bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visual analysis of hot spots and trends in research of meteorology and hemorrhagic fever with renal syndrome: a bibliometric analysis based on CiteSpace and VOSviewer
Authors: Dong Yonghai , Ding Sheng , Zhang Tianchen , Zhou Wenfang , Si Hongyu , Yang Chen , Liu Xiaoqing 
Published: August 2024

Objective: We here displayed the global research trends of meteorology and hemorrhagic fever with renal syndrome (HFRS) as a visual knowledge map by using bibliometrics and revealed the research directions, hotspots, trends, and frontiers in this field.Methods: Using Web of Science core collection as the data source and with CiteSpace and VOSviewer software, we collected and analyzed the annual number of papers, cooperative relationships (countries, institutions, authors, etc.), citations (literature citation, literature co-citation, literature publication, etc.), keywords (emergence, clustering, etc.) of meteorology, and HFRS-related research data for the past 30 years, and drew a visual map.Results: In total, this study included 313 papers investigating the relationship between meteorology and HFRS. The first paper was published in 1992. Globally, United States had the largest number of publications in this field, and the Chinese Center for Disease Control and Prevention was the most influential institution conducting related research (20 articles published, and the mediation centrality was 0.24). Several small author cooperation clusters were formed; however, the number of papers published by the same scholar and the co-citation frequency were low. Cazelles Bernard (7 articles) published the highest number of articles in this field, and Gubler DJ was the author with the most co-citations (55 times). The most frequently cited journal was Emerging Infectious Diseases. In this field, the top three high-frequency keywords were “hemorrhagic fever,” “transmission,” and “temperature.” According to keyword cluster analysis, the top three themes were dengue, dechlorane plus, and bank voles. The timeline spectrum exhibited that dengue clustering had a good temporal continuity. The trend analysis of emergent words revealed that the research on “temperature,” “meteorological factors” and “Puumala hantavirus” has gradually appeared in recent years.Conclusion: This study represents the first comprehensive exploration of global trends, hotspots, frontiers, and developments in the relationship between meteorology and HFRS, utilizing CiteSpace and VOSviewer software. The findings of this study are crucial for elucidating the influence of climate change on disease transmission patterns and offering novel insights for forthcoming epidemiological research and public health interventions.
Mendelian randomization analysis identified potential genes pleiotropically associated with gout
Authors: Wang Yu , Chen Jiahao , Yao Hang , Li Yuxin , Xu Xiaogang , Zhang Delin 
Published: August 2024

BackgroundThis study aims to prioritize genes potentially involved in multifactorial or causal relationships with gout.MethodsUsing the Summary Data-based Mendelian Randomization (SMR) approach, this research analyzed expression quantitative trait loci (eQTL) data from blood and renal tissues and genome-wide association study (GWAS) data related to gout. It sought to identify genetic loci potentially involved in gout. Heterogeneity testing was conducted with the HEIDI test, and results were adjusted for the False Discovery Rate (FDR). Blood cis-eQTL data were sourced from the eQTLGen Consortium’s summary-level data, and renal tissue data came from the V8 release of the GTEx eQTL summary data. Gout GWAS data was sourced from the FinnGen Documentation of the R10 release.ResultSMR analysis identified 14 gene probes in the eQTLGen blood summary-level data significantly associated with gout. The top five ranked genes are: ENSG00000169231 (labeled THBS3, PSMR = 4.16 × 10−13), ENSG00000231064 (labeled THBS3-AS1, PSMR = 1.88 × 10−8), ENSG00000163463 (labeled KRTCAP2, PSMR = 3.88 × 10−6), ENSG00000172977 (labeled KAT5, PSMR = 1.70 × 10−5), and ENSG00000161395 (labeled PGAP3, PSMR = 3.24 × 10−5). Notably, increased expression of KRTCAP2 and PGAP3 is associated with an increased risk of gout, whereas increased expression of THBS3, THBS3-AS1, and KAT5 is associated with a reduced gout risk. No significant gene associations with gout were observed in renal tissue, likely due to the limited sample size of kidney tissue.ConclusionOur findings have highlighted several genes potentially involved in the pathogenesis of gout. These results offer valuable insights into the mechanisms of gout and identify potential therapeutic targets for its treatment.
The role of herpes simplex virus infection in the etiology of head and neck cancer–a Mendelian randomization study
Authors: Yan Ming , Xiao Li-yuan , Gosau Martin , Smeets Ralf , Feng Hong-chao , Burg Simon , Fu Ling-ling , Friedrich Reinhard E. 
Published: August 2024

IntroductionHead and neck cancer (HNC) is a complex disease, and multiple risk factors can lead to its progression. Observational studies indicated that herpes simplex virus (HSV) may be correlated with the risk of HNC. However, the causal effects and direction between them were still unclear.MethodsThis study utilized a Mendelian randomization (MR) approach for causality assessment between HSV infection and Head and neck cancer based on the latest public health data and Genome-Wide Association Study (GWAS) data. The causal effects were estimated using IVW, weighted median, and MR-Egger. A reverse MR analysis was subsequently performed. Cochrans Q test, MR‐Egger intercept test, leave one out analysis, and the funnel plot were all used in sensitivity analyses.ResultsGenetically predicted higher level of HSV-1 IgG was causally related to HNC (OR=1.0019, 95%CI=1.0003–1.0036, p=0.0186, IVW) and oral and oropharyngeal cancer (OR=1.0018, 95%CI=1.0004–1.0033, p=0.0105, IVW). The reverse MR analysis did not demonstrate a reverse causal relationship between HSV and HNC. However, HSV-2 infection was not causally related to HNC data and oropharyngeal cancer data. Sensitivity analysis was performed and revealed no heterogeneity and horizontal pleiotropy.ConclusionCollectively, a significant association was noted between HSV infection and increased risk of HNC, providing valuable insights into the etiology of this malignancy. Further in-depth study is needed to validate these findings and elucidate the underpinning mechanisms.
Longitudinal transcriptomic analysis reveals persistent enrichment of iron homeostasis and erythrocyte function pathways in severe COVID-19 ARDS
Authors: Eltobgy Moemen , Johns Finny , Farkas Daniela , Leuenberger Laura , Cohen Sarah P. , Ho Kevin , Karow Sarah , Swoope Gabrielle , Pannu Sonal , Horowitz Jeffrey C. , Mallampalli Rama K. , Englert Joshua A. , Bednash Joseph S. 
Published: August 2024

IntroductionThe acute respiratory distress syndrome (ARDS) is a common complication of severe COVID-19 and contributes to patient morbidity and mortality. ARDS is a heterogeneous syndrome caused by various insults, and results in acute hypoxemic respiratory failure. Patients with ARDS from COVID-19 may represent a subgroup of ARDS patients with distinct molecular profiles that drive disease outcomes. Here, we hypothesized that longitudinal transcriptomic analysis may identify distinct dynamic pathobiological pathways during COVID-19 ARDS.MethodsWe identified a patient cohort from an existing ICU biorepository and established three groups for comparison: 1) patients with COVID-19 ARDS that survived hospitalization (COVID survivors, n = 4), 2) patients with COVID-19 ARDS that did not survive hospitalization (COVID non-survivors, n = 5), and 3) patients with ARDS from other causes as a control group (ARDS controls, n = 4). RNA was isolated from peripheral blood mononuclear cells (PBMCs) at 4 time points (Days 1, 3, 7, and 10 following ICU admission) and analyzed by bulk RNA sequencing.ResultsWe first compared transcriptomes between groups at individual timepoints and observed significant heterogeneity in differentially expressed genes (DEGs). Next, we utilized the likelihood ratio test to identify genes that exhibit different patterns of change over time between the 3 groups and identified 341 DEGs across time, including hemoglobin subunit alpha 2 (HBA1, HBA2), hemoglobin subunit beta (HBB), von Willebrand factor C and EGF domains (VWCE), and carbonic anhydrase 1 (CA1), which all demonstrated persistent upregulation in the COVID non-survivors compared to COVID survivors. Of the 341 DEGs, 314 demonstrated a similar pattern of persistent increased gene expression in COVID non-survivors compared to survivors, associated with canonical pathways of iron homeostasis signaling, erythrocyte interaction with oxygen and carbon dioxide, erythropoietin signaling, heme biosynthesis, metabolism of porphyrins, and iron uptake and transport.DiscussionThese findings describe significant differences in gene regulation during patient ICU course between survivors and non-survivors of COVID-19 ARDS. We identified multiple pathways that suggest heme and red blood cell metabolism contribute to disease outcomes. This approach is generalizable to larger cohorts and supports an approach of longitudinal sampling in ARDS molecular profiling studies, which may identify novel targetable pathways of injury and resolution.
The relationship between influenza vaccine hesitancy and vaccine literacy among youth and adults in China
Authors: Wang Li , Guo Mengjie , Wang Yan , Chen Ren , Wei Xiaolin 
Published: August 2024

ObjectivesThe present study aimed to assess influenza vaccine hesitancy and vaccine literacy levels among youth and adults in China, as well as the association between them.MethodsAn online cross-sectional survey was conducted in Mainland China. Participants’ total vaccine literacy and three sub-dimension vaccine literacy (knowledge literacy, competence literacy, and decision-making literacy) were assessed by a validated vaccine literacy scale. Having received influenza vaccination in the past three years or intending to accept it in next influenza season indicates less influenza vaccine hesitancy.ResultsAmong 997 participants, a sub-optimal vaccine literacy was observed, with a mean score of 66.83 ± 10.27. Regression models 1–4 revealed that participants with middle (aOR: 1.431, P=0.039, 95% CI: 1.018~2.010) or high (aOR: 1.651, P=0.006, 95% CI: 1.157~2.354) total vaccine literacy, as well as those with high competence literacy (aOR: 1.533, P=0.017, 95% CI: 1.079~2.180), or high decision-making literacy (aOR: 1.822, P=0.001, 95% CI: 1.261~2.632) were more likely to have been vaccinated against influenza at least once in past three years. However, those with a high knowledge literacy were associated with a lower influenza vaccine rate (aOR: 0.676, P=0.046, 95% CI: 0.460~0.994). Regression models 5–8 revealed that participants with middle (aOR: 1.661, P=0.008, 95% CI: 1.142~2.414) or high total vaccine literacy (aOR: 2.645, P=0.000, 95% CI: 1.774~3.942), as well as those with middle (aOR: 1.703, P=0.005, 95% CI: 1.177~2.464) or high competence literacy (aOR: 2.346, P=0.000, 95% CI: 1.159~3.461), or high decision-making literacy (aOR: 2.294, P=0.000, 95% CI: 1.531~3.436) were more likely to express the willingness to receive the influenza vaccine in the next influenza season.ConclusionThe participants’ influenza vaccine hesitancy was negatively associated with their total vaccine literacy levels and two of the three sub-dimensions: competence literacy and decision-making literacy. Knowledge literacy suggested a positive or no relationship with influenza vaccine hesitancy.
The association between energy-adjusted dietary inflammatory index and metabolic syndrome and its mediatory role for cardiometabolic diseases: a prospective cohort study
Authors: Pourmontaseri Hossein , Sepehrinia Matin , Kuchay Mohammad Shafi , Farjam Mojtaba , Vahid Farhad , Dehghan Azizallah , Homayounfar Reza , Naghizadeh Mohammad Mehdi , Hebert James R. 
Published: August 2024

BackgroundMetabolic syndrome (MetS) is a collection of medical conditions that elevate the chance of cardiovascular disease. An unhealthy diet is a major risk factors for MetS through different mechanisms, especially systemic chronic inflammation.ObjectiveThis study aimed to investigate the effect of dietary inflammatory potential on MetS incidence and the role of MetS in the association between Energy-adjusted dietary inflammatory index (E-DII) and cardiometabolic diseases.MethodsIn this prospective cohort study, 10,138 participants were recruited. All participants were divided into MetS or non-MetS groups based on the Adult Treatment Panel III criteria. The E-DII was used to assess the inflammatory potential of diet. After excluding the participants with MetS at baseline, 2252 individuals were followed for 5 years (longitudinal phase), and the effect of E-DII on MetS incidence was investigated using logistic regression models (p-value &lt;0.05).ResultsThe cohort’s mean age (45.1% men) was 48.6 ± 10.0 years. E-DII ranged from −6.5 to 5.6 (mean: −0.278 ± 2.07). Higher E-DII score had a 29% (95%CI: 1.22–1.36) increased risk for incidence of MetS and its components during five-year follow-up. Also, E-DII was significantly associated with the prevalence of MetS (OR = 1.55, 95%CI: 1.51–1.59). Among MetS components, E-DII had the strongest association with waist circumference in the cross-sectional study (OR = 2.17, 95%CI: 2.08–2.25) and triglyceride in the longitudinal study (OR = 1.19, 95%CI: 1.13–1.25). The association between E-DII and MetS was consistent in both obese (OR = 1.13, 95%CI:1.05–1.21) and non-obese (OR = 1.42, 95%CI: 1.27–1.60) individuals and stronger among non-obese participants. Additionally, MetS mediated the association between E-DII and hypertension, diabetes, and myocardial infarction.ConclusionIn conclusion, a pro-inflammatory diet consumption is associated with a higher risk of MetS and its components. Furthermore, a pro-inflammatory diet increases the risk of cardiometabolic diseases. The higher E-DII had a stronger association with MetS, even among normal-weight individuals.
Spatiotemporal correlation enhanced real-time 4D-CBCT imaging using convolutional LSTM networks
Authors: Zhang Hua , Chen Kai , Xu Xiaotong , You Tao , Sun Wenzheng , Dang Jun 
Published: August 2024

PurposeTo enhance the accuracy of real-time four-dimensional cone beam CT (4D-CBCT) imaging by incorporating spatiotemporal correlation from the sequential projection image into the single projection-based 4D-CBCT estimation process.MethodsWe first derived 4D deformation vector fields (DVFs) from patient 4D-CT. Principal component analysis (PCA) was then employed to extract distinctive feature labels for each DVF, focusing on the first three PCA coefficients. To simulate a wide range of respiratory motion, we expanded the motion amplitude and used random sampling to generate approximately 900 sets of PCA labels. These labels were used to produce 900 simulated 4D-DVFs, which in turn deformed the 0% phase 4D-CT to obtain 900 CBCT volumes with continuous motion amplitudes. Following this, the forward projection was performed at one angle to get all of the digital reconstructed radiographs (DRRs). These DRRs and the PCA labels were used as the training data set. To capture the spatiotemporal correlation in the projections, we propose to use the convolutional LSTM (ConvLSTM) network for PCA coefficient estimation. For network testing, when several online CBCT projections (with different motion amplitudes that cover the full respiration range) are acquired and sent into the network, the corresponding 4D-PCA coefficients will be obtained and finally lead to a full online 4D-CBCT prediction. A phantom experiment is first performed with the XCAT phantom; then, a pilot clinical evaluation is further conducted.ResultsResults on the XCAT phantom and the patient data show that the proposed approach outperformed other networks in terms of visual inspection and quantitative metrics. For the XCAT phantom experiment, ConvLSTM achieves the highest quantification accuracy with MAPE(Mean Absolute Percentage Error), PSNR (Peak Signal-to-Noise Ratio), and RMSE(Root Mean Squared Error) of 0.0459, 64.6742, and 0.0011, respectively. For the patient pilot clinical experiment, ConvLSTM also achieves the best quantification accuracy with that of 0.0934, 63.7294, and 0.0019, respectively. The quantification evaluation labels that we used are 1) the Mean Absolute Error (MAE), 2) the Normalized Cross Correlation (NCC), 3)the Structural Similarity Index Measurement(SSIM), 4)the Peak Signal-to-Noise Ratio (PSNR), 5)the Root Mean Squared Error(RMSE), and 6) the Absolute Percentage Error (MAPE).ConclusionThe spatiotemporal correlation-based respiration motion modeling supplied a potential solution for accurate real-time 4D-CBCT reconstruction.
Risk prediction model for postoperative pneumonia in esophageal cancer patients: A systematic review
Authors: Jiang Yaxin , Li Zimeng , Jiang Weiting , Wei Tingyu , Chen Bizhen 
Published: August 2024

BackgroundNumerous studies have developed or validated prediction models to estimate the likelihood of postoperative pneumonia (POP) in esophageal cancer (EC) patients. The quality of these models and the evaluation of their applicability to clinical practice and future research remains unknown. This study systematically evaluated the risk of bias and applicability of risk prediction models for developing POP in patients undergoing esophageal cancer surgery.MethodsPubMed, Embase, Web of Science, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), WanFang Database and Chinese Biomedical Literature Database were searched from inception to March 12, 2024. Two investigators independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability.ResultA total of 14 studies involving 23 models were included. These studies were mainly published between 2014 and 2023. The applicability of all studies was good. However, all studies exhibited a high risk of bias, primarily attributed to inappropriate data sources, insufficient sample size, irrational treatment of variables and missing data, and lack of model validation. The incidence of POP in patients undergoing esophageal cancer surgery ranged from 14.60% to 39.26%. The most frequently used predictors were smoking, age, chronic obstructive pulmonary disease(COPD), diabetes mellitus, and methods of thoracotomy. Inter-model discrimination ranged from 0.627 to 0.850, sensitivity ranged between 60.7% and 84.0%, and specificity ranged from 59.1% to 83.9%.ConclusionIn all included studies, good discrimination was reported for risk prediction models for POP in patients undergoing esophageal cancer surgery, indicating stable model performance. However, according to the PROBAST checklist, all studies had a high risk of bias. Future studies should use the predictive model assessment tool to improve study design and develop new models with larger samples and multicenter external validation.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42024527085.
Assessing how individuals conceptualize numeric pain ratings: validity and reliability of the Pain Schema Inventory (PSI–6) Short Form
Authors: Wiederien Robert C. , Wang Dan , Frey-Law Laura A. 
Published: August 2024

BackgroundWhile numeric scales to represent pain intensity have been well validated, individuals use various conceptualizations when assigning a number to pain intensity, referred to as pain rating schema. The 18-item Pain Schema Inventory (PSI-18) quantifies pain rating schema by asking for numeric values for multiple mild, moderate or severe pain conditions. This study aimed to assess the validity and reliability of a shortened form of the PSI, using only 6 items (PSI-6).MethodsA secondary analysis was performed on two existing datasets. The first (n = 641) involved a community-based population that completed the PSI-18. The second (n = 182) included participants with chronic pain who completed the PSI-6 twice, one week apart. We assessed face validity, convergent validity, offset biases, test-retest reliability, and internal consistency of the PSI-6 compared to the PSI-18.ResultsBoth the PSI-18 and PSI-6 demonstrated excellent face validity. The PSI-6 demonstrated excellent convergent validity relative to the PSI-18, with correlations from r = 0.88 to 0.92. Bland-Altman plots revealed offset biases near zero (&lt; 0.22 on 0–10 scale) across all categories of mild, moderate, severe and average pain. Internal consistency was excellent, with Cronbach's Alpha = 0.91 and 0.80, for PSI-18 and PSI-6 respectively. Test-retest reliability of the PSI-6 was high with correlations from r = 0.70–0.76.ConclusionThe PSI-6 is a valid and reliable tool to assess pain rating schema with reduced subject burden, to better interpret individuals’ pain ratings and adjust for inter-individual variability.
Distinguishing types and severity of pediatric pneumonia using modified lung ultrasound score
Authors: Xie Wen , Ruan Junxian , Jiang Qiuxia , Zheng Jingyang , Lin Weiru , Lyu Guorong 
Published: August 2024

ObjectiveThis study aimed to investigate the diagnostic utility of the modified lung ultrasound score (MLUS) in distinguishing between Mycoplasma pneumonia and viral pneumonia in children and evaluate their severity.MethodsA prospective collection of 137 suspected cases of community-acquired pneumonia in children admitted to the Quanzhou Maternity and Children's Hospital in Quanzhou City, Fujian Province, from January 2023 to December 2023 constituted the study cohort. All patients underwent lung ultrasound examinations, and MLUS scores were assigned based on ultrasound findings, including pleural lines, A-lines, B-lines, and lung consolidations. Based on the pathogenic results, the patients were categorized into the Mycoplasma pneumonia (74 cases) and viral pneumonia (63 cases) groups. The severity was classified as mild (110 cases) or severe (27 cases). The diagnostic value of MLUS for Mycoplasma pneumonia and viral pneumonia in children was analyzed.Results(1) MLUS scores were significantly different between the Mycoplasma pneumonia (15, 10–21) and viral pneumonia (8, 5–16) groups (P = 0.002). ROC curve analysis indicated that using a cut-off value of 11, MLUS exhibited a sensitivity of 70.3%, specificity of 58.7%, and an area under curve (AUC) of 0.653 for diagnosing Mycoplasma pneumonia. Furthermore, large-area lung consolidation on ultrasound images demonstrated good diagnostic performance for predicting Mycoplasma pneumonia, with an AUC of 0.763, a sensitivity of 71.6%, and a specificity of 81.0%. (2) MLUS scores were significantly different between the mild pneumonia (10.5, 5–17) and severe pneumonia (21, 16–29) groups (P &lt; 0.001). ROC curve analysis using a cut-off value of 16 showed a sensitivity of 77.8%, specificity of 73.6%, and AUC of 0.818 for diagnosing severe pneumonia. Multivariate regression analysis revealed that both MLUS and white blood cell count were independent factors influencing the severity. The constructed nomogram model demonstrated robust stability with a sensitivity of 85.2%, a specificity of 74.5%, and an AUC of 0.858 for predicting severe childhood pneumonia.ConclusionMLUS, coupled with ultrasound signs of large-area lung consolidation, had reference significance for the differential diagnosis of Mycoplasma pneumonia and viral pneumonia in children and can be a preliminary assessment of the severity of viral pneumonia or mycoplasma pneumonia in children.