bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cytokine profiling and transcriptomics in mononuclear cells define immune variants in Meniere Disease
Authors: Flook Marisa , Rojano Elena , Gallego-Martinez Alvaro , Escalera-Balsera Alba , Perez-Carpena Patricia , Moleon M. del Carmen , Gonzalez-Aguado Rocio , Rivero de Jesus Victoria , Domínguez-Durán Emilio , Frejo Lidia , G. Ranea Juan A. , Lopez-Escamez Jose Antonio 
Published: February 2024

AbstractMeniere Disease (MD) is a chronic inner ear disorder characterized by vertigo attacks, sensorineural hearing loss, tinnitus, and aural fullness. Extensive evidence supporting the inflammatory etiology of MD has been found, therefore, by using transcriptome analysis, we aim to describe the inflammatory variants of MD. We performed Bulk RNAseq on 45 patients with definite MD and 15 healthy controls. MD patients were classified according to their basal levels of IL-1β into 2 groups: high and low. Differentially expression analysis was performed using the ExpHunter Suite, and cell type proportion was evaluated using the estimation algorithms xCell, ABIS, and CIBERSORTx. MD patients showed 15 differentially expressed genes (DEG) compared to controls. The top DEGs include IGHG1 (p = 1.64 $$\times$$
×
10−6) and IGLV3-21 (p = 6.28 $$\times$$
×
10−3), supporting a role in the adaptative immune response. Cytokine profiling defines a subgroup of patients with high levels of IL-1β with up-regulation of IL6 (p = 7.65 $$\times$$
×
10−8) and INHBA (p = 3.39 $$\times$$
×
10−7) genes. Transcriptomic data from peripheral blood mononuclear cells support a proinflammatory subgroup of MD patients with high levels of IL6 and an increase in naïve B-cells, and memory CD8+ T cells.
Practical high-dimensional quantum key distribution protocol over deployed multicore fiber
Authors: Zahidy Mujtaba , Ribezzo Domenico , De Lazzari Claudia , Vagniluca Ilaria , Biagi Nicola , Müller Ronny , Occhipinti Tommaso , Oxenløwe Leif K. , Galili Michael , Hayashi Tetsuya , Cassioli Dajana , Mecozzi Antonio , Antonelli Cristian , Zavatta Alessandro , Bacco Davide 
Published: February 2024

AbstractQuantum key distribution (QKD) is a secure communication scheme for sharing symmetric cryptographic keys based on the laws of quantum physics, and is considered a key player in the realm of cyber-security. A critical challenge for QKD systems comes from the fact that the ever-increasing rates at which digital data are transmitted require more and more performing sources of quantum keys, primarily in terms of secret key generation rate. High-dimensional QKD based on path encoding has been proposed as a candidate approach to address this challenge. However, while proof-of-principle demonstrations based on lab experiments have been reported in the literature, demonstrations in realistic environments are still missing. Here we report the generation of secret keys in a 4-dimensional hybrid time-path-encoded QKD system over a 52-km deployed multicore fiber link forming by looping back two cores of a 26-km 4-core optical fiber. Our results indicate that robust high-dimensional QKD can be implemented in a realistic environment by combining standard telecom equipment with emerging multicore fiber technology.
Targeted delivery of Fc-fused PD-L1 for effective management of acute and chronic colitis
Authors: Tang Xudong , Shang Yangyang , Yang Hong , Song Yalan , Li Shan , Qin Yusi , Song Jingyi , Chen Kang , Liu Yang , Zhang Dinglin , Chen Lei 
Published: February 2024

AbstractThe PD-1/PD-L1 pathway in mucosal immunity is currently actively explored and considered as a target for inflammatory bowel disease (IBD) treatment. However, systemic PD-L1 administration may cause unpredictable adverse effects due to immunosuppression. Here we show that reactive oxygen species (ROS)-responsive nanoparticles enhance the efficacy and safety of PD-L1 in a mouse colitis model. The nanoparticles control the accumulation and release of PD-L1 fused to Fc (PD-L1-Fc) at inflammatory sites in the colon. The nanotherapeutics shows superiority in alleviating inflammatory symptoms over systemic PD-L1-Fc administration and mitigates the adverse effects of PD-L1-Fc administration. The nanoparticles-formulated PD-L1-Fc affects production of proinflammatory and anti-inflammatory cytokines, attenuates the infiltration of macrophages, neutrophils, and dendritic cells, increases the frequencies of Treg, Th1 and Tfh cells, reshapes the gut microbiota composition; and increases short-chain fatty acid production. In summary, PD-L1-Fc-decorated nanoparticles may provide an effective and safe strategy for the targeted treatment of IBD.
Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer
Authors: Chen Yangzi , Wang Bohong , Zhao Yizi , Shao Xinxin , Wang Mingshuo , Ma Fuhai , Yang Laishou , Nie Meng , Jin Peng , Yao Ke , Song Haibin , Lou Shenghan , Wang Hang , Yang Tianshu , Tian Yantao , Han Peng , Hu Zeping 
Published: February 2024

AbstractGastric cancer (GC) represents a significant burden of cancer-related mortality worldwide, underscoring an urgent need for the development of early detection strategies and precise postoperative interventions. However, the identification of non-invasive biomarkers for early diagnosis and patient risk stratification remains underexplored. Here, we conduct a targeted metabolomics analysis of 702 plasma samples from multi-center participants to elucidate the GC metabolic reprogramming. Our machine learning analysis reveals a 10-metabolite GC diagnostic model, which is validated in an external test set with a sensitivity of 0.905, outperforming conventional methods leveraging cancer protein markers (sensitivity < 0.40). Additionally, our machine learning-derived prognostic model demonstrates superior performance to traditional models utilizing clinical parameters and effectively stratifies patients into different risk groups to guide precision interventions. Collectively, our findings reveal the metabolic landscape of GC and identify two distinct biomarker panels that enable early detection and prognosis prediction respectively, thus facilitating precision medicine in GC.
Single-cell transcriptomics identifies the differentiation trajectory from inflammatory monocytes to pro-resolving macrophages in a mouse skin allergy model
Authors: Miyake Kensuke , Ito Junya , Takahashi Kazufusa , Nakabayashi Jun , Brombacher Frank , Shichino Shigeyuki , Yoshikawa Soichiro , Miyake Sachiko , Karasuyama Hajime 
Published: February 2024

AbstractBoth monocytes and macrophages are heterogeneous populations. It was traditionally understood that Ly6Chi classical (inflammatory) monocytes differentiate into pro-inflammatory Ly6Chi macrophages. Accumulating evidence has suggested that Ly6Chi classical monocytes can also differentiate into Ly6Clo pro-resolving macrophages under certain conditions, while their differentiation trajectory remains to be fully elucidated. The present study with scRNA-seq and flow cytometric analyses reveals that Ly6ChiPD-L2lo classical monocytes recruited to the allergic skin lesion sequentially differentiate into Ly6CloPD-L2hi pro-resolving macrophages, via intermediate Ly6ChiPD-L2hi macrophages but not Ly6Clo non-classical monocytes, in an IL-4 receptor-dependent manner. Along the differentiation, classical monocyte-derived macrophages display anti-inflammatory signatures followed by metabolic rewiring concordant with their ability to phagocytose apoptotic neutrophils and allergens, therefore contributing to the resolution of inflammation. The failure in the generation of these pro-resolving macrophages drives the IL-1α-mediated cycle of inflammation with abscess-like accumulation of necrotic neutrophils. Thus, we clarify the stepwise differentiation trajectory from Ly6Chi classical monocytes toward Ly6Clo pro-resolving macrophages that restrain neutrophilic aggravation of skin allergic inflammation.
A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy
Authors: Sharma Vaibhav , Yakimovich Artur 
Published: February 2024

AbstractHigh-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefacts could be addressed using modern-day machine learning and deep learning algorithms, this is widely impeded by the lack of suitable datasets. To address this, here we present a purpose-created open dataset of high-content microscopy sample preparation artefact. It consists of high-content microscopy of laboratory dust titrated on fixed cell culture specimens imaged with fluorescence filters covering the complete spectral range. To ensure this dataset is suitable for supervised machine learning tasks like image classification or segmentation we propose rule-based annotation strategies on categorical and pixel levels. We demonstrate the applicability of our dataset for deep learning by training a convolutional-neural-network-based classifier.
Study on the algorithm of fault recording analysis combining its time-domain waveforms with phase-domain trajectories
Authors: Ge Qun , Ren Lu , Li Jia 
Published: February 2024

AbstractThe untimely handling of faults in a power system has a negative impact on its operation and even the national economy, and this requires coordination in the functions of protective relaying as well as supervisory & control devices, where digital fault recorders are used to record fault waveforms of electrical physical quantities. The fault recording of a simulated current is taken as the research object in this article, and it is transformed from the time-domain waveform into a phase-domain trajectory, which is used to analyze fault feature parameters and then reformulate the waveform. The original waveform of the current will be substituted by the reformulated one with fault features to realize functions in the power system. The algorithm of reformulating fault recording, the correlativity of the reformulated waveform and its original one, and errors produced in the research process are researched. The high correlation coefficient between the reformulated waveform and its original one shows that the algorithm studied in the article offers a simple and convenient option for fault recording analysis.
A bioluminescent and homogeneous assay for monitoring GPCR-mediated cAMP modulation and PDE activity
Authors: Mikheil Dareen , Larsen Matthew A. , Hsiao Kevin , Murray Nathan H. , Ugo Tim , Wang Hui , Goueli Said A. 
Published: February 2024

Abstract3′,5′-Cyclic adenosine monophosphate (cAMP), the first identified second messenger, is implicated in diverse cellular processes involving cellular metabolism, cell proliferation and differentiation, apoptosis, and gene expression. cAMP is synthesized by adenylyl cyclase (AC), which converts ATP to cAMP upon activation of Gαs-protein coupled receptors (GPCRs) in most cases and hydrolyzed by cyclic nucleotide phosphodiesterases (PDEs) to 5′-AMP. Dysregulation of cAMP signaling is implicated in a wide range of pathophysiological conditions such as cardiovascular diseases, neurodegenerative and behavioral disorders, cancers, diabetes, obesity, cataracts, and others. Therefore, cAMP targeted therapies have been and are still undergoing intense investigation for the treatment of these and other diseases. This highlights the need for developing assays to detect and monitor cAMP levels. In this study, we show cAMP Lumit assay as a highly specific homogeneous bioluminescent assay suitable for high throughput screenings with a large assay window and a wide dynamic range for cAMP detection. We believe that this assay will aid and simplify drug discovery screening efforts for cAMP signaling targeted therapies.
Shock impact simulation model along with the harmonic effect of the working device
Authors: Grządziela Andrzej , Kluczyk Marcin , Piskur Paweł , Naus Krzysztof 
Published: February 2024

AbstractThis study analyses the impact of initial conditions on the results of numerical simulations of the fan load with underwater detonation and simultaneously typical harmonic loads from the operating device. It was shown that different initial conditions affect both displacement and velocity results. Furthermore, significant differences were indicated when comparing the results with devices without harmonic loads. The results indicate the need for more detailed analyses at the initial stage of modelling the impact resistance of devices planned for ship installation.
Projections of the North Atlantic warming hole can be constrained using ocean surface density as an emergent constraint
Authors: Park In-Hong , Yeh Sang-Wook 
Published: February 2024

AbstractThere are large uncertainties in the projections of the future of the warming hole, which is defined as the cooling trend in the subpolar North Atlantic Ocean despite of global warming. Here, we found that the uncertainty in the future changes of the warming hole is mainly due to model bias rather than either natural variability or climate change scenario. Observations and model results constrain the future warming hole intensity in terms of its relationship with the present-day surface density in the subpolar North Atlantic. Models with a low present-day surface density tend to project a weaker warming hole intensity (i.e., a stronger temperature increase) due to a suppressed oceanic deep convection in the future than models with a high surface density. This relationship was robust across all scenarios and was used to reduce the uncertainty of the future warming hole intensity by 39% in the high emissions scenario.
Enhancing the potential of rapeseed cake as protein-source food by γ-irradiation
Authors: Xiong Chuan , Zou Xin , Phan Chia-Wei , Huang Wenli , Zhu Yu 
Published: February 2024

Abstract
Rapeseed cake serves as a by-product in the oil extraction industry, characterized by its elevated protein content. However, the presence of antinutritional factors limits the utilization of rapeseed cake as a viable protein source. In this study, different doses of γ-irradiation were used to irradiate rapeseed cake and rapeseed protein isolate was extracted through a modified alkaline solution and acid precipitation method from rapeseed cake. The chemical composition and in vivo acute toxicity of rapeseed protein isolate were determined. The protein recovery rate of rapeseed protein isolate was 39.08 ± 3.01% after irradiation, while the content of antinutritional factors was significantly reduced. Moreover, γ-irradiation did not have any experimentally related effects on clinical observations or clinicopathology in mice. Overall, the reduced antinutrients and increased functional properties suggest that the irradiation of rapeseed cake (&lt;9 kGy) could be utilized as a pre-treatment in the development of rapeseed cake-based value-added protein products.
A magnetic reconnection model for the hot explosion with both ultraviolet and Hα wing emissions
Authors: Cheng Guanchong , Ni Lei , Chen Yajie , Lin Jun 
Published: February 2024

Context. Ellerman bombs (EBs) with significant Hα wing emissions and ultraviolet bursts (UV bursts) with strong Si IV emissions are two kinds of small transient brightening events that occur in the low solar atmosphere. The statistical observational results indicate that about 20% of the UV bursts connect with EBs. While some promising models exist for the formation mechanism of colder EBs in conjunction with UV bursts, the topic remains an area of ongoing research and investigation.
Aim. We numerically investigated the magnetic reconnection process between the emerging arch magnetic field and the lower atmospheric background magnetic field. We aim to find out if the hot UV emissions and much colder Hα wing emissions can both appear in the same reconnection process and how they are located in the reconnection region.
Methods. The open-source code NIRVANA was applied to perform the 2.5D magnetohydrodynamic (MHD) simulation. We developed the related sub-codes to include the more realistic radiative cooling process for the photosphere and chromosphere and the time-dependent ionization degree of hydrogen. The initial background magnetic field is 600 G, and the emerged magnetic field in the solar atmosphere is of the same magnitude, meaning that it results in a low- β magnetic reconnection environment. We also used the radiative transfer code RH1.5D to synthesize the Si IV and Hα spectral line profiles based on the MHD simulation results.
Results. Magnetic reconnection between emerged and background magnetic fields creates a thin, curved current sheet, which then leads to the formation of plasmoid instability and the nonuniform density distributions. Initially, the temperature is below 8000 K. As the current sheet becomes more vertical, denser plasmas are drained by gravity, and hotter plasmas above 20 000 K appear in regions with lower plasma density. The mix of hot tenuous and much cooler dense plasmas in the turbulent reconnection region can appear at about the same height, or even in the same plasmoid. Through the reconnection region, the synthesized Si IV emission intensity can reach above 106 erg s−1 sr−1 cm−2 Å−1 and the spectral line profile can be wider than 100 km s−1, the synthesized Hα line profile also show the similar characteristics of a typical EB. The turbulent current sheet is always in a dense plasma environment with an optical depth larger than 6.5 × 10−5 due to the emerged magnetic field pushing high-density plasmas upward.
Conclusions. Our simulation results indicate that the cold EB and hot UV burst can both appear in the same reconnection process in the low chromosphere, the EB can either appear several minutes earlier than the UV burst, or they can simultaneously appear at the similar altitude in a turbulent reconnection region below the middle chromosphere.
Unraveling the Influence of Age, IQ, Education, and Negative Symptoms
on Neurocognitive Performance in Schizophrenia: A Conditional Inference Tree
Analysis
Authors: Hart Xenia M. , Mitsukura Yasue , Bies Robert R. , Uchida Hiroyuki 
Published: February 2024

Abstract
Introduction The complex nature of neurocognitive impairment in
schizophrenia has been discussed in light of the mixed effects of antipsychotic
drugs, psychotic symptoms, dopamine D2 receptor blockade, and
intelligence quotient (IQ). These factors have not been thoroughly examined
before.
Methods This study conducted a comprehensive re-analysis of the CATIE data
using machine learning techniques, in particular Conditional Inference Tree
(CTREE) analysis, to investigate associations between neurocognitive functions
and moderating factors such as estimated trough dopamine D2 receptor
blockade with risperidone, olanzapine, or ziprasidone, Positive and Negative
Syndrome Scale (PANSS), and baseline IQ in 573 patients with schizophrenia.
Results The study reveals that IQ, age, and education
consistently emerge as significant predictors across all neurocognitive domains.
Furthermore, higher severity of PANSS-negative symptoms was associated
with lower cognitive performance scores in several domains. CTREE analysis, in
combination with a genetic algorithm approach, has been identified as
particularly insightful for illustrating complex interactions between variables.
Lower neurocognitive function was associated with factors such as age>52
years, IQ<94/95,<12/13 education years, and more pronounced negative
symptoms (score<26).
Conclusions These findings emphasize the multifaceted nature of
neurocognitive functioning in patients with schizophrenia, with the
PANSS-negative score being an important predictor. This gives rise to a role in
addressing negative symptoms as a therapeutic objective for enhancing cognitive
impairments in these patients. Further research must examine nonlinear
relationships among various moderating factors identified in this work,
especially the role of D2 occupancy.
Tetraphenylmethane Derivatives Containing Nitrogen Heterocycles
Authors: Kotha Sambasivarao , Singh Deepshikha 
Published: February 2024

AbstractWe disclose a useful approach to novel tetrahedral building blocks containing N-heterocycles. Pyrrole was introduced on to the tetraphenylmethane (TPM) core by employing the RCM strategy, Clauson–Kaas reaction, Paal–Knorr condensation, and Ullmann coupling as key steps. In addition, various heterocyclic derivatives of TPM were prepared using nickel catalysts. We also studied the photophysical properties of the synthesized TPM derivatives containing different peripheral substituents and found that they exhibit high quantum yields.
PillHarmonics: An Orchestrated Pharmacogenetics Medication Clinical Decision Support Service
Authors: Dolin Robert H. , Shenvi Edna , Alvarez Carla , Barrows Randolph C. , Boxwala Aziz , Lee Benson , Nathanson Brian H. , Kleyner Yelena , Hagemann Rachel , Hongsermeier Tonya , Kapusnik-Uner Joan , Lakdawala Adnan , Shalaby James 
Published: February 2024

Abstract
Objectives Pharmacogenetics (PGx) is increasingly important in individualizing therapeutic management plans, but is often implemented apart from other types of medication clinical decision support (CDS). The lack of integration of PGx into existing CDS may result in incomplete interaction information, which may pose patient safety concerns. We sought to develop a cloud-based orchestrated medication CDS service that integrates PGx with a broad set of drug screening alerts and evaluate it through a clinician utility study.
Methods We developed the PillHarmonics service for implementation per the CDS Hooks protocol, algorithmically integrating a wide range of drug interaction knowledge using cloud-based screening services from First Databank (drug–drug/allergy/condition), PharmGKB (drug–gene), and locally curated content (drug–renal/hepatic/race). We performed a user study, presenting 13 clinicians and pharmacists with a prototype of the system's usage in synthetic patient scenarios. We collected feedback via a standard questionnaire and structured interview.
Results Clinician assessment of PillHarmonics via the Technology Acceptance Model questionnaire shows significant evidence of perceived utility. Thematic analysis of structured interviews revealed that aggregated knowledge, concise actionable summaries, and information accessibility were highly valued, and that clinicians would use the service in their practice.
Conclusion Medication safety and optimizing efficacy of therapy regimens remain significant issues. A comprehensive medication CDS system that leverages patient clinical and genomic data to perform a wide range of interaction checking and presents a concise and holistic view of medication knowledge back to the clinician is feasible and perceived as highly valuable for more informed decision-making. Such a system can potentially address many of the challenges identified with current medication-related CDS.