bluuebunny/crossref_metadata_2025_split huggingface dataset:
Beyond race: Recruitment of diverse participants in clinical genomics research for rare disease
Authors: Young Jennifer L. , Halley Meghan C. , Anguiano Beatriz , Fernandez Liliana , Bernstein Jonathan A. , Wheeler Matthew T. , Tabor Holly K. ,   Undiagnosed Diseases Network Consortium
Published: August 2022

Purpose: Despite recent attention to increasing diversity in clinical genomics research, researchers still struggle to recruit participants from varied sociodemographic backgrounds. We examined the experiences of parents from diverse backgrounds with enrolling their children in clinical genomics research on rare diseases. We explored the barriers and facilitators parents encountered and possible impacts of sociodemographic factors on their access to research.Methods: We utilized semi-structured interviews with parents of children participating in the Undiagnosed Diseases Network. Interview data were analyzed using comparative content analysis.Results: We interviewed 13 Hispanic, 11 non-Hispanic White, four Asian, and two biracial parents. Participants discussed different pathways to clinical genomics research for rare disease as well as how sociodemographic factors shaped families’ access. Themes focused on variation in: 1) reliance on providers to access research; 2) cultural norms around health communication; 3) the role of social capital in streamlining access; and 4) the importance of language-concordant research engagement.Conclusion: Our findings suggest that variables beyond race/ethnicity may influence access in clinical genomics research. Future efforts to diversify research participation should consider utilizing varied recruitment strategies to reach participants with diverse sociodemographic characteristics.
Significance of ZEB2 in the immune microenvironment of colon cancer
Authors: Xie Hao , Wu Zhaoying , Li Zhenhan , Huang Yong , Zou Junwei , Zhou Hailang 
Published: August 2022

Background: ZEB2 is a protein-coding gene that is differentially expressed in tumors and can regulate the growth of tumor cells. This study investigated the specific regulatory mechanism of ZEB2 in COAD, a common cancer with high rates of morbidity and mortality.Methods: Multi-omics panoramic display of expression and function of ZEB2 in colon cancer. R software was used to study the expression of ZEB2 in 33 types of cancer. Furthermore, RT-PCR was used to detect the expression of ZEB2 in colon cancers and para-cancer tissues, as well as in colon cancer cells and normal cells. The ssGSEA was then used to explore the relationship between ZEB2 and immune cells, with UALCAN, EWAS and MEXPRESS applied to explore the methylation of ZEB2. The relationship between immunomodulators and chemokines (or receptors) based on expression data, copy number data, methylation data, and mutation data of ZEB2 was investigated using TISIDB. Finally, a protein interaction network of ZEB2 was constructed, and GO and KEGG analyses were performed on the differentially expressed genes.Results: ZEB2 is downregulated in most cancers, including COAD. The infiltration of the immune cells NK CD56 and Th17 cells was negatively correlated with ZEB2 expression, while the other 22 cells were positively correlated with ZEB2 expression. The DNA methylation of ZEB2 and the methylation of the ZEB2 protein on the EWAS website increased significantly. Analysis of the methylation levels and ZEB2 expression revealed that only the DNA methylation level and the expression of ZEB2 were significantly negatively correlated. The tumor-infiltrating lymphocytes positively correlated with the expression of ZEB2 but negatively correlated with the methylation of ZEB2. The same trend was observed for immunomodulators, chemokines, and receptors. The network showed that the protein performed certain biological functions, thereby affecting disease symptoms.Conclusion: These findings provide evidence that ZEB2-based therapy may represent a powerful treatment strategy for COAD.
Neutrophil extracellular traps: New players in cancer research
Authors: Zhao Junjie , Jin Jiaqi 
Published: August 2022

NETs are chromatin-derived webs extruded from neutrophils as a result of either infection or sterile stimulation using chemicals, cytokines, or microbes. In addition to the classical role that NETs play in innate immunity against infection and injuries, NETs have been implicated extensively in cancer progression, metastatic dissemination, and therapy resistance. The purpose of this review is to describe recent investigations into NETs and the roles they play in tumor biology and to explore their potential as therapeutic targets in cancer treatment.
Metabolic profiling reveals new serum signatures to discriminate lupus nephritis from systemic lupus erythematosus
Authors: Zhang Yamei , Gan Lingling , Tang Jie , Liu Dan , Chen Gang , Xu Bei 
Published: August 2022

BackgroundLupus nephritis (LN) occurs in 50% of patients with systemic lupus erythematosus (SLE), causing considerable morbidity and even mortality. Previous studies had shown the potential of metabolic profiling in the diagnosis of SLE or LN. However, few metabonomics studies have attempted to distinguish SLE from LN based on metabolic changes. The current study was designed to find new candidate serum signatures that could differentiate LN from SLE patients using a non-targeted metabonomics method based on ultra high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS).MethodMetabolic profiling of sera obtained from 21 healthy controls, 52 SLE patients and 43 LN patients. We used SPSS 25.0 for statistical analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and metabolic pathway analysis were used to analyze the metabolic data.ResultsUpon comparison of SLE and LN groups, 28 differential metabolites were detected, the majority of which were lipids and amino acids. Glycerolphospholipid metabolism, pentose and glucuronate interconversions and porphyrin and chlorophyll metabolism were obviously enriched in LN patients versus those with SLE. Among the 28 characteristic metabolites, five key serum metabolites including SM d34:2, DG (18:3(9Z,12Z,15Z)/20:5(5Z,8Z,11Z,14Z,17Z)/0:0), nervonic acid, Cer-NS d27:4, and PC (18:3(6Z,9Z,12Z)/18:3(6Z,9Z,12Z) performed higher diagnostic performance in discriminating LN from SLE (all AUC &gt; 0.75). Moreover, combined analysis of neuritic acid, C1q, and CysC (AUC = 0.916) produced the best combined diagnosis.ConclusionThis study identified five serum metabolites that are potential indicators for the differential diagnosis of SLE and LN. Glycerolphospholipid metabolism may play an important role in the development of SLE to LN. The metabolites we screened can provide more references for the diagnosis of LN and more support for the pathophysiological study of SLE progressed to LN.
Prevalence and associated risk factors of chronic kidney disease: A case study within SIME clinics in Quito, Ecuador 2019–2021
Authors: Eguiguren-Jiménez Lucía , Miles Joshua , Ocampo Jaime , Andrade Jeanette Mary 
Published: August 2022

BackgroundEcuador has been experiencing an epidemiological transition due to its demographic and lifestyle changes, where non-communicable diseases are the leading cause of death, including chronic kidney disease (CKD). Quito, Ecuador's capital city, is one of the cities burdened by CKD, yet it is unknown the factors that contribute to the rising incidence of this disease. The purpose of this study was to estimate the prevalence of CKD among non-institutionalized adults in Quito between 2019 and 2021, and to examine its associations with various risk factors.MethodsFor the analysis of prevalence, the Kidney Disease: Improving Global Outcomes guidelines were used, where an estimated glomerular filtration rate (eGFR) of &lt; 60 ml/min/1.73 m2 was counted as a presumed case of CKD. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was used to calculate eGFR. Multiple linear regression models were used to determined associations between blood pressure, blood glucose, sex, and zone with eGFR. A t-test of independence was used to determine difference in means between sex and zone and eGFR.ResultsA prevalence of 7.2% was found, in which almost 45% of the participants were classified within stages 2–4 of this disease. The risk factors that were significantly associated with eGFR were systolic blood pressure (β = −0.43, p &lt; 0.001), sex, and zone (p &lt; 0.001).ConclusionsOverall a high prevalence of CKD was found among adults who visited SIME clinics in Quito. Associations between main risk factors and eGFR were found, yet further research is needed to explore CKD in Ecuador and its main cities.
Non-pharmacological interventions of travel restrictions and cancelation of public events had a major reductive mortality affect during pre-vaccination coronavirus disease 2019 period
Authors: Wen Haoyu , Shi Fang , Liu Yan , Xie Cong , Qin Guiyu , Wang Fang , Liu Xiaoxue , Bai Jianjun , Hong Qiumian , Ma Runxue , Yu Chuanhua 
Published: August 2022

BackgroundThe coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease that poses a continuous threat to global public health. Many non-pharmacological interventions (NPIs) have been implemented to control the COVID-19 pandemic since the beginning. The aim of this study was to assess the impact of various NPIs on COVID-19 mortality during pre-vaccination and vaccination periods.MethodsThe COVID-19 data used in this study comes from Our World in Data, we used the Oxford Strict Index (OSI) and its five combination interventions as independent variables. The COVID-19 mortality date (MRT) was defined as a date when daily rate of 0.02 COVID-19 deaths per 100,000 population in a country was reached, and the COVID-19 vaccination date (VRT) was defined as people vaccinated reaching 70%. Linear regression and random forest models were used to estimate the impact of various NPI implementation interventions during pre-vaccination and vaccination periods. The performance of models was assessed among others with Shapley Additive Explanations (SHAP) explaining the prediction capability of the model.ResultsDuring the pre-vaccination period, the various NPIs had strong protective effect. When the COVID-19 MRT was reached, for every unit increase in OSI, the cumulative mortality as of June 30, 2020 decreased by 0.71 deaths per 100,000 people. Restrictions in travel (SHAP 1.68) and cancelation of public events and gatherings (1.37) had major reducing effect on COVID-19 mortality, while staying at home (0.26) and school and workplace closure (0.26) had less effect. Post vaccination period, the effects of NPI reduced significantly: cancelation of public events and gatherings (0.25), staying at home (0.22), restrictions in travel (0.14), and school and workplace closure (0.06).ConclusionContinued efforts are still needed to promote vaccination to build sufficient immunity to COVID-19 in the population. Until herd immunity is achieved, NPI is still important for COVID-19 prevention and control. At the beginning of the COVID-19 pandemic, the stringency of NPI implementation had a significant negative association with COVID-19 mortality; however, this association was no longer significant after the vaccination rate reached 70%. As vaccination progresses, “cancelation of public events and gatherings” become more important for COVID-19 mortality.
Integrative analysis of gut microbiota and fecal metabolites in metabolic associated fatty liver disease patients
Authors: Yang Lidan , Dai Yuzhao , He He , Liu Zhi , Liao Shenling , Zhang Yu , Liao Ga , An Zhenmei 
Published: August 2022

ObjectiveMetabolic associated fatty liver disease (MAFLD) affects nearly a quarter of the world’s population. Our study aimed to characterize the gut microbiome and overall changes in the fecal and serum metabolomes in MAFLD patients.MethodsThirty-two patients diagnosed with MAFLD and 30 healthy individuals (control group, CG) were included in this study, the basic clinical characteristics and laboratory test results including routine biochemistry, etc. were recorded for all, and their serum and fecal samples were collected. A portion of the fecal samples was subjected to 16S rDNA sequencing, and the other portion of the fecal samples and serum samples were subjected to non-targeted metabolomic detection based on liquid chromatography-mass spectrometry (LC–MS). Statistical analysis of clinical data was performed using SPSS software package version 25.0 (SPSS Inc., Chicago, IL, United States). The analysis of 16S rDNA sequencing results was mainly performed by R software (V. 2.15.3), and the metabolomics data analysis was mainly performed by CD 3.1 software. Two-tailed p value &lt; 0.05 was considered statistically significant.ResultsThe 16S sequencing data suggested that the species richness and diversity of MAFLD patients were reduced compared with controls. At the phylum level, the relative abundance of Bacteroidota, Pseudomonadota, and Fusobacteriota increased and Bacillota decreased in MAFLD patients. At the genus level, the relative abundances of Prevotella, Bacteroides, Escherichia-Shigella, etc. increased. 2,770 metabolites were detected in stool samples and 1,245 metabolites were detected in serum samples. The proportion of differential lipid metabolites in serum (49%) was higher than that in feces (21%). There were 22 differential metabolites shared in feces and serum. And the association analysis indicated that LPC 18:0 was positively correlated with Christensenellaceae_R-7_group, Oscillospiraceae_UCG-002; neohesperidin was also positively correlated with Peptoniphilus, Phycicoccus, and Stomatobaculum.ConclusionMicrobial sequencing data suggested decreased species richness and diversity and altered β-diversity in feces. Metabolomic analysis identified overall changes in fecal and serum metabolites dominated by lipid molecules. And the association analysis with gut microbes provided potentially pivotal gut microbiota-metabolite combinations in MAFLD patients, which might provide new clues for further research on the disease mechanism and the development of new diagnostic markers and treatments.
The intriguing dose-dependent effect of selected amphiphilic compounds on insulin amyloid aggregation: Focus on a cholesterol-based detergent, Chobimalt
Authors: Siposova Katarina , Petrenko Viktor I. , Garcarova Ivana , Sedlakova Dagmar , Almásy László , Kyzyma Olena A. , Kriechbaum Manfred , Musatov Andrey 
Published: August 2022

The amyloidogenic self-assembly of many peptides and proteins largely depends on external conditions. Among amyloid-prone proteins, insulin attracts attention because of its physiological and therapeutic importance. In the present work, the amyloid aggregation of insulin is studied in the presence of cholesterol-based detergent, Chobimalt. The strategy to elucidate the Chobimalt-induced effect on insulin fibrillogenesis is based on performing the concentration- and time-dependent analysis using a combination of different experimental techniques, such as ThT fluorescence assay, CD, AFM, SANS, and SAXS. While at the lowest Chobimalt concentration (0.1 µM; insulin to Chobimalt molar ratio of 1:0.004) the formation of insulin fibrils was not affected, the gradual increase of Chobimalt concentration (up to 100 µM; molar ratio of 1:4) led to a significant increase in ThT fluorescence, and the maximal ThT fluorescence was 3-4-fold higher than the control insulin fibril’s ThT fluorescence intensity. Kinetic studies confirm the dose-dependent experimental results. Depending on the concentration of Chobimalt, either (i) no effect is observed, or (ii) significantly, ∼10-times prolonged lag-phases accompanied by the substantial, ∼ 3-fold higher relative ThT fluorescence intensities at the steady-state phase are recorded. In addition, at certain concentrations of Chobimalt, changes in the elongation-phase are noticed. An increase in the Chobimalt concentrations also triggers the formation of insulin fibrils with sharply altered morphological appearance. The fibrils appear to be more flexible and wavy-like with a tendency to form circles. SANS and SAXS data also revealed the morphology changes of amyloid fibrils in the presence of Chobimalt. Amyloid aggregation requires the formation of unfolded intermediates, which subsequently generate amyloidogenic nuclei. We hypothesize that the different morphology of the formed insulin fibrils is the result of the gradual binding of Chobimalt to different binding sites on unfolded insulin. A similar explanation and the existence of such binding sites with different binding energies was shown previously for the nonionic detergent. Thus, the data also emphasize the importance of a protein partially-unfolded state which undergoes the process of fibrils formation; i.e., certain experimental conditions or the presence of additives may dramatically change not only kinetics but also the morphology of fibrillar aggregates.
Proteomics and bioinformatics analysis of follicular fluid from patients with polycystic ovary syndrome
Authors: Wang Wenqi , Jiang Qi , Niu Yue , Ding Qiaoqiao , Yang Xiao , Zheng Yanjun , Hao Jing , Wei Daimin 
Published: August 2022

Objectives: Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder with heterogeneous manifestations and complex etiology. We used quantitative proteomics analysis based on mass spectrometry to identify the differences in proteomics profiles for follicular fluid obtained from patients with or without PCOS and explore possible mechanisms underlying PCOS.Methods: Follicular fluid samples were collected from infertile patients with (n = 9) or without (n = 9) PCOS. Total protein was extracted, quantitatively labeled with a tandem mass tag (TMT), and analyzed using liquid chromatography-mass spectrometry (LC‐MS). TMT-based proteomics and bioinformatics analysis were used to determine the differentially expressed proteins (DEPs) and understand the protein networks. The analysis included protein annotation, unsupervised hierarchical clustering, functional classification, functional enrichment and clustering, and protein-protein interaction analysis. Selected DEPs were confirmed by ELISA, and correlation analysis was performed between these DEPs and the clinical characteristics.Results: In this study, we have identified 1,216 proteins, including 70 DEPs (32 upregulated proteins, 38 downregulated proteins). Bioinformatics analysis revealed that the inflammatory response, complement and coagulation cascades, activation of the immune response, lipid transport, and regulation of protein metabolic processes were co-enriched in patients with PCOS. Based on ELISA results, insulin-like growth factor binding protein 1 (IGFBP1) and apolipoprotein C2 (APOC2) were differentially expressed between patients with and without PCOS. Follicular IGFBP1 showed a positive correlation with the serum levels of high-density lipoprotein cholesterol (HDL-C) (r = 0.3046, p = 0.0419), but negatively correlated with the serum levels of anti-Müllerian hormone (AMH) (r = –0.2924, p = 0.0354) and triglycerides (r = –0.3177, p = 0.0246). Follicular APOC2 was negatively correlated with the serum apolipoprotein A1 (APOA1) levels (r = 0.4509, p = 0.0002).Conclusion: Our study identified DEPs in the follicular fluid of patients with PCOS. Inflammatory response, complement and coagulation cascades, activation of the immune response, lipid transport, and regulation of protein metabolic process were deregulated in PCOS, which may play essential roles in the pathogenesis of PCOS.
Real-world applicability of glial fibrillary acidic protein and neurofilament light chain in Alzheimer’s disease
Authors: Parvizi Tandis , König Theresa , Wurm Raphael , Silvaieh Sara , Altmann Patrick , Klotz Sigrid , Rommer Paulus Stefan , Furtner Julia , Regelsberger Günther , Lehrner Johann , Traub-Weidinger Tatjana , Gelpi Ellen , Stögmann Elisabeth 
Published: August 2022

Background: Blood-based biomarkers may add a great benefit in detecting the earliest neuropathological changes in patients with Alzheimer’s disease (AD). We examined the utility of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) regarding clinical diagnosis and differentiation between amyloid positive and negative patients. To evaluate the practical application of these biomarkers in a routine clinical setting, we conducted this study in a heterogeneous memory-clinic population.Methods: We included 167 patients in this retrospective cross-sectional study, 123 patients with an objective cognitive decline [mild cognitive impairment (MCI) due to AD, n = 63, and AD-dementia, n = 60] and 44 age-matched healthy controls (HC). Cerebrospinal fluid (CSF) and plasma concentrations of NfL and GFAP were measured with single molecule array (SIMOA®) technology using the Neurology 2-Plex B kit from Quanterix. To assess the discriminatory potential of different biomarkers, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared.Results: We constructed a panel combining plasma NfL and GFAP with known AD risk factors (Combination panel: age+sex+APOE4+GFAP+NfL). With an AUC of 91.6% (95%CI = 0.85–0.98) for HC vs. AD and 81.7% (95%CI = 0.73–0.90) for HC vs. MCI as well as an AUC of 87.5% (95%CI = 0.73–0.96) in terms of predicting amyloid positivity, this panel showed a promising discriminatory power to differentiate these populations.Conclusion: The combination of plasma GFAP and NfL with well-established risk factors discerns amyloid positive from negative patients and could potentially be applied to identify patients who would benefit from a more invasive assessment of amyloid pathology. In the future, improved prediction of amyloid positivity with a noninvasive test may decrease the number and costs of a more invasive or expensive diagnostic approach.
High neutrophil percentage and neutrophil-lymphocyte ratio in acute phase of ischemic stroke predict cognitive impairment: A single-center retrospective study in China
Authors: Shang Tianling , Ma Bo , Shen Yanxin , Wei Chunxiao , Wang Zicheng , Zhai Weijie , Li Mingxi , Wang Yongchun , Sun Li 
Published: August 2022

Background and aimsRecently, various hemocyte and blood cell ratios have garnered researchers' attention, as a low-cost, widely prevalent, and easy-to-measure index for diagnosing and predicting disease. Therefore, we sought to investigate the effect and predictive value of the peripheral blood neutrophil percentage and neutrophil-lymphocyte ratio (NLR) in the acute phase of ischemic stroke (AIS) in post-stroke cognitive impairment (PSCI).MethodsWe selected 454 patients with mild AIS and acquired general clinical data. The patients were divided into PSCI and post-stroke no cognitive impairment (PSNCI) groups according to their Montreal Cognitive Assessment (MOCA) scores. We assessed whether there were differences in clinical data, peripheral blood neutrophil percentage, and NLR values between the different groups. We also analyzed the independent influences on the occurrence of PSCI using a binary logistic regression. Receiver operating characteristic (ROC) curves were used to analyze the predictive value of the above inflammatory indicators and models containing different inflammatory indicators for PSCI.ResultsIn total, 454 patients were included, of whom 253 (55.7%) patients were in the PSCI group, with a mean age of 62.15 ± 7.34 years and median neutrophil percentage and NLR of 0.64 (0.32–0.95) and 2.39 (0.71–54.46), respectively. Both neutrophil percentage (adjusted OR = 1.025; 95% confidence interval: 1.005–1.406) and NLR as a categorical variable (Q5, adjusted OR = 2.167; 95% CI: 1.127–4.166) were independent risk factors for PSCI, and the Q5 group (NLR ≥ 4.05) had significantly worse overall cognition and executive function.ConclusionsNeutrophil percentage and NLR in the acute phase of AIS were independently associated with PSCI, and a high NLR was strongly associated with executive function. In addition, neutrophil percentage and NLR have diagnostic values for PSCI.