bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting ocean hypoxia in salmonid fish farms
Authors: Cerqueira Vitor , Pimentel João , Korus Jennie , Bravo Francisco , Amorim Joana , Oliveira Mariana , Swanson Andrew , Filgueira Ramón , Grant Jon , Torgo Luis 
Published: July 2024

IntroductionHypoxia is defined as a critically low-oxygen condition of water, which, if prolonged, can be harmful to fish and many other aquatic species. In the context of ocean salmon fish farming, early detection of hypoxia events is critical for farm managers to mitigate these events to reduce fish stress, however in complex natural systems accurate forecasting tools are limited. The goal of this research is to use a machine learning approach to forecast oxygen concentration and predict hypoxia events in marine net-pen salmon farms.MethodsThe developed model is based on gradient boosting and works in two stages. First, we apply auto-regression to build a forecasting model that predicts oxygen concentration levels within a cage. We take a global forecasting approach by building a model using the historical data provided by sensors at several marine fish farms located in eastern Canada. Then, the forecasts are transformed into binary probabilities that indicate the likelihood of a low-oxygen event. We leverage the cumulative distribution function to compute these probabilities.Results and discussionWe tested our model in a case study that included several cages across 14 fish farms. The experiments suggest that the model can detect future hypoxic events with a commercially acceptable false alarm rate. The resulting probabilistic predictions and oxygen concentration forecasts can help salmon farmers to prioritize resources, and reduce harm to crops.
Clinical characteristics and risk factors for mortality in pneumonia-associated acute respiratory distress syndrome patients: a single center retrospective cohort study
Authors: Li Junlu , Zhou Jiaxin , Tan Yingshuai , Hu Chunling , Meng Qingshan , Gao Jing , Xing Lihua 
Published: July 2024

BackgroundPathogenic diversity may have contributed to the high mortality of pneumonia-associated acute respiratory distress syndrome (p-ARDS). Metagenomics next-generation sequencing (mNGS) serves as a valuable diagnostic tool for early pathogen identification. However, its clinical utility in p-ARDS remains understudied. There are still limited researches on the etiology, clinical characteristics and risk factors for 28-day mortality in p-ARDS patients.MethodsA single center retrospective cohort study of 75 p-ARDS patients was conducted. Patients were categorized into survival and deceased groups based on their 28-day outcomes. A comprehensive clinical evaluation was conducted, including baseline characteristics, laboratory indicators, outcomes and pathogen identification by mNGS and traditional microbiological testing. We then evaluated the diagnostic value of mNGS and identified clinical characteristics and risk factors for 28-day mortality in p-ARDS.ResultThe overall ICU mortality was 26.67%, and the 28-day mortality was 57.33%, with 32 cases (42.67%) in the survival group, and 43 cases (57.33%) in the deceased group. Patients in the deceased group were older than those in the survival group (68(59,73) years vs. 59(44,67) years, P=0.04). The average lengths of ICU and hospital stay were 9(5,13) days and 14(7,21) days, respectively. The survival group had longer lengths of ICU and hospital stay (ICU: 11(7,17) days and hospital: 17(9,27) days) compared to the deceased group (ICU: 8(4,11) days and hospital: 12(6,19) days) (P&lt;0.05). Survival patients exhibited lower Acute Physiology and Chronic Health Evaluation (APACHE) II score on the 3rd and 7th days, higher lymphocyte counts, higher CD3+ and CD8+ T cell counts compared to deceased patients (P&lt;0.05). Multivariate logistic regression analysis identified age, APACHE II scores on 3rd and 7th days, CD8+ T cell count and length of ICU as independent risk factors for 28-day mortality in p-ARDS patients. mNGS demonstrated a significantly higher overall pathogen detection rate (70/75, 93.33%) compared to the traditional method (50/75, 66.67%, P=0.022). The average turnaround time (TAT) for mNGS was significantly shorter at 1(1,1) day compared to 4(3,5) days for the traditional method (P&lt;0.001).ConclusionMetagenome next-generation sequencing can be used as a valuable tool for identifying pathogens in p-ARDS, reducing diagnostic time and improving accuracy. Early application of mNGS alongside traditional methods is recommended for p-ARDS. Furthermore, older age, higher APACHE II scores, lower lymphocyte counts and lymphocyte subset counts were associated with increased mortality in p-ARDS patients, highlighting the importance of timely assessment of immune status and disease severity, especially in elderly.
Assessment of left atrial function provides incremental value: the left atrial volumetric/mechanical coupling index in patients with chronic kidney disease
Authors: Ji Liqin , Gao Xue , Xiao Weiwei , Yu Shaomei 
Published: July 2024

BackgroundHeart failure is a common cause of adverse cardiovascular outcomes in patients with chronic kidney disease (CKD). Left atrial (LA) characteristics are thought to be involved in the development of heart failure. However, LA assessment is complex. Though a variety of parameters have been defined, there is no single parameter that best defines LA function. Pilot data indicate that left atrial volumetric/mechanical coupling index (LACI) may be useful, but data with CKD are lacking.AimThe objective of this study was to define LACI in a cohort of patients with CKD and to assess its value in evaluating LA function and predicting heart failure.MethodsA cohort of patients with CKD was enrolled at our hospital between 2021 and 2023. Follow-up was performed for heart failure. LACI is a volumetric to mechanical coupling index, calculated as the ratio of the LA volume index to the tissue-Doppler myocardial velocity at atrial contraction. Spearman’s rank correlation or Pearson’s correlation was used to calculate the correlation between LACI and echocardiographic/hemodynamic variables. Receiver operating characteristic curve (ROC) analysis was utilised to derive the area under the curve (AUC) for LACI, LVGLS, LASr, LASct and LASI for the detection of heart failure. Kaplan-Meier survival curves were employed to compare clinical outcomes based on LACI thresholds. A multivariable logistic regression analysis was employed to assess the relationship between risk factors and elevated LACI. Cox proportional hazards regression was used to identify risk factors for heart failure.ResultsLACI showed a positive correlation with NT-proBNP, CK-MB, LAVI, E/e’ and LASI (r = 0.504, 0.536, 0.856, 0.541 and 0.509, p &lt; 0.001); and a negative correlation with LASr (r = −0.509, p &lt; 0.001). On the ROC analysis for the determination of heart failure, the AUC of LACI was comparable to those of LVGLS (0.588 vs. 509, p = 0.464), LASr (0.588 vs. 0.448, p = 0.132), LASct (0.588 vs. 0.566, p = 0.971) and LASI (0.588 vs. 0.570, p = 0.874). The cardiovascular risk factors increased by LACI were age, BMI, diabetes, triglycerides, LA size, LASr, LASI, E/A, E/e’ and EF (p &lt; 0.05). During a median follow-up of 16 months (range, 6–28 months), the event-free survival curves demonstrated a higher risk of heart failure in the group with LACI &gt; 5.0 (log-rank test: P &lt; 0.001). LACI &gt; 5.0 was an independent predictor of heart failure [OR: 0.121, 95% CI (0.020–0.740), p = 0.022].ConclusionLACI may prove to be a valuable tool for assessing LA function in patients with CKD, and could be integrated into the routine assessment of LA for the purpose of prognostic assessment and clinical decision-making in patients with CKD.
Genetic drivers of human plasma metabolites that determine mortality in heart failure patients with reduced ejection fraction
Authors: Revathi Venkateswaran Vandana , She Ruicong , Gui Hongsheng , Luzum Jasmine A. , Bryson Timothy D. , Malouf Zack E. , Williams L. Keoki , Sabbah Hani N. , Gardell Stephen J. , Lanfear David E. 
Published: July 2024

BackgroundHeart failure with reduced ejection fraction (HFrEF) remains a significant public health issue, with the disease advancing despite neurohormonal antagonism. Energetic dysfunction is a likely contributor to residual disease progression, and we have previously reported a strong association of plasma metabolite profiles with survival among patients with HFrEF. However, the genetic and biologic mechanisms that underlie the metabolite-survival association in HFrEF were uncertain.Methods and resultsWe performed genetic mapping of the key metabolite parameters, followed by mediation analyses of metabolites and genotypes on survival, and genetic pathway analyses. Patients with HFrEF (n = 1,003) in the Henry Ford Pharmacogenomic Registry (HFPGR; 500 self-reported Black/African race patients [AA], 503 self-reported White/European race patients [EA], and 249 deaths over a median of 2.7 years) with genome-wide genotyping and targeted metabolomic profiling of plasma were included. We tested genome-wide association (GWA) of single nucleotide polymorphisms (SNPs) with the prognostic metabolite profile (PMP) and its components; first stratified by race, and then combined via meta-analysis for the entire cohort. Seven independent loci were identified as GWA significant hits in AA patients (3 for PMP and 4 for individual metabolites), one of which was also significant in the entire cohort (rs944469). No genome wide significant hits were found in White/EA patients. Among these SNPs, only rs35792152, (a hit for 3.HBA) tended to be associated with mortality in standard survival analysis (HR = 1.436, p = 0.052). The mediation analyses indicated several significant associations between SNPs, metabolites, and mortality in AA patients. Functional annotation mapping (FUMA) implicated inflammation, DNA metabolic, and mRNA splicing processes.ConclusionsGWAS of key metabolites and survival along with FUMA pathway analysis revealed new candidate genes which unveiled molecular pathways that contribute to HF disease progression via metabolic and energetic abnormalities.
The velocity extraction and feature analysis of glacier surface motion in the Gongar region based on multi-source remote sensing data
Authors: Gu Fang , Zhang Sicong , Zhang Qinqin , Li Dan , Fu Yingzi , Chen Xuehua 
Published: July 2024

The movement of glaciers plays a crucial role in environmental and geological processes, significantly influencing the formation and dynamics of ice bodies. This study leverages feature tracking technology to analyze optical and Synthetic Aperture Radar (SAR) remote sensing imagery, specifically GF-1 optical images and GF-3, Sentinel-1 SAR images, captured during the 2020 to 2021 ablation season in Gongar. The aim was to quantify glacier surface velocities and to evaluate the comparative effectiveness of different remote sensing modalities in capturing these dynamics. Our findings indicate a strong consistency in the spatial distribution of glacier surface velocities derived from diverse remote sensing data sources, with high-precision optical imagery (GF-1) yielding the most accurate velocity measurements, followed by Sentinel-1 SAR data. Notably, large glaciers in Gongar exhibited rapid movements, with an average velocity of 0.16 m/d, primarily at elevations between 4,500 and 6,500 m. The fastest velocities were recorded at approximately 4,500 m elevation. Glaciers with inclines ranging from 10° to 60° displayed the highest velocities within the 20°–30° slope range. It was observed that glaciers on the southeast slope moved faster, exhibiting the highest average surface velocity, in contrast to those on the west slope, which moved more slowly. The surface velocity of the ice tongue region of Krayaylak Glacier that the largest glacier in Pamir, was observed to be lower than 0.6 m/d, indicating a slow movement speed. The study also reveals that the effectiveness of different remote sensing data in detecting glacier velocity in Gongar, with high-resolution data more accurately capturing surface velocities in melting areas or those with slower movement. This study underscores the importance of multi-source remote sensing data in understanding glacier dynamics and contributes valuable insights into the mechanisms driving glacier movements.
Association between blood lead levels and parathyroid hormone among United States adolescents aged 12–19: a cross-sectional study
Authors: He Baomei , Wang Xiaowei , Luo Huanjun , Zhou Qin 
Published: July 2024

AimsStudies on the association between serum lead levels and parathyroid function in adolescents are lacking. Therefore, in this study, we elucidated the possible association between blood lead levels (BLLs) and the parathyroid hormone (PTH) in adolescents aged 12–19 years in the United States.MethodsIn this study, information from the database of the National Health and Nutrition Examination Survey was utilized. The study included 3919 participants from survey cycles between 2003–2004 and 2005–2006. Multivariable linear regression analysis was performed to determine the correlation between BLLs and PTH. Furthermore, smooth curve fitting was utilized to analyze the dose–response relationship between BLLs and PTH.ResultsMultivariable linear regression analysis revealed that every 1 μg/dL increase in BLLs was associated with 0.67 pg/mL increase in PTH (β = 0.67, 95% CI: 0.16–1.18, p &lt; 0.01). However, sex-stratified subgroup analysis revealed that this positive association was only observed in males (β = 1.16, 95% CI: 0.50–1.83 p &lt; 0.01). Smooth curve fitting revealed a positive correlation between BLLs and PTH.ConclusionsIn adolescents in the United States, BLLs are positively correlated with PTH, particularly in males.
Observational and genetic association of non-alcoholic fatty liver disease and calcific aortic valve disease
Authors: Hao Qing-Yun , Zeng Yu-Hong , Lin Ying , Guo Jing-Bin , Li Shi-Chao , Yang Ping-Zhen , Gao Jing-Wei , Li Ze-Hua 
Published: July 2024

BackgroundNon-alcoholic fatty liver disease (NAFLD) has emerged as a predominant driver of chronic liver disease globally and is associated with increased cardiovascular disease morbidity and mortality. However, the association between NAFLD and calcific aortic valve disease remains unclear. We aimed to prospectively investigate the association between NAFLD and incident aortic valve calcification (AVC), as well as its genetic relationship with incident calcific aortic valve stenosis (CAVS).MethodsA post hoc analysis was conducted on 4226 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) database. We employed the adjusted Cox models to assess the observational association between NAFLD and incident AVC. Additionally, we conducted two-sample Mendelian randomization (MR) analyses to investigate the genetic association between genetically predicted NAFLD and calcific aortic valve stenosis (CAVS), a severe form of CAVD. We repeated the MR analyses by excluding NAFLD susceptibility genes linked to impaired very low-density lipoprotein (VLDL) secretion.ResultsAfter adjustment for potential risk factors, participants with NAFLD had a hazard ratio of 1.58 (95% CI: 1.03–2.43) for incident AVC compared to those without NAFLD. After excluding genes associated with impaired VLDL secretion, the MR analyses consistently showed the significant associations between genetically predicted NAFLD and CAVS for 3 traits: chronic elevation of alanine aminotransferase (odds ratio = 1.13 [95% CI: 1.01–1.25]), imaging-based NAFLD (odds ratio = 2.81 [95% CI: 1.66–4.76]), and biopsy-confirmed NAFLD (odds ratio = 1.12 [95% CI: 1.01–1.24]). However, the association became non-significant when considering all NAFLD susceptibility genes.ConclusionsNAFLD was independently associated with an elevated risk of incident AVC. Genetically predicted NAFLD was also associated with CAVS after excluding genetic variants related to impaired VLDL secretion.
Genetically predicted metabolites mediate the causal associations between autoimmune thyroiditis and immune cells
Authors: Chen Yongzhao , Jiang Bo , Qu Cheng , Jiang Chaoyu , Zhang Chen , Wang Yanxue , Chen Fei , Sun Xitai , Su Lei , Luo Yuqian 
Published: July 2024

IntroductionWe aimed to comprehensively investigate the causal relationship between 731 immune cell traits and autoimmune thyroiditis (AIT) and to identify and quantify the role of 1400 metabolic traits as potential mediators in between.MethodsUsing summary-level data from genome-wide association studies (GWAS) we performed a two-sample bidirectional Mendelian randomization (MR) analysis of genetically predicted AIT and 731 immune cell traits. Furthermore, we used a two-step MR analysis to quantify the proportion of the total effects (that the immune cells exerted on the risk of AIT) mediated by potential metabolites.ResultsWe identified 24 immune cell traits (with odds ratio (OR) ranging from 1.3166 6 to 0.6323) and 10 metabolic traits (with OR ranging from 1.7954 to 0.6158) to be causally associated with AIT, respectively. Five immune cell traits (including CD38 on IgD+ CD24-, CD28 on CD28+ CD45RA+ CD8br, HLA DR+ CD4+ AC, TD CD4+ %CD4+, and CD8 on EM CD8br) were found to be associated with the risk of AIT, which were partially mediated by metabolites (including glycolithocholate sulfate, 5alpha-androstan-3alpha,17beta-diol disulfate, arachidonoylcholine, X-15486, and kynurenine). The proportion of genetically predicted AIT mediated by the identified metabolites could range from 5.58% to 17.7%.DiscussionOur study identified causal associations between AIT and immune cells which were partially mediated by metabolites, thus providing guidance for future clinical and basic research.
The association of metabolic syndrome with telomere length as a marker of cellular aging: a systematic review and meta-analysis
Authors: Ibraheem Shelash Al-Hawary Sulieman , Ali Alzahrani Abdullah , Ghaleb Maabreh Hatem , Abed Jawad Mohammed , Alsaadi Salim B. , Kareem Jabber Noura , Alawadi Ahmed , Alsalamy Ali , Alizadeh Farideh 
Published: July 2024

BackgroundIt has been suggested that metabolic syndrome (MetS) accelerates the aging process, potentially contributing to the development of age-related complications. Available studies examining the relation of MetS to telomere length (TL), a putative biological marker of aging, have yielded inconclusive findings. This meta-analysis was performed to investigate the association between MetS and TL.MethodsA comprehensive systematic search was conducted in PubMed and Scopus databases to identify relevant literature published up to February 2024. Standard mean difference (SMD) and standardized beta coefficient (β) with their 95% confidence intervals (CI) were used as effect sizes to measure the associations using the random effects model.ResultsA total of nine studies, comprising a total sample size of 8,606 participants, were eligible for the meta-analysis. No significant difference in mean TL was found between patients with and without MetS (SMD = −0.03, 95%CI = −0.17 to 0.10), with a significant heterogeneity across the studies (I2 = 89.7.0%, p ≤ 0.001). In contrast, it was revealed that MetS is negatively related to TL (β = −0.08, 95%CI = −0.15 to −0.004). In the subgroup analysis, this finding was supported by the International Diabetes Federation (IDF) definition of MetS.ConclusionThis meta-analysis highlighted that MetS may be linked to a shorter TL. Additional studies are required to confirm this finding.
The complete chloroplast genome sequences of nine melon varieties (Cucumis melo L.): lights into comparative analysis and phylogenetic relationships
Authors: Hu Jianpeng , Yao Jinchen , Lu Jimei , Liu Weiwei , Zhao Zhiqiang , Li Yaqian , Jiang Lu , Zha Liangping 
Published: July 2024

Melon (Cucumis melo L.) is one of the most extensively grown horticulture crops of the world. Based on the morphological characters, melon was formerly divided into two subspecies, Cucumis melo ssp. melo and C. melo ssp. agrestis. However, the present methods are still inadequate to distinguish between them. The phylogenetic analysis based on chloroplast genome sequences could provide essential evidence for the classification of melon varieties. We sequenced the chloroplast genomes of nine different melon varieties by the Illumina Hiseq and performed bioinformatic analyses including repeat element analysis, genome comparison and phylogenetic analysis. The results showed that the melon chloroplast genome has a typical quadripartite structure that was conserved across the analyzed sequences. Its length ranges between 155, 558 and 156, 569 bp, with a total GC content varying from 36.7% to 37%. We found 127–132 genes in melon chloroplast genomes, including 85–87 protein-coding regions, 34–37 tRNA and 6-8 rRNA genes. The molecular structure, gene order, content, codon usage, long repeats, and simple sequence repeats (SSRs) were mostly conserved among the nine sequenced genomes. Phylogenetic analysis showed that the chloroplast genome could clearly distinguish between C. melo ssp. melo and C. melo ssp. agrestis. This study not only provides valuable knowledge on melon chloroplasts, but also offers a theoretical basis and technical support for the genetic breeding of melons.
Daily habits, diseases, drugs and knee osteoarthritis: a two-sample Mendelian randomization analysis
Authors: Zhou Yaqiong , Wang Qi , Chen Liping , Bo Yun , Zhang Yuanyuan 
Published: July 2024

BackgroundThe causal relationship between daily habits, diseases, drugs, and knee osteoarthritis (KOA) remains unclear. This study utilized a two-sample Mendelian randomization (MR) method to investigate the causal links between these factors and KOA, providing new insights for KOA prevention.MethodsSNPs strongly associated with exposure factors (daily habits, diseases, drugs) were extracted from publicly available genome-wide association study (GWAS) as instrumental variables (IVs). We then selected GWAS of KOA as the outcome, conducting a two-sample MR analysis.ResultsOur findings revealed significant causal relationships between several factors and KOA. There was a notable association with time spent watching TV (OR = 4.038; 95% CI: 1.859–8.770; P = 4.192E-04), frequency of friend/family visits (OR = 0.415; 95% CI: 0.219–0.788; P = 7.174E-03), smoking history (OR = 0.781; 95% CI: 0.663–0.921; P = 3.235E-03), gastroesophageal reflux disease (GERD) (OR = 1.519; 95% CI: 1.244–1.856; P = 4.183E-05), hypercholesterolemia (OR = 0.498; 95% CI: 0.290–0.855; P = 0.011), hypothyroidism (OR = 1.048; 95% CI: 1.013–1.084; P = 6.645E-03), use of antithrombotic agents (OR = 0.892; 95% CI: 0.816–0.976; P = 0.013), statin medication (OR = 0.956; 95% CI: 0.916–0.998; P = 0.041), and thyroid preparations (OR = 1.042; 95% CI: 1.014–1.071; P = 2.974E-03) with KOA. Specifically, KOA was positively associated with longer time spent watching TV, GERD, hypothyroidism and thyroid preparations, however showed a negative correlation with more frequent visits from friends or family, smoking history, hypercholesterolemia, antithrombotic agents and statin medication. Sensitivity analysis indicated no significant pleiotropy in these studies (P &gt; 0.05).ConclusionThis comprehensive study underscores the significance of modifying certain habits to mitigate the risk of KOA. Additionally, the elevated risk of KOA among individuals with GERD, hypothyroidism, and those using thyroid preparations warrants attention. These results would be beneficial for clinical research and nursing education.