bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association Between High-Sensitivity C-Reactive Protein and Diabetic Kidney Disease in Patients With Type 2 Diabetes Mellitus
Authors: Tang Min , Cao Han , Wei Xiao-Hui , Zhen Qin , Liu Fang , Wang Yu-Fan , Fan Neng-Guang , Peng Yong-De 
Published: June 2022

ObjectiveHigh-sensitivity C-reactive protein (hs-CRP) is an inflammatory marker. This study aimed to identify the correlation between hs-CRP levels and diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM).Materials/MethodsThis cross-sectional and observational study included 927 patients with T2DM. We collected the data of patients based on their medical data, including sociodemographic characteristics, concomitant diseases, laboratory results, and medical therapy. Multivariate logistic regression analysis was conducted to assess the relationship between hs-CRP levels and DKD. A restricted cubic spline (RCS) was used to assess the correlation of hs-CRP levels on a continuous scale with the DKD.ResultsIn total, 927 patients were recruited in our study. The median age of the recruited patients was 55 years, and there were 346 female patients and 581 male patients. The hs-CRP levels were evidently higher in patients with DKD than those without DKD. After adjusting for age, sex, diastolic blood pressure, systolic blood pressure, body mass index, neck circumference, waist circumference, hypertension, duration of diabetes, common carotid artery plaque, fasting plasma glucose, glycated hemoglobin, hemoglobin, erythrocyte, leukocyte, γ-glutamyl transferase, albumin, urea nitrogen, uric acid and triglyceride, a significant increase in the odds ratios (ORs) for DKD in the fourth hs-CRP quartile compared with the first quartile was observed (P value for trend= 0.003), and the ORs (95% confidence intervals) in the fourth quartile of hs-CRP were 1.968 (1.244–3.114) for DKD compared to the first quartile.. Moreover, the RCS curves presented a positive association between hs-CRP and DKD in total subjects, male subjects and female subjects, respectively.ConclusionsThe results of our study indicated that hs-CRP levels were significantly and positively correlated with the presence of DKD, which may provide predictive and diagnostic values in clinical practice.
Self-Reported Walking Pace and Risk of Cardiovascular Diseases: A Two-Sample Mendelian Randomization Study
Authors: Chen Lu , Sun Xingang , He Yuxian , Zheng Liangrong 
Published: June 2022

Background: In observational studies, the self-reported walking pace has been associated with the risk of cardiovascular diseases (CVD). However, whether those associations indicate causal links remains unclear. We performed two-sample Mendelian randomization (MR) analyses to evaluate the causal effect of walking pace on several CVD outcomes, including atrial fibrillation (AF), heart failure (HF), any stroke, ischemic stroke (IS), and IS subtypes.Methods: Genetic variants associated with self-reported walking pace were selected as instrumental variables (IVs) from the latest genome-wide association studies (GWAS). Summary-level data for outcomes were obtained from the corresponding GWAS and the FinnGen consortium. The random-effects inverse variance weighted (IVW) method was used as the main MR analysis, supplemented by replication analyses using data from the FinnGen. To explore the effect of pleiotropy due to adiposity-related traits, we further conducted MR analyses by excluding the adiposity-related IVs and regression-based multivariable MR adjusting for body mass index (BMI).Results: The MR results indicated significant inverse associations of self-reported walking pace with risks of AF [odds ratio (OR), 0.577; 95% confidence interval (CI), 0.442, 0.755; p = 5.87 × 10−5], HF (OR, 0.307; 95% CI, 0.229, 0.413; p = 5.31 × 10−15), any stroke (OR, 0.540; 95% CI, 0.388, 0.752; p = 2.63 × 10−4) and IS (OR, 0.604; 95% CI, 0.427, 0.853; p = 0.004) and suggestive inverse association of self-reported walking pace with cardioembolic stroke (CES) (OR, 0.492; 95% CI, 0.259, 0.934; p = 0.030). Similar results were replicated in the FinnGen consortium and persisted in the meta-analysis. However, there was no causality between walking pace and large artery stroke (OR, 0.676; 95% CI, 0.319, 1.434; p = 0.308) or small vessel stroke (OR, 0.603; 95% CI, 0.270, 1.349; p = 0.218). When excluding adiposity-related IVs and adjusting for BMI, the associations for HF and any stroke did not change substantially, whereas the associations for AF, IS, and CES were weakened.Conclusion: Our findings suggested that genetically predicted increasing walking pace exerted beneficial effects on AF, HF, any stroke, IS, and CES. Adiposity might partially mediate the effect of walking pace on AF, IS, and CES.
ABCA12 Promotes Proliferation and Migration and Inhibits Apoptosis of Pancreatic Cancer Cells Through the AKT Signaling Pathway
Authors: Zheng Songyuan , Liu Dongyan , Wang Feifei , Jin Youyan , Zhao Siqiao , Sun Siyu , Wang Sheng 
Published: June 2022

Background: As a malignant tumor, pancreatic cancer is difficult to detect in its early stage. Pancreatic cancer progresses rapidly and has a short survival time. Most cases have metastasized to distant organs before diagnosis. The mechanism of induction of pancreatic cancer is not fully understood.Methods: In this study, bioinformatics predicted ATP binding cassette subfamily A member 12 (ABCA12) expression in pancreatic tissues and performed survival analysis, risk assessment, and enrichment analysis. The expression of ABCA12 in 30 pairs of clinical samples was detected by immunohistochemistry and we analyzed its correlation with clinical information. Both reverse transcription polymerase chain reaction (RT–PCR) and western blot analysis were used to detect mRNA and protein expression in cell lines. Two different siRNAs and SW1990 cell line were used to construct pancreatic cancer cell models with ABCA12 knockdown. Cell viability was evaluated by cell counting kit-8 (CCK-8) and EdU proliferation assays. Wound healing assays and Transwell assays were used to measure the ability of cell migration and invasion. Flow cytometry was used to investigate the effect of ABCA12 on the proliferation cycle and apoptosis of pancreatic cancer. Western blot analysis detected changes in apoptosis, migration, and other pathway proteins in SW1990 cells after transfection.Results:ABCA12 is highly expressed in pancreatic cancer tissues and cells. After ABCA12 was knocked down, the proliferation, invasion, and migration of SW1990 cells were significantly reduced, and apoptosis was increased. The changes in pathway proteins suggested that ABCA12 may regulate the progression of pancreatic cancer through the AKT pathway.Conclusion: We found that ABCA12 is differentially expressed in pancreatic tissues and cells. ABCA12 can also affect the biological behavior of pancreatic cancer cells effectively, which may serve as a new target for pancreatic cancer diagnosis and treatment.
Identification and Validation of Prognostic Model for Pancreatic Ductal Adenocarcinoma Based on Necroptosis-Related Genes
Authors: Xie Haoran , Xu Jingxian , Xie Zhiwen , Xie Ni , Lu Jiawei , Yu Lanting , Li Baiwen , Cheng Li 
Published: June 2022

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with a poor prognosis. Recently, necroptosis has been reported to participate in the progression of multiple tumors. However, few studies have revealed the relationship between necroptosis and PDAC, and the role of necroptosis in PDAC has not yet been clarified.Methods: The mRNA expression data and corresponding clinical information of PDAC patients were downloaded from the TCGA and GEO databases. The necroptosis-related genes (NRGs) were obtained from the CUSABIO website. Consensus clustering was performed to divide PDAC patients into two clusters. Univariate and LASSO Cox regression analyses were applied to screen the NRGs related to prognosis to construct the prognostic model. The predictive value of the prognostic model was evaluated by Kaplan-Meier survival analysis and ROC curve. Univariate and multivariate Cox regression analyses were used to evaluate whether the risk score could be used as an independent predictor of PDAC prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-sample gene set enrichment analysis (ssGSEA) were used for functional enrichment analysis. Finally, using qRT-PCR examined NRGs mRNA expression in vitro.Results: Based on the TCGA database, a total of 22 differential expressed NRGs were identified, among which eight NRGs (CAPN2, CHMP4C, PLA2G4F, PYGB, BCL2, JAK3, PLA2G4C and STAT4) that may be related to prognosis were screened by univariate Cox regression analysis. And CAPN2, CHMP4C, PLA2G4C and STAT4 were further selected to construct the prognostic model. Kaplan-Meier survival analysis and ROC curve showed that there was a significant correlation between the risk model and prognosis. Univariate and multivariate Cox regression analyses showed that the risk score of the prognostic model could be used as an independent predictor. The model efficacy was further demonstrated in the GEO cohort. Functional analysis revealed that there were significant differences in immune status between high and low-risk groups. Finally, the qRT-PCR results revealed a similar dysregulation of NRGs in PDAC cell lines.Conclusion: This study successfully constructed and verified a prognostic model based on NRGs, which has a good predictive value for the prognosis of PDAC patients.
The Antibody Dependant Neurite Outgrowth Modulation Response Involvement in Spinal Cord Injury
Authors: Capuz Alice , Karnoub Mélodie-Anne , Osien Sylvain , Rose Mélanie , Mériaux Céline , Fournier Isabelle , Devos David , Vanden Abeele Fabien , Rodet Franck , Cizkova Dasa , Salzet Michel 
Published: June 2022

Spinal cord injury (SCI) represents a major medical challenge. At present, there is still no cure to treat it efficiently and enable functional recovery below the injury site. Previously, we demonstrated that inflammation determines the fate of the physiopathology. To decipher the molecular mechanisms involved in this process, we performed a meta-analysis of our spatio-temporal proteomic studies in the time course of SCI. This highlighted the presence of IgG isotypes in both spinal cord explants and their secretomes. These IgGs were detected in the spinal cord even if no SCI occurred. However, during the time course following SCI, abundance of IgG1 and IgG2 subclasses (a, b, c) varied according to the spatial repartition. IgG1 was clearly mostly abundant at 12 h, and a switch to IgG2a was observed after 24 h. This IgG stayed predominant 3, 7, and 10 days after SCI. A protein related to IgM as well as a variable heavy chain were only detected 12 h after lesion. Interestingly, treatment with RhoA inhibitor influenced the abundance of the various IgG isotypes and a preferential switch to IgG2c was observed. By data reuse of rat dorsal root ganglion (DRG) neurons RNAseq datasets and RT-PCR experiments performed on cDNA from DRG sensory neurons ND7/23 and N27 dopaminergic neural cell lines, we confirmed expression of immunoglobulin heavy and light chains (constant and variable) encoding genes in neurons. We then identified CD16 and CD32b as their specific receptors in sensory neuron cell line ND7/23 and their activation regulated neurites outgrowth. These results suggest that during SCI, neuronal IgG isotypes are released to modulate neurites outgrowth. Therefore, we propose a new view of the SCI response involving an antibody dependent neurite outgrowth modulation (ADNM) which could be a precursor to the neuroinflammatory response in pathological conditions.
Three-Dimensional Impact Localization on Concrete Structures Using Novel Enhanced Cross-Correlation Algorithm and Designed Concrete Implantable Module
Authors: Chen Qingjun , Yang Ziqian , Li Xiuquan , Sun Xiangtao , Kong Qingzhao 
Published: June 2022

Concrete structures are often subjected to undesirable impact loads. Impact localization in near real time is greatly essential for providing early warnings and evaluating impact load effects. In this article, a novel enhanced cross-correlation (ECC) algorithm enabled by a designed concrete implantable module (CIM) is proposed for precise prediction of the impact location on concrete structures. The stability of the ECC algorithm under the noise condition was numerically studied. The numerical results demonstrate that the proposed ECC algorithm has high adaptability in the low signal-to-noise ratio (SNR) condition compared with the traditional algorithm, which provides the possibility for employing this approach in real projects. In the experimental study, a series of impact tests on a concrete beam specimen were conducted to verify the accuracy of the proposed method for impact localization. The results indicate that the maximum and minimum distance errors between the real and predicted impact positions are 54.1 and 12.5 mm, respectively. Both the numerical and experimental studies demonstrate the feasibility of the proposed method for the prediction of impact locations.
The Efficiency of Convalescent Plasma Therapy in the Management of Critically Ill Patients Infected With COVID-19: A Matched Cohort Study
Authors: Pan Chun , Chen Hui , Xie Jianfeng , Huang Yingzi , Yang Yi , Du Bin , Qiu Haibo 
Published: June 2022

BackgroundThe convalescent plasma of patients who recover from coronavirus disease 2019 (COVID-19) contains high titers of neutralizing antibodies, which has potential effects on the viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and improving the prognosis of patients with COVID-19. The goal of this study was to clarify the effects of convalescent plasma therapy on the 60-day mortality and negative conversion rate of SARS-CoV-2 during the hospitalization of patients with severe and life-threatening COVID-19 infection.MethodsThis was a retrospective, case-matched cohort study that involved patients with severe COVID-19 infections. The patients who received convalescent plasma therapy were matched by age, sex, diabetes, hypertension, heart failure, the onset of symptoms to hospital admission, respiratory support pattern, lymphocyte count, troponin, Sequential organ failure assessment (SOFA), glucocorticoid, and antiviral agents to no more than three patients with COVID-19 who did not receive convalescent plasma therapy. A Cox regression model and competing risk analysis were used to evaluate the effects of convalescent plasma therapy on these patients.ResultsTwenty-six patients were in the convalescent plasma therapy group, and 78 patients were in the control group. Demographic characteristics were similar in both groups, except for the SOFA score. Convalescent plasma therapy did not improve 60-day mortality [hazard ratio (HR) 1.44, 95% CI 0.82–2.51, p = 0.20], but the SARS-CoV-2 negative conversion rate for 60 days after admission was higher in the convalescent plasma group (26.9 vs. 65.4%, p = 0.002) than in the control. Then, a competing risk analysis was performed, which considered events of interest (the negative conversion rate of SARS-CoV-2) and competing events (death) in the same model. Convalescent plasma therapy improved events of interest (p = 0.0002).ConclusionConvalescent plasma therapy could improve the SARS-CoV-2 negative conversion rate but could not improve 60-day mortality in patients with severe and life-threatening COVID-19 infection.Clinical Trial NumberThe study was registered at ClinicalTrials.gov (NCT04616976).
Hepatic Arterial Infusion Chemotherapy With Folfirinox or Oxaliplatin Alone in Metastatic Colorectal Cancer
Authors: Randrian Violaine , Pernot Simon , Sionneau Baptiste , Smith Denis , Lim Annie , Touchefeu Yann , Gallois Claire , Turpin Anthony , Javed Sahir , Guimbaud Rosine , Rivera Pascale , Karoui Mehdi , Auclin Edouard , Taieb Julien 
Published: June 2022

BackgroundHepatic arterial infusion (HAI) of chemotherapy is an option for the treatment of patients with liver metastases from colorectal cancer (LMCRC). Though HAI with oxaliplatin (HAI-Ox) is generally used, intravenous (IV) 5-fluoro-uracil (5FU)-oxaliplatin-irinotecan HAI (HAI-Folfirinox) is feasible and leads to curative-intent surgery in 30% of pretreated patients. We compared the efficacy and safety of HAI-Ox and HAI-Folfirinox.MethodsPatients who underwent HAI chemotherapy for LMCRC were retrospectively included from 2008 to 2019 from six French expert centers.ResultsData were collected from 273 previously treated patients with LMCRC. Patients received HAI-Folfirinox (n = 52) or HAI-Ox (n = 221) combined with IV chemotherapy. The objective response rate (ORR) was 43.2% in patients with HAI-Folfirinox and 45.9% (ns) in patients with HAI-Ox. Median overall survival (OS) was 17 months (95% CI: 15–32.3) with HAI-Folfirinox and 26.2 months (95% CI: 19.4–34.4; p = 0.1) with HAI-Ox. Median progression-free survival (PFS) was 7.9 months (95% CI: 4.9–10.3) with HAI-Folfirinox and 6.4 months (95% CI: 6.0–7.7; p = 0.6) with HAI-Ox. The secondary liver resection rate was 35.6% with HAI-Folfirinox and 16.7% with HAI-Ox (p = 0.007). Grade 2 and above toxicities were significantly more frequent with HAI-Folfirinox. In the global population, only 2 factors were prognostic for OS in multivariable analyses: liver-only disease [hazard ratio (HR): 0.4; 95% CI 0.20–0.83; p = 0.013] and local complications of the catheter (HR: 3.8; 95% CI 1.6–9.0; p = 0.002).ConclusionHepatic arterial infusion results in high response rates, secondary resections, and long survival in pretreated patients with LMCRC.
CK5/6 and GATA3 Defined Phenotypes of Muscle-Invasive Bladder Cancer: Impact in Adjuvant Chemotherapy and Molecular Subtyping of Negative Cases
Authors: Koll Florestan J. , Schwarz Alina , Köllermann Jens , Banek Severine , Kluth Luis , Wittler Clarissa , Bankov Katrin , Döring Claudia , Becker Nina , Chun Felix K.H. , Wild Peter J. , Reis Henning 
Published: June 2022

Introduction and ObjectiveIdentifying patients that benefit from cisplatin-based adjuvant chemotherapy is a major issue in the management of muscle-invasive bladder cancer (MIBC). The purpose of this study is to correlate “luminal” and “basal” type protein expression with histological subtypes, to investigate the prognostic impact on survival after adjuvant chemotherapy and to define molecular consensus subtypes of “double negative” patients (i.e., without expression of CK5/6 or GATA3).Materials and MethodsWe performed immunohistochemical (IHC) analysis of CK5/6 and GATA3 for surrogate molecular subtyping in 181 MIBC samples. The mRNA expression profiles for molecular consensus classification were determined in CK5/6 and GATA3 (double) negative cases using a transcriptome panel with 19.398 mRNA targets (HTG Molecular Diagnostics). Data of 110 patients undergoing radical cystectomy were available for survival analysis.ResultsThe expression of CK5/6 correlated with squamous histological subtype (96%) and expression of GATA3 was associated with micropapillary histology (100%). In the multivariate Cox-regression model, patients receiving adjuvant chemotherapy had a significant survival benefit (hazard ratio [HR]: 0.19 95% confidence interval [CI]: 0.1–0.4, p &lt; 0.001) and double-negative cases had decreased OS (HR: 4.07; 95% CI: 1.5–10.9, p = 0.005). Double negative cases were classified as NE-like (30%), stroma-rich (30%), and Ba/Sq (40%) consensus molecular subtypes and displaying different histological subtypes.ConclusionImmunohistochemical-based classification was associated with histological subtypes of urothelial MIBC. IHC markers like CK5/6 and GATA3 that are used in pathological routine could help to identify patients with basal and luminal tumor characteristics. However, a two-sided classification system might not sufficiently reflect the heterogeneity of bladder cancer to make treatment decisions. Especially the group of IHC-double negative cases, as further analyzed by mRNA expression profiling, are a heterogeneous group with different implications for therapy.
Machine Learning Approaches for Hospital Acquired Pressure Injuries: A Retrospective Study of Electronic Medical Records
Authors: Levy Joshua J. , Lima Jorge F. , Miller Megan W. , Freed Gary L. , O'Malley A. James , Emeny Rebecca T. 
Published: June 2022

BackgroundMany machine learning heuristics integrate well with Electronic Medical Record (EMR) systems yet often fail to surpass traditional statistical models for biomedical applications.ObjectiveWe sought to compare predictive performances of 12 machine learning and traditional statistical techniques to predict the occurrence of Hospital Acquired Pressure Injuries (HAPI).MethodsEMR information was collected from 57,227 hospitalizations acquired from Dartmouth Hitchcock Medical Center (April 2011 to December 2016). Twelve classification algorithms, chosen based upon classic regression and recent machine learning techniques, were trained to predict HAPI incidence and performance was assessed using the Area Under the Receiver Operating Characteristic Curve (AUC).ResultsLogistic regression achieved a performance (AUC = 0.91 ± 0.034) comparable to the other machine learning approaches. We report discordance between machine learning derived predictors compared to the traditional statistical model. We visually assessed important patient-specific factors through Shapley Additive Explanations.ConclusionsMachine learning models will continue to inform clinical decision-making processes but should be compared to traditional modeling approaches to ensure proper utilization. Disagreements between important predictors found by traditional and machine learning modeling approaches can potentially confuse clinicians and need to be reconciled. These developments represent important steps forward in developing real-time predictive models that can be integrated into EMR systems to reduce unnecessary harm.
The Association of CSF sTREM2 With Cognitive Decline and Its Dynamic Change in Parkinson's Disease: Analysis of the PPMI Cohort
Authors: Qin Qixiong , Wan Hengming , Wang Danlei , Li Jingyi , Qu Yi , Zhao Jingwei , Li Jiangting , Xue Zheng 
Published: June 2022

BackgroundSoluble fragment of triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) is a biomarker of microglial activation and increased in several neurodegenerative diseases. However, the role of sTREM2 in Parkinson's diseases (PDs) remains unclear. This study aims to investigate whether CSF sTREM2 is changed during the pathology of PD and its association with cognitive decline.MethodsWe recruited 219 de novo patients with PD and 100 healthy controls from Parkinson's Progression Markers Initiative (PPMI). Cross-sectional and longitudinal associations between cognition and CSF sTREM2 were evaluated using multivariable-adjusted models. To assess the changes in CSF sTREM2 during the pathology of PD, patients were classified through the A/T classification framework with addition of α-synuclein (α-syn), which we implemented based on the CSF amyloid β-peptide 1−42 (A) and phosphorylated tau (T) and α-syn (S).ResultsThe CSF sTREM2 did not differ between healthy controls and patients with PD or between PD clinical subgroups (p &gt; 0.05). However, higher baseline CSF sTREM2 predicted greater global cognitive decline in patients with PD (β = −0.585, p = 0.039). Moreover, after a mean follow-up of 5.51 ± 1.31 years, baseline CSF sTREM2 that elevated in the middle tertile (HR = 2.426, 95% CI: 1.023–5.754, p = 0.044) and highest tertile (HR = 2.833, 95% CI: 1.226–6.547, p = 0.015) were associated with a future high risk of cognitive decline. Additionally, CSF sTREM2 decreased in abnormal Aβ pathology (A+) and α-syn pathology (S+) but normal tau pathology, while increased in abnormal phosphorylated tau (T+) (p &lt; 0.05).ConclusionCSF sTREM2 may be a promising predictor for the cognitive decline in PD rather than a diagnostic biomarker. The dynamic change in CSF sTREM2 in PD may help to the monitor of neuronal injury and microglial activity.