bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hepatitis D infection induces IFN-β-mediated NK cell activation and TRAIL-dependent cytotoxicity
Authors: Groth Christopher , Maric Jovana , Garcés Lázaro Irene , Hofman Tomáš , Zhang Zhenfeng , Ni Yi , Keller Franziska , Seufert Isabelle , Hofmann Maike , Neumann-Haefelin Christoph , Sticht Carsten , Rippe Karsten , Urban Stephan , Cerwenka Adelheid 
Published: December 2023

Background and aimsThe co-infection of hepatitis B (HBV) patients with the hepatitis D virus (HDV) causes the most severe form of viral hepatitis and thus drastically worsens the course of the disease. Therapy options for HBV/HDV patients are still limited. Here, we investigated the potential of natural killer (NK) cells that are crucial drivers of the innate immune response against viruses to target HDV-infected hepatocytes.MethodsWe established in vitro co-culture models using HDV-infected hepatoma cell lines and human peripheral blood NK cells. We determined NK cell activation by flow cytometry, transcriptome analysis, bead-based cytokine immunoassays, and NK cell-mediated effects on T cells by flow cytometry. We validated the mechanisms using CRISPR/Cas9-mediated gene deletions. Moreover, we assessed the frequencies and phenotype of NK cells in peripheral blood of HBV and HDV superinfected patients.ResultsUpon co-culture with HDV-infected hepatic cell lines, NK cells upregulated activation markers, interferon-stimulated genes (ISGs) including the death receptor ligand tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), produced interferon (IFN)-γ and eliminated HDV-infected cells via the TRAIL-TRAIL-R2 axis. We identified IFN-β released by HDV-infected cells as an important enhancer of NK cell activity. In line with our in vitro data, we observed activation of peripheral blood NK cells from HBV/HDV co-infected, but not HBV mono-infected patients.ConclusionOur data demonstrate NK cell activation in HDV infection and their potential to eliminate HDV-infected hepatoma cells via the TRAIL/TRAIL-R2 axis which implies a high relevance of NK cells for the design of novel anti-viral therapies.
Manifestation of subacute cutaneous lupus erythematosus during treatment with anti-PD-1 antibody cemiplimab – a case report
Authors: Fietz Simon , Fröhlich Anne , Mauch Cornelia , de Vos-Hillebrand Luka , Fetter Tanja , Landsberg Jennifer , Hoffmann Friederike , Sirokay Judith 
Published: December 2023

IntroductionThe anti-programmed cell death protein 1 (PD-1) antibody cemiplimab has shown promising results in the treatment of unresectable or metastatic squamous cell carcinoma, however, frequently leads to immune-related adverse events limiting therapy efficacy. Although cutaneous side effects are common, only very few cases of cutaneous lupus erythematosus have been reported under anti-PD-1 immunotherapy. So far, no case of cutaneous lupus has been described under treatment with cemiplimab.Case reportFor the first time, we report the case of a patient with advanced squamous cell carcinoma, who developed clinical and histological findings in sun-exposed skin that were consistent with anti-SS-A/Ro antibody-positive subacute cutaneous lupus erythematosus (SCLE) under treatment with cemiplimab. Additionally, laboratory chemical analyses revealed a severe immune-related hepatitis without clinical symptoms. Both, the SCLE and the hepatitis, resolved after the administration of topical and systemic steroids and the discontinuation of anti-PD-1 therapy.ConclusionTreatment with cemiplimab can be associated with the appearance of cutaneous lupus erythematosus in sun-exposed areas. Application of topical and systemic glucocorticoids can lead to a rapid resolution of the skin eruptions. Moreover, our case illustrates the possibility of simultaneously occurring severe immune-related adverse events. This highlights the importance of additional diagnostics to avoid overlooking additional immune-related adverse events.
Enhancement of dieckol extraction yield from Ecklonia cava through optimization of major variables in generally recognized as safe solvent-based process
Authors: Shin Hyeonmi , Lee Jeongho , Bae Jihyun , Lee Kang Hyun , Yoo Hah Young , Park Chulhwan 
Published: December 2023

Ecklonia cava (EC), an edible brown macroalga abundant in intertidal areas of East Asia (Korea, Japan, and China), contains high-value bioactive compounds such as dieckol, which has antifungal, anti-inflammatory, antitumor, and antihyperlipidemic activities. However, no studies have been reported on the utilization of EC as a biorefinery feedstock, and the design of a more economical and high-yield process is required for the utilization of dieckol for the human healthcare industry. In this study, we designed a bioprocess for the high-yield recovery of dieckol from EC in a generally recognized as safe (GRAS) solvent to facilitate its application in the food and healthcare industries. Preliminary studies identified ethanol as an efficient solvent with the highest dieckol extraction yield (2.9 mg/g biomass). In order to maximize the recovery of dieckol from EC, the major extraction variables (solvent concentration, reaction temperature, and reaction time) were optimized based on statistical methods. Based on the predictive model, the numerical optimization determined that the solution with the highest dieckol content per weight of extract (62.6 vol% ethanol concentration, 54.2°C temperature, 13.2 min) was the optimal extraction condition. Under the determined conditions, the dieckol yield from EC achieved 6.4 mg dieckol/g EC (95.5% agreement with the predicted value). The designed process offers several advantages, including improving the utilization feasibility of EC, utilizing GRAS solvents with potential human applications, short extraction time (13.2 min), maximized process yield, and the highest dieckol recovery compared to previous reports.
Comparative transcriptome analysis of SARS-CoV-2, SARS-CoV, MERS-CoV, and HCoV-229E identifying potential IFN/ISGs targets for inhibiting virus replication
Authors: Liu Yuzhuang , Lu Tianyi , Li Cuidan , Wang Xiaotong , Chen Fei , Yue Liya , Jiang Chunlai 
Published: December 2023

IntroductionSince its outbreak in December 2019, SARS-CoV-2 has spread rapidly across the world, posing significant threats and challenges to global public health. SARS-CoV-2, together with SARS-CoV and MERS-CoV, is a highly pathogenic coronavirus that contributes to fatal pneumonia. Understanding the similarities and differences at the transcriptome level between SARS-CoV-2, SARS-CoV, as well as MERS-CoV is critical for developing effective strategies against these viruses.MethodsIn this article, we comparatively analyzed publicly available transcriptome data of human cell lines infected with highly pathogenic SARS-CoV-2, SARS-CoV, MERS-CoV, and lowly pathogenic HCoV-229E. The host gene expression profiles during human coronavirus (HCoV) infections were generated, and the pathways and biological functions involved in immune responses, antiviral efficacy, and organ damage were intensively elucidated.ResultsOur results indicated that SARS-CoV-2 induced a stronger immune response versus the other two highly pathogenic HCoVs. Specifically, SARS-CoV-2 induced robust type I and type III IFN responses, marked by higher upregulation of type I and type III IFNs, as well as numerous interferon-stimulated genes (ISGs). Further Ingenuity Pathway Analysis (IPA) revealed the important role of ISGs for impeding SARS-CoV-2 infection, and the interferon/ISGs could be potential targets for therapeutic interventions. Moreover, our results uncovered that SARS-CoV-2 infection was linked to an enhanced risk of multi-organ toxicity in contrast to the other two highly pathogenic HCoVs.DiscussionThese findings provided valuable insights into the pathogenic mechanism of SARS-CoV-2, which showed a similar pathological feature but a lower fatality rate compared to SARS-CoV and MERS-CoV.
Mitochondrial genome sequence of the protist Ancyromonas sigmoides Kent, 1881 (Ancyromonadida) from the Sugluk Inlet, Hudson Strait, Nunavik, Québec
Authors: Gastineau Romain , Harðardóttir Sara , Guilmette Caroline , Lemieux Claude , Turmel Monique , Otis Christian , Boyle Brian , Levesque Roger C. , Gauthier Jeff , Potvin Marianne , Lovejoy Connie 
Published: December 2023

IntroductionThere is little information on evolutionarily ancient eukaryotes, which are often referred to as basal eukaryotes, in Arctic waters. Despite earlier studies being conducted in the Russian White Sea, only few have been reported.MethodsFollowing a shotgun sequence survey of diatom cultures from Sugluk Inlet off the Hudson Strait in Northern Québec, we obtained the complete mitochondrial genome and the operon of nuclear ribosomal RNA genes from a strain that matches that of Ancyromonas sigmoides (Kent, 1881).ResultsThe sequence of the mitogenome retrieved was 41,889 bp in length and encoded 38 protein-coding genes, 5 non-conserved open-reading frames, and 2 rRNA and 24 tRNA genes. The mitogenome has retained sdh2 and sdh3, two genes of the succinate dehydrogenase complex, which are sometimes found among basal eukaryotes but seemingly missing among the Malawimonadidae, a lineage sister to Ancyromonadida in some phylogenies. The phylogeny inferred from the 18S rRNA gene associated A. sigmoides from Sugluk Inlet with several other strains originating from the Arctic. The study also unveiled the presence of a metagenomic sequence ascribed to bacteria in GenBank, but it was clearly a mitochondrial genome with a gene content highly similar to that of A. sigmoides, including the non-conserved open-reading frames.DiscussionAfter re-annotation, a phylogeny was inferred from mitochondrial protein sequences, and it strongly associated A. sigmoides with the misidentified organism, with the two being possibly conspecific or sibling species as they are more similar to one another than to species of the genus Malawimonas. Overall our phylogeny showed that the ice associated ancryomonads were clearly distinct from more southerly strains.
Unveiling microbial biomarkers of ruminant methane emission through machine learning
Authors: Peng Chengyao , May Ali , Abeel Thomas 
Published: December 2023

BackgroundEnteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine learning algorithms have shown success in associating human gut microbiome with various human diseases, there have been limited efforts to employ these algorithms to establish microbial biomarkers for methane emissions in ruminants.MethodsIn this study, we aim to identify potential methane biomarkers for methane emission from ruminants by employing regression algorithms commonly used in human microbiome studies, coupled with different feature selection methods. To achieve this, we analyzed the microbiome compositions and identified possible confounding metadata variables in two large public datasets of Holstein cows. Using both the microbiome features and identified metadata variables, we trained different regressors to predict methane emission. With the optimized models, permutation tests were used to determine feature importance to find informative microbial features.ResultsAmong the regression algorithms tested, random forest regression outperformed others and allowed the identification of several crucial microbial taxa for methane emission as members of the native rumen microbiome, including the genera Piromyces, Succinivibrionaceae UCG-002, and Acetobacter. Additionally, our results revealed that certain herd locations and feed composition markers, such as the lipid intake and neutral-detergent fiber intake, are also predictive features for methane emissions.ConclusionWe demonstrated that machine learning, particularly regression algorithms, can effectively predict cow methane emissions and identify relevant rumen microorganisms. Our findings offer valuable insights for the development of microbiome-based precision feed strategies aiming at reducing methane emissions.
Selective oxytocin receptor activation prevents prefrontal circuit dysfunction and social behavioral alterations in response to chronic prefrontal cortex activation in male rats
Authors: Janz Philipp , Knoflach Frederic , Bleicher Konrad , Belli Sara , Biemans Barbara , Schnider Patrick , Ebeling Martin , Grundschober Christophe , Benekareddy Madhurima 
Published: December 2023

IntroductionSocial behavioral changes are a hallmark of several neurodevelopmental and neuropsychiatric conditions, nevertheless the underlying neural substrates of such dysfunction remain poorly understood. Building evidence points to the prefrontal cortex (PFC) as one of the key brain regions that orchestrates social behavior. We used this concept with the aim to develop a translational rat model of social-circuit dysfunction, the chronic PFC activation model (CPA).MethodsChemogenetic designer receptor hM3Dq was used to induce chronic activation of the PFC over 10 days, and the behavioral and electrophysiological signatures of prolonged PFC hyperactivity were evaluated. To test the sensitivity of this model to pharmacological interventions on longer timescales, and validate its translational potential, the rats were treated with our novel highly selective oxytocin receptor (OXTR) agonist RO6958375, which is not activating the related vasopressin V1a receptor.ResultsCPA rats showed reduced sociability in the three-chamber sociability test, and a concomitant decrease in neuronal excitability and synaptic transmission within the PFC as measured by electrophysiological recordings in acute slice preparation. Sub-chronic treatment with a low dose of the novel OXTR agonist following CPA interferes with the emergence of PFC circuit dysfunction, abnormal social behavior and specific transcriptomic changes.DiscussionThese results demonstrate that sustained PFC hyperactivity modifies circuit characteristics and social behaviors in ways that can be modulated by selective OXTR activation and that this model may be used to understand the circuit recruitment of prosocial therapies in drug discovery.
Claims-based algorithm to estimate the Expanded Disability Status Scale for multiple sclerosis in a German health insurance fund: a validation study using patient medical records
Authors: Muros-Le Rouzic Erwan , Ghiani Marco , Zhuleku Evi , Dillenseger Anja , Maywald Ulf , Wilke Thomas , Ziemssen Tjalf , Craveiro Licinio 
Published: December 2023

BackgroundThe Expanded Disability Status Scale (EDSS) quantifies disability and measures disease progression in multiple sclerosis (MS), however is not available in administrative claims databases.ObjectivesTo develop a claims-based algorithm for deriving EDSS and validate it against a clinical dataset capturing true EDSS values from medical records.MethodsWe built a unique linked dataset combining claims data from the German AOK PLUS sickness fund and medical records from the Multiple Sclerosis Management System 3D (MSDS3D). Data were deterministically linked based on insurance numbers. We used 69 MS-related diagnostic indicators recorded with ICD-10-GM codes within 3 months before and after recorded true EDSS measures to estimate a claims-based EDSS proxy (pEDSS). Predictive performance of the pEDSS was assessed as an eight-fold (EDSS 1.0–7.0, ≥8.0), three-fold (EDSS 1.0–3.0, 4.0–5.0, ≥6.0), and binary classifier (EDSS &lt;6.0, ≥6.0). For each classifier, predictive performance measures were determined, and overall performance was summarized using a macro F1-score. Finally, we implemented the algorithm to determine pEDSS among an overall cohort of patients with MS in AOK PLUS, who were alive and insured 12 months prior to and after index diagnosis.ResultsWe recruited 100 people with MS insured by AOK PLUS who had ≥1 EDSS measure in MSDS3D between 01/10/2015 and 30/06/2019 (620 measurements overall). Patients had a mean rescaled EDSS of 3.2 and pEDSS of 3.0. The pEDSS deviated from the true EDSS by 1.2 points, resulting in a mean squared error of prediction of 2.6. For the eight-fold classifier, the macro F1-score of 0.25 indicated low overall predictive performance. Broader severity groupings were better performing, with the three-fold and binary classifiers for severe disability achieving a F1-score of 0.68 and 0.84, respectively. In the overall AOK PLUS cohort (3,756 patients, 71.9% female, mean 51.9 years), older patients, patients with progressive forms of MS and those with higher comorbidity burden showed higher pEDSS.ConclusionGenerally, EDSS was underestimated by the algorithm as mild-to-moderate symptoms were poorly captured in claims across all functional systems. While the proxy-based approach using claims data may not allow for granular description of MS disability, broader severity groupings show good predictive performance.
Cohort analysis of novel SPAST variants in SPG4 patients and implementation of in vitro and in vivo studies to identify the pathogenic mechanism caused by splicing mutations
Authors: Ferese Rosangela , Scala Simona , Suppa Antonio , Campopiano Rosa , Asci Francesco , Zampogna Alessandro , Chiaravalloti Maria Antonietta , Griguoli Annamaria , Storto Marianna , Pardo Alba Di , Giardina Emiliano , Zampatti Stefania , Fornai Francesco , Novelli Giuseppe , Fanelli Mirco , Zecca Chiara , Logroscino Giancarlo , Centonze Diego , Gambardella Stefano 
Published: December 2023

IntroductionPure hereditary spastic paraplegia (SPG) type 4 (SPG4) is caused by mutations of SPAST gene. This study aimed to analyze SPAST variants in SPG4 patients to highlight the occurrence of splicing mutations and combine functional studies to assess the relevance of these variants in the molecular mechanisms of the disease.MethodsWe performed an NGS panel in 105 patients, in silico analysis for splicing mutations, and in vitro minigene assay.Results and discussionThe NGS panel was applied to screen 105 patients carrying a clinical phenotype corresponding to upper motor neuron syndrome (UMNS), selectively affecting motor control of lower limbs. Pathogenic mutations in SPAST were identified in 12 patients (11.42%), 5 missense, 3 frameshift, and 4 splicing variants. Then, we focused on the patients carrying splicing variants using a combined approach of in silico and in vitro analysis through minigene assay and RNA, if available. For two splicing variants (i.e., c.1245+1G&gt;A and c.1414-2A&gt;T), functional assays confirm the types of molecular alterations suggested by the in silico analysis (loss of exon 9 and exon 12). In contrast, the splicing variant c.1005-1delG differed from what was predicted (skipping exon 7), and the functional study indicates the loss of frame and formation of a premature stop codon. The present study evidenced the high splice variants in SPG4 patients and indicated the relevance of functional assays added to in silico analysis to decipher the pathogenic mechanism.
A novel animal model of neuropathic corneal pain–the ciliary nerve constriction model
Authors: Seyed-Razavi Yashar , Kenyon Brendan M. , Qiu Fangfang , Harris Deshea L. , Hamrah Pedram 
Published: December 2023

IntroductionNeuropathic pain arises as a result of peripheral nerve injury or altered pain processing within the central nervous system. When this phenomenon affects the cornea, it is referred to as neuropathic corneal pain (NCP), resulting in pain, hyperalgesia, burning, and photoallodynia, severely affecting patients’ quality of life. To date there is no suitable animal model for the study of NCP. Herein, we developed an NCP model by constriction of the long ciliary nerves innervating the eye.MethodsMice underwent ciliary nerve constriction (CNC) or sham procedures. Safety was determined by corneal fluorescein staining to assess ocular surface damage, whereas Cochet-Bonnet esthesiometry and confocal microscopy assessed the function and structure of corneal nerves, respectively. Efficacy was assessed by paw wipe responses within 30 seconds of applying hyperosmolar (5M) saline at Days 3, 7, 10, and 14 post-constriction. Additionally, behavior was assessed in an open field test (OFT) at Days 7, 14, and 21.ResultsCNC resulted in significantly increased response to hyperosmolar saline between groups (p &lt; 0.0001), demonstrating hyperalgesia and induction of neuropathic pain. Further, animals that underwent CNC had increased anxiety-like behavior in an open field test compared to controls at the 14- and 21-Day time-points (p &lt; 0.05). In contrast, CNC did not result in increased corneal fluorescein staining or decreased sensation as compared to sham controls (p &gt; 0.05). Additionally, confocal microscopy of corneal whole-mounts revealed that constriction resulted in only a slight reduction in corneal nerve density (p &lt; 0.05), compared to naïve and sham groups.DiscussionThe CNC model induces a pure NCP phenotype and may be a useful model for the study of NCP, recapitulating features of NCP, including hyperalgesia in the absence of ocular surface damage, and anxiety-like behavior.
Prognosis of comatose patients with reduced EEG montage by combining quantitative EEG features in various domains
Authors: Tao Tao , Lu Shiqi , Hu Nan , Xu Dongyang , Xu Chenyang , Li Fajun , Wang Qin , Peng Yuan 
Published: December 2023

ObjectiveAs the frontoparietal network underlies recovery from coma, a limited frontoparietal montage was used, and the prognostic values of EEG features for comatose patients were assessed.MethodsCollected with a limited frontoparietal EEG montage, continuous EEG recordings of 81 comatose patients in ICU were used retrospectively. By the 60-day Glasgow outcome scale (GOS), the patients were dichotomized into favorable and unfavorable outcome groups. Temporal-, frequency-, and spatial-domain features were automatically extracted for comparison. Partial correlation analysis was applied to eliminate redundant factors, and multiple correspondence analysis was used to explore discrimination between groups. Prognostic characteristics were calculated to assess the performance of EEG feature-based predictors established by logistic regression. Analyses were performed on all-patients group, strokes subgroup, and traumatic brain injury (TBI) subgroup.ResultsBy analysis of all patients, raised burst suppression ratio (BSR), suppressed root mean square (RMS), raised power ratio of β to α rhythm (β/α), and suppressed phase-lag index between F3 and P4 (PLI [F3, P4]) were associated with unfavorable outcome, and yielded AUC of 0.790, 0.811, 0.722, and 0.844, respectively. For the strokes subgroup, the significant variables were BSR, RMS, θ/total, θ/δ, and PLI (F3, P4), while for the TBI subgroup, only PLI (F3, P4) was significant. BSR combined with PLI (F3, P4) gave the best predictor by cross-validation analysis in the all-patients group (AUC = 0.889, 95% CI: 0.819–0.960).ConclusionFeatures extracted from limited frontoparietal montage EEG served as valuable coma prognostic tools, where PLI (F3, P4) was always significant. Combining PLI (F3, P4) with features in other domains may achieve better performance.SignificanceA limited-montage EEG coupled with an automated algorithm is valuable for coma prognosis.