Unveiling the Potential of Migrasomes: A Machine-Learning-Driven Signature for Diagnosing Acute Myocardial Infarction.

BACKGROUND: Recent studies have demonstrated that the migrasome, a newly functional extracellular vesicle, is potentially significant in the occurrence, progression, and diagnosis of cardiovascular diseases. Nonetheless, its diagnostic significance and biological mechanism in acute myocardial infarction (AMI) have yet to be fully explored. METHODS: To remedy this gap, we employed an integrative machine learning (ML) framework composed of 113 ML combinations within five independent AMI cohorts to establish a predictive migrasome-related signature (MS). To further elucidate the biological mechanism underlying MS, we implemented single-cell RNA sequencing (scRNA-seq) of cardiac Cd45+ cells from AMI-induced mice. Ultimately, we conducted mendelian randomization (MR) and molecular docking to unveil the therapeutic effectiveness of MS. RESULTS: MS demonstrated robust predictive performance and superior generalization, driven by the optimal combination of Stepglm and Lasso, on the expression of nine migrasome genes (BMP1, ITGB1, NDST1, TSPAN1, TSPAN18, TSPAN2, TSPAN4, TSPAN7, TSPAN9, and WNT8A). Notably, ITGB1 was found to be predominantly expressed in cardiac macrophages in AMI-induced mice, mechanically regulating macrophage transformation between anti-inflammatory and pro-inflammatory. Furthermore, we showed a positive causality between genetic predisposition towards ITGB1 expression and AMI risk, positioning it as a causative gene. Finally, we showed that ginsenoside Rh1, which interacts closely with ITGB1, could represent a novel therapeutic approach for repressing ITGB1. CONCLUSIONS: Our MS has implications in forecasting and curving AMI to inform future diagnostic and therapeutic strategies for AMI.

Leveraging a neutrophil-derived PCD signature to predict and stratify patients with acute myocardial infarction: from AI prediction to biological interpretation.

BACKGROUND: Programmed cell death (PCD) has recently been implicated in modulating the removal of neutrophils recruited in acute myocardial infarction (AMI). Nonetheless, the clinical significance and biological mechanism of neutrophil-related PCD remain unexplored. METHODS: We employed an integrative machine learning-based computational framework to generate a predictive neutrophil-derived PCD signature (NPCDS) within five independent microarray cohorts from the peripheral blood of AMI patients. Non-negative matrix factorization was leveraged to develop an NPCDS-based AMI subtype. To elucidate the biological mechanism underlying NPCDS, we implemented single-cell transcriptomics on Cd45+ cells isolated from the murine heart of experimental AMI. We finally conducted a Mendelian randomization (MR) study and molecular docking to investigate the therapeutic value of NPCDS on AMI. RESULTS: We reported the robust and superior performance of NPCDS in AMI prediction, which contributed to an optimal combination of random forest and stepwise regression fitted on nine neutrophil-related PCD genes (MDM2, PTK2B, MYH9, IVNS1ABP, MAPK14, GNS, MYD88, TLR2, CFLAR). Two divergent NPCDS-based subtypes of AMI were revealed, in which subtype 1 was characterized as inflammation-activated with more vibrant neutrophil activities, whereas subtype 2 demonstrated the opposite. Mechanically, we unveiled the expression dynamics of NPCDS to regulate neutrophil transformation from a pro-inflammatory phase to an anti-inflammatory phase in AMI. We uncovered a significant causal association between genetic predisposition towards MDM2 expression and the risk of AMI. We also found that lidoflazine, isotetrandrine, and cepharanthine could stably target MDM2. CONCLUSION: Altogether, NPCDS offers significant implications for prediction, stratification, and therapeutic management for AMI.

Exploring the dynamics and trends of carbon emission spatiotemporal patterns in the Chengdu-Chongqing Economic Zone, China, from 2000 to 2020.

Analysis of the spatial-temporal pattern and trend of carbon emissions provides an important scientific basis for the development of a low-carbon economy. Based on the corrected NPP-VIIRS and DMSP/OLS nighttime light data, a carbon emission model for the Chengdu-Chongqing Economic Zone (CCEZ) in China is constructed. Furthermore, the article establishes an integrated qualitative and quantitative research system. The qualitative results show that at the city and county scales, the high carbon emission areas and counties are mainly distributed in Chengdu and Chongqing, while the low carbon emission areas are concentrated in the marginal cities of the CCEZ and the counties with low levels of industrialization around the Sichuan Basin. The high-carbon emission zone tended to expand to the north, and the low-carbon emission zone tended to expand to the south. At the grid scale, the carbon emissions of the CCEZ fluctuated and increased from 2000 to 2020, forming a trend connected with those of the central city, with high carbon emissions at the core and radiating outward expansion. Quantitative analysis revealed that carbon emissions at the county and grid scales exhibited a significant positive global spatial correlation, and the overall correlation degree exhibited an increasing trend.

Does chili pepper consumption affect BMI and obesity risk? A cross-sectional analysis.

Background: The effects of chili intake on overweight and obesity have attracted significant interest in recent years. This study aimed to investigate the correlation between chili consumption frequency, body mass index (BMI), and obesity prevalence in the American population. Methods: Data from participants in National Health and Nutrition Examination Survey (NHANES) 2003-2006 were collected. We enrolled 6,138 participants with complete information on chili intake and BMI in this cross-sectional study. Multivariate logistic regression and sensitivity analyses were conducted to explore the relationship between chili intake frequency and BMI and obesity. Subgroup analyses and interaction tests were employed to assess the stability of the observed correlation. Results: Increased chili consumption frequency was linked to higher BMI values and a greater prevalence of obesity. Compared to the non-consumption group, the highest frequency group had a multivariate-adjusted ß of 0.71 (95% CI: 0.05, 1.38) for BMI and an OR of 1.55 (95% CI: 1.22, 1.97) for obesity in the fully adjusted model. This positive association between chili intake frequency and obesity was more pronounced in females and older adults (≥ 60 years old). Conclusion: Our findings suggest a positive association between chili intake frequency and BMI and obesity in United States adults, suggesting that controlling chili intake frequency could potentially contribute to improved weight management in the general population.

Effect of a 3D-printed reconstruction automated matching system for selecting the size of a left double-lumen tube: a study protocol for a prospective randomised controlled trial.

INTRODUCTION: Lung isolation is primarily accomplished using a double-lumen tube (DLT) or bronchial blocker. A precise and accurate size of the DLT is a prerequisite for ensuring its accurate placement. Three-dimensional (3D) reconstruction technology can be used to accurately reproduce tracheobronchial structures to improve the accuracy of DLT size selection. Therefore, we have developed automatic comparison software for 3D reconstruction based on CT data (3DRACS). In this study, we aimed to evaluate the efficiency of using 3DRACS to select the DLT size for endobronchial intubation in comparison with using the 'blind' DLT intubation method to determine the DLT size, which is based on height and sex. METHODS AND ANALYSIS: This is a prospective, single-centre, double-blind randomised controlled trial. In total, 200 patients scheduled for lung resection using a left DLT will be randomly allocated to the 3D group or the control group at a 1:1 ratio. A 3DRACS will be used for the 3D group to determine the size of the DLT, while in the case of the control group, the size of the DLT will be determined according to patient height and sex. The primary outcome is the success rate of placement of the left DLT without fibreoptic bronchoscopy (FOB). The secondary outcomes include the following: successful intubation time, degree of pulmonary atrophy, grade of airway injury, oxygenation during one-lung ventilation, postoperative sore throat and hoarseness, and number of times FOB is used. ETHICS AND DISSEMINATION: Ethical approval has been obtained from our local ethics committee (approval number: SCCHEC-02-2022-155). Written informed consent will be obtained from all participants before randomisation, providing them with clear instructions about the purpose of the study. The results will be disseminated through peer-reviewed publications and conferences. TRIAL REGISTRATION NUMBER: NCT06258954.

Identifying OGN as a Biomarker Covering Multiple Pathogenic Pathways for Diagnosing Heart Failure: From Machine Learning to Mechanism Interpretation.

BACKGROUND: The pathophysiologic heterogeneity of heart failure (HF) necessitates a more detailed identification of diagnostic biomarkers that can reflect its diverse pathogenic pathways. METHODS: We conducted weighted gene and multiscale embedded gene co-expression network analysis on differentially expressed genes obtained from HF and non-HF specimens. We employed a machine learning integration framework and protein-protein interaction network to identify diagnostic biomarkers. Additionally, we integrated gene set variation analysis, gene set enrichment analysis (GSEA), and transcription factor (TF)-target analysis to unravel the biomarker-dominant pathways. Leveraging single-sample GSEA and molecular docking, we predicted immune cells and therapeutic drugs related to biomarkers. Quantitative polymerase chain reaction validated the expressions of biomarkers in the plasma of HF patients. A two-sample Mendelian randomization analysis was implemented to investigate the causal impact of biomarkers on HF. RESULTS: We first identified COL14A1, OGN, MFAP4, and SFRP4 as candidate biomarkers with robust diagnostic performance. We revealed that regulating biomarkers in HF pathogenesis involves TFs (BNC2, MEOX2) and pathways (cell adhesion molecules, chemokine signaling pathway, cytokine-cytokine receptor interaction, oxidative phosphorylation). Moreover, we observed the elevated infiltration of effector memory CD4+ T cells in HF, which was highly related to biomarkers and could impact immune pathways. Captopril, aldosterone antagonist, cyclopenthiazide, estradiol, tolazoline, and genistein were predicted as therapeutic drugs alleviating HF via interactions with biomarkers. In vitro study confirmed the up-regulation of OGN as a plasma biomarker of HF. Mendelian randomization analysis suggested that genetic predisposition toward higher plasma OGN promoted the risk of HF. CONCLUSIONS: We propose OGN as a diagnostic biomarker for HF, which may advance our understanding of the diagnosis and pathogenesis of HF.

Trajectory of pain threshold and its association with acute pain after thoracic surgery: a prospective observational study.

BACKGROUND: Postoperative analgesic management is an ongoing challenge. The pain threshold (PT) is an objective index that reflects the body's sensitivity to pain and can be used for quantitative pain assessment. We hypothesized that the PT is correlated with postoperative pain and can thus be used to guide postoperative pain management. METHODS: This study involved 93 patients who underwent thoracoscopic surgery from December 2019 to February 2020. The PT was measured with transcutaneous electrical stimulation before surgery (T0) and at 1 h (T1), 6 h (T6), and 24 h (T24) after surgery. The visual analogue scale (VAS) score was used to evaluate the severity of postoperative pain at the same time. The PT variation (PTV) after surgery was calculated as the ratio of the postoperative PT to preoperative PT. RESULTS: The postoperative PT was higher than the preoperative PT and showed a downward trend within 24 h after surgery; the PTV also showed a downward trend within 24 h after surgery. PT-T1 was negatively correlated with VAS-T1 at rest and during motion (rest: VAS-T1r = - 0.274, P = 0.008; motion: VAS-T1r = - 0.298, P = 0.004). PTV-T1 was negatively correlated with VAS-T1 during motion (r = - 0.213, P = 0.04). Lower VAS-T1 scores (< 4) at rest and during motion were associated with higher PT-T1 (rest: t = 2.452, P = 0.016; motion: t = 2.138, P = 0.035). The intraoperative sufentanil dose was associated with a postoperative increase in PTV-T1. Increased rescue analgesic administration was associated with PTV elevation. However, the incidence of dizziness in patients with moderate PTV-T24 was lower than that in patients with high or low PTV-T24 (χ2 = 8.297, P = 0.015). CONCLUSIONS: The postoperative PT was higher than the preoperative PT and showed a downward trend within 24 h after surgery; PTV also showed a downward trend within 24 h after surgery. The PT and PTV were negatively correlated with the pain intensity at rest and during motion and were associated with perioperative analgesic consumption and the incidence of adverse events.

Hemodynamic Influences of Remimazolam Versus Propofol During the Induction Period of General Anesthesia: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

BACKGROUND: Remimazolam is a novel ultrashort-effect benzodiazepine. In 2020, the US Food and Drug Administration approved it for procedural sedation. Remimazolam is beneficial for consistent sedation and quick recovery in painless gastrointestinal endoscopy. Propofol is one of the most commonly used intravenous anesthetics in clinical practice. Recently, only a few studies have compared propofol with remimazolam for general anesthesia induction. OBJECTIVES: The purpose of our systematic review and meta-analysis was to compare the hemodynamic effects of remimazolam and propofol during the induction of general anesthesia. STUDY DESIGN: Systematic review and meta-analysis of randomized, controlled trials. METHODS: The authors retrieved the PubMed, Embase, Cochrane Library, and Web of Science databases for studies published through September 30, 2022, which reported relevant prospective randomized controlled trials (RCTs) comparing remimazolam with propofol for general anesthesia. The primary outcome was hemodynamic changes, including the absolute value of fluctuation of mean arterial pressure (delta MAP) and heart rate delta HR). The secondary outcomes were the following 2 indicators: the occurrence of total adverse events and the quality of recovery from general anesthesia at 24 hours postsurgery. RevMan 5.4.1 (The Nordic Cochrane Centre for The Cochrane Collaboration) and trial sequential analysis were used to execute the statistical analyses. The different domains of bias were judged by the Cochrane risk of the bias assessment tool. RESULTS: The authors identified 189 papers in PubMed, Embase, Cochrane Library, and Web of Science. Eight articles with 964 patients were selected. The included studies had moderate quality. For primary outcomes, the lower delta HR (mean difference [MD] = -4.99; 95% CI, -7.97 to -2.00; I² = 41.6%; P = 0.001] and delta MAP (MD = -5.91; 95% CI. -8.57 to -3.24; I² = 0%; P < 0.0001) represent more stable hemodynamic characteristics in the remimazolam group. Regarding secondary outcomes, a considerably lower incidence of total adverse events was noted in the remimazolam group than that for the propofol group (odds ratio [OR] = 0.40; 95% CI, 0.28 to 0.58; I² = 63%; P < 0.00001). In comparison to the propofol group, remimazolam achieved an advantage score of quality of recovery -15 in 24 hours postsurgery (MD = 5.31, 95% CI, 1.51 to 9.12; I² = 87%; P = 0.006). LIMITATION: Firstly, there are only a handful of published RCTs on the administration of remimazolam in general anesthesia. In addition, due to patient privacy, we could not extract individual patient data, therefore we could not combine and assess any variations in patient characteristics. CONCLUSION: Evidence suggests that remimazolam has a lower hemodynamic effect during general anesthesia and fewer perioperative adverse effects after general anesthesia than propofol; however, which agent is superior regarding quality benefit in postoperative recovery based on the studies included here remains inconclusive. Additional RCTs with updated meta-analyses to enlarge the sample size and properly analyze the benefit-to-risk ratio to patients are needed to determine the evidence for such a relatively new medicine.

Hierarchically structured passive radiative cooling ceramic with high solar reflectivity.

Passive radiative cooling using nanophotonic structures is limited by its high cost and poor compatibility with existing end uses, whereas polymeric photonic alternatives lack weather resistance and effective solar reflection. We developed a cellular ceramic that can achieve highly efficient light scattering and a near-perfect solar reflectivity of 99.6%. These qualities, coupled with high thermal emissivity, allow the ceramic to provide continuous subambient cooling in an outdoor setting with a cooling power of >130 watts per square meter at noon, demonstrating energy-saving potential on a worldwide scale. The color, weather resistance, mechanical robustness, and ability to depress the Leidenfrost effect are key features ensuring the durable and versatile nature of the cooling ceramic, thereby facilitating its commercialization in various applications, particularly building construction.

Effects of perioperative intravenous glucocorticoids on perioperative neurocognitive disorders in adults after surgery: A PRISMA-compliant meta-analysis of randomized controlled trials.

BACKGROUND: Randomized controlled trials (RCTs) have shown uncertain clinical benefits from perioperative intravenous glucocorticoids for perioperative neurocognitive disorders (PND). Thus, this meta-analysis was performed to evaluate whether perioperative intravenous glucocorticoids can decrease the occurrence of PND among adults undergoing surgery. METHODS: We searched 4 databases (MEDLINE, Embase, CENTRAL and Web of Science) for RCTs that assessed the incidence of PND in adults (aged ≥ 18 years old) after surgery. Two reviewers independently assessed the studies for eligibility, extracted data, and assessed the risk of bias in each study. We assessed the certainty of evidence using GRADEpro software. RESULTS: A total of 10 studies (N = 14,967) were eligible. Compared with controls, glucocorticoids were not associated with reducing the risk of postoperative cognitive dysfunction (POCD) (risk ratio [RR]: 0.79 95% confidence interval [CI]: 0.41-1.55, P = .50, I2 = 85%), risk of postoperative delirium (POD) (RR: 0.87 95% CI: 0.74-1.03, P = .10, I2 = 36%), the length of stay in intensive care unit (ICU) (mean difference [MD] -0.21 95% CI: -1.20 to 0.79, P = .68, I2 = 84%), 30-day mortality (RR: 0.92 95% CI: 0.59-1.46, P = .73, I2 = 0%), or postoperative atrial fibrillation (RR: 0.94 95% CI: 0.86-1.01, P = .11, I2 = 25%). However, there was significant difference between glucocorticoids and control group in the length of hospital stay (LOS) (MD: -0.39 95% CI: -0.62 to -0.16, P = .001, I2 = 0%), and postoperative infections (RR: 0.65 95% CI: 0.56-0.76, P < .00001, I2 = 0%). CONCLUSIONS: Perioperative intravenous glucocorticoids did not reduce the risk of PND in adults after surgery but might be associated with shorter the LOS and lower the incidence of postoperative infections. More, larger, higher-quality RCTs including neurological surgery or hip fracture surgery and different doses of glucocorticoids compared with placebos are needed to explore the intervention effects.

Perovskite Smart Windows: The Light Manipulator in Energy-Efficient Buildings.

Uncontrolled sunlight entering through windows contributes to substantial heating and cooling demands in buildings, which leads to high energy consumption from the buildings. Recently, perovskite smart windows have emerged as innovative energy-saving technologies, offering the potential to adaptively control indoor solar heat gain through their impressive sunlight modulation capabilities. Moreover, harnessing the high-efficiency photovoltaic properties of perovskite materials, these windows have the potential to generate power, thereby realizing more advanced windows with combined light modulation and energy harvesting capabilities. This review summarizes the recent advancements in various chromic perovskite materials for achieving light modulation, focusing on both perovskite structures and underlying switching mechanisms. The discussion also encompasses device engineering strategies for smart windows, including the improvement of their optical and transition performance, durability, combination with electricity generation, and the evaluation of their energy-saving performance in building applications. Furthermore, the challenges and opportunities associated with perovskite smart windows are explicated, aimed at stimulating more academic research and advancing their pragmatic implementation for building energy efficiency and sustainability.

Effects of combined binding of chlorogenic acid/caffeic acid and gallic acid to trypsin on their synergistic antioxidant activity, enzyme activity and stability.

The combined application of multiple natural polyphenols in functional foods may provide better health benefits. The binding of polyphenols with different structures to proteins will affect their respective functions. Spectroscopy and molecular docking were used to investigate the competitive binding of chlorogenic acid (CGA)/caffeic acid (CA) and gallic acid (GA) to trypsin. The effects of different molecular structures and the order of adding the three phenolic acids on the binding were assessed. The stability of trypsin and its docked complexes with CGA/CA/GA was evaluated by molecular dynamics simulation. The effects of the binding process on the activity and thermal stability of trypsin, as well as on the antioxidant activity and stability of CGA/CA/GA were explored. The competitive binding of CGA/CA and GA to trypsin affected their synergistic antioxidant effects. The results may provide a reference for the combined application of CGA/CA and GA in food and pharmaceutical fields.

Comprehensive Bioinformatics Analysis Reveals PTPN1 (PTP1B) Is a Promising Immunotherapy Target Associated with T Cell Function for Liver Cancer.

Recently, PTP1B was identified as a novel immune checkpoint whose removal can unleash T cell responses. However, research on the influence of PTP1B as an immune regulator on liver cancer is limited. This study aimed to investigate the immunological correlation and function of PTP1B in liver cancer. The expression profiles and corresponding clinical information of liver cancer patients were obtained from the TCGA and ICGC databases. GSE146115 and GSE98638 retrieved from the GEO database were used for the single-cell RNA-seq analysis. The mRNA expression of PTP1B (PTPN1) was increased in patients with most malignancies (all p < 0.05), including liver cancer (p < 0.001). Furthermore, up-regulated PTPN1 was connected to advanced tumor stage (p < 0.05) and worse prognosis (p < 0.01) in liver cancer. Through Cox regression analysis, PTPN1 was considered as an independent prognosis factor of overall survival (p < 0.05) and acted as a high-risk factor (hazard ratio > 1). Gene function and pathway analysis suggested PTPN1 was involved in T cell-related immune responses. Moreover, a close relationship was also found between PTPN1 expression and immune checkpoints as well as immune cells, especially with T cell-related checkpoints (all p < 0.001) and T cells (all p < 0.001). Single-cell RNA-seq analysis further illustrated that the enrichment of PTPN1 in the T cell population may be linked to its exhaustion in the liver cancer microenvironment. Overall, PTPN1 (PTP1B) closely related to T cell may function as an immunotherapy target for liver cancer.

Proposing Intelligent Approach to Predicting Air Kerma within Radiation Beams of Medical X-ray Imaging Systems.

The air kerma is a key parameter in medical diagnostic radiology. Radiologists use the air kerma parameter to evaluate organ doses and any associated patient hazards. The air kerma can be simply described as the deposited kinetic energy once a photon passes through the air, and it represents the intensity of the radiation beam. Due to the heel effect in the X-ray sources of medical imaging systems, the air kerma is not uniform within the X-ray beam's field of view. Additionally, the X-ray tube voltage can also affect this nonuniformity. In this investigation, an intelligent technique based on the radial basis function neural network (RBFNN) is presented to predict the air kerma at every point within the fields of view of the X-ray beams of medical diagnostic imaging systems based on discrete and limited measured data. First, a diagnostic imaging system was modeled with the help of the Monte Carlo N Particle X version (MCNPX) code. It should be noted that a tungsten target and beryllium window with a thickness of 1 mm (no extra filter was applied) were used for modeling the X-ray tube. Second, the air kerma was calculated at various discrete positions within the conical X-ray beam for tube voltages of 40 kV, 60 kV, 80 kV, 100 kV, 120 kV, and 140 kV (this range covers most medical X-ray imaging applications) to provide the adequate dataset for training the network. The X-ray tube voltage and location of each point at which the air kerma was calculated were used as the RBFNN inputs. The calculated air kerma was also assigned as the output. The trained RBFNN model was capable of estimating the air kerma at any random position within the X-ray beam's field of view for X-ray tube voltages within the range of medical diagnostic radiology (20-140 kV).

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure.

The etiologies and pathogenesis of dilated cardiomyopathy (DCM) with heart failure (HF) remain to be defined. Thus, exploring specific diagnosis biomarkers and mechanisms is urgently needed to improve this situation. In this study, three gene expression profiling datasets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Gene Expression Omnibus (GEO) database. GSE29819 and GSE21610 were combined into the training group, while GSE17800 was the test group. We used the weighted gene co-expression network analysis (WGCNA) and identified fifteen driver genes highly associated with DCM with HF in the module. We performed the least absolute shrinkage and selection operator (LASSO) on the driver genes and then constructed five machine learning classifiers (random forest, gradient boosting machine, neural network, eXtreme gradient boosting, and support vector machine). Random forest was the best-performing classifier established on five Lasso-selected genes, which was utilized to select out NPPA, OMD, and PRELP for diagnosing DCM with HF. Moreover, we observed the up-regulation mRNA levels and robust diagnostic accuracies of NPPA, OMD, and PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable up-regulation expression patterns in various cardiomyocytes of DCM patients. Besides, through gene set enrichment analysis (GSEA), we found TGF-ß signaling pathway, correlated with NPPA, OMD, and PRELP, was the underlying mechanism of DCM with HF. Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.

Gut microbiota display alternative profiles in patients with early-onset colorectal cancer.

Background: The incidence of early-onset colorectal cancer (EOCRC) is increasing worldwide. This study aimed to explore whether there is an alternative gut microbiota profile in patients with early-onset colorectal cancer. Methods: A total of 24 patients with EOCRC, 43 patients with late-onset colorectal cancer and 31 young volunteers were included in this study. The diversity of their fecal bacteria was explored using 16S ribosomal RNA gene sequencing. Cluster of ortholog genes (COG) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) were used to detect enrichment pathways among the three groups. Results: Community separations were observed among the three groups. The Shannon index of the EOCRC group was significantly lower than the LOCRC group (P=0.007) and the NC group (P=0.008). Both PCoA analysis (Principal co-ordinates analysis, P=0.001) and NMDS (non-metric multidimensional scaling, stress=0.167, P=0.001) analysis indicated significant difference in beta diversity among the three groups. Fusobacteria, Bacteroidetes, and Clostridia were the most abundant bacteria in the EOCRC group, LOCRC group, and NC group, respectively. The results of COG showed that transcription (P=0.01398), defense mechanisms (P=0.04304), inorganic ion transport and metabolism (P=0.00225) and cell wall/membrane/envelope biogenesis (P=0.02534) were differentially expressed among the three groups. The KEGG modules involved in membrane transport (P=0.00856) and porphyrin and chlorophyll metabolism (P=0.04909) were differentially expressed among the three groups. Conclusion: Early-onset colorectal cancer patients have a different gastrointestinal microbiota derangement compared to late-onset colorectal cancer patients. This dysbiosis can be reflected in the species diversity of the microbiota, the abundance of bacteria, and the abnormal functional predictions.

Genome-wide association analysis of milk production, somatic cell score, and body conformation traits in Holstein cows.

Milk production and body conformation traits are critical economic traits for dairy cows. To understand the basic genetic structure for those traits, a genome wide association study was performed on milk yield, milk fat yield, milk fat percentage, milk protein yield, milk protein percentage, somatic cell score, body form composite index, daily capacity composite index, feed, and leg conformation traits, based on the Illumina Bovine HD100k BeadChip. A total of 57, 12 and 26 SNPs were found to be related to the milk production, somatic cell score and body conformation traits in the Holstein cattle. Genes with pleiotropic effect were also found in this study. Seven significant SNPs were associated with multi-traits and were located on the PLEC, PLEKHA5, TONSL, PTGER4, and LCORL genes. In addition, some important candidate genes, like GPAT3, CEBPB, AGO2, SLC37A1, and FNDC3B, were found to participate in fat metabolism or mammary gland development. These results can be used as candidate genes for milk production, somatic cell score, and body conformation traits of Holstein cows, and are helpful for further gene function analysis to improve milk production and quality.