Identifying potential causal effects of Parkinson's disease: A polygenic risk score-based phenome-wide association and mendelian randomization study in UK Biobank.

There is considerable uncertainty regarding the associations between various risk factors and Parkinson's Disease (PD). This study systematically screened and validated a wide range of potential PD risk factors from 502,364 participants in the UK Biobank. Baseline data for 1851 factors across 11 categories were analyzed through a phenome-wide association study (PheWAS). Polygenic risk scores (PRS) for PD were used to diagnose Parkinson's Disease and identify factors associated with PD diagnosis through PheWAS. Two-sample Mendelian randomization (MR) analysis was employed to assess causal relationships. PheWAS results revealed 267 risk factors significantly associated with PD-PRS among the 1851 factors, and of these, 27 factors showed causal evidence from MR analysis. Compelling evidence suggests that fluid intelligence score, age at first sexual intercourse, cereal intake, dried fruit intake, and average total household income before tax have emerged as newly identified risk factors for PD. Conversely, maternal smoking around birth, playing computer games, salt added to food, and time spent watching television have been identified as novel protective factors against PD. The integration of phenotypic and genomic data may help to identify risk factors and prevention targets for PD.

Air pollution, greenspace exposure and risk of Parkinson's disease: a prospective study of 441,462 participants.

BACKGROUND: The current understandings of the relationship between air pollution (AP), greenspace exposure and Parkinson's Disease (PD) remain inconclusive. METHODS: We engaged 441,462 participants from the UK Biobank who were not diagnosed with PD. Utilizing Cox proportional hazard regression model, relationships between AP [nitrogen dioxide (NO2), and nitrogen oxides (NOX), particulate matter < 2.5 µm in aerodynamic diameter(PM2.5), coarse particulate matter between 2.5 µm and 10 µm in aerodynamic diameter(PM2.5-10), particulate matter < 10 µm in aerodynamic diameter(PM10)], greenspace exposure, and PD risk were determined independently. Our analyses comprised three models, adjusted for covariates, and affirmed through six sensitivity analyses to bolster the robustness of our findings. Moreover, mediation analysis was deployed to discern the mediating effect of AP between greenspaces and PD. RESULTS: During a median follow-up of 12.23 years (5,574,293 person-years), there were 3,293 PD events. Each interquartile (IQR) increment in NO2 and PM10 concentrations were associated with 10% and 8% increase in PD onset risk, while the increases in NOX, PM2.5 and PM2.5-10 were not associated with PD risk. Additionally, greenspace may safeguard by reducing NO2 and PM10 levels, with the effect mediated by NO2 and PM10 in greenspace-PD relationship. CONCLUSION: Our findings indicate that an IQR increase in ambient NO2 and PM10 concentrations was associated with risk of PD development, while other pollutants (NOX, PM2.5 and PM2.5-10) were not associated with PD risk. Firstly, we find that augmented exposure to greenspace was associated with the lower PD risk by reducing NO2 and PM10 levels.

Atrial Cardiomyopathy Predicts the Functional Outcome and Mortality in Stroke Patients.

AIM: Atrial cardiomyopathy (ACM) is characterized by atrial dysfunction. This study aims to assess the prognostic significance of ACM in patients with noncardioembolic stroke (NCS). METHODS: Patients with NCS within seven days of onset were prospectively enrolled between January 2019 and December 2020. ACM was defined as either an N-terminal pro-brain natriuretic peptide (NT-pro BNP) ＞250 pg/ml or a P-terminal force in precordial lead V1 (PTFV1) ≥ 5000µV·ms. A poor functional outcome was determined as a score of 3-6 on the modified Rankin Scale (mRS) within a 2-year follow-up period. Logistic regression and Cox regression analyses were employed to examine the relationship between ACM and the long-term prognosis of patients with NCS. RESULTS: A total of 1,346 patients were enrolled, of whom 299 (22.2%) patients were diagnosed with ACM. A total of 207(15.4%) patients experienced a poor functional outcome, and 58 (4.3%) patients died. A multivariate logistic regression analysis indicated that ACM was significantly associated with a poor functional outcome in NCS patients [adjusted odds ratio (aOR): 2.01; 95% confidence interval (CI): 1.42-2.87; p＜0.001]. Additionally, a multivariate Cox regression analysis showed that an NT-pro BNP ＞250 pg/ml was significantly associated with an increased risk of all-cause mortality [adjusted hazard ratio (aHR), 2.51; 95% CI: 1.42-4.43; p=0.001]. CONCLUSIONS: ACM may serve as a novel predictor of a poor long-term functional outcome in patients with NCS. Elevated NT-pro BNP levels (＞250 pg/ml) were found to be associated with a higher risk of all-cause mortality. These findings warrant further validation in multicenter studies.

Shared Genetic Architecture between Parkinson's Disease and Brain Structural Phenotypes.

BACKGROUND: Patients with Parkinson's disease (PD) have consistently demonstrated brain structure abnormalities, indicating the presence of shared etiological and pathological processes between PD and brain structures; however, the genetic relationship remains poorly understood. OBJECTIVE: The aim of this study was to investigate the extent of shared genetic architecture between PD and brain structural phenotypes (BSPs) and to identify shared genomic loci. METHODS: We used the summary statistics from genome-wide association studies to conduct MiXeR and conditional/conjunctional false discovery rate analyses to investigate the shared genetic signatures between PD and BSPs. Subsequent expression quantitative trait loci mapping in the human brain and enrichment analyses were also performed. RESULTS: MiXeR analysis identified genetic overlap between PD and various BSPs, including total cortical surface area, average cortical thickness, and specific brain volumetric structures. Further analysis using conditional false discovery rate (FDR) identified 21 novel PD risk loci on associations with BSPs at conditional FDR < 0.01, and the conjunctional FDR analysis demonstrated that PD shared several genomic loci with certain BSPs at conjunctional FDR < 0.05. Among the shared loci, 16 credible mapped genes showed high expression in the brain tissues and were primarily associated with immune function-related biological processes. CONCLUSIONS: We confirmed the polygenic overlap with mixed directions of allelic effects between PD and BSPs and identified multiple shared genomic loci and risk genes, which are likely related to immune-related biological processes. These findings provide insight into the complex genetic architecture associated with PD. © 2023 International Parkinson and Movement Disorder Society.

Erratum: SNHG3 promotes migration, invasion, and epithelial-mesenchymal transition of breast cancer cells through the miR-186-5p/ZEB1 axis.

[This corrects the article on p. 585 in vol. 13, PMID: 33594311.].

Identifying causal genes for migraine by integrating the proteome and transcriptome.

BACKGROUND: While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. METHODS: We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. RESULTS: We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. CONCLUSIONS: Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.

ABCD2 score has equivalent stroke risk prediction for anterior circulation TIA and posterior circulation TIA.

Transient ischemic attack (TIA) was clinically divided into anterior circulation (AC) or posterior circulation (PC). Previous study reported that ABCD2 score could predict the stroke risk after AC-TIA but might have limitation for PC-TIA. We aimed to classify TIA depending on neuroimaging and assess the value of ABCD2 score for predicting stroke risk in different territories. Research data was from TIA database of the First Affiliated Hospital of Zhengzhou University. TIA patients with acute infarction on diffuse weighted imaging [that is, transient symptoms with infarction (TSI)] were divided into anterior and posterior circulation groups according to the location of infarction. The outcome was recurrent stroke within 7 and 90 days. The predictive power of ABCD2 score was determined using area under receiver operator characteristic curve (AUC) analyses. Overall, 382 AC-TSI and 112 PC-TSI patients were included. There were 38 (9.9%) AC-TSI patients and 11(9.8%) PC-TSI patients who had recurrent stroke at 7 days, and 66 (17.3%) AC-TSI patients and 19 (17.0%) PC-TSI patients who had recurrent stroke within 90 days. At 7 days, the AUC for ABCD2 score was 0.637 (95% confidence interval CI 0.554-0.720) in anterior circulation and 0.683 (95% CI 0.522-0.845) in posterior circulation. The C statistics for ABCD2 score in the two groups were not statistically significant (Z = - 0.499; P = 0.62). Similar result was found when the outcome time-point was set at 90 days. ABCD2 score could predict the short-term risk of recurrent stroke after AC-TSI and PC-TSI, and had similar predictive abilities for AC-TSI and PC-TSI.

[Protective effects of estrogen modified hBMSC on HG-induced injury of vascular endothelial cells].

Objective: To investigate the protective effects and potential mechanisms of estrogen modified human bone marrow mesenchymal stem cells (hBMSC) on high glucose (HG)-induced injury of vascular endothelial cells. Methods: hBMSCs were cultured under 30 mmol/l glucose to establish a high glucose model (HG), and then were divided into four groups as following: HG group (HG control, without any treatment), HG+E2 group (cells were treated with 20 µmol/L estrogen), HG+E2+ Triciribine group (cells were pretreated with 5 µmol/L protein kinase B (PKB/Akt) inhibitor for 45 min, and then modified by 20 µmol/L estrogen), and NG group (cells were cultured under normal conditions). After 12 h treatment, the cell viability of hBMSC was detected by CCK8 assay, and the contents of NO, VEGF and IL8 in the supernatant of cultured medium in each group were detected by nitrate reductase and ELISA assay (n=6). After 48 h, the expression levels of endothelial nitric oxide synthase (eNOS) and phosphorylated eNOS (p-eNOS) were detected by Western blot (n=3). In addition, the cell supernatant of each group was further extracted as conditioned medium to culture HUVECs, and the cells were subsequently divided into HG-CM group (HUVECs were treated with HG group's conditioned medium), HG+E2-CM group (HUVECs were treated with HG+E2 group's conditioned medium), HG+E2+Triciribine-CM group (HUVECs were treated with HG+E2+ Triciribine group's conditioned medium) and HG-H group (HUVEC were cultured under HG condition, which were treated with final concentration 30 mmol/l glucose). The cell viability of HUVECs in each group was detected by CCK8 assay after 12 h cultured (n=6). After 24 h treatment, the apoptosis rate of HUVECs in each group was detected by flow cytometry (n=3). Furthermore, the migration rate of HUVECs in each group was observed by wound healing assay after 48 h cultured (n=3). Results: Compared with NG group, the cell viability and eNOS protein phosphorylation level of hBMSC in HG group and the contents of NO, VEGF and IL-8 in the supernatant of cultured medium were decreased (P<0.05). Compared with HG group, the cell viability and eNOS protein phosphorylation level in HG+E2 group and the contents of NO, VEGF and IL-8 in cultured medium supernatant were increased significantly (P<0.05), whereas pre-treatment of hBMSC cells with a Akt inhibitor Triciribine, the above indexes showed reverse changes (P<0.05). Furthermore, compared with HG-CM group, the cell viability and migration ability (P<0.05) of HUVECs in HG+E2-CM group were increased significantly (P<0.05), and the proportion of apoptosis was decreased (P<0.05). While compared with HG+E2-CM group, the cell viability and migration ability of HUVECs in HG+E2+Triciribine-CM group were decreased (P<0.05), and the proportion of apoptosis was increased (P<0.05). Conclusion: Estrogen may promote the secretion of NO, VEGF and IL-8 by activating the Akt/eNOS signaling pathway of hBMSC cells, increase the cell viability and migration ability of HUVECs and inhibit the occurrence of apoptosis, play a protective role against the injury of HUVECs induced by HG condition.

Transcriptomic Analysis Reveals the Correlation between End-of-Day Far Red Light and Chilling Stress in Setaria viridis.

Low temperature and end-of-day far-red (EOD-FR) light signaling are two key factors limiting plant production and geographical location worldwide. However, the transcriptional dynamics of EOD-FR light conditions during chilling stress remain poorly understood. Here, we performed a comparative RNA-Seq-based approach to identify differentially expressed genes (DEGs) related to EOD-FR and chilling stress in Setaria viridis. A total of 7911, 324, and 13431 DEGs that responded to low temperature, EOD-FR and these two stresses were detected, respectively. Further DEGs analysis revealed that EOD-FR may enhance cold tolerance in plants by regulating the expression of genes related to cold tolerance. The result of weighted gene coexpression network analysis (WGCNA) using 13431 nonredundant DEGs exhibited 15 different gene network modules. Interestingly, a CO-like transcription factor named BBX2 was highly expressed under EOD-FR or chilling conditions. Furthermore, we could detect more expression levels when EOD-FR and chilling stress co-existed. Our dataset provides a valuable resource for the regulatory network involved in EOD-FR signaling and chilling tolerance in C4 plants.

Characterization of regulatory modules controlling leaf angle in maize.

Leaf angle is an important agronomic trait determining maize (Zea mays) planting density and light penetration into the canopy and contributes to the yield gain in modern maize hybrids. However, little is known about the molecular mechanisms underlying leaf angle beyond the ZmLG1 (liguleless1) and ZmLG2 (Liguleless2) genes. In this study, we found that the transcription factor (TF) ZmBEH1 (BZR1/BES1 homolog gene 1) is targeted by ZmLG2 and regulates leaf angle formation by influencing sclerenchyma cell layers on the adaxial side. ZmBEH1 interacted with the TF ZmBZR1 (Brassinazole Resistant 1), whose gene expression was also directly activated by ZmLG2. Both ZmBEH1 and ZmBZR1 are bound to the promoter of ZmSCL28 (SCARECROW-LIKE 28), a third TF that influences leaf angle. Our study demonstrates regulatory modules controlling leaf angle and provides gene editing targets for creating optimal maize architecture suitable for dense planting.

A Nomogram That Includes Neutrophils and High-Density Lipoprotein Cholesterol Can Predict the Prognosis of Acute Ischaemic Stroke.

Lipids are implicated in inflammatory responses affecting acute ischaemic stroke prognosis. Therefore, we aimed to develop a predictive model that considers neutrophils and high-density lipoprotein cholesterol to predict its prognosis. This prospective study enrolled patients with acute ischaemic stroke within 24 h of onset between January 2015 and December 2017. The main outcome was a modified Rankin Scale score ≥3 at the 90th day of follow-up. Patients were divided into training and testing sets. The training set was divided into four states according to the median of neutrophils and high-density lipoprotein cholesterol levels in all patients. Through binary logistic regression analysis, the relationship between factors and prognosis was determined. A nomogram based on the results was developed; its predictive value was evaluated through internal and external validations. Altogether, 1,090 patients were enrolled with 872 (80%) and 218 (20%) in the training and testing sets, respectively. In the training set, the major outcomes occurred in 24 (10.4%), 24 (11.6%), 37 (17.2%), and 49 (22.3%) in states 1-4, respectively (P = 0.002). Validation of calibration and decision curve analyses showed that the nomogram showed better performance. The internal and external testing set receiver operating characteristics verified the predictive value [area under the curve = 0.794 (0.753-0.834), P < 0.001, and area under the curve = 0.973 (0.954-0.992), P < 0.001, respectively]. A nomogram that includes neutrophils and high-density lipoprotein cholesterol can predict the prognosis of acute ischaemic stroke, thus providing us with an effective visualization tool.

Validation of CSR model to predict stroke risk after transient ischemic attack.

It is essential to identify high risk transient ischemic attack (TIA) patients. The previous study reported that the CSR (comprehensive stroke recurrence) model, a neuroimaging model, had a high predictive ability of recurrent stroke. The aims of this study were to validate the predictive value of CSR model in TIA patients and compare the predictive ability with ABCD3-I score. Data were analyzed from the prospective hospital-based database of patients with TIA which defined by the World Health Organization time-based criteria. The predictive outcome was stroke occurrence at 90 days. The receiver-operating characteristic (ROC) curves were plotted and the C statistics were calculated as a measure of predictive ability. Among 1186 eligible patients, the mean age was 57.28 ± 12.17 years, and 474 (40.0%) patients had positive diffusion-weighted imaging (DWI). There were 118 (9.9%) patients who had stroke within 90 days. In 1186 TIA patients, The C statistic of CSR model (0.754; 95% confidence interval [CI] 0.729-0.778) was similar with that of ABCD3-I score (0.717; 95% CI 0.691-0.743; Z = 1.400; P = 0.1616). In 474 TIA patients with positive DWI, C statistic of CSR model (0.725; 95% CI 0.683-0.765) was statistically higher than that of ABCD3-I score (0.626; 95% CI 0.581-0.670; Z = 2.294; P = 0.0245). The CSR model had good predictive value for assessing stroke risk after TIA, and it had a higher predictive value than ABCD3-I score for assessing stroke risk for TIA patients with positive DWI.

Interpretable CNN for ischemic stroke subtype classification with active model adaptation.

BACKGROUND: TOAST subtype classification is important for diagnosis and research of ischemic stroke. Limited by experience of neurologist and time-consuming manual adjudication, it is a big challenge to finish TOAST classification effectively. We propose a novel active deep learning architecture to classify TOAST. METHODS: To simulate the diagnosis process of neurologists, we drop the valueless features by XGB algorithm and rank the remaining ones. Utilizing active learning framework, we propose a novel causal CNN, in which it combines with a mixed active selection criterion to optimize the uncertainty of samples adaptively. Meanwhile, KL-focal loss derived from the enhancement of Focal loss by KL regularization is introduced to accelerate the iterative fine-tuning of the model. RESULTS: To evaluate the proposed method, we construct a dataset which consists of totally 2310 patients. In a series of sequential experiments, we verify the effectiveness of each contribution by different evaluation metrics. Experimental results show that the proposed method achieves competitive results on each evaluation metric. In this task, the improvement of AUC is the most obvious, reaching 77.4. CONCLUSIONS: We construct a backbone causal CNN to simulate the neurologist process of that could enhance the internal interpretability. The research on clinical data also indicates the potential application value of this model in stroke medicine. Future work we would consider various data types and more comprehensive patient types to achieve fully automated subtype classification.

Chromatin and regulatory differentiation between bundle sheath and mesophyll cells in maize.

C4 plants partition photosynthesis enzymes between the bundle sheath (BS) and the mesophyll (M) cells for the better delivery of CO2 to RuBisCO and to reduce photorespiration. To better understand how C4 photosynthesis is regulated at the transcriptional level, we performed RNA-seq, ATAC-seq, ChIP-seq and Bisulfite-seq (BS-seq) on BS and M cells isolated from maize leaves. By integrating differentially expressed genes with chromatin features, we found that chromatin accessibility coordinates with epigenetic features, especially H3K27me3 modification and CHH methylation, to regulate cell type-preferentially enriched gene expression. Not only the chromatin-accessible regions (ACRs) proximal to the genes (pACRs) but also the distal ACRs (dACRs) are determinants of cell type-preferentially enriched expression. We further identified cell type-preferentially enriched motifs, e.g. AAAG for BS cells and TGACC/T for M cells, and determined their corresponding transcription factors: DOFs and WRKYs. The complex interaction between cis and trans factors in the preferential expression of C4 genes was also observed. Interestingly, cell type-preferentially enriched gene expression can be fine-tuned by the coordination of multiple chromatin features. Such coordination may be critical in ensuring the cell type-specific function of key C4 genes. Based on the observed cell type-preferentially enriched expression pattern and coordinated chromatin features, we predicted a set of functionally unknown genes, e.g. Zm00001d042050 and Zm00001d040659, to be potential key C4 genes. Our findings provide deep insight into the architectures associated with C4 gene expression and could serve as a valuable resource to further identify the regulatory mechanisms present in C4 species.

Interpretability Analysis of One-Year Mortality Prediction for Stroke Patients Based on Deep Neural Network.

Clinically, physicians collect the benchmark medical data to establish archives for a stroke patient and then add the follow up data regularly. It has great significance on prognosis prediction for stroke patients. In this paper, we present an interpretable deep learning model to predict the one-year mortality risk on stroke. We design sub-modules to reconstruct features from original clinical data that highlight the dissimilarity and temporality of different variables. The model consists of Bidirectional Long Short-Term Memory (Bi-LSTM), in which a novel correlation attention module is proposed that takes the correlation of variables into consideration. In experiments, datasets are collected clinically from the department of neurology in a local AAA hospital. It consists of 2,275 stroke patients hospitalized in the department of neurology from 2014 to 2016. Our model achieves a precision of 0.9414, a recall of 0.9502 and an F1-score of 0.9415. In addition, we provide the analysis of the interpretability by visualizations with reference to clinical professional guidelines.

Nonfocal Symptoms in Patients with Transient Ischemic Attack and Association with Stroke Risk.

BACKGROUND AND OBJECTIVE: Patients with transient ischemic attack（TIA）occasionally showed nonfocal symptoms, such as decreased consciousness, amnesia and non-rotatory dizziness. This study intended to evaluate the effect of nonfocal symptoms on the prognosis of patients with TIA. METHODS: Data from the prospective hospital-based TIA database of the First Affiliated Hospital of Zhengzhou University were analyzed. The predictive outcome was stroke occurrence at 1 year. Cumulative risks of stroke in patients with and without nonfocal symptoms were estimated with Kaplan-Meier models. RESULTS: We studied 1384 patients with TIA (842 men; mean age, 56±13 years), including 450 (32.5%) with nonfocal symptoms. In the first year after TIA, stroke occurred in 168（12.1%） patients. There was no difference in the risk of stroke between patients with both focal and nonfocal symptoms and patients with focal symptoms alone (11.8% vs 12.4%, log-rank; P=0.691). CONCLUSIONS: The occurrence of nonfocal symptoms did not increase the risk of stroke at one-year follow-up compared to the occurrence of focal symptoms alone.

Atherogenic Index of Plasma Predicts Outcomes in Acute Ischemic Stroke.

Aim: The atherogenic index of plasma (AIP) was significantly related to adverse outcomes in patients with cardiovascular disease. Our aim was to investigate the association between AIP and adverse outcomes in acute ischemic stroke. Methods: Patients with acute ischemic stroke (AIS) admitted between 2015 and 2018 were prospectively enrolled in this study. Functional outcomes were evaluated by the modified Rankin Scale (mRS). Poor outcomes were defined as mRS 3-6. The relationship of AIP with the risk of outcomes was analyzed by multivariate logistic regression models. Results: A total of 1,463 patients with AIS within 24 h of symptom onset were enrolled. The poor outcome group had a significantly higher level of AIP [0.09 (-0.10 to 0.27) vs. 0.04 (-0.09 to 0.18), p < 0.001] compared with the good outcome group. Multivariable logistic regression analysis showed that higher AIP was associated with poor outcomes in all the stroke patients (OR 1.84, 95% CI, 1.23-2.53, p = 0.007), which was more evident in patients with large-artery atherosclerosis subtype (OR 1.90, 95% CI, 1.53-2.62, p = 0.002), but not in the other subtypes. Receiver operating curve (ROC) analysis revealed that the best predictive cutoff value of AIP was 0.112, with a sensitivity of 70.8% and a specificity of 59.2%, and the area under the ROC curves for AIP was 0.685. Conclusion: AIP may be an important and independent predictor of the outcome of dysfunction in patients with AIS, especially the stroke subtype of large-artery atherosclerosis.

Prognostic nutritional index predicts clinical outcomes in patients with cerebral venous sinus thrombosis.

BACKGROUND: Lower prognostic nutritional index (PNI) is related to the poor prognosis of cardiovascular diseases. However, little is known about PNI and its relationship with the prognosis of cerebral venous sinus thrombosis (CVST). METHODS: CVST patients were retrospectively identified from January 2013 till June 2019. Patients in the acute / subacute phase were selected as subjects. Poor prognosis was defined as a modified Rankin Scale (mRS) of 3-6. Multivariate logistic regression analysis was used to confirm if lower PNI was associated with a poor prognosis. RESULTS: A total of 297 subjects with follow-up data were enrolled. Thirty-three (11.1%) had a poor outcome. Multivariate logistic regression analysis suggested that PNI was an important predictive factor of poor outcome in acute/subacute CVST (odds ratio, 0.903; 95% CI, 0.833-0.978; P = 0.012). The optimal cut-off value for predicting the poor prognosis of PNI was 44.2. Kaplan-Meier analysis and log-rank test suggested that the lower the PNI value, the higher the mortality rate (P < 0.001). In addition, the nomogram that was set up showed that lower PNI was an index of poor prognosis. The c-index for acute/subacute patients with CVST was 0.872. CONCLUSION: Lower PNI is correlated with a higher risk of adverse clinical outcomes in patients with acute/subacute CVST.

PPR647 Protein Is Required for Chloroplast RNA Editing, Splicing and Chloroplast Development in Maize.

Chloroplasts play an essential role in plant growth and development. Any factors affecting chloroplast development will lead to abnormal plant growth. Here, we characterized a new maize mutant, albino seedling mutant 81647 (as-81647), which exhibits an entirely albino phenotype in leaves and eventually died before the three-leaf stage. Transmission electron microscopy (TEM) demonstrated that the chloroplast thylakoid membrane was impaired and the granum lamellae significantly decreased in as-81647. Map-based cloning and transgenic analysis confirmed that PPR647 encodes a new chloroplast protein consisting of 11 pentratricopeptide repeat domains. Quantitative real-time PCR (qRT-PCR) assays and transcriptome analysis (RNA-seq) showed that the PPR647 mutation significantly disrupted the expression of PEP-dependent plastid genes. In addition, RNA splicing and RNA editing of multiple chloroplast genes showed severe defects in as-81647. These results indicated that PPR647 is crucial for RNA editing, RNA splicing of chloroplast genes, and plays an essential role in chloroplast development.