Genome-wide QTL mapping for agronomic traits in the winter wheat cultivar Pindong 34 based on 90K SNP array.

Introduction: Agronomic traits are key components of wheat yield. Exploitation of the major underlying quantitative trait loci (QTLs) can improve the yield potential in wheat breeding. Methods: In this study, we constructed a recombinant inbred line (RIL) population from Mingxian 169 (MX169) and Pindong 34 (PD34) to determine the QTLs for grain length (GL), grain width (GW), grain length-to-width ratio (LWR), plant height (PH), spike length (SL), grain number per spike (GNS), and the thousand grain weight (TGW) across four environments using wheat 90K SNP array. Results: A QTL associated with TGW, i.e., QTGWpd.swust-6BS, was identified on chromosome 6B, which explained approximately 14.1%-16.2% of the phenotypic variation. In addition, eight QTLs associated with GL were detected across six chromosomes in four different test environments. These were QGLpd.swust-1BL, QGLpd.swust-2BL, QGLpd.swust-3BL.1, QGLpd.swust-3BL.2, QGLpd.swust-5DL, QGLpd.swust-6AL, QGLpd.swust-6DL.1, and QGLpd.swust-6DL.2. They accounted for 9.0%-21.3% of the phenotypic variation. Two QTLs, namely, QGWpd.swust-3BS and QGWpd.swust-6DL, were detected for GW on chromosomes 3B and 6D, respectively. These QTLs explained 12.8%-14.6% and 10.8%-15.2% of the phenotypic variation, respectively. In addition, two QTLs, i.e., QLWRpd.swust-7AS.1 and QLWRpd.swust-7AS.2, were detected on chromosome 7A for the grain LWR, which explained 10.9%-11.6% and 11.6%-11.2% of the phenotypic variation, respectively. Another QTL, named QGNSpd-swust-6DS, was discovered on chromosome 6D, which determines the GNS and which accounted for 11.4%-13.8% of the phenotypic variation. Furthermore, five QTLs associated with PH were mapped on chromosomes 2D, 3A, 5A, 6B, and 7B. These QTLs were QPHpd.swust-2DL, QPHpd.swust-3AL, QPHpd.swust-5AL, QPHpd.swust-6BL, and QPHpd.swust-7BS, which accounted for 11.3%-19.3% of the phenotypic variation. Lastly, a QTL named QSLpd.swust-3AL, conferring SL, was detected on chromosome 3A and explained 16.1%-17.6% of the phenotypic variation. All of these QTLs were defined within the physical interval of the Chinese spring reference genome. Discussion: The findings of this study have significant implications for the development of fine genetic maps, for genomic breeding, and for marker-assisted selection to enhance wheat grain yield.

Efficient heavy metal ion removal by fluorographene nanochannel templated molecular sieve: a molecular dynamics simulation study.

Environmental water contamination, particularly by heavy metal ions, has emerged as a worldwide concern due to their non-biodegradable nature and propensity to accumulate in soil and living organisms, posing a significant risk to human health. Therefore, the effective removal of heavy metal ions from wastewater is of utmost importance for both public health and environmental sustainability. In this study, we propose and design a membrane consisting of fluorographene (F-GRA) nanochannels to investigate its heavy metal ion removal capacity through molecular dynamics simulation. Although many previous studies have revealed the good performance of lamellar graphene membranes for desalination, how the zero-charged graphene functionalized by fluorine atoms (fully covered by negative charges) affects the heavy metal ion removal capacity is still unknown. Our F-GRA membrane exhibits an exceptional water permeability accompanied by an ideal heavy metal ion rejection rate. The superior performance of F-GRA membrane in removing heavy metal ions can be attributed to the negative charge of the F-GRA surface, which results in electrostatic attraction to positively charged ions that facilitates the optimal ion capture. Our analysis of the potential of mean force further reveals that water molecule exhibits the lowest free energy barrier relative to ions when passing through the F-GRA channel, indicating that water transport is energetically more favorable than ion. Additional simulations of lamellar graphene membranes show that graphene membranes have higher water permeabilities compared with F-GRA membranes, while robustly compromising the heavy meal ion rejection rates, and thus F-GRA membranes show better performances. Overall, our theoretical research offers a potential design approach of F-GRA membrane for heavy metal ions removal in future industrial wastewater treatment.

Potential toxicity of graphene (oxide) quantum dots via directly covering the active site of anterior gradient homolog 2 protein.

Graphene quantum dots (GQDs) have attracted significant attention in biomedicine, while extensive investigations have revealed a reverse regarding the potential biotoxicity of GQDs. In order to supplementing the understanding of the toxicity profile of GQDs, this study employs a molecular dynamics (MD) simulation approach to systematically investigate the potential toxicity of both GQDs and Graphene Oxide Quantum Dots (GOQDs) on the Anterior Gradient Homolog 2 (AGR2) protein, a key protein capable of protecting the intestine. We construct two typical simulation systems, in which an AGR2 protein is encircled by either GQDs or GOQDs. The MD results demonstrate that both GQDs and GOQDs can directly make contact with and even cover the active site (specifically, the Cys81 amino acid) of the AGR2 protein. This suggests that GQDs and GOQDs have the capability to inhibit or interfere with the normal biological interaction of the AGR2 active site with its target protein. Thus, GQDs and GOQDs exhibit potential detrimental effects on the AGR2 protein. Detailed analyses reveal that GQDs adhere to the Cys81 residue due to van der Waals (vdW) interaction forces, whereas GOQDs attach to the Cys81 residue through a combination of vdW (primary) and Coulomb (secondary) interactions. Furthermore, GQDs aggregation typically adsorb onto the AGR2 active site, while GOQDs adsorb to the active site of AGR2 one by one. Consequently, these findings shed new light on the potential adverse impact of GQDs and GOQDs on the AGR2 protein via directly covering the active site of AGR2, providing valuable molecular insights for the toxicity profile of GQD nanomaterials.

The neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and neutrophil-to-high-density-lipoprotein ratio are correlated with the severity of Parkinson's disease.

Background: Inflammation plays a pivotal role in the pathogenesis of Parkinson's disease (PD). However, the correlation between peripheral inflammatory markers and the severity of PD remains unclear. Methods: The following items in plasma were collected for assessment among patients with PD (n = 303) and healthy controls (HCs; n = 303) were assessed for the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and neutrophil-to-high-density-lipoprotein ratio (NHR) in plasma, and neuropsychological assessments were performed for all patients with PD. Spearman rank or Pearson correlation was used to evaluate the correlation between the NLR, the LMR and the NHR and the severity of PD. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the NLR, LMR and NHR for PD. Results: The plasma NLR and NHR were substantially higher in patients with PD than in HCs, while the plasma LMR was substantially lower. The plasma NLR was positively correlated with Hoehn and Yahr staging scale (H&Y), Unified Parkinson's Disease Rating Scale (UPDRS), UPDRS-I, UPDRS-II, and UPDRS-III scores. Conversely, it exhibited a negative relationship with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Furthermore, the plasma NHR was positively correlated with H&Y, UPDRS, UPDRS-I, UPDRS-II and UPDRS-III scores. Moreover, negative associations were established between the plasma LMR and H&Y, UPDRS, UPDRS-I, UPDRS-II, and UPDRS-III scores. Finally, based on the ROC curve analysis, the NLR, LMR and NHR exhibited respectable PD discriminating power. Conclusion: Our research indicates that a higher NLR and NHR and a lower LMR may be relevant for assessing the severity of PD and appear to be promising disease-state biomarker candidates.

Villin headpiece unfolding upon binding to boridene mediated by the "anchoring-perturbation" mechanism.

We employ molecular dynamics (MD) simulations to investigate the influence of boridene on the behavior of a protein model, HP35, with the aim of assessing the potential biotoxicity of boridene. Our MD results reveal that HP35 can undergo unfolding via an "anchoring-perturbation" mechanism upon adsorption onto the boridene surface. Specifically, the third helix of HP35 becomes tightly anchored to the boridene surface through strong electrostatic interactions between the abundant molybdenum atoms on the boridene surface and the oxygen atoms on the HP35 backbone. Meanwhile, the first helix, experiencing continuous perturbation from the surrounding water solution over an extended period, suffers from potential breakage of hydrogen bonds, ultimately resulting in its unfolding. Our findings not only propose, for the first time to our knowledge, the "anchoring-perturbation" mechanism as a guiding principle for protein unfolding but also reveal the potential toxicity of boridene on protein structures.

Mendelian randomization reveals association between retinal thickness and non-motor symptoms of Parkinson's disease.

Retinal thickness is related to Parkinson's disease (PD), but its association with the severity of PD is still unclear. We conducted a Mendelian randomized (MR) study to explore the association between retinal thickness and PD. For the two-sample MR analysis, the summary statistics obtained from genome-wide association studies on the thickness of Retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) were employed as exposure, while the summary statistics associated with PD were used as the outcome. The primary approach utilized was inverse variance weighted. To correct for multiple testing, the false discovery rate (FDR) was employed. For sensitivity analysis, an array of robust MR methods was utilized. We found genetically predicted significant association between reduced RNFL thickness and a reduced risk of constipation in PD (odds ratio [OR] = 0.854, 95% confidence interval [CI] (0.782, 0.933), P < 0.001, FDR-corrected P = 0.018). Genetically predicted reduced RNFL thickness was associated with a reduced Unified Parkinson's Disease Rating Scale total score (ß = -0.042, 95% CI (-0.079, 0.005), P = 0.025), and reduced GCIPL thickness was associated with a lower risk of constipation (OR = 0.901, 95% CI (0.821, 0.988), P = 0.027) but a higher risk of depression (OR = 1.103, 95% CI (1.016, 1.198), P = 0.020), insomnia (OR = 1.090, 95% CI (1.013, 1.172), P = 0.021), and rapid eye movement sleep behaviour disorder (RBD) (OR = 1.198, 95% CI (1.061, 1.352), P = 0.003). In conclusion, we identify an association between retinal thickness and non-motor symptoms (constipation, depression, insomnia and RBD) in PD, highlighting the potential of retinal thickness as a biomarker for PD nonmotor symptoms.

Graphene quantum dots blocking the channel egresses of cytochrome P450 enzyme (CYP3A4) reveals potential toxicity.

Graphene quantum dots (GQDs) have garnered significant attention, particularly in the biomedical domain. However, extensive research reveals a dichotomy concerning the potential toxicity of GQDs, presenting contrasting outcomes. Therefore, a comprehensive understanding of GQD biosafety necessitates a detailed supplementation of their toxicity profile. In this study, employing a molecular dynamics (MD) simulation approach, we systematically investigate the potential toxicity of GQDs on the CYP3A4 enzyme. We construct two distinct simulation systems, wherein a CYP3A4 protein is enveloped by either GQDs or GOQDs (graphene oxide quantum dots). Our results elucidate that GQDs come into direct contact with the bottleneck residues of Channels 2a and 2b of CYP3A4. Furthermore, GQDs entirely cover the exits of Channels 2a and 2b, implying a significant hindrance posed by GQDs to these channels and consequently leading to toxicity towards CYP3A4. In-depth analysis reveals that the adsorption of GQDs to the exits of Channels 2a and 2b is driven by a synergistic interplay of hydrophobic and van der Waals (vdW) interactions. In contrast, GOQDs only partially obstruct Channel 1 of CYP3A4, indicating a weaker influence on CYP3A4 compared to GQDs. Our findings underscore the potential deleterious impact of GQDs on the CYP3A4 enzyme, providing crucial molecular insights into GQD toxicology.

Development of a nomogram based on radiomics and semantic features for predicting chromosome 7 gain/chromosome 10 loss in IDH wild-type histologically low-grade gliomas.

Purpose: To predict chromosome 7 gain and chromosome 10 loss (+7/-10) in IDH wild-type (IDH-wt) histologically low-grade gliomas (LGG) by machine learning models based on MRI radiomics and semantic features. Methods: A total of 122 patients diagnosed as IDH-wt histologically LGG were retrospectively included in this study. The patients were randomly divided into a training group and a test group in a ratio of 7:3. The radiomics features were extracted from axial T1WI, T2WI, FLAIR and CET1 sequences, respectively. The distance correlation (DC) and least absolute shrinkage and selection operator (LASSO) were used to select the radiomics signatures. Three machine learning algorithms including neural network (NN), support vector machine (SVM), and linear discriminant analysis (LDA) were used to construct radiomics models. In addition, a nomogram was developed by combining the optimal radiomics signature with clinical risk factors, and the potential clinical utility of the nomogram was evaluated using decision curve analysis. Results: The LDA+DC model was identified as the optimal classifier among the six radiomics models. Necrosis was determined as a risk factor for +7/-10 in IDH-wt histologically LGG. The nomogram achieved the best performance, with an AUC of 0.854 and an accuracy of 0.778 in the independent test group. The decision curve of the nomogram confirmed its clinical usefulness in a wide range of thresholds. Conclusion: The nomogram combining radiomics and semantic features can predict the +7/-10 status effectively, which may contribute to the risk stratification and individualized treatment planning of patients with IDH-wt histologically LGG.

Machine learning models based on multi-parameter MRI radiomics for prediction of molecular glioblastoma: a new study based on the 2021 World Health Organization classification.

BACKGROUND: The 2021 World Health Organization (WHO) classification considers a histological low grade glioma with specific molecular characteristics as molecular glioblastoma (mGBM). Accurate identification of mGBM will aid in risk stratification of glioma patients. PURPOSE: To explore the value of machine learning models based on magnetic resonance imaging (MRI) radiomics features in predicting mGBM. MATERIAL AND METHODS: In total, 166 patients histologically diagnosed as low-grade diffuse glioma (WHO II and III) were included in the study. Fifty-three cases were reclassified as mGBM based on molecular status. Four dimensionality reduction methods including distance correlation (DC), gradient boosted decision tree (GBDT), least absolute shrinkage and selection operator (LASSO) and minimal redundancy maximal relevance (MRMR) were used to select the optimal signatures. Six machine learning algorithms including support vector machine (SVM), linear discriminant analysis (LDA), neural network (NN), logistic regression (LR), K-nearest neighbour (KNN) and decision tree (DT) were used to develop the classifiers. The relative SD was used to evaluate the stability of the models, and the area under the curve values in the independent test group were used to evaluate their performances. RESULTS: NN_DC was determined as the optimal classifier due to the highest area under the curve of 0.891 in the test group. The classification accuracy, sensitivity, specificity, positive predictive value and negative predictive value of NN_DC were 0.915, 0.842, 0.950, 0.889 and 0.927, respectively. CONCLUSION: Machine learning models can predict mGBM non-invasively, which may help to develop personalized treatment strategies for neurosurgeons and provide an effective tool for accurate stratification in clinical trials.

Nomograms Based on MRI Radiomics for Differential Diagnosis and Predicting BRAFV600E Expression in Pleomorphic Xanthoastrocytoma and Ganglioglioma.

RATIONALE AND OBJECTIVES: This study was designed to investigate the value of nomograms based on MRI radiomics and clinical semantic features in identifying pleomorphic xanthoastrocytoma (PXA) and ganglioglioma (GG) as well as predicting BRAFV600E expression. MATERIALS AND METHODS: This study included 265 patients histologically diagnosed with PXA (n = 113) and GG (n = 152). T1WI, T2WI, and CET1 sequences were utilized to extract radiomics features. Univariate analysis, Spearman correlation analysis, and the least absolute shrinkage and selection operator were used for dimensionality reduction and feature selection. Following this, logistic regression was utilized to establish the radiomics model. Univariate and multivariate analyses of clinical semantic features were applied, and clinical models were constructed. The nomograms were established by merging radiomics and clinical features. Furthermore, ROC curve analysis was used for examining the model performance, whereas the decision curve analysis (DCA) examined the clinical utility of the nomograms. RESULTS: Nomograms achieved the best predictive efficacy compared to clinical and radiomics models alone. Concerning the differentiation between PXA and GG, the area under the curve (AUC) values of the nomogram were 0.879 (0.828-0.930) and 0.887 (0.805-0.969) for the training and testing cohorts, respectively. For predicting BRAFV600E expression, the AUC values of the nomogram were 0.873 (0.811-0.936) and 0.851 (0.740-0.963) for the training and testing cohorts, respectively. DCA confirmed the clinical utility of the nomograms. CONCLUSION: Nomograms based on radiomics and clinical semantic features were noninvasive tools for differential diagnosis of PXA and GG and predicting BRAFV600E expression, which may be helpful for assessing patient prognosis and developing individualized treatment strategies.

Moderate binding of villin headpiece protein to C3N3 nanosheet reveals the suitable biocompatibility of this nanomaterial.

Since its recent successful synthesis and due to its promising physical and chemical properties, the carbon nitrite nanomaterial, C3N3, has attracted considerable attention in various scientific areas. However, thus far, little effort has been devoted to investigating the structural influence of the direct interaction of this 2D nanomaterial and biomolecules, including proteins and biomembranes so as to understand the physical origin of its bio-effect, particularly from the molecular landscape. Such information is fundamental to correlate to the potential nanotoxicology of the C3N3 nanomaterial. In this work, we explored the potential structural influence of a C3N3 nanosheet on the prototypical globular protein, villin headpiece (HP35) using all-atom molecular dynamics (MD) simulations. We found that HP35 could maintain its native conformations upon adsorption onto the C3N3 nanosheet regardless of the diversity in the binding sites, implying the potential advantage of C3N3 in protecting the biomolecular structure. The adsorption was mediated primarily by vdW interactions. Moreover, once adsorbed on the C3N3 surface, HP35 remains relatively fixed on the nanostructure without a distinct lateral translation, which may aid in keeping the structural integrity of the protein. In addition, the porous topological structure of C3N3 and the special water layer present on the C3N3 holes conjointly contributed to the restricted motion of HP35 via the formation of a high free energy barrier and a steric hindrance to prevent the surface displacement. This work revealed for the first time the potential influence of the 2D C3N3 nanomaterial in the protein structure and provided the corresponding in-depth molecular-level mechanism, which is valuable for future applications of C3N3 in bionanomedicine.

Non-pharmacological and drug treatment of autonomic dysfunction in multiple system atrophy: current status and future directions.

Multiple system atrophy (MSA) is a sporadic, fatal, and rapidly progressive neurodegenerative disease of unknown etiology that is clinically characterized by autonomic failure, parkinsonism, cerebellar ataxia, and pyramidal signs in any combination. Early onset and extensive autonomic dysfunction, including cardiovascular dysfunction characterized by orthostatic hypotension (OH) and supine hypertension, urinary dysfunction characterized by overactive bladder and incomplete bladder emptying, sexual dysfunction characterized by sexual desire deficiency and erectile dysfunction, and gastrointestinal dysfunction characterized by delayed gastric emptying and constipation, are the main features of MSA. Autonomic dysfunction greatly reduces quality of life and increases mortality. Therefore, early diagnosis and intervention are urgently needed to benefit MSA patients. In this review, we aim to discuss the systematic treatment of autonomic dysfunction in MSA, and focus on the current methods, starting from non-pharmacological methods, such as patient education, psychotherapy, diet change, surgery, and neuromodulation, to various drug treatments targeting autonomic nerve and its projection fibers. In addition, we also draw attention to the interactions among various treatments, and introduce novel methods proposed in recent years, such as gene therapy, stem cell therapy, and neural prosthesis implantation. Furthermore, we elaborate on the specific targets and mechanisms of action of various drugs. We would like to call for large-scale research to determine the efficacy of these methods in the future. Finally, we point out that studies on the pathogenesis of MSA and pathophysiological mechanisms of various autonomic dysfunction would also contribute to the development of new promising treatments and concepts.

Healthy Human Fecal Microbiota Transplantation into Mice Attenuates MPTP-Induced Neurotoxicity via AMPK/SOD2 Pathway.

Increasing evidence has shown that gut dysbacteriosis may play a crucial role in neuroinflammation in Parkinson's disease (PD). However, the specific mechanisms that link gut microbiota to PD remain unexplored. Given the critical roles of blood-brain barrier (BBB) dysfunction and mitochondrial dysfunction in the development of PD, we aimed to evaluate the interactions among the gut microbiota, BBB, and mitochondrial resistance to oxidation and inflammation in PD. We investigated the effects of fecal microbiota transplantation (FMT) on the physiopathology of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice. The aim was to explore the role of fecal microbiota from PD patients and healthy human controls in neuroinflammation, BBB components, and mitochondrial antioxidative capacity via the AMPK/SOD2 pathway. Compared to control mice, MPTP-treated mice exhibited elevated levels of Desulfovibrio, whereas mice given FMT from PD patients exhibited enriched levels of Akkermansia and mice given FMT from healthy humans showed no significant alterations in gut microbiota. Strikingly, FMT from PD patients to MPTP-treated mice significantly aggravated motor impairments, dopaminergic neurodegeneration, nigrostriatal glial activation and colonic inflammation, and inhibited the AMPK/SOD2 signaling pathway. However, FMT from healthy human controls greatly improved the aforementioned MPTP-caused effects. Surprisingly, the MPTP-treated mice displayed a significant loss in nigrostriatal pericytes, which was restored by FMT from healthy human controls. Our findings demonstrate that FMT from healthy human controls can correct gut dysbacteriosis and ameliorate neurodegeneration in the MPTP-induced PD mouse model by suppressing microgliosis and astrogliosis, ameliorating mitochondrial impairments via the AMPK/SOD2 pathway, and restoring the loss of nigrostriatal pericytes and BBB integrity. These findings raise the possibility that the alteration in the human gut microbiota may be a risk factor for PD and provide evidence for potential application of FMT in PD preclinical treatment.

Prognostic value of autophagy-related genes based on single-cell RNA-sequencing in colorectal cancer.

Background: Colorectal cancer (CRC) is the second most common cancer in China. Autophagy plays an important role in the initiation and development of CRC. Here, we assessed the prognostic value and potential functions of autophagy-related genes (ARGs) using integrated analysis using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA). Methods: We analyzed GEO-scRNA-seq data from GEO using various single-cell technologies, including cell clustering, and identification of differentially expressed genes (DEGs) in different cell types. Additionally, we performed gene set variation analysis (GSVA). The differentially expressed ARGs among different cell types and those between CRC and normal tissues were identified using TCGA-RNA-seq data, and the hub ARGs were screened. Finally, a prognostic model based on the hub ARGs was constructed and validated, and patients with CRC in TCGA datasets were divided into high- and low-risk groups based on their risk-score, and immune cells infiltration and drug sensitivity analyses between the two groups were performed. Results: We obtained single-cell expression profiles of 16,270 cells, and clustered them into seven types of cells. GSVA revealed that the DEGs among the seven types of cells were enriched in many signaling pathways associated with cancer development. We screened 55 differentially expressed ARGs, and identified 11 hub ARGs. Our prognostic model revealed that the 11 hub ARGs including CTSB, ITGA6, and S100A8, had a good predictive ability. Moreover, the immune cell infiltrations in CRC tissues were different between the two groups, and the hub ARGs were significantly correlated with the enrichment of immune cell infiltration. The drug sensitivity analysis revealed that the patients in the two risk groups had difference in their response to anti-cancer drugs. Conclusion: We developed a novel prognostic 11-hub ARG risk model, and these hubs may act as potential therapeutic targets for CRC.

A DWI-based radiomics-clinical machine learning model to preoperatively predict the futile recanalization after endovascular treatment of acute basilar artery occlusion patients.

OBJECTIVE: To develop an effective machine learning model to preoperatively predict the occurrence of futile recanalization (FR) of acute basilar artery occlusion (ABAO) patients with endovascular treatment (EVT). MATERIALS AND METHODS: Data from 132 ABAO patients (109 male [82.6 %]; mean age ± standard deviation, 59.1 ± 12.5 years) were randomly divided into the training (n = 106) and test cohort (n = 26) with a ratio of 8:2. FR is defined as a poor outcome [modified Rankin Scale (mRS) 4-6] despite a successful recanalization [modified Thrombolysis in Cerebral Infarction (mTICI) ≥ 2b]. A total of 1130 radiomics features were extracted from diffusion-weighted imaging (DWI) images. The least absolute shrinkage and selection operator (LASSO) regression method was applicated to select features. Support vector machine (SVM) was applicated to construct radiomics and clinical models. Finally, a radiomics-clinical model that combined clinical with radiomics features was developed. The models were evaluated by receiver operating characteristic (ROC) curve and decision curve. RESULTS: The area under the receiver operating characteristic (ROC) curve (AUC) of the radiomics-clinical model was 0.897 (95 % confidence interval, 0.837-0.958) in the training cohort and 0.935 (0.833-1.000) in the test cohort. The AUC of the radiomics model was 0.887 (0.824-0.951) in the training cohort and 0.840 (0.680-1.000) in the test cohort. The AUC of the clinical model was 0.746 (0.652-0.840) in the training cohort and 0.766 (0.569-0.964) in the test cohort. The AUC of the radiomics-clinical model was significantly larger than the clinical model (p = 0.016). A radiomics-clinical nomogram was developed. The decision curve analysis indicated its clinical usefulness. CONCLUSION: The DWI-based radiomics-clinical machine learning model achieved satisfactory performance in predicting the FR of ABAO patients preoperatively.

Causal effect of gut-microbiota-derived metabolite trimethylamine N-oxide on Parkinson's disease: A Mendelian randomization study.

BACKGROUND AND PURPOSE: It has been suggested that trimethylamine N-oxide (TMAO) is related to Parkinson's disease (PD) in observational studies. However, the direction of this association is inconsistent. An exploratory Mendelian randomization study was conducted to investigate whether TMAO and its precursors have a causal relationship with PD. METHODS: Summary statistics were obtained for single nucleotide polymorphisms related to circulating levels of TMAO, betaine, carnitine and choline, and the corresponding data for the risk, age at onset and progression of PD from genome-wide association studies. Inverse-variance weighting was used as the primary method for effect estimation. The false discovery rate was applied to the correction of multiple testing. A p value of association <0.05 but above the false discovery rate corrected threshold was deemed suggestive evidence of a possible association. A range of robust Mendelian randomization methods were used for sensitivity analysis. RESULTS: Suggestive evidence was observed of an inverse causal effect of TMAO on motor fluctuations (odds ratio [OR] 0.851, 95% confidence interval [CI] 0.731, 0.990, p = 0.037) and carnitine on insomnia (OR 0.817, 95% CI 0.700, 0.954, p = 0.010) and a positive causal effect of betaine on Hoehn-Yahr stage (OR 1.397, 95% CI 1.112, 1.756, p = 0.004), Unified Parkinson's Disease Rating Scale (UPDRS) III score (ß = 0.138, 95% CI 0.051, 0.225, p = 0.002), motor fluctuations (OR 1.236, 95% CI 1.011, 1.511, p = 0.039), and choline on UPDRS IV (ß = 0.106, 95% CI 0.026, 0.185, p = 0.009) and modified Schwab and England Activities of Daily Living Scale score (ß = 0.806, 95% CI 0.127, 1.484, p = 0.020). CONCLUSIONS: Our findings provide suggestive evidence that TMAO and its precursors have a causal effect on the progression of PD. Further investigation of the underlying mechanisms is required.

Increased expression of NOP14 is associated with improved prognosis due to immune regulation in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the third most common of cancer-related deaths. Nucleolar protein 14 (NOP14) is known to play different roles in diverse types of cancers. However, little is known about its roles in CRC. Here, we assessed the prognostic value and functions of NOP14 in CRC using the data from The Cancer Genome Atlas (TCGA) and validated them based on the data from Gene Expression Omnibus (GEO). METHODS: NOP14 mRNA and protein data in CRC was obtained from the TCGA, GEO, human protein atlas (HPA), and UALCAN databases. Survival and Cox regression analysis was performed to assess the prognostic value of NOP14 in CRC patients. Next, to evaluate the potential functions of NOP14, a protein-protein interaction (PPI) network was constructed and gene set enrichment analysis (GSEA) of differential expression genes (DEGs) associated with dysregulated NOP14 was performed. Finally, to investigate the immune response associated with NOP14 expression in CRC, we analyzed the correlations between immune cells infiltration and NOP14 expression level. Additionally, the correlations between immune molecule expression levels with NOP14 expression level were analyzed. RESULTS: High NOP14 mRNA expression was observed in CRC tissues based on the data from TCGA and GEO datasets. Similarly, high NOP14 protein levels were found in CRC tissues according to the immunohistochemical images from HPA. Interestingly, high NOP14 expression level was associated with an improved prognosis in CRC patients. Univariate and multivariate Cox regression analysis indicated that high NOP14 expression level was an independent protective factor for CRC patients. With the support of PPI network analysis, we found several risk genes interacted with NOP14. GSEA revealed that high NOP14 expression inhibited several signal pathways involved in tumor formation and development. Additionally, high NOP14 expression was positively associated with most kinds of immune cell infiltrations and the expression levels of some molecules related to immune activation. CONCLUSION: Altogether, these results indicated that high NOP14 expression leads to improved prognosis in CRC patients by inhibiting the signaling pathways involved in tumor growth and promoting the immune responses.

Diagnosis and treatment of diverticular hemorrhage in small intestine: A retrospective study.

BACKGROUND AND STUDY AIMS: Small intestine diverticula are the most common cause of gastrointestinal hemorrhage, but prompt diagnosis remains challenging. Thus, this study aimed to identify strategies for the diagnosis and treatment of diverticular hemorrhage. PATIENTS AND METHODS: Patients who presented with gastrointestinal tract bleeding to Guangzhou First People's Hospital between 2008 and 2014 were retrospectively examined. Gastrorrhagia and colonic hemorrhage were excluded based on the gastroscopy and colonoscopy findings, and the bleeding sites were in the small intestine. Data regarding patient characteristics, methods of diagnosis, treatment, and prognosis were collected. RESULTS: Eighty-five patients met the study criteria, and 45 patients were diagnosed with diverticular hemorrhage using double balloon enteroscopy, capsule endoscopy, computed tomography (CT), or digital subtraction angiography (DSA). Among these patients, 10 presented with massive bleeding and hemodynamic instability. All 45 patients underwent surgery and recovered with no complications, and all patients were followed-up for over 3 years, with no cases of recurrent hemorrhage. CONCLUSION: Diverticular hemorrhage is the most common cause of small intestine bleeding. Double balloon enteroscopy, capsule endoscopy, CT, and DSA are effective methods for diagnosing small intestine diverticular hemorrhage. Surgical resection of the involved region is necessary and may achieve complete cure.

Erythrocytes Are an Independent Protective Factor for Vascular Cognitive Impairment in Patients With Severe White Matter Hyperintensities.

Background and Purpose: Hemoglobin is one of the main proteins in erythrocytes. There are significant correlations between low hemoglobin and white matter hyperintensities (WMH) and cognitive impairment. This study explored whether erythrocytopenia has predictive value for vascular cognitive impairment (VCI) in patients with WMH. Method: We conducted a cross-sectional study of 302 patients, including 62 with cerebral small vessel disease and 240 with stroke. Basic demographic data and fasting blood were collected. First, all patients were divided into normal cognition (NC), mild VCI (mVCI), and severe VCI (sVCI) groups (subgroups later) based on cognitive behavior scores. Second, all patients were divided into mild WMH (mWMH) and severe WMH (sWMH) groups based on Fazekas scores. The differences in blood markers between different groups or subgroups with different cognitive levels were analyzed by univariate analysis. Then, binary logistic regression was used to analyze the diagnostic value of erythrocyte counts for VCI in the sWMH group, and ordinal logistic regression was used to analyze the predictive value of multiple variables for different cognitive levels. Results: Univariate analysis showed that erythrocytes, hemoglobin, high-sensitivity C-reactive protein, retinol binding protein and prealbumin were potential blood markers for different cognitive levels in sWMH patients. Among them, erythrocytopenia has good predictive value for the diagnosis of mVCI (AUC = 0.685, P = 0.008) or sVCI (AUC = 0.699, P = 0.003) in patients with sWMH. Multivariate joint analysis showed that erythrocytes were an independent protective factor reducing the occurrence of VCI in patients with sWMH (OR = 0.633, P = 0.045). Even after adjusting for age, there was still a significant difference (P = 0.047). Conclusion: Erythrocytes are an independent protective factor for VCI in patients with sWMH. Promoting hematopoietic function may have potential value for prevention of cognitive decline in patients with cerebrovascular disease.