bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gender-specific differences in central blood pressure and optimal target blood pressure based on the prediction of cardiovascular events
Authors: Kim Min-Sik , Kim Gee-Hee 
Published: October 2022

BackgroundHypertension (HBP) is a common disease among both men and women. Central blood pressure (CBP) is a method of evaluating aorta pressure that can assess the intrinsic BP of an individual patient that more closely correlates with cardiovascular disease (CVD) outcomes than peripheral BP parameters. We evaluated gender-specific differences in CBP and optimal target BP based on a composite outcome of CVD, heart failure (HF), and hypertensive complications in patients with HBP.MethodPatients were enrolled from June 2011 to December 2015 and were followed through December 2019. CBP was measured using radial tonometry. The primary endpoint was a composite outcome.ResultThe median follow-up period for enrolled patients was 6.5 years. Out of a total of 2,115 patients with an average age of 57.9 ± 13.6 years, 266 patients (12.6%) had events of primary end points during the follow-up period. There was no difference in the lowest BP level between men and women in the incidence of CVD. Among the women (49.6%), 78.1% were postmenopausal. In a multivariable Cox proportional hazards model, CBP and systolic BP showed an increase in risk of 10 and 11%, respectively, with every 10 mmHg increase, and there was a similar trend of 12 and 13%, respectively, in postmenopausal women. However, PP showed an increase in risk of about 2% every 10 mmHg increase, but a tendency to increase risk by 19% in postmenopausal women.ConclusionThis study demonstrated that postmenopausal women will continue to show increased risk for CVD at BP higher than the optimal level. Conversely, there was no increase in CV risk due to menopause at BP values below the optimal level. Therefore, well-controlled BP is more important in postmenopausal women.
Combining bioinformatics, network pharmacology and artificial intelligence to predict the mechanism of celastrol in the treatment of type 2 diabetes
Authors: Wu Ming , Zhang Yan 
Published: October 2022

BackgroundType 2 diabetes (T2D) is a common chronic disease with many serious complications. Celastrol can prevent and treat type 2 diabetes by reversing insulin resistance in a number of ways. However, the specific mechanisms by which celastrol prevents and treats T2D are not well understood. The aim of this study was to explore the key gene targets and potential signaling pathway mechanisms of celastrol for the treatment of T2D.MethodsGSE184050 was downloaded from the Gene Expression Omnibus online database. Blood samples from patients and healthy individuals with T2D were analyzed to identify differentially expressed genes (DEGs), and a protein−protein interaction network (PPI) was constructed. Key gene analysis of DEGs was performed using the MCODE plugin in Cystoscope as well as the Hubba plugin, and intersections were taken to obtain hub genes, which were displayed using a Venn diagram. Enrichment analysis was then performed via the ClueGo plugin in Cytoscape and validated using Gene Set Enrichment Analysis. The therapeutic targets of celastrol were then analyzed by pharmacophore network pharmacology, intersected to identify the therapeutic targets of celastrol, enriched for all targets, and intersected to obtain the signaling pathways for celastrol treatment. The protein structures of the therapeutic targets were predicted using the artificial intelligence AlphaFold2. Finally, molecular docking was used to verify whether celastrol could be successfully docked to the predicted targets.Results618 DEGs were obtained, and 9 hub genes for T2D were identified by the MCODE and Hubba plug-ins, including ADAMTS15, ADAMTS7, ADAMTSL1, SEMA5B, ADAMTS8, THBS2, HBB, HBD and HBG2. The DEG-enriched signaling pathways mainly included the ferroptosis and TGF-beta signaling pathways. A total of 228 target genes were annotated by pharmacophore target analysis, and the therapeutic targets were identified, including S100A11, RBP3, HBB, BMP7 and IQUB, and 9 therapeutic signaling pathways were obtained by an intersectional set. The protein structures of the therapeutic targets were successfully predicted by AlphaFold2, and docking was validated using molecular docking.ConclusionCelastrol may prevent and treat T2D through key target genes, such as HBB, as well as signaling pathways, such as the TGF-beta signaling pathway and type II diabetes mellitus.
An Asian case of combined 17α-hydroxylase/17,20-lyase deficiency due to homozygous p.R96Q mutation: A case report and review of the literature
Authors: Liao Qian , Shen Rufei , Liao Mingyu , Ran Chenxi , Zhou Ling , Zhang Yuling , Peng Guiliang , Sun Zheng , Zheng Hongting , Long Min 
Published: October 2022

BackgroundCombined 17α-hydroxylase/17,20-lyase deficiency (17-OHD) is a very rare form of congenital adrenal hyperplasia (CAH) caused by mutations in the CYP17A1 gene. Almost 100 different mutations of the CYP17A1 gene have been reported, including p.R96Q mutation, but no case of p.R96Q mutation has been described in Asian populations.Case presentationWe describe a 22-year-old female patient of 46,XY karyotype, who presented with pseudohermaphrodism, primary amenorrhea, underdeveloped secondary sexual characteristics, delayed epiphyseal healing, hypertension, and hypokalemia. The diagnosis of 17-OHD was reached by measurement of steroid hormones and abdominal CT scan and confirmed by genetic sequencing, which revealed a homozygous p.R96Q missense mutation in the CYP17A1 gene. The patient received treatment with dexamethasone and estradiol, and 4 months of follow-up showed that both blood pressure and potassium were well controlled.ConclusionsThis is the first Asian case of CAH caused by a homozygous p.R96Q missense mutation in the CYP17A1 gene. Herein, we highlight the role of inguinal hernia in the early diagnosis of female 17-OHD and the necessity of removing the ectopic testis.
Exploring methane cycling in an arctic lake in Kangerlussuaq Greenland using stable isotopes and 16S rRNA gene sequencing
Authors: Cadieux Sarah B. , Schütte Ursel M. E. , Hemmerich Chris , Powers Sarah , White Jeffrey R. 
Published: October 2022

Lakes are currently responsible for a significant amount of total natural methane emission. Microbial oxidation of methane plays a central role in Arctic carbon cycling, potentially reducing methane emissions from lakes, though little is known about methane cycling in the water column of Arctic lakes. We previously detected surprisingly large enrichments of heavy carbon and hydrogen isotopes of methane in three small lakes in Greenland suggesting unusually efficient methanotrophic communities in these Arctic lakes. Using stable isotope and 16S rRNA gene sequencing we determined carbon and hydrogen isotopes and microbial community composition down the water column of Teardrop lake, under open-water conditions. We found that isotopic values of methane in Teardrop lake were again highly enriched 13C and 2H at 4 m depth with −13.2‰ and −27.1‰ values for carbon and hydrogen isotopes, respectively. Methane concentrations slightly increased at the depth interval with isotope enrichment, not typical of classic methanotrophy. Consistent with isotopic enrichment of the heavy isotopes we detected the highest relative abundance of putative methanotrophs, in particular Methylovulum at 4 m. The highest relative abundance of putative methanogens was detected at 3 m as well as at 5 m. At the same depth interval, temperature and oxidation reduction potential also increase, supporting increased microbial activity within the water column. Based on geochemical and microbial observations, we suggest that the methane cycling in Teardrop lake is decoupled from a traditional depth dependent model where the dominant source of methane is in the anoxic sediments. Instead, methane in the water column is likely from a combination of anoxic sediment, littoral transport and oxic methanogenesis in the mid-water column, and recycling of carbon within the water column is leading to extreme isotope enrichments. Thus, understanding linkages between depth-dependent microbial dynamics and methane biogeochemistry are necessary to constrain the sensitivity of the methane cycle to future climate change.
The shared biomarkers and pathways of systemic lupus erythematosus and metabolic syndrome analyzed by bioinformatics combining machine learning algorithm and single-cell sequencing analysis
Authors: Wang Yingyu , Huang Zhongzhou , Xiao Yu , Wan Weiguo , Yang Xue 
Published: October 2022

BackgroundSystemic lupus erythematosus (SLE) is one of the most prevalent systemic autoimmune diseases, and metabolic syndrome (MetS) is the most common metabolic disorder that contains hypertension, dyslipidemia, and obesity. Despite clinical evidence suggested potential associations between SLE and MetS, the underlying pathogenesis is yet unclear.MethodsThe microarray data sets of SLE and MetS were obtained from the Gene Expression Omnibus (GEO) database. To identify the shared genes between SLE and MetS, the Differentially Expressed Genes (DEGs) analysis and the weighted gene co-expression network analysis (WGCNA) were conducted. Then, the GO and KEGG analyses were performed, and the protein-protein interaction (PPI) network was constructed. Next, Random Forest and LASSO algorithms were used to screen shared hub genes, and a diagnostic model was built using the machine learning technique XG-Boost. Subsequently, CIBERSORT and GSVA were used to estimate the correlation between shared hub genes and immune infiltration as well as metabolic pathways. Finally, the significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data.ResultsUsing limma and WGCNA, we identified 153 shared feature genes, which were enriched in immune- and metabolic-related pathways. Further, 20 shared hub genes were screened and successfully used to build a prognostic model. Those shared hub genes were associated with immunological and metabolic processes in peripheral blood. The scRNA-seq results verified that TNFSF13B and OAS1, possessing the highest diagnostic efficacy, were mainly expressed by monocytes. Additionally, they showed positive correlations with the pathways for the metabolism of xenobiotics and cholesterol, both of which were proven to be active in this comorbidity, and shown to be concentrated in monocytes.ConclusionThis study identified shared hub genes and constructed an effective diagnostic model in SLE and MetS. TNFSF13B and OAS1 had a positive correlation with cholesterol and xenobiotic metabolism. Both of these two biomarkers and metabolic pathways were potentially linked to monocytes, which provides novel insights into the pathogenesis and combined therapy of SLE comorbidity with MetS.
A novel twelve-gene signature to predict neoadjuvant chemotherapy response and prognosis in breast cancer
Authors: Wu Jin , Tian Yuan , Liu Wei , Zheng Hong , Xi Yuanyin , Yan Yuzhao , Hu Ying , Liao Bin , Wang Minghao , Tang Peng 
Published: October 2022

BackgroundAccurate evaluation of the response to neoadjuvant chemotherapy (NAC) provides important information about systemic therapies for breast cancer, which implies pharmacological response, prognosis, and guide further therapy. Gene profiles overcome the shortcomings of the relatively limited detection indicators of the classical pathological evaluation criteria and the subjectivity of observation, but are complicated and expensive. Therefore, it is essential to develop a more accurate, repeatable, and economical evaluation approach for neoadjuvant chemotherapy responses.MethodsWe analyzed the transcriptional profiles of chemo-resistant breast cancer cell lines and tumors of chemo-resistant breast cancer patients in the GSE25066 dataset. We preliminarily screened out common significantly differentially expressed genes and constructed a NAC response risk model using LASSO regression and univariate and multivariate analyses. The differences in bioinformatic features of tumor cells, immune characteristics, and prognosis were compared between high and low-risk group. The potential drugs that could reverse chemotherapy resistance in breast cancer were screened by the CMap database.ResultsThirty-six genes were commonly up/down-regulated in both NAC chemo-resistant tumors and cells compared to the sensitive tumors and wild-type cells. Through LASSO regression, we obtained a risk model composed of 12 genes. The risk model divided patients into high and low-risk groups. Univariate and multivariate Cox regression analyses suggested that the risk score is an independent prognostic factor for evaluating NAC response in breast cancer. Tumors in risk groups exhibited significant differences in molecular biological characteristics, tumor-infiltrating lymphocytes, and immunosuppressive molecule expression. Our results suggested that the risk score was also a good prognostic factor for breast cancer. Finally, we screened potential drugs that could reverse chemotherapy resistance in breast cancer.ConclusionA novel 12 gene-signature could be used to predict NAC response and predict prognosis in breast cancer.
Effects of jet nebulization on ventilator performance with different invasive ventilation modes: A bench study
Authors: Li Xinyu , Tan Wei , Zhao Hongwen , Wang Wei , Dai Bing , Hou Haijia 
Published: October 2022

BackgroundThe effects of jet nebulization on ventilator performance in the volume control mode (VC) and pressure control mode (PC) of ventilation have not been determined.ObjectivesThe present study investigated the impact of jet nebulization on ventilator performance in different modes in vitro.MethodsTwo types of jet nebulizer (ventilator-integrated jet nebulizers, external jet nebulizer) and six types of ventilator were connected with a simulated lung to simulate aerosol therapy during mechanical ventilation. The ventilation modes were set to VC and PC, and the driving flows of external jet nebulizer were set at 4 L/min and 8 L/min, respectively. Jet nebulizers were placed between patient airway and Y-piece or at 15 cm from the Y-piece in the inspiratory limb. The effects of jet nebulization were compared with the baseline of triggering performance, control performance, and tidal volume under different experimental conditions.ResultsVentilator-integrated jet nebulizers had no effect on ventilator performance in different modes (all P &gt; 0.05). However, the effects of external jet nebulizers on ventilator performance varied widely: for triggering performance, all parameters were increased in different modes and nebulization positions (all P &lt; 0.05), including the time from the beginning of the inspiratory effort to the lowest value of airway pressure needed to trigger the ventilator (TPmin), the time to trigger (Ttrig), and the magnitude of airway pressure drop needed to trigger (Ptrig); for control performance, peak inspiratory pressure (Ppeak) and peak inspiratory flow(Pflow) were increased in the VC mode (P &lt; 0.05), but not significantly changed in the PC mode (P &gt; 0.05);the actual tidal volume (VT) and expiratory tidal volume monitored (VTe) were significantly increased (P &lt; 0.05), however, the inspiratory tidal volume monitored (VTi) was not affected by jet nebulization in the VC mode. In the PC mode, there were no significant changes in VT, whereas VTi decreased and VTe increased (P &lt; 0.05). The higher the driving flow of external jet nebulizers, the stronger the impact on ventilator performance (all P &lt; 0.05).ConclusionTriggering performance was decreased in both the VC and PC modes when using an external jet nebulizer, while the effects of nebulization on control performance and tidal volume varied significantly.
Multi-omics analyses reveal the specific changes in gut metagenome and serum metabolome of patients with polycystic ovary syndrome
Authors: Yang Zhandong , Fu Huijiao , Su Huihui , Cai Xuzi , Wang Yan , Hong Yanjun , Hu Jing , Xie Zhiyong , Wang Xuefeng 
Published: October 2022

ObjectiveThe purpose of this study was to investigate the specific alterations in gut microbiome and serum metabolome and their interactions in patients with polycystic ovary syndrome (PCOS).MethodsThe stool samples from 32 PCOS patients and 18 healthy controls underwent the intestinal microbiome analysis using shotgun metagenomics sequencing approach. Serum metabolome was analyzed by ultrahigh performance liquid chromatography quadrupole time-of-flight mass spectrometry. An integrative network by combining metagenomics and metabolomics datasets was constructed to explore the possible interactions between gut microbiota and circulating metabolites in PCOS, which was further assessed by fecal microbiota transplantation (FMT) in a rat trial.ResultsFecal metagenomics identified 64 microbial strains significantly differing between PCOS and healthy subjects, half of which were enriched in patients. These changed species showed an ability to perturb host metabolic homeostasis (including insulin resistance and fatty acid metabolism) and inflammatory levels (such as PI3K/Akt/mTOR signaling pathways) by expressing sterol regulatory element-binding transcription factor-1, serine/threonine-protein kinase mTOR, and 3-oxoacyl-[acyl-cattier-protein] synthase III, possibly suggesting the potential mechanisms of gut microbiota underlying PCOS. By integrating multi-omics datasets, the panel comprising seven strains (Achromobacter xylosoxidans, Pseudomonas sp. M1, Aquitalea pelogenes, Porphyrobacter sp. HL-46, Vibrio fortis, Leisingera sp. ANG-Vp, and Sinorhizobium meliloti) and three metabolites [ganglioside GM3 (d18:0/16:0), ceramide (d16:2/22:0), and 3Z,6Z,9Z-pentacosatriene] showed the highest predictivity of PCOS (AUC: 1.0) with sensitivity of 0.97 and specificity of 1.0. Moreover, the intestinal microbiome modifications by FMT were demonstrated to regulate PCOS phenotypes including metabolic variables and reproductive hormones.ConclusionOur findings revealed key microbial and metabolite features and their interactions underlying PCOS by integrating multi-omics approaches, which may provide novel insights into discovering clinical diagnostic biomarkers and developing efficient therapeutic strategies for PCOS.
Association of Obstructive Sleep Apnea-Hypopnea Syndrome with hearing loss: A systematic review and meta-analysis
Authors: Wang Chaoyu , Xu Fu , Chen Mingdi , Chen Xiaojuan , Li Chunhe , Sun Xishi , Zhang Yu , Liao Huizhao , Wu Qinglan , Chen Huimin , Li Shunhong , Zhu Jinru , Lin Junyan , Ou Xudong , Zou Zhihong , Li Yuming , Chen Riken , Zheng Zhenzhen , Wang Yang 
Published: October 2022

ObjectiveThis study seeks to investigate the relationship between Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) and hearing impairment by meta-analysis.MethodsCochrane Library, PubMed, Embase, Web of Science and other databases are searched from their establishment to July 1st, 2022. Literature on the relationship between OSAHS and hearing loss is collected, and two researchers independently perform screening, data extraction and quality evaluation on the included literature. Meta-analysis is performed using RevMan 5.4.1 software. According to the heterogeneity between studies, a random-effects model or fixed-effects model is used for meta-analysis.ResultsA total of 10 articles are included, with 7,867 subjects, 1,832 in the OSAHS group and 6,035 in the control group. The meta-analysis shows that the incidence of hearing impairment in the OSAHS group is higher than in the control group (OR = 1.38; 95% CI 1.18–1.62, Z = 4.09, P &lt; 0.001), and the average hearing threshold of OSAHS patients is higher than that of the control group (MD = 5.89; 95% CI 1.87–9.91, Z = 2.87, P = 0.004). After stratifying the included studies according to hearing frequency, the meta-analysis shows that the OSAHS group has a higher threshold of 0.25, and the response amplitudes at frequencies 2, 4, 6, and 8 kHz are all higher than those of the control group.ConclusionCompared with the control group, the OSAHS group has a higher incidence of hearing loss, mainly high-frequency hearing loss. Thus, OSAHS is closely associated with and a risk factor for hearing loss.
Salivary microRNA profiling dysregulation in autism spectrum disorder: A pilot study
Authors: Kalemaj Zamira , Marino Maria Michela , Santini Annamaria Chiara , Tomaselli Giovanni , Auti Amogh , Cagetti Maria Grazia , Borsello Tiziana , Costantino Antonella , Inchingolo Francesco , Boccellino Mariarosaria , Di Domenico Marina , Tartaglia Gianluca Martino 
Published: October 2022

IntroductionAutism spectrum disorders (ASD) are the most prevalent neurobiological disorders in children. The etiology comprises genetic, epigenetic, and environmental factors such as dysfunction of the immune system. Epigenetic mechanisms are mainly represented by DNA methylation, histone modifications, and microRNAs (miRNA). The major explored epigenetic mechanism is mediated by miRNAs which target genes known to be involved in ASD pathogenesis. Salivary poly-omic RNA measurements have been associated with ASD and are helpful to differentiate ASD endophenotypes. This study aims to comprehensively examine miRNA expression in children with ASD and to reveal potential biomarkers and possible disease mechanisms so that they can be used to improve faction between individuals by promoting more personalized therapeutic approaches.Materials and methodsSaliva samples were collected from 10 subjects: 5 samples of children with ASD and 5 from healthy controls. miRNAs were analyzed using an Illumina Next-Generation-Sequencing (NGS) system.ResultsPreliminary data highlighted the presence of 365 differentially expressed miRNAs. Pathway analysis, molecular function, biological processes, and target genes of 41 dysregulated miRNAs were assessed, of which 20 were upregulated, and 21 were downregulated in children with ASD compared to healthy controls.ConclusionThe results of this study represent preliminary but promising data, as the identified miRNA pathways could represent useful biomarkers for the early non-invasive diagnosis of ASD.