bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanistic study of pre-eclampsia and macrophage-associated molecular networks: bioinformatics insights from multiple datasets
Authors: Cao Jinfeng , Jiang Wenxin , Yin Zhe , Li Na , Tong Chao , Qi Hongbo 
Published: May 2024

BackgroundPre-eclampsia is a pregnancy-related disorder characterized by hypertension and proteinuria, severely affecting the health and quality of life of patients. However, the molecular mechanism of macrophages in pre-eclampsia is not well understood.MethodsIn this study, the key biomarkers during the development of pre-eclampsia were identified using bioinformatics analysis. The GSE75010 and GSE74341 datasets from the GEO database were obtained and merged for differential analysis. A weighted gene co-expression network analysis (WGCNA) was constructed based on macrophage content, and machine learning methods were employed to identify key genes. Immunoinfiltration analysis completed by the CIBERSORT method, R package “ClusterProfiler” to explore functional enrichment of these intersection genes, and potential drug predictions were conducted using the CMap database. Lastly, independent analysis of protein levels, localization, and quantitative analysis was performed on placental tissues collected from both preeclampsia patients and healthy control groups.ResultsWe identified 70 differentially expressed NETs genes and found 367 macrophage-related genes through WGCNA analysis. Machine learning identified three key genes: FNBP1L, NMUR1, and PP14571. These three key genes were significantly associated with immune cell content and enriched in multiple signaling pathways. Specifically, these genes were upregulated in PE patients. These findings establish the expression patterns of three key genes associated with M2 macrophage infiltration, providing potential targets for understanding the pathogenesis and treatment of PE. Additionally, CMap results suggested four potential drugs, including Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin, which may have the potential to reverse pre-eclampsia.ConclusionStudying the expression levels of three key genes in pre-eclampsia provides valuable insights into the prevention and treatment of this condition. We propose that these genes play a crucial role in regulating the maternal-fetal immune microenvironment in PE patients, and the pathways associated with these genes offer potential avenues for exploring the molecular mechanisms underlying preeclampsia and identifying therapeutic targets. Additionally, by utilizing the Connectivity Map database, we identified drug targets like Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin as potential clinical treatments for preeclampsia.
Proof-of-concept for an automatable mortality prediction scoring in hospitalised older adults
Authors: Ho Vanda W. T. , Ling Natalie M. W. , Anbarasan Denishkrshna , Chan Yiong Huak , Merchant Reshma Aziz 
Published: May 2024

IntroductionIt is challenging to prognosticate hospitalised older adults. Delayed recognition of end-of-life leads to failure in delivering appropriate palliative care and increases healthcare utilisation. Most mortality prediction tools specific for older adults require additional manual input, resulting in poor uptake. By leveraging on electronic health records, we aim to create an automatable mortality prediction tool for hospitalised older adults.MethodsWe retrospectively reviewed electronic records of general medicine patients ≥75 years at a tertiary hospital between April–September 2021. Demographics, comorbidities, ICD-codes, age-adjusted Charlson Comorbidity Index (CCI), Hospital Frailty Risk Score, mortality and resource utilization were collected. We defined early deaths, late deaths and survivors as patients who died within 30 days, 1 year, and lived beyond 1 year of admission, respectively. Multivariate logistic regression analyses were adjusted for age, gender, race, frailty, and CCI. The final prediction model was created using a stepwise logistic regression.ResultsOf 1,224 patients, 168 (13.7%) died early and 370 (30.2%) died late. From adjusted multivariate regression, risk of early death was significantly associated with ≥85 years, intermediate or high frail risk, CCI &gt; 6, cardiovascular risk factors, AMI and pneumonia. For late death, risk factors included ≥85 years, intermediate frail risk, CCI &gt;6, delirium, diabetes, AMI and pneumonia. Our mortality prediction tool which scores 1 point each for age, pneumonia and AMI had an AUC of 0.752 for early death and 0.691 for late death.ConclusionOur mortality prediction model is a proof-of-concept demonstrating the potential for automated medical alerts to guide physicians towards personalised care for hospitalised older adults.
LCASPMDA: a computational model for predicting potential microbe-drug associations based on learnable graph convolutional attention networks and self-paced iterative sampling ensemble
Authors: Yang Zinuo , Wang Lei , Zhang Xiangrui , Zeng Bin , Zhang Zhen , Liu Xin 
Published: May 2024

IntroductionNumerous studies show that microbes in the human body are very closely linked to the human host and can affect the human host by modulating the efficacy and toxicity of drugs. However, discovering potential microbe-drug associations through traditional wet labs is expensive and time-consuming, hence, it is important and necessary to develop effective computational models to detect possible microbe-drug associations.MethodsIn this manuscript, we proposed a new prediction model named LCASPMDA by combining the learnable graph convolutional attention network and the self-paced iterative sampling ensemble strategy to infer latent microbe-drug associations. In LCASPMDA, we first constructed a heterogeneous network based on newly downloaded known microbe-drug associations. Then, we adopted the learnable graph convolutional attention network to learn the hidden features of nodes in the heterogeneous network. After that, we utilized the self-paced iterative sampling ensemble strategy to select the most informative negative samples to train the Multi-Layer Perceptron classifier and put the newly-extracted hidden features into the trained MLP classifier to infer possible microbe-drug associations.Results and discussionIntensive experimental results on two different public databases including the MDAD and the aBiofilm showed that LCASPMDA could achieve better performance than state-of-the-art baseline methods in microbe-drug association prediction.
Performance evaluation of a SARS-CoV-2 and influenza A/B combo rapid antigen test
Authors: Rosenblatt Kevin P. , Romeu Hugo , Romeu Camille , Granger Elder 
Published: May 2024

Introduction: The global COVID-19 pandemic and seasonal influenza outbreaks have drawn attention to the critical need for accurate and efficient diagnostic tools.Methods: The performance of the InstaView COVID-19/Flu Ag Combo Test, which was designed to simultaneously detect the SARS-CoV-2, influenza A, and influenza B viruses, was analytically and clinically evaluated.Results: The InstaView COVID-19/Flu Ag Combo Test exhibited robust detection capabilities, accurately identifying SARS-CoV-2, influenza A, and influenza B viruses over a wide concentration range (1.41 × 103 to 7.05 × 104 TCID50/mL). Extensive testing against potential cross-reactants and interferences yielded no false-positive results, indicating the high specificity of the test. Clinical evaluation further confirmed the kit’s reliability, with sensitivity ranging from 95.1% to 98.2% for SARS-CoV-2, 88.9%–95.2% for influenza A, and 91.7%–100% for influenza B depending on the sample type. The specificity was consistently 100% for all of the targeted viruses.Discussion: The InstaView COVID-19/Flu Ag Combo Test thus demonstrated high performance, ease of use, rapid results, and the ability to precisely detect SARS-CoV-2 and influenza A/B infections, making it an effective tool in streamlining diagnostic workflows, optimizing resource allocation, and improving patient outcomes.
Unveiling the domino effect: a nine-year follow-up on pentalogy of central nervous system induced by a large unruptured cerebral arteriovenous malformation: a case report and literature review
Authors: He Yunsen , Tao Ye , Tian Jing , Bao Mingbin , Zhang Mengjun , Huang Qinjiang , Li Hongliang , Chang Xinxin , Li Kun , Liu Ping , Guo Lili , Qin Xiaohong , Huang Caiquan , Wu Bo 
Published: May 2024

BackgroundThe disruption of intracranial fluid dynamics due to large unruptured cerebral arteriovenous malformation (AVM) commonly triggers a domino effect within the central nervous system. This phenomenon is frequently overlooked in prior clinic and may lead to catastrophic misdiagnoses. Our team has documented the world’s first case of so-called AVM Pentalogy (AVMP) induced by a AVM.Clinical presentation and resultA 30-year-old female was first seen 9 years ago with an occasional fainting, at which time a huge unruptured AVM was discovered. Subsequently, due to progressive symptoms, she sought consultations from several prestigious neurosurgical departments in China, where all consulting neurosurgeons opted for conservation treatment due to perceived surgical risks. During the follow-up period, the patient gradually presented with hydrocephalus, empty sella, secondary Chiari malformation, syringomyelia, and scoliosis (we called as AVMP). When treated in our department, she already displayed numerous symptoms, including severe intracranial hypertension. Our team deduced that the hydrocephalus was the primary driver of her AVMP symptoms, representing the most favorable risk profile for intervention. As expected, a ventriculoperitoneal shunt successfully mitigated all symptoms of AVMP at 21-months post-surgical review.ConclusionDuring the monitoring of unruptured AVM, it is crucial to remain vigilant for the development or progression of AVMP. When any component of AVMP is identified, thorough etiological studies and analysis of cascade reactions are imperative to avert misdiagnosis. When direct AVM intervention is not viable, strategically addressing hydrocephalus as part of the AVMP may serve as the critical therapeutic focus.
Association of body mass index with rapid eye movement sleep behavior disorder in Parkinson’s disease
Authors: Gu Si-Chun , Yuan Xiao-Lei , Yin Ping , Li Yuan-Yuan , Wang Chang-De , Gu Min-Jue , Xu Li-Min , Gao Chen , Wu You , Hu Yu-Qing , Yuan Can-Xing , Cao Yang , Ye Qing 
Published: May 2024

BackgroundThe association between body mass index (BMI) and rapid eye-movement (REM) sleep-related behavioral disorder (RBD) in Parkinson’s disease (PD) remains unknown. Our study was to investigate the association of BMI with RBD in PD patients.MethodsIn this cross-sectional study, a total of 1,115 PD participants were enrolled from Parkinson’s Progression Markers Initiative (PPMI) database. BMI was calculated as weight divided by height squared. RBD was defined as the RBD questionnaire (RBDSQ) score with the cutoff of 5 or more assessed. Univariable and multivariable logistic regression models were performed to examine the associations between BMI and the prevalence of RBD. Non-linear correlations were explored with use of restricted cubic spline (RCS) analysis. And the inflection point was determined by the two-line piecewise linear models.ResultsWe identified 426 (38.2%) RBD. The proportion of underweight, normal, overweight and obese was 2.61, 36.59, 40.36, and 20.44%, respectively. In the multivariate logistic regression model with full adjustment for confounding variables, obese individuals had an odds ratio of 1.77 (95% confidence interval: 1.21 to 2.59) with RBD compared with those of normal weight. In the RCS models with three knots, BMI showed a non-linear association with RBD. The turning points of BMI estimated from piecewise linear models were of 28.16 kg/m2, 28.10 kg/m2, and 28.23 kg/m2 derived from univariable and multivariable adjusted logistic regression models. The effect modification by depression on the association between BMI and RBD in PD was also found in this study. Furthermore, the sensitivity analyses linked with cognition, education, and ethnic groups indicated the robustness of our results.ConclusionThe current study found a significant dose–response association between BMI and RBD with a depression-based difference in the impact of BMI on RBD in PD patients.
Predictive value of red cell distribution width for overlap syndrome in obstructive sleep apnea
Authors: Akyol Gurses Asli , Akyildiz Utku Ogan 
Published: May 2024

PurposeObstructive sleep apnea syndrome (OSAS) and chronic obstructive pulmonary disease (COPD) are prevalent disorders, and the concurrence so-called overlap syndrome (OVS) is not rare either. Early recognition of OVS is essential because this group is more prone to cardiovascular morbidities and requires effective multidisciplinary follow-up. This study aimed to evaluate RDW in patients with severe OSAS and investigate whether it can predict OVS.Patients and methods96 patients were retrospectively analyzed, of whom 66 were found to have severe OSAS alone and 30 OVS during diagnostic workups. Demographic, polysomnographic, and laboratory results, including RDW, were compared between groups. Multivariate logistic regression was used to determine independent associates of OVS.ResultsGender and body mass index (BMI) were similar, however, the mean age and RDW were higher in the OVS group (p:0.008, p:0.002). The increase in RDW remained significant after adjustment for age, BMI, and cardiovascular risk factors. An RDW value of &gt;13.65% was shown to have a 78.3% sensitivity and 60% specificity for predicting OVS in severe OSAS (p:0.004).ConclusionThe results suggest that RDW can be a reliable indicator for diagnosing OVS in OSAS. It can help in identifying the subset of patients who would benefit from proper consultations and multidisciplinary follow-up, leading to appropriate treatment of each disease component and effective monitoring to prevent adverse cardiovascular outcomes.
Research application of session-RPE in monitoring the training load of elite endurance athletes
Authors: Yang Shengjie , Yin Yiquan , Qiu Zhaoyi , Meng Qingjun 
Published: May 2024

PurposeTRIMP and sRPE are both representative indicators of training load(TL), and the correlation between two has been widely demonstrated across various sports. The aim of this study was to investigate the reliability of sRPE-TRIMP correlation across different intensities/duration of training in cross-country skiing, and whether sRPE can serve as an validity supplement to TRIMP data in cases of lost heart rate data.Method10 athletes were used as the experimental objects. The intensity, duration and RPE of 273 different types of training sessions were collected, and statistical methods were used for data analysis.Results1. There was a significant correlation between sRPE and TRIMP (r = 0.68, p &lt; 0.05), but the correlation differs among the LIT, MIT and HIT groups (r = 0.70, 0.46, r = 0.31, p &lt; 0.05) 2. sRPE-TRIMP correlation among three different time duration in the LIT group (0-60 min, 60-120 min and 120-180 min), are all highly significant (r = 0.70, 0.67, 0.69, p &lt; 0.05) and the LRsRPE-TRIMP of 3 duration have no significant differences (chow test, p &gt; 0.05). 3. The difference in actual training duration between samples was the main reason for the difference in the application effect of sRPE, because the actual training duration ratio of LIT was 89.7 ± 16.4%; MIT, 98.5 ± 6.2%; and HIT, 94.4 ± 13.5%.Conclusion1. The linear relationship between sRPE and TRIMP (LRsRPE-TRIMP) is more significant in LIT compared to that in MIT and HIT. 2. Variations in the duration of LIT sessions do not affect the consistency of the relationship between sRPE and TRIMP. 3. Discrepancies between actual and planned training durations directly impact the significance of the LRsRPE-TRIMP.
The long noncoding RNA SUMO1P3 as urinary biomarker for monitoring bladder cancer progression
Authors: Galbiati Silvia , Bettiga Arianna , Colciago Giorgia , Senti Chiara , Trevisani Francesco , Villa Giulia , Marzinotto Ilaria , Ghidini Michele , Passalacqua Rodolfo , Montorsi Francesco , Salonia Andrea , Vago Riccardo 
Published: May 2024

IntroductionUrothelial Bladder Cancer (BC) is the ninth most common cancer worldwide. It is classified into Non Muscle Invasive (NMIBC) and Muscle Invasive Bladder Cancer (MIBC), which are characterized by frequent recurrences and progression rate, respectively. The diagnosis and monitoring are obtained through invasive methods as cystoscopy and post-surgery biopsies. Thus, a panel of biomarkers able to discriminate BC based on grading or staging represents a significant step forward in the patients’ workup. In this perspective, long non-coding RNAs (lncRNAs) are emerged as reliable candidates as potential biomarker given their specific and regulated expression. In the present work we propose two lncRNAs, the Small Ubiquitin Modifier 1 pseudogene 3 (SUMO1P3), a poorly characterized pseudogene, and the Urothelial Carcinoma Associated 1 (UCA1) as candidates to monitor the BC progression.MethodsThis study was a retrospective trial enrolling NMIBC and MIBC patients undergoing surgical intervention: the expression of the lncRNA SUMO1P3 and UCA1 was evaluated in urine from 113 subjects (cases and controls). The receiver operating characteristic curve analysis was used to evaluate the performance of single or combined biomarkers in discriminating cases from controls.ResultsSUMO1P3 and UCA1 expression in urine was able to significantly discriminate low grade NMIBC, healthy control and benign prostatic hyperplasia subjects versus high grade NMIBC and MIBC patients. We also demonstrated that miR-320a, which binds SUMO1P3, was reduced in high grade NMIBC and MIBC patients and the SUMO1P3/miR-320a ratio was used to differentiate cases versus controls, showing a statistically significant power. Finally, we provided an automated method of RNA extraction coupled to ddPCR analysis in a perspective of clinical application.DiscussionWe have shown that the lncRNA SUMO1P3 is increased in urine from patients with high grade NMIBC and MIBC and that it is likely to be good candidate to predict bladder cancer progression if used alone or in combination with UCA1 or with miRNA320a.
Exploiting tertiary lymphoid structures gene signature to evaluate tumor microenvironment infiltration and immunotherapy response in colorectal cancer
Authors: Xu Zhu , Wang Qin , Zhang Yiyao , Li Xiaolan , Wang Mei , Zhang Yuhong , Pei Yaxin , Li Kezhen , Yang Man , Luo Liping , Wu Chuan , Wang Weidong 
Published: May 2024

BackgroundTertiary lymphoid structures (TLS) is a particular component of tumor microenvironment (TME). However, its biological mechanisms in colorectal cancer (CRC) have not yet been understood. We desired to reveal the TLS gene signature in CRC and evaluate its role in prognosis and immunotherapy response.MethodsThe data was sourced from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Based on TLS-related genes (TRGs), the TLS related subclusters were identified through unsupervised clustering. The TME between subclusters were evaluated by CIBERSORT and xCell. Subsequently, developing a risk model and conducting external validation. Integrating risk score and clinical characteristics to create a comprehensive nomogram. Further analyses were conducted to screen TLS-related hub genes and explore the relationship between hub genes, TME, and biological processes, using random forest analysis, enrichment and variation analysis, and competing endogenous RNA (ceRNA) network analysis. Multiple immunofluorescence (mIF) and immunohistochemistry (IHC) were employed to characterize the existence of TLS and the expression of hub gene.ResultsTwo subclusters that enriched or depleted in TLS were identified. The two subclusters had distinct prognoses, clinical characteristics, and tumor immune infiltration. We established a TLS-related prognostic risk model including 14 genes and validated its predictive power in two external datasets. The model’s AUC values for 1-, 3-, and 5-year overall survival (OS) were 0.704, 0.737, and 0.746. The low-risk group had a superior survival rate, more abundant infiltration of immune cells, lower tumor immune dysfunction and exclusion (TIDE) score, and exhibited better immunotherapy efficacy. In addition, we selected the top important features within the model: VSIG4, SELL and PRRX1. Enrichment analysis showed that the hub genes significantly affected signaling pathways related to TLS and tumor progression. The ceRNA network: PRRX1-miRNA (hsa-miR-20a-5p, hsa-miR-485–5p) -lncRNA has been discovered. Finally, IHC and mIF results confirmed that the expression level of PRRX1 was markedly elevated in the TLS- CRC group.ConclusionWe conducted a study to thoroughly describe TLS gene signature in CRC. The TLS-related risk model was applicable for prognostic prediction and assessment of immunotherapy efficacy. The TLS-hub gene PRRX1, which had the potential to function as an immunomodulatory factor of TLS, could be a therapeutic target for CRC.
Optical diagnosis in still images of colorectal polyps: comparison between expert endoscopists and PolyDeep, a Computer-Aided Diagnosis system
Authors: Davila-Piñón Pedro , Nogueira-Rodríguez Alba , Díez-Martín Astrid Irene , Codesido Laura , Herrero Jesús , Puga Manuel , Rivas Laura , Sánchez Eloy , Fdez-Riverola Florentino , Glez-Peña Daniel , Reboiro-Jato Miguel , López-Fernández Hugo , Cubiella Joaquín 
Published: May 2024

BackgroundPolyDeep is a computer-aided detection and classification (CADe/x) system trained to detect and classify polyps. During colonoscopy, CADe/x systems help endoscopists to predict the histology of colonic lesions.ObjectiveTo compare the diagnostic performance of PolyDeep and expert endoscopists for the optical diagnosis of colorectal polyps on still images.MethodsPolyDeep Image Classification (PIC) is an in vitro diagnostic test study. The PIC database contains NBI images of 491 colorectal polyps with histological diagnosis. We evaluated the diagnostic performance of PolyDeep and four expert endoscopists for neoplasia (adenoma, sessile serrated lesion, traditional serrated adenoma) and adenoma characterization and compared them with the McNemar test. Receiver operating characteristic curves were constructed to assess the overall discriminatory ability, comparing the area under the curve of endoscopists and PolyDeep with the chi- square homogeneity areas test.ResultsThe diagnostic performance of the endoscopists and PolyDeep in the characterization of neoplasia is similar in terms of sensitivity (PolyDeep: 89.05%; E1: 91.23%, p=0.5; E2: 96.11%, p&lt;0.001; E3: 86.65%, p=0.3; E4: 91.26% p=0.3) and specificity (PolyDeep: 35.53%; E1: 33.80%, p=0.8; E2: 34.72%, p=1; E3: 39.24%, p=0.8; E4: 46.84%, p=0.2). The overall discriminative ability also showed no statistically significant differences (PolyDeep: 0.623; E1: 0.625, p=0.8; E2: 0.654, p=0.2; E3: 0.629, p=0.9; E4: 0.690, p=0.09). In the optical diagnosis of adenomatous polyps, we found that PolyDeep had a significantly higher sensitivity and a significantly lower specificity. The overall discriminative ability of adenomatous lesions by expert endoscopists is significantly higher than PolyDeep (PolyDeep: 0.582; E1: 0.685, p &lt; 0.001; E2: 0.677, p &lt; 0.0001; E3: 0.658, p &lt; 0.01; E4: 0.694, p &lt; 0.0001).ConclusionPolyDeep and endoscopists have similar diagnostic performance in the optical diagnosis of neoplastic lesions. However, endoscopists have a better global discriminatory ability than PolyDeep in the optical diagnosis of adenomatous polyps.