bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Origin of Patient-Derived Cancer Organoids from Pathologically Undiagnosed Specimen in Patients with Pancreatobiliary Cancers
Authors: Kim Bomi , Park Jiho , Na Hee Young , Park Sinwoo , Jin Jeonghwa , Jung Kwangrok , Lee Jong-chan , Hwang Jin-Hyeok , Seo Minseok , Kim Jaihwan 
Published: July 2024

Abstract

Purpose
Tissue confirmation of pancreatobiliary cancer is often difficult because of the location of the tumor and structure of the surrounding blood vessels. Patient-derived cancer organoids (PDCOs) reflect the genomic characteristics of individual cancers. Although diverse attempts to construct PDCOs for various pancreatobiliary cancer models are ongoing, no research results have yet confirmed the possibility of performing a precise diagnosis on PDCOs derived from pathologically negative patient samples.
Methods
We obtained a total of nine samples, including pathologically negative samples, from four patients (three patients with pancreatic cancer and one patient with gallbladder cancer) using different tissue acquisition methods to establish PDCOs (success rate 75%).
Results
We successfully verified whether the constructed PDCOs could represent the tissues of patients with pancreatobiliary cancer at each multi-omics level using tumor panel sequencing, single-cell RNA sequencing, hematoxylin and eosin, and immunohistochemical staining. PDCOs from pathologically negative samples showed expression patterns of malignant ductal cell-related biomarkers similar to those of other pathologically positive samples. Furthermore, the expression patterns at the single-cell level in PDCO from patients ultimately diagnosed with gallbladder cancer after surgery were different from those in patients with pancreatic cancer.
Conclusion
Therefore, PDCOs could be used for precision therapy from positive as well as negative samples.
Equation Development for Predicting Phreatic Line in Silty Clay Soils under Groundwater Inundation
Authors: Alsaffar Abdul Kareem Khaleel , Hamad Riyadh , Majeed Zaid Hameed , Alsareji Osamah J. 
Published: July 2024

Abstract

The threat of rising groundwater inundation, estimated by the elevation of the water table above the ground surface, is highly impacting various infrastructure Components. That issue can potentially damage Critical infrastructure elements such as foundations of buildings, bridges, roads, and other essential aspects. This problem will intensify when it is linked to the growing frequency of severe weather events and alterations in land use, which increases groundwater withdrawals. Among others, the important goal is to understand groundwater inundation and its effects on infrastructures (footings and soil), find methodologies for vulnerability evaluation and damage mitigation, and highlight the significant challenges and opportunities for future research. A laboratory model was constructed to simulate the actual conditions. A seepage of high-water level through Silty Clay Soil was tested to determine an equation of a phreatic line in such homogenous soil. A unitless relationship was estimated to represent the equation of the parabolic curve of the phreatic line ( Y2/H2 = 1-X/L), and it was successfully applied after being tested statistically in two methods (1) R2 formula (0.97–0.99); (2)RMSE method (average 0.69), (0–1). To track the change in parameters, the following two parameters were taken in the analysis: 1- Type of soil (silty clay soil) 2- Height of water table.
Enhancing Critical Current Density in Thin Superconductor Layers by Moiré Pinning Centers
Authors: Owjifard Zahra , Tavana Ali , Hosseini Mehdi 
Published: July 2024

Abstract

One important factor affecting the critical current density in type-II superconductors is the formation of artificial pinning centers. Hence, the engineering of pinning centers in superconducting systems has garnered considerable attention. In this study, the effect of moiré patterned pinning centers on the critical current density of superconducting tapes is investigated. The Langevin equation is solved by taking into account the prominent forces within the superconductor medium, using the appropriate boundary conditions for vortices. The vortex dynamics is investigated by performing molecular dynamics simulations, which are used to calculate the corresponding critical current densities. Results show a significant enhancement in the critical current density at particular angles of the relative rotation of the primary lattices. It is also revealed that for stronger pinning forces, the calculated critical current densities are higher in the moiré lattices compared to the primary lattices of pinning centers.
Enhancing Doctor-Patient Communication Using Large Language Models for Pathology Report Interpretation
Authors: Yang Xiongwen , Xiao Yi , Liu Di , Zhang Yun , Deng Huiyin , Huang Jian , Shi Huiyou , Liu Dan , Liang Maoli , Jin Xing , Sun Yongpan , Yao Jing , Zhou XiaoJiang , Guo Wankai , He Yang , Tang WeiJuan , Xu Chuan 
Published: July 2024

Abstract

Background
Large language models (LLMs) are increasingly utilized in healthcare settings. Postoperative pathology reports, which are essential for diagnosing and determining treatment strategies for surgical patients, frequently include complex data that can be challenging for patients to comprehend. This complexity can adversely affect the quality of communication between doctors and patients, potentially impacting patient outcomes.
Materials and Methods
This study analyzed text pathology reports from four hospital between October and December 2023, focusing on malignant tumors. Using GPT-4, we developed templates for interpretive pathology reports (IPRs) to simplify medical terminology for non-professionals. We randomly selected 70 reports to generate these templates and evaluated the remaining 628 reports for consistency and readability.
Results
Among 698 pathology reports analyzed, the interpretation through LLMs significantly improved readability and patient understanding. The average communication time between doctors and patients decreased by over 70%, from 35 minutes to 10 minutes (P < 0.001), with the use of IPRs. The study also found that patients scored higher on understanding levels when provided with AI-generated reports, from 5.23 points to 7.98 points (P < 0.001), with the use of IPRs. indicating an effective translation of complex medical information.
Conclusion
This research demonstrates the efficacy of LLMs like GPT-4 in enhancing doctor-patient communication by translating pathology reports into more accessible language. By improving comprehension and reducing communication time, AI applications in medical settings can enhance patient outcomes and satisfaction, highlighting the potential of AI to bridge gaps between medical professionals and the public in healthcare environments.
Methylation assay in KMT2B related dystonia: a novel diagnostic validation tool
Authors: Carvalho Gleyson Francisco da Silva , Gusmão Claudio Melo , Wolff Beatriz Martins , Vieira Lucas Liro , Gasparini Yanca Oliveira , Costa Mariana Ribeiro , Mendes Rafaela Silva , Castro Matheus Augusto Araujo , Sakuma Mayara T , Kok Fernando , Kulikowski Leslie Domenici 
Published: July 2024

Abstract

Background/Objectives: KMT2B-related dystonia (DYT28, OMIM #617284), is a progressive neurological condition characterized by early-onset movement disorders with autosomal dominant inheritance. In this study, we describe the use of a genome methylation epi-signature methodology to functionally validate 2 variants of uncertain significance (VUS) in the KMT2B gene.
Methods: Genome-wide methylation status was assessed using the EPIC methylation assay in peripheral blood samples from two subjects with early-onset movement disorder and missense variants of uncertain significance in the KMT2B gene (p.Leu1720Phe and p.Tyr2515Cys). After QC and normalization steps, we compared the M-values for all 144 probes, previously described as an EpiSign for KMT2B-related dystonia, between the two subjects and 14 controls individuals.
Results: The individual harboring the p.Tyr2515Cys variant exhibited a hypermethylation profile compatible with pathogenic/likely pathogenic variants in KMT2B, allowing for variant reclassification, conclusive genetic counseling, and patient stratification for deep brain stimulation. In contrast, the individual harboring the p.Leu1720Phe variant had a methylation status similar to controls, practically ruling out KMT2B-related dystonia.
Conclusion: Investigation of methylation status can be a powerful tool to determine pathogenicity when facing KMT2B variants of uncertain significance. Methylation results may optimize genetic counseling and positively impact patient care.
One-Year Outcomes of a Digital Twin Intervention for Type 2 Diabetes: A Retrospective Real-World Study
Authors: Shamanna Paramesh , Erukulapati Ravi Shankar , Shukla Ashutosh , Shah Lisa , Willis Bree , Thajudeen Mohamed , Kovil Rajiv , Baxi Rahul , Wali Mohsin , Damodharan Suresh , Joshi Shashank 
Published: July 2024

Abstract

This retrospective observational study, building on prior research that demonstrated the efficacy of the Digital Twin (DT) Precision Treatment Program over shorter follow-up periods​​, aimed to examine glycemic control and reduced anti-diabetic medication use after one year in a DT commercial program. T2D patients enrolled had adequate hepatic and renal function and no recent cardiovascular events. DT intervention powered by artificial intelligence utilises precision nutrition, activity, sleep, and deep breathing exercises. Outcome measures included HbA1c change, medication reduction, anthropometrics, insulin markers, and CGM metrics. Of 1985 enrollees, 132 (6.6%) were lost to follow-up, leaving 1853 participants who completed one year. At one year, participants exhibited significant reductions in HbA1c [mean change (SD) -1.8 (1.7)%, p<0.0001], with 1650 (89.0%) achieving HbA1c levels below 7%. At baseline, participants were taking mean anti-diabetic medications of 1.9 (1.4) which decreased to 0.5 (0.7) after one year [change: -1.5 (1.3), p<0.0001]. There were also significant decreases in weight [-4.8 (6.0) kg, p<0.0001], improvements in insulin resistance as measured by HOMA2-IR [-0.1 (1.2), p=0.00005], and enhancements in β-cell function [HOMA2-B; +21.6 (47.7); p<0.0001], along with better CGM metrics. These findings suggest that DT intervention could play a vital role in the future of T2D care.
A potential clue of IL-17A as a helper assist paraquat and T cell infiltration into brain parenchyma
Authors: Shi Ge , Wang Kaidong , Hu Rong , Li Yang , Jiao Yuxuan , Li Yonghang , Li Yujing , Qi Ai , Huang Min 
Published: July 2024

Abstract

Paraquat (PQ), a globally widely used and highly residual herbicide, is one of the potential environmental risk factors for neurodegenerative diseases (NDs). Before exerting neurotoxicity, however, PQ needs to break through the blood-brain barrier (BBB), how it penetrates the BBB and reaches the brain parenchyma remains a mystery. Recently, peripheral T cells and cytokine infiltrates into the brain have been involved in the development of NDs. But, the main reason for the infiltrating is not yet unrevealed. BBB plays a crucial role in the communication of T cells between the central nervous system (CNS) and the peripheral. Hence, whether T cells and their cytokines serve as core assistants to assist PQ infiltrating the BBB exerting neurotoxicity, in this article, C57BL/6J mice treated with PQ experienced down emotion and learning and memory abilities decreased. Pathologically, neurons and microglia respectively exhibit selective spatial damage and hyperresponsiveness. Simultaneously there were capture the traces of CD3 and its subsets of CD4/8, as well as IL-17A. Surprisingly, the response of T cells from peripheral blood and spleen to PQ gradually leans towards Th17 cells and secretes IL-17A. Therefore, it is highly suspected that IL-17A plays a role in disrupting the BBB. In vitro, bEnd.3 cells were specifically constructed with IL-17A, and PQ or mixture revealed IL-17A takes part in PQ-induced BBB disruption. Altogether, PQ responds to peripheral T cells to react and secrete IL-17A, which destroys BBB and assists PQ and T cells or other factors in infiltrating brain parenchyma.
FOCUS-MUSE DWI in Primary Rectal Cancer: Comparison with FOCUS, MUSE, and Single-shot DWI
Authors: Feng Weiming , Zhu Lan , Wang Kangning , Dai Jiankun , Ma Qianchen , Shen Hailin , Yuan Fei , Zhang Huan 
Published: July 2024

Abstract

Background
To assess the reliability of constrained undistorted single-shot diffusion-weighted imaging (FOCUS_DWI), multiplexed sensitivity-encoding_DWI (MUSE_DWI), single-shot echo planar imaging DWI (SS_DWI) and the combination of FOCUS and MUSE (FOCUS-MUSE_DWI) in primary rectal cancer by evaluating image quality and T staging performance.
Methods
Patients with primary rectal cancer underwent 3.0T MR scans with four DWI sequences. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values were measured. T stage and subjective image quality were assessed. Statistical analyses included intraclass correlation coefficient (ICC), Fleiss Kappa test, Friedman test, Chi-square tes, Paired t-test, and Spearman correlation analysis.
Results
A total of 45 patients (mean age: 60.45 ± 9.79, 30 men) were evaluated. FOCUS-MUSE_DWI exhibited the highest CNR (6.43 ± 0.94 and 6.44 ± 0.90 for two readers, respectively), adequate SNR (49.81 ± 6.60 and 49.67 ± 6.09 for two readers, respectively) with the best ADC repeatability (mean absolute difference: 8.44). No significant T staging differences were observed among DWI sequences (p ≥ 0.908). FOCUS-MUSE_DWI achieved the highest total image quality score (median value: 16) compared with other three sequences (p ≤ 0.001). Good to excellent agreement observed in both interobserver and intraobserver assessments (kappa > 0.600).
Conclusion
FOCUS-MUSE_DWI demonstrated good reliability with commendable T staging performance, the best ADC repeatability, sufficient SNR, the best CNR among four DWI sequences and could be the recommended sequence for clinical evaluation.
Resilience in a time of stress: revealing the molecular underpinnings of coral survival following thermal bleaching events
Authors: Nunn Brook , Brown Tanya , Timmins-Schiffman Emma , Mudge Miranda , Riffle Michael , Axworthy Jeremy , Dilworth Jenna , Kenkel Carly , Zaneveld Jesse , Rodrigues Lisa , Padilla-Gamiño Jacqeline 
Published: July 2024

Abstract

Coral bleaching events from thermal stress are increasing globally in duration, frequency, and intensity. Bleaching occurs when a coral’s algal symbionts are expelled, resulting in a loss of color. While bleaching can result in mortality, some corals survive, reacquire their symbionts, and recover. In this study, we experimentally bleached Montipora capitata to examine molecular and physiological signatures of intrinsic differences between corals that recover (resilient) compared to those that die (susceptible). All corals were collected from the same bay and monitored for eight months post-bleaching to identify genets exhibiting long-term resilience and survival. Using an integrated systems-biology approach that included quantitative mass spectrometry-based proteomics, 16S rRNA of the microbiome, total lipids, symbiont community composition and density, we explored molecular-level mechanisms of tolerance in experimental corals pre- and post-bleaching and identified predictive biomarkers of resilience that distinguish resilient and susceptible corals before thermal-induced bleaching events. Prior to thermal stress, resilient corals were characterized by a more diverse microbiome and increased abundances of proteins essential for carbon and nitrogen acquisition strategies, symbiont retention and acquisition, and pathogen resistance. Susceptible corals had early signs of symbiont rejection and had resorted to using urea uptake pathways for carbon and nitrogen. Further, proteins identified prior to bleaching were amplified after bleaching, suggesting these pathways may be deterministic of a coral’s fate when thermally bleached. Our results have important implications for the future of reefs, revealing molecular factors necessary for surviving thermally-induced bleaching events and identifying promising diagnostic biomarker candidates for coral reef management and restoration applications.
Macrophage depletion in inflamed rat knees prevents the activation of synovial mesenchymal stem cells by weakening Nampt and Spp1 signaling
Authors: Kodama Hayato , Endo Kentaro , Sekiya Ichiro 
Published: July 2024

Abstract

Background
Macrophages and mesenchymal stem cells (MSCs) engage in crucial interplay during inflammation and have significant roles in tissue regeneration. Synovial MSCs, as key players in joint regeneration, are known to proliferate together with macrophages in synovitis. However, the crosstalk between synovial MSCs and macrophages remains unclear. In this study, we investigated changes in the activation of synovial MSCs in inflamed rat knees following selective depletion of macrophages with clodronate liposomes.
Methods
Acute inflammation was induced in rat knee joints by injection of carrageenan (day 0). Clodronate liposomes were administered intra-articularly on days 1 and 4 to deplete macrophages, with empty liposomes as a control. Knee joints were collected on day 7 for evaluation by histology, flow cytometry, and colony-forming assays. Concurrently, synovial MSCs were cultured and subjected to proliferation assays, flow cytometry, and chondrogenesis assessments. We also analyzed their crosstalk using single-cell RNA sequencing (scRNA-seq).
Results
Clodronate liposome treatment significantly reduced CD68-positive macrophage numbers and suppressed synovitis. Immunohistochemistry and flow cytometry showed decreased expression of CD68 (a macrophage marker) and CD44 and CD271 (MSC markers) in the clodronate group, while CD73 expression remained unchanged. The number of colony-forming cells per 1,000 nucleated cells and per gram of synovium was significantly lower in the clodronate group than in the control group. Cultured synovial MSCs from both groups showed comparable proliferation, surface antigen expression, and chondrogenic capacity. scRNA-seq identified seven distinct synovial fibroblast (SF) subsets, with a notable decrease in the Mki67+ SF subset, corresponding to synovial MSCs, in the clodronate group. Clodronate treatment downregulated genes related to extracellular matrix organization and anabolic pathways in Mki67+ SF. Cell-cell communication analysis revealed diminished Nampt and Spp1 signaling interaction between macrophages and Mki67+ SF and diminished Ccl7, Spp1, and Csf1 signaling interaction between Mki67+ SF and macrophages in the clodronate group.
Conclusions
Macrophage depletion with clodronate liposomes suppressed synovitis and reduced the number and activity of synovial MSCs, highlighting the significance of macrophage-derived Nampt and Spp1 signals in synovial MSC activation. These findings offer potential therapeutic strategies to promote joint tissue regeneration by enhancing beneficial signals between macrophages and synovial MSCs.
Urbanization Rate Associated with Renewable in Electricity Production and CO 2 Emissions in Jordan: A Threshold Regression Approach
Authors: Bashayreh Ala' , Al-Hindawi Hatem , Tahtamouni Abla 
Published: July 2024

Abstract

This study examines the relationship between urbanization rates associated with the increasing dependency on renewable electricity production and CO2 emissions per capita and gross domestic per capita in Jordan. The empirical analysis uses annual data from Jordan for the period 1990–2022 to answer the question: What is/are the threshold urbanization rate/s that pushes CO2 emissions per capita to decline? Results suggest that two threshold values exist for Jordan, which implies a nonlinear relationship between urbanization rate and CO2 emissions per capita. The estimated threshold regression model shows (0.78, 0.91) as the threshold values of urbanization rate, and values between these thresholds push CO2 emissions per capita to decline. In addition, there is a significant negative relationship between these two variables.
How urine metabolomics can help in the follow-up of kidney transplant recipients: An untargeted metabolomics-based multiplatform study
Authors: Cirillo Arianna , Resimont Guillaume , Massias Justine , Guitton Yann , Jouret François , Vidal-Petiot Emmanuelle , Flamant Martin , Delanaye Pierre , de Tullio Pascal 
Published: July 2024

Abstract

Kidney transplantation (KTx) offers the best outcomes for patients with end-stage renal disease. Monitoring kidney graft function is crucial for transplant recipients (KTR) but current biomarkers are insufficient to predict kidney function evolution. This study aimed to identify new predictive biomarkers using untargeted Nuclear Magnetic Resonance (NMR) and mass spectrometry (MS)-based metabolomic approaches.
In a cohort of 56 French KTR patients, urinary samples were collected 3 months post-KTx, and glomerular filtration rate (GFR) was measured at 3 and 12 months. Patients were categorized as “progressors” or “stable” based on a 7% decline or stability in kidney function over this period. Untargeted NMR- and MS-based metabolomic analyses were performed, followed by dual integration. Multivariate statistical analysis of urinary samples identified biomarker panels linked to GFR evolution. The combined approach enhanced discrimination and predictive performance (Combined platforms: Q2= 0.829, AUC= 0.845, Accuracy= 0.79 vs. NMR: Q2= 0.775, AUC= 0.794, Accuracy= 0.64).
Early post-transplantation urinary metabolome analysis shows promise in predicting GFR evolution at 1 year, potentially leading to innovative tools for improving post-transplant patient care.
A Methodology to Select and Adjust Quantum Noise Models Through Emulators: Benchmarking Against Real Backends
Authors: Bravo-Montes J.A. , Bastante Miriam , Botella Guillermo , Barrio Alberto del , García-Herrero F. 
Published: July 2024

Abstract

Currently, access to quantum processors is costly in terms of time, and power.There are quantum simulators and emulators on the market that offer alternativesfor evaluating the behavior of a real quantum processor. However, these emulationenvironments present accuracy deviations from real devices, mainly becauseof difficult-to-model error sources. In this study, a methodology is proposed thatallows the selection of noise models and adjustment of their parameters, consideringthe nature of the backends (technology, topology, vendor, model, etc.).The proposed methodology is illustrated using a small superconducting examplebased on the ibm perth backend (seven qubits) and a comparison between thequantum emulators Qaptiva and Qiskit, where six different noise models areapplied, achieving a fidelity deviation of 0.686% at best with respect to the real device.