticians and epidemiologists to transform data into actionable health knowledge.
  • Academic health centers have established centralized Quantitative Science Units focused on the professional growth of quantitative scientists and high-quality research output, but lack clear guidelines on team formation and management.
  • A working group of Quantitative Science Unit leaders from six institutions aims to share best practices and tools for developing, managing, and evaluating Quantitative Science Teams, thereby improving research collaboration and adapting to changing research demands.
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  • The study aimed to explore sex-based differences in patients with glioblastoma to enhance personalized treatment and improve outcomes, focusing on differences in tumor parameters and survival.
  • Data from 1832 patients was analyzed, revealing that women were diagnosed at an older median age and had lower tumor volumes compared to men, who generally had higher performance scores.
  • Despite these differences in tumor characteristics, the research found no significant discrepancies in survival outcomes or mortality rates between sexes, although certain factors like age and treatment type influenced mortality risk for both genders.
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() infections are the most common sexually transmitted infection (STI). Despite effective antibiotics for , undetected infections or delayed treatment can lead to infertility, ectopic pregnancies, and chronic pelvic pain. Besides humans, chlamydia poses similar health challenges in animals such as () in pigs.

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Real-time dynamics of vibrationally and electronically excited I molecules has been investigated experimentally using the pump-probe technique. A 2-photon excitation was performed either at 269 nm or 266 nm. An electronic and vibrational wavepacket was built as coherent superposition of a few (269 nm excitation) or many (266 nm excitation) Rydberg states of the and series partly coupled with ion-pair states.

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Patient-reported outcome (PRO) scores have been utilized more frequently, but the relationship of PRO scores to determinants of health and social inequities has not been widely studied. Our goal was to determine the association of PRO scores with social determinants. All patients with a new cancer diagnosis who completed a PRO survey from 2020 to 2022 were included.

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  • Multiple sclerosis (MS) is a common neurodegenerative disease in young adults that leads to neurological decline, with relapsing-remitting MS (RRMS) being the most prevalent type, which may progress to primary progressive MS (PPMS).
  • The study aimed to identify distinct serum metabolite profiles that differentiate RRMS and PPMS patients from healthy subjects (HS) using advanced metabolomics techniques.
  • Results showed specific metabolic alterations in both RRMS and PPMS when compared to HS, suggesting potential metabolic biomarkers that could help in distinguishing between the different forms of MS and normal health.
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Unresolved and uncontrolled inflammation is considered a hallmark of pathogenesis in chronic inflammatory diseases like multiple sclerosis (MS), suggesting a defective resolution process. Inflammatory resolution is an active process partially mediated by endogenous metabolites of dietary polyunsaturated fatty acids (PUFA), collectively termed specialized pro-resolving lipid mediators (SPMs). Altered levels of resolution mediators have been reported in several inflammatory diseases and may partly explain impaired inflammatory resolution.

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  • The study analyzed the epigenetic changes in gliomas from 132 patients over time, comparing initial and recurrent tumors in both IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) types.
  • IDHwt gliomas remained stable in their epigenetic profile, while IDHmut gliomas showed a notable decrease in DNA methylation, making their profiles more similar to IDHwt tumors.
  • The research identified HOXD13 as crucial for the evolution of IDHmut tumors and found that treatment led to changes in the tumor microenvironment, like increased blood vessel formation and T-cell presence, mimicking the characteristics of IDHwt gliomas.
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Background: Lung cancer is the leading cause of cancer-related death. Although lung cancer screening has been shown to reduce mortality, only a small fraction of eligible people receive screening. This study briefly educated screening-eligible individuals about lung cancer risk, prevention, and screening recommendations.

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In various cancer models, dietary interventions have been shown to inhibit tumor growth, improve anticancer drug efficacy, and enhance immunity, but no such evidence exists for epithelial ovarian cancer (EOC), the most lethal gynecologic cancer. The anticancer immune responses induced by 16-h intermittent fasting (IF) were studied in mice with EOC. IF consistently reduced metabolic growth factors and cytokines that stimulate tumor growth, creating a tumor-hostile environment.

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  • Recurrence of meningiomas is hard to predict with current methods, making it important to find noninvasive ways to identify patients at risk of recurrence.
  • This study examines DNA methylation in blood and tissue samples from 155 meningioma patients, discovering unique markers and utilizing artificial intelligence to create models for predicting recurrence.
  • The findings suggest that using liquid biopsy could provide a reliable and noninvasive method for diagnosis and predicting outcomes in meningioma patients, enhancing personalized treatment strategies.
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X-linked adrenoleukodystrophy is a severe demyelinating neurodegenerative disease mainly affecting males. The severe cerebral adrenoleukodystrophy (cALD) phenotype has a poor prognosis and underlying mechanism of onset and progression of neuropathology remains poorly understood. In this study we aim to integrate metabolomic and microRNA (miRNA) datasets to identify variances associated with cALD.

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Purpose: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas.

Methods: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed.

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We investigated the excited-state dynamics of 4-(dimethylamino)benzethyne (4-DMABE) in a combined theoretical and experimental study using surface-hopping simulations and time-resolved ionisation experiments. The simulations predict a decay of the initially excited S state into the S state in only a few femtoseconds, inducing a subsequent partial twist of the dimethylamino group within ∼100 fs. This leads to drastically reduced Franck-Condon factors for the ionisation transition to the cationic ground state, thus inhibiting the effective ionisation of the molecule, which leads to a vanishing photoelectron signal on a similar timescale as observed in our time-resolved photoelectron spectra.

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Epithelial Ovarian Cancer (EOC) is the most lethal gynecologic cancer with limited genetic alterations identified that can be therapeutically targeted. In tumor bearing mice, short-term fasting, fasting mimicking diet and calorie restriction enhance the activity of antineoplastic treatment by modulating systemic metabolism and boosting anti-tumor immunity. We tested the outcome of sixteen-hour intermittent fasting (IF) on mouse EOC progression with focus on fasting driven antitumor immune responses.

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