bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of humoral and cellular response to three doses of anti-SARS-CoV-2 BNT162b2 vaccine in patients with hematological malignancies and older subjects
Authors: Laquintana Valentina , Mottini Carla , Marchesi Francesco , Marcozzi Benedetta , Terrenato Irene , Sperandio Eleonora , de Latouliere Luisa , Carrieri Francesca , Pimpinelli Fulvia , Pontone Martina , Pellini Raul , Campo Flaminia , Conti Laura , Accetta Celeste , Mandoj Chiara , Petrone Fabrizio , Di Bella Ornella , Vujovic Branka , Morrone Aldo , Compagnone Mirco , Principato Eugenia , Pinto Eleonora , Papa Elena , Falcucci Paolo , La Malfa Antonia , Pallocca Matteo , De Marco Federico , Piaggio Giulia , Ciliberto Gennaro , Mengarelli Andrea , di Martino Simona 
Published: January 2024

BackgroundFew data are available about the durability of the response, the induction of neutralizing antibodies, and the cellular response upon the third dose of the anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in hemato-oncological patients.ObjectiveTo investigate the antibody and cellular response to the BNT162b2 vaccine in patients with hematological malignancy.MethodsWe measured SARS-CoV-2 anti-spike antibodies, anti-Omicron neutralizing antibodies, and T-cell responses 1 month after the third dose of vaccine in 93 fragile patients with hematological malignancy (FHM), 51 fragile not oncological subjects (FNO) aged 80–92, and 47 employees of the hospital (healthcare workers, (HW), aged 23-66 years. Blood samples were collected at day 0 (T0), 21 (T1), 35 (T2), 84 (T3), 168 (T4), 351 (T pre-3D), and 381 (T post-3D) after the first dose of vaccine. Serum IgG antibodies against S1/S2 antigens of SARS-CoV-2 spike protein were measured at every time point. Neutralizing antibodies were measured at T2, T3 (anti-Alpha), T4 (anti-Delta), and T post-3D (anti-Omicron). T cell response was assessed at T post-3D.ResultsAn increase in anti-S1/S2 antigen antibodies compared to T0 was observed in the three groups at T post-3D. After the third vaccine dose, the median antibody level of FHM subjects was higher than after the second dose and above the putative protection threshold, although lower than in the other groups. The neutralizing activity of antibodies against the Omicron variant of the virus was tested at T2 and T post-3D. 42.3% of FHM, 80,0% of FNO, and 90,0% of HW had anti-Omicron neutralizing antibodies at T post-3D. To get more insight into the breadth of antibody responses, we analyzed neutralizing capacity against BA.4/BA.5, BF.7, BQ.1, XBB.1.5 since also for the Omicron variants, different mutations have been reported especially for the spike protein. The memory T-cell response was lower in FHM than in FNO and HW cohorts. Data on breakthrough infections and deaths suggested that the positivity threshold of the test is protective after the third dose of the vaccine in all cohorts.ConclusionFHM have a relevant response to the BNT162b2 vaccine, with increasing antibody levels after the third dose coupled with, although low, a T-cell response. FHM need repeated vaccine doses to attain a protective immunological response.
Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion
Authors: Li Pengping , Wang Shaowen , Wan Hong , Huang Yuqing , Yin Kexin , Sun Ke , Jin Haigang , Wang Zhenyu 
Published: January 2024

BackgroundGiven the lack of research on disulfidptosis, our study aimed to dissect its role in pan-cancer and explore the crosstalk between disulfidptosis and cancer immunity.MethodsBased on TCGA, ICGC, CGGA, GSE30219, GSE31210, GSE37745, GSE50081, GSE22138, GSE41613, univariate Cox regression, LASSO regression, and multivariate Cox regression were used to construct the rough gene signature based on disulfidptosis for each type of cancer. SsGSEA and Cibersort, followed by correlation analysis, were harnessed to explore the linkage between disulfidptosis and cancer immunity. Weighted correlation network analysis (WGCNA) and Machine learning were utilized to make a refined prognosis model for pan-cancer. In particular, a customized, enhanced prognosis model was made for glioma. The siRNA transfection, FACS, ELISA, etc., were employed to validate the function of c-MET.ResultsThe expression comparison of the disulfidptosis-related genes (DRGs) between tumor and nontumor tissues implied a significant difference in most cancers. The correlation between disulfidptosis and immune cell infiltration, including T cell exhaustion (Tex), was evident, especially in glioma. The 7-gene signature was constructed as the rough model for the glioma prognosis. A pan-cancer suitable DSP clustering was made and validated to predict the prognosis. Furthermore, two DSP groups were defined by machine learning to predict the survival and immune therapy response in glioma, which was validated in CGGA. PD-L1 and other immune pathways were highly enriched in the core blue gene module from WGCNA. Among them, c-MET was validated as a tumor driver gene and JAK3-STAT3-PD-L1/PD1 regulator in glioma and T cells. Specifically, the down-regulation of c-MET decreased the proportion of PD1+ CD8+ T cells.ConclusionTo summarize, we dissected the roles of DRGs in the prognosis and their relationship with immunity in pan-cancer. A general prognosis model based on machine learning was constructed for pan-cancer and validated by external datasets with a consistent result. In particular, a survival-predicting model was made specifically for patients with glioma to predict its survival and immune response to ICIs. C-MET was screened and validated for its tumor driver gene and immune regulation function (inducing t-cell exhaustion) in glioma.
Dynamic immune signatures of patients with advanced non–small-cell lung cancer for infection prediction after immunotherapy
Authors: Luo Yung-Hung , Shen Chia-I , Chiang Chi-Lu , Huang Hsu-Ching , Chen Yuh-Min 
Published: January 2024

BackgroundPulmonary infections are a crucial health concern for patients with advanced non–small-cell lung cancer (NSCLC). Whether the clinical outcome of pulmonary infection is influenced by immunotherapy(IO) remains unclear. By evaluating immune signatures, this study investigated the post-immunotherapy risk of pulmonary infection in patients with lung cancer and identified circulating biomarkers that predict post-immunotherapy infection.MethodsBlood specimens were prospectively collected from patients with NSCLC before and after chemotherapy(C/T) and/or IO to explore dynamic changes in immune signatures. Real-world clinical data were extracted from medical records for outcome evaluation. Mass cytometry and ELISA were employed to analyze immune signatures and cytokine profiles to reveal potential correlations between immune profiles and the risk of infection.ResultsThe retrospective cohort included 283 patients with advanced NSCLC. IO was associated with a lower risk of pneumonia (odds ratio=0.46, p=0.012). Patients receiving IO and remained pneumonia-free exhibited the most favorable survival outcomes compared with those who received C/T or developed pneumonia (p&lt;0.001). The prospective cohort enrolled 30 patients. The proportion of circulating NK cells significantly increased after treatment in IO alone (p&lt;0.001) and C/T+IO group (p&lt;0.01). An increase in cell densities of circulating PD-1+CD8+(cytotoxic) T cells (p&lt;0.01) and PD-1+CD4+ T cells (p&lt;0.01) were observed in C/T alone group after treatment. In IO alone group, a decrease in cell densities of TIM-3+ and PD-1+ cytotoxic T cells (p&lt;0.05), and PD-1+CD4+ T cells (p&lt;0.01) were observed after treatment. In C/T alone and C/T+IO groups, cell densities of circulating PD-1+ cytotoxic T cells significantly increased in patients with pneumonia after treatment(p&lt;0.05). However, in IO alone group, cell density of PD-1+ cytotoxic T cells significantly decreased in patients without pneumonia after treatment (p&lt;0.05). TNF-α significantly increased after treatment with IO alone (p&lt;0.05) but decreased after C/T alone (p&lt;0.01).ConclusionsOur results indicate that the incorporation of immunotherapy into treatment regimens may potentially offer protective effects against pulmonary infection. Protective effects are associated with reduction of exhausted T-cells and augmentation of TNF-α and NK cells. Exhausted T cells, NK cells, and TNF-α may play crucial roles in immune responses against infections. These observations highlight the potential utility of certain circulating biomarkers, particularly exhausted T cells, for predicting post-treatment infections.
Tree shrews as a new animal model for systemic sclerosis research
Authors: Zheng Leting , Chen Shuyuan , Wu Qiulin , Li Xi , Zeng Wen , Dong Fei , An Weiwei , Qin Fang , Lei Ling , Zhao Cheng 
Published: January 2024

ObjectiveSystemic sclerosis (SSc) is a chronic systemic disease characterized by immune dysregulation and fibrosis for which there is no effective treatment. Animal models are crucial for advancing SSc research. Tree shrews are genetically, anatomically, and immunologically closer to humans than rodents. Thus, the tree shrew model provides a unique opportunity for translational research in SSc.MethodsIn this study, a SSc tree shrew model was constructed by subcutaneous injection of different doses of bleomycin (BLM) for 21 days. We assessed the degree of inflammation and fibrosis in the skin and internal organs, and antibodies in serum. Furthermore, RNA sequencing and a series of bioinformatics analyses were performed to analyze the transcriptome changes, hub genes and immune infiltration in the skin tissues of BLM induced SSc tree shrew models. Multiple sequence alignment was utilized to analyze the conservation of selected target genes across multiple species.ResultsSubcutaneous injection of BLM successfully induced a SSc model in tree shrew. This model exhibited inflammation and fibrosis in skin and lung, and some developed esophageal fibrosis and secrum autoantibodies including antinuclear antibodies and anti-scleroderma-70 antibody. Using RNA sequencing, we compiled skin transcriptome profiles in SSc tree shrew models. 90 differentially expressed genes (DEGs) were identified, which were mainly enriched in the PPAR signaling pathway, tyrosine metabolic pathway, p53 signaling pathway, ECM receptor interaction and glutathione metabolism, all of which are closely associated with SSc. Immune infiltration analysis identified 20 different types of immune cells infiltrating the skin of the BLM-induced SSc tree shrew models and correlations between those immune cells. By constructing a protein-protein interaction (PPI) network, we identified 10 hub genes that were significantly highly expressed in the skin of the SSc models compared to controls. Furthermore, these genes were confirmed to be highly conserved in tree shrews, humans and mice.ConclusionThis study for the first time comfirmed that tree shrew model of SSc can be used as a novel and promising experimental animal model to study the pathogenesis and translational research in SSc.
Combined analysis of host IFN-γ, IL-2 and IP-10 as potential LTBI biomarkers in ESAT-6/CFP-10 stimulated blood
Authors: Rapulana Antony M. , Mpotje Thabo , Baiyegunhi Omolara O. , Ndlovu Hlumani , Smit Theresa K. , McHugh Timothy D. , Marakalala Mohlopheni J. 
Published: January 2024

Background: Accurate diagnosis of latent tuberculosis infected (LTBI) individuals is important in identifying individuals at risk of developing active tuberculosis. Current diagnosis of LTBI routinely relies on the detection and measurement of immune responses using the Tuberculin Skin Test (TST) and interferon gamma release assays (IGRAs). However, IGRA, which detects Mycobacterium tuberculosis specific IFN-γ, is associated with frequent indeterminate results, particularly in immunosuppressed patients. There is a need to identify more sensitive LTBI point of care diagnostic biomarkers. The aim of this study was to assess the validity of early secreted antigen target 6 kDa (ESAT-6) and culture filtrate protein 10 (CFP-10) stimulated plasma to identify additional cytokines and chemokines as potential biomarkers of LTBI.Method: The levels of 27 cytokines and chemokines were measured by Bio-Plex Pro cytokine, chemokine and growth factor assay in ESAT-6 and CFP-10 co-stimulated plasma from 20 LTBI participants with positive IGRA (Quantiferon TB Gold plus) and 20 healthy controls with negative IGRA. Traditional ELISA was used to validate the abundance of the best performing markers in 70 LTBI and 72 healthy participants. All participants were HIV negative.Results: We found that Interleukin 1 receptor antagonist (IL1ra) (p = 0.0056), Interleukin 2 (IL-2) (p &lt; 0.0001), Interleukin 13 (IL-13) (p &lt; 0.0001), Interferon gamma-induced protein 10 (IP-10) (p &lt; 0.0001), and Macrophage inflammatory protein-1 beta (MIP1b) (p = 0.0010) were significantly higher in stimulated plasma of LTBI compared to healthy individuals. Stimulated plasma IL-2 (cutoff 100 pg/mL), IP-10 (cutoff 300 pg/mL) and IL-13 (5 pg/mL) showed potential in diagnosing LTBI with PPV = 100%, 0.89.4%, and 80.9% and NPV = 86.9%, 0.85.7%, and 84.2%, respectively.Conclusion: Our data shows that co-stimulating whole blood with ESAT-6 and CFP-10 may help distinguish LTBI from healthy individuals. We also identified IL-2 and IP-10 as potential biomarkers that could be added to the currently used IFN-γ release assays in detection of LTBI.
Detection and evaluation of signals for immune-related adverse events: a nationwide, population-based study
Authors: Kim Eo Jin , Kim Ye-Jee , Heo Ja Yoon , Kim Minju , Lee Soohyeon , Seo Seyoung , Myung Jisun , Oh Ji Seon , Park Sook Ryun 
Published: January 2024

BackgroundImmune checkpoint inhibitors (ICIs) are one of the main pillars of cancer therapy. Since other studies such as clinical trial and retrospective study have limitations for detecting the immune-related adverse events (irAEs) characterized by unpredictable onset, nonspecific symptoms and wide clinical spectrum, we aimed to identify the incidence of irAEs and to detect and evaluate the signals using real-world data.MethodsCancer patients treated with anticancer medications were analyzed using the nationwide health insurance claims database of South Korea from 2017 to 2019, and Clinical Data Warehouse (CDW) database of Asan Medical Center (AMC), a tertiary referral hospital, from 2012 to 2019. AEs of ICI users were compared with those of non-ICI anticancer medication users. PD-1 inhibitors (nivolumab and pembrolizumab) and PD-L1 inhibitors (atezolizumab) were evaluated. We defined an AE as a newly added diagnosis after the ICI prescription using an ICD-10 diagnostic code. A signal was defined as an AE that was detected by any one of the four indices of data mining: hazard ratio (HR), proportional claims ratio (PCR), claims odds ratio (COR), or information component (IC). All detected signals were reviewed and classified into well-known or potential irAEs. Signal verification was performed for targeted AEs using CDW of AMC using diagnostic codes and text mining.ResultsWe identified 118 significant signals related to ICI use. We detected 31 well-known irAEs, most of which were endocrine diseases and skin diseases. We also detected 33 potential irAEs related to disorders in the nervous system, eye, circulatory system, digestive system, skin and subcutaneous tissues, and bones. Especially, portal vein thrombosis and bone disorders such as osteoporosis with pathological fracture and fracture of shoulder, upper arm, femur, and lower leg showed high HR in ICI users than in non-ICI users. The signals from hospital database were verified using diagnostic codes and text mining.ConclusionThis real-world data analysis demonstrated an efficient approach for signal detection and evaluation of ICI use. An effective real-world pharmacovigilance system of the nationwide claims database and the EMR could complement each other in detecting significant AE signals.
Applying the estimand and target trial frameworks to external control analyses using observational data: a case study in the solid tumor setting
Authors: Polito Letizia , Liang Qixing , Pal Navdeep , Mpofu Philani , Sawas Ahmed , Humblet Olivier , Rufibach Kaspar , Heinzmann Dominik 
Published: January 2024

Introduction: In causal inference, the correct formulation of the scientific question of interest is a crucial step. The purpose of this study was to apply causal inference principles to external control analysis using observational data and illustrate the process to define the estimand attributes.Methods: This study compared long-term survival outcomes of a pooled set of three previously reported randomized phase 3 trials studying patients with metastatic non-small cell lung cancer receiving front-line chemotherapy and similar patients treated with front-line chemotherapy as part of routine clinical care. Causal inference frameworks were applied to define the estimand aligned with the research question and select the estimator to estimate the estimand of interest.Results: The estimand attributes of the ideal trial were defined using the estimand framework. The target trial framework was used to address specific issues in defining the estimand attributes using observational data from a nationwide electronic health record-derived de-identified database. The two frameworks combined allow to clearly define the estimand and the aligned estimator while accounting for key baseline confounders, index date, and receipt of subsequent therapies. The hazard ratio estimate (point estimate with 95% confidence interval) comparing the randomized clinical trial pooled control arm with the external control was close to 1, which is indicative of similar survival between the two arms.Discussion: The proposed combined framework provides clarity on the causal contrast of interest and the estimator to adopt, and thus facilitates design and interpretation of the analyses.
Comparative gene co-expression networks show enrichment of brassinosteroid and vitamin B processes in a seagrass under simulated ocean warming and extreme climatic events
Authors: Booth Mitchell W. , Sinclair Elizabeth A. , Jung Elisabeth Maria U. , Austin Rachel , Bayer Philipp E. , Krauss Siegfried L. , Breed Martin F. , Kendrick Gary A. 
Published: January 2024

IntroductionOcean warming combined with extreme climatic events, such as marine heatwaves and flash flooding events, threaten seagrasses globally. How seagrasses cope with these challenges is uncertain, particularly for range-edge populations of species such as Posidonia australis in Shark Bay, Western Australia. Analyzing gene expression while manipulating multiple stressors provides insight into the genetic response and resilience of seagrasses to climate change. We conducted a gene expression study on a polyploid clone of P. australis during an 18-week mesocosm experiment to assess the responses to single and combined future climate change-associated stressors. MethodsPlants were exposed to (1) future ocean warming temperature (baseline +1.5°C) followed by a simulated marine heat wave (baseline +5.5°C), (2) light deprivation simulating observed marine heatwave driven turbidity (95% shade) at baseline temperatures, or (3) both stressors simultaneously. Basal leaf meristems were sampled for gene expression analysis using RNA-seq at four time points during the experiment. Weighted gene co-expression network analysis, GO term enrichment, and KEGG pathway enrichment analyses were used to identify stress responses. ResultsShaded plants showed specific gene enrichment for shade avoidance (programmed cell death) after three weeks of stress, and before any heated tanks showed a specific heat response. Shaded plants were positively correlated with programmed cell death and stress-related processes at the end of the experiment. Once ocean warming temperatures (+1.5°C) were in effect, gene enrichment for heat stress (e.g., ROS scavenging and polyamine metabolism) was present. Vitamin B processes, RNA polymerase II processes. and light-related meristematic phase changes were expressed with the addition of simulated MHW. Heated plants showed meristematic growth signatures as well as trehalose and salicylic acid metabolism. Brassinosteroid-related processes were significantly enriched in all stressor treatments at all time points, except for the isolated heat-stressed plants three weeks after stressor initiation. DiscussionGene expression responses to the interaction between heat waves and turbidity-induced light reduction support the observed geographical scale mortality in seagrasses observed for P. australis in Shark Bay, suggesting that even this giant polyploid clone will be negatively impacted by more extreme climate change projections.
The association between Long-COVID symptomology, perceived symptom burden and mental health in COVID-19 patients in Shijiazhuang, China: a population-based health survey
Authors: Li Yufei , Lam Lawrence T. , Xiao Ying , Qiu Zhengqi , Zhang Yanming 
Published: January 2024

BackgroundLong-COVID (LC) refers to post-acute COVID-19 symptoms that can last for months or longer after the initial infection, affecting the physical health of infected patients. This study aims to investigate the association between the symptomology of LC and the mental health of patients in China. It also aims to examine the relationship between the perceived symptom burden and mental health of these patients.MethodsA population-based stratified cluster sample was recruited, using a standard sampling procedure, from a prefecture-level city in Northern China. Participants included patients who had tested positive for COVID-19 after December 2022. LC symptomology was assessed using a LC symptoms checklist where the perceived symptom burden was measured by the included 5-point Likert scales. Mental health of patients was measured using the Depression, Anxiety, and Stress Scale (DASS), the original Connor-Davidson Resilience Scale (CD-RISC), and the Duke-UNC Functional Social Support Questionnaire (DUFSS). Data were analysed using multiple linear regression models.ResultsAbout 25% of respondents, experienced COVID symptoms lasting longer than two months that could only be explained by the infection. Post-exertional malaise (22.2%) and fatigue (21.2%) were the most common symptoms. After controlling for potential confounding variables, LC symptomology was significantly and positively associated with depression (t=2.09, p=0.037) and anxiety (t=4.51, p&lt;0.001), but not stress. Perceived symptoms burden was also positively and significantly related to depression (β=0.35, p&lt;0.001), anxiety (β=0.54, p&lt;0.001), and stress (β=0.35, p&lt;0.001), suggesting a dose-response relationship between perceived symptom burden and mental ill health.ConclusionThis study highlights the importance of recognising the risk of LC, patients’ perception of the symptom burden and its potential impact on mental health. Healthcare professionals should be aware of the complexity of psychological comorbidities among infected patients reporting prolonged symptoms, and be able to give advice regarding long-term management of the symptoms.