Optimal time point for neutrophil-to-lymphocyte ratio to predict stroke-associated pneumonia.

PURPOSE: This study aimed at the population receiving thrombolytic therapy and to explore the optimal time point for neutrophil-to-lymphocyte ratio (NLR) in predicting stroke-associated pneumonia (SAP). METHODS: We assessed patients undergoing intravenous thrombolysis (IVT) for acute ischemic stroke. Blood parameters were sampled before thrombolysis (within 30 min after admission) and within 24-36 h after thrombolysis, respectively. The primary outcome measure was the occurrence of SAP. Multivariate logistic regression analysis was performed to analyze the association between admission blood parameters and the event of SAP. We also used receiver operating characteristic (ROC) curve analysis to assess the discriminative ability of blood parameters measured at different times in predicting SAP. RESULTS: Among the 388 patients, SAP occurred in 60 (15%) patients. Multivariate logistic regression analysis showed that NLR was significantly associated with SAP (NLR before IVT: aOR = 1.288; 95%CI = 1.123-1.476; p < 0.001; NLR after IVT: (aOR = 1.127, 95%CI = 1.017-1.249; p = 0.023). The ROC curve showed that the predictive ability of NLR after IVT was better than NLR before IVT, not only in predicting the occurrence of SAP but also in predicting short-term and long-term functional outcomes, hemorrhagic transformation, and 1-year mortality. CONCLUSION: Increased NLR measured within 24-36 h after IVT has a significant predictive effect on the occurrence of SAP and can be used to predict short-term and long-term poor functional outcomes, hemorrhagic transformation, and 1-year mortality.

Delineating the Role of Mitophagy Inducers for Alzheimer Disease Patients.

Alzheimer's disease (AD) is the most common cause of dementia in elderly that serves to be a formidable socio-economic and healthcare challenge in the 21st century. Mitochondrial dysfunction and impairment of mitochondrial-specific autophagy, namely mitophagy, have emerged as important components of the cellular processes contributing to the development of AD pathologies, namely amyloid-ß plaques (Aß) and neurofibrillary tangles (NFT). Here, we highlight the recent advances in the association between impaired mitophagy and AD, as well as delineate the potential underlying mechanisms. Furthermore, we conduct a systematic review the current status of mitophagy modulators and analyzed their relevant mechanisms, evaluating on their advantages, limitations and current applications in clinical trials for AD patients. Finally, we describe how deep learning may be a promising method to rapid and efficient discovery of mitophagy inducers as well as general guidance for the workflow of the process.

The Association Between Admission Anemia and Poststroke Depression.

ABSTRACT: Poststroke depression (PSD) is the most frequent and important neuropsychiatric problem afflicting these patients. Anemia is common in many of these individuals presenting with acute stroke. This study determined whether there is a relationship between anemia on hospital admission and PSD. Two hundred eighty-four acute stroke patients were included in the study. Among them, there were 88 PSD patients, whereas another 196 were non-PSD patients. Clinical depression symptoms were diagnosed according to DSM-4 (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) criteria and a HAMD-17 (the 17-item Hamilton Depression Scale) score ≥8 at 1 month after stroke. In the PSD patients, 27.3% of them presented with anemia, whereas only 12.8% of the non-PSD patients had this condition. There was a negative correlation between hemoglobin level and HAMD-17 score in all patients. A binary logistic regression analysis revealed that anemia was independently associated with PSD after adjustment for sex, National Institutes of Health Stroke Scale scores, mRS (modified Rankin Scale) scores, BI (Barthel Index) scores, RBC (red blood cell), and hematocrit. In conclusion, anemia at admission is associated with PSD seen in these patients 1 month later. Therefore, anemia is a possible predictor of PSD.

Individualized predictions of early isolated distal deep vein thrombosis in patients with acute ischemic stroke: a retrospective study.

BACKGROUND: Although isolated distal deep vein thrombosis (IDDVT) is a clinical complication for acute ischemic stroke (AIS) patients, very few clinicians value it and few methods can predict early IDDVT. This study aimed to establish and validate an individualized predictive nomogram for the risk of early IDDVT in AIS patients. METHODS: This study enrolled 647 consecutive AIS patients who were randomly divided into a training cohort (n = 431) and a validation cohort (n = 216). Based on logistic analyses in training cohort, a nomogram was constructed to predict early IDDVT. The nomogram was then validated using area under the receiver operating characteristic curve (AUROC) and calibration plots. RESULTS: The multivariate logistic regression analysis revealed that age, gender, lower limb paralysis, current pneumonia, atrial fibrillation and malignant tumor were independent risk factors of early IDDVT; these variables were integrated to construct the nomogram. Calibration plots revealed acceptable agreement between the predicted and actual IDDVT probabilities in both the training and validation cohorts. The nomogram had AUROC values of 0.767 (95% CI: 0.742-0.806) and 0.820 (95% CI: 0.762-0.869) in the training and validation cohorts, respectively. Additionally, in the validation cohort, the AUROC of the nomogram was higher than those of the other scores for predicting IDDVT. CONCLUSIONS: The present nomogram provides clinicians with a novel and easy-to-use tool for the prediction of the individualized risk of IDDVT in the early stages of AIS, which would be helpful to initiate imaging examination and interventions timely.

Hemostasis functions are associated with hemorrhagic transformation in non-atrial fibrillation patients: a case-control study.

BACKGROUND: Hemorrhagic transformation (HT) is a serious neurological complication of acute ischemic stroke (AIS) after revascularization. The majority of AIS patients do not have atrial fibrillation (AF) which could also develop into HT. In this study, we aimed to explore whether hemostasis parameters are risk factors of HT in non-AF patients. METHODS: We consecutively enrolled 285 AIS patients with HT. Meanwhile, age- and sex-matched 285 AIS patients without HT were included. The diagnosis of HT was determined by brain CT or MRI during hospitalization. All patients were divided into two subgroups based on the presence of AF and explore the differences between the two subgroups. Blood samples were obtained within 24 h of admission, and all patients were evenly classified into three tertiles according to platelet counts (PLT) levels. RESULTS: In this study, we found the first PLT tertile (OR = 3.509, 95%CI = 1.268-9.711, P = 0.016) was independently associated with HT in non-AF patients, taking the third tertile as a reference. Meanwhile, we also found mean platelet volume (MPV) (OR = 0.605, 95%CI = 0.455-0.805, P = 0.001) and fibrinogen (FIB) (OR = 1.928, 95%CI = 1.346-2.760, P < 0.001) were significantly associated with HT in non-AF patients. But in AF patients, hemostasis parameters showed no significant difference. Meanwhile, we found the MPV (OR = 1.314, 95%CI = 1.032-1.675, P = 0.027) and FIB (OR = 1.298, 95%CI = 1.047-1.610, P = 0.018) were significantly associated with long-term outcomes in non-AF HT patients. CONCLUSIONS: Low PLT, low MPV, and high FIB levels were independently associated with HT in non-AF patients. Additionally, MPV and FIB levels were significantly associated with unfavorable long-term outcomes in non-AF HT patients. Our study showed that hemostasis functions at admission may be beneficial for clinicians to recognize patients with a high risk of HT at an early stage and improve unfavorable long-term outcomes in non-AF patients.

Dysbiosis of lower respiratory tract microbiome are associated with inflammation and microbial function variety.

BACKGROUND: Lower respiratory tract (LRT) microbiome has been reported to associate with pulmonary diseases. Unregulated inflammation is an underlying cause of variable lung diseases. The lung microbiome may play an important role in the smoking-induced inflammatory lung diseases. What's more, the function of microbiome may be more important for understanding how microbes interact with host. Our study aims to explore the effects of smoking on the lower respiratory tract microbiome, the association between variation of lower respiratory tract microbiome and inflammation and whether smoking exposure changes the function of lower respiratory tract microbime. METHODS: Forty male mice were randomly divided into smoking group and non-smoking group, and the smoking group was exposed to cigarette smoke for 2 h per day for 90 days. After experiment, the blood samples were collected to measure the concentration of interleukin-6 (IL-6) and C reactive protein (CRP) by ELISA. Lung tissue samples were used to detect the community and diversity of lower respiratory tract microbiome through 16S rRNA gene quantification and sequencing technology. ANOSIM and STAMP were performed to analyze the differences of the microbial community structure between smoking group and non-smoking group. SPSS 24.0 software was used to analyze the correlations between microbiome and inflammation mediators through scatter plots and Spearman correlation coefficient. Microbial metabolic function was predicted by PICRUSt based on the 16 s rRNA gene quantification and sequencing results. PATRIC database was searched for the potential pathogenic bacteria in lower respiratory tract. RESULTS: Our results suggested that smoking had markedly effects on the microbiota structure of lower respiratory tract based on Bray-Curtis distance (R2 = 0.084, p = 0.005) and on unweighted uniFrac distance (R2 = 0.131, p = 0.002). Smoking mainly affected the abundance of microbiome which belong to Proteobacteria phyla and Firmicutes phyla. Moreover, our results also found that smoking increased the abundance of Acinetobacter, Bacillus and Staphylococcus, which were defined as pathogenic bacteria. Inflammatory mediators were observed to associate with certain microbiome at every level. Most of microbiome which were associated with inflammation belonged to Proteobacteria phyla or Firmicutes phyla. Moreover, we found that the decreased microbiome in smoking group, including Oceanospirillales, Desulfuromonadales, Nesterenkonia, and Lactobacillaceae, all were negatively correlated with IL-6 or CRP. Based on the level of inflammation, the abundance of microbiome differs. At genus level, Lactobacillus, Pelagibacterium, Geobacter and Zoogloea were significantly higher in smoking group with lower IL-6 concentration. The abundance of microbiome was not observed any statistical difference in subgroups with different weight. Three dominant genus, defined as pathogen, were found higher in the smoking group. The microbial functional prediction analysis revealed that ABC-type transport systems, transcription factors, amino acide transport and metabolism, arginine and proline metabolism et al. were distinctively decreased in smoking group, while the proportions of replication, recombination and repair, ribosome, DNA repair and recombination proteins were increased in smoking group (q < 0.05). CONCLUSIONS: Members of Proteobacteria phyla and Firmicutes phyla played an important role in the microbial community composition and keeping a relatively balanced homeostasis. Microbiome dysbiosis might break the balance of immune system to drive lung inflammation. There might exist potential probiotics in lower respiratory tract, such as Lactobacillaceae. The altered function of Lower respiratory tract microbiome under smoking exposure may affect the physiological homeostasis of host.

Striatal overexpression of ß-arrestin2 counteracts L-dopa-induced dyskinesia in 6-hydroxydopamine lesioned Parkinson's disease rats.

Prolonged administration of Levodopa (L-dopa) therapy can generate L-dopa-induced dyskinesia (LID). Accumulating evidence indicates that hyper-activation of the dopamine D1 receptor (D1R) and the cAMP signaling cascade in the medium spiny neurons (MSNs) of the striatum are involved in LID. Previous studies have shown that striatal ß-arrestin2 overexpression significantly reduces LID severity and have indicated that ß-arrestin2 may play a causal role in the dyskinesia sensitization process. L-dopa-induced changes in the expression of signaling molecules and other proteins in the striatum were examined immunohistochemically and by western blot. A rAAV (recombinant adeno-associated virus) vector was used to overexpress and ablate ß-arrestin2. We found that striatal overexpression of AAV-mediated ß-arrestin2 produced less severe AIMs (abnormal involuntary movements) in response to L-dopa, whereas selective deletion of ß-arrestin2 in the striatal neurons dramatically enhanced the severity of dyskinesia induced by L-dopa. Furthermore, no significant improvements in motor behavior (FFT: forelimb functional test) were seen with the inhibition or overexpression of ß-arrestin2. Finally, overexpression of ß-arrestin2 diminished L-dopa-induced D1R and phosphor-DARPP32/ERK levels. Viral deletion of ß-arrestin2 markedly enhanced the key biochemical markers in the direct pathway. We found that increased availability of ß-arrestin2 ameliorated dyskinesia severity with no influence on the anti-Parkinsonian action of L-dopa, suggesting a promising approach for controlling LID in Parkinson's disease. In addition, overexpression of ß-Arrestin2 prevented the development of LID by inhibiting G protein-dependent D1R and phosphor-DARPP32/ERK signaling in dyskinetic rats.

Effects of smoking on the lower respiratory tract microbiome in mice.

BACKGROUND: Recent studies break with traditional opinion that the lower respiratory tract is sterile, and increasingly focus on the lung microbiome and disease. Smoking, as an important etiology of inflammatory lung disease, was considered as a factor influencing lung microbiome variations in our study, and we aimed to study the effect of smoking on inflammation and microbial diversity and community. METHODS: Forty male mice were selected and randomly divided into a smoking and a non-smoking group. Mice in the smoking group were exposed to smoke smog for 2 h/day for 90 days. Blood and lung tissues were obtained after the experiment, and ELISA was used to measure interleukin-6 and C reactive protein concentrations. 16S rRNA gene quantification and sequencing technology were used to compare microbial diversity and community between the two groups. SAS 9.1 and R software were used to analyze the data. RESULTS: Thirty-six mice survived, and the weight of the smoking group increased more slowly than that of the non-smoking group. Denser inflammation and congestion were observed in the lungs of the smoking mice compared with the non-smoking group Higher microbial diversity was observed in the smoking group, and Enterobacter, Acidimicrobiales_norank, and Caulobacteraceae_Unclassified genus were significantly more abundant in the non-smoking group (P < 0.001). CONCLUSIONS: Smoking altered microbial diversities and communities in the lower respiratory tract of mice. Microbial variation should be considered in future studies focusing on smoking-induced inflammatory disease.

Role of sLOX-1 in intracranial artery stenosis and in predicting long-term prognosis of acute ischemic stroke.

Objective: The role of sLOX-1 in acute ischemic stroke still remains unclear. This study aims to demonstrate the value of sLOX-1 in evaluating degrees of intracranial artery stenosis and to predict prognosis in stroke. Methods: Two hundred and seventy-two patients were included in this study and basic data were collected within 72 hr on admission. We assessed the association between sLOX-1 levels and stroke conditions in one-year duration. After adjusting for potential confounders, regression analyses were performed. Results: We found that sLOX-1 levels were increased significantly in severe patients compared to the mild stroke group (p = .011). After adjusting confounders, sLOX-1 was associated with a poor functional outcome in patients with an adjusted OR of 2. 946 (95% CI, 1.788-4.856, p < .001). There was also positive correlation between sLOX-1 levels and the degrees of intracranial artery stenosis in the different groups (p = .029). Conclusions: Our study demonstrated that sLOX-1 levels could be used to evaluate the severity of stroke and the degrees of intracranial artery stenosis. Furthermore, sLOX-1 could be exploited to predict the long-term functional outcome of stroke.