BACKGROUND Hemorrhagic transformation (HT) is a common complication of acute ischemic stroke (AIS), and inflammation has been found to play an important role in the occurrence of HT. We aimed to investigate the impact of lymphocyte-to-monocyte ratio (LMR), a maker of inflammatory status, on HT in patients with AIS. METHODS Consecutive AIS patients within 7 days from stroke onset were enrolled between January 2016 and October 2017. LMR was calculated according to lymphocyte and monocyte counts obtained within 24 h on admission. Patients were categorized into three groups according to LMR tertiles. HT was detected by follow-up computed tomography (CT) or magnetic resonance imaging (MRI) during hospitalization. The multivariate logistic analysis was used to evaluate the independent relationship between LMR and HT. RESULTS A total of 1005 patients were finally included. HT was observed in 99 (9.9%) patients, with 51 (5.1%) hemorrhagic infarction (HI) and 48 (4.8%) parenchymal hematoma (PH). After adjustment for potential confounders, the odds ratio (OR) of HT was 0.523 (95% confidence interval [CI] 0.293-0.936, P = 0.029) for the highest LMR tertile compared with the lowest tertile. Multiple-adjusted spline regression model showed a nonlinear approximately L-shaped relationship between LMR levels and HT (P for nonlinear trend = 0.030). There was no significant association of baseline LMR with PH (OR 0.562, 95% CI 0.249-1.268, P = 0.165). CONCLUSION Lower LMR was independently related to higher risk of HT in patients with AIS. Admission LMR may be used as one of the predictors for HT. Further prospective multicenter studies are needed to validate our findings.Several neurophysiological abnormalities have been described in blepharospasm, including loss of inhibition in sensorimotor pathways at cortical and brainstem level and abnormalities of sensory processing. These changes have traditionally been linked to a basal ganglia dysfunction. However, this interpretation has recently been questioned and alternative pathophysiological model positing that dystonia is a network disorder has been proposed. On the basis of available information, we can speculate that loss of inhibition at cortical and brainstem level and abnormalities of sensory processing in blepharospasm probably reflect the functional derangement of a network involving frontal and parietal cortical areas, basal ganglia, thalamus, and, possibly, the cerebellum.INTRODUCTION Hematoma expansion (HE) after intracerebral hemorrhage (ICH) is associated with short-term mortality, but its impact on long-term prognosis is still unclear. The aim of this study was to evaluate the impact of HE on long-term survival and functional status after spontaneous ICH. METHODS Consecutive patients admitted with spontaneous ICH were prospectively enrolled and followed up for a minimum of 2 years. We compared short-term ( less then  30 days) and long-term survival and functional status between ICH patients with HE (HE+) and those without (HE-). Main outcomes were mortality and poor outcome, defined as modified Rankin Scale ≥ 3. Secondary outcomes included recurrent ICH, admission to institutionalized care, and ischemic events (stroke, myocardial infarction, and systemic embolism). RESULTS Overall, 140 patients were included (mean age 74.9 years, male 59.3%) and followed up for a mean of 2.25 years. HE+ patients (25.7%) had larger hematoma volume at admission (23.8 ml vs 15.3 ml, p  less then  0.05), higher NIHSS score (14.6 vs 10.5, p  less then  0.05) and higher cumulative mortality (59.3% vs 39.2%, p  less then  0.05) compared to HE- patients. Survival analysis showed that HE+ confers higher mortality and worse functional status at all time points. HE did not associate with secondary outcomes. DISCUSSION HE translates into higher mortality and functional dependence over long-term follow-up. Strategies limiting HE might benefit long-term functional status.Artificial intelligence (AI) refers to machines or software that process information and interact with the world as understanding beings. Examples of AI in medicine include the automated reading of chest X-rays and the detection of heart dysrhythmias from wearables. A key promise of AI is its potential to apply logical reasoning at the scale of data too vast for the human mind to comprehend. This scaling up of logical reasoning may allow clinicians to bring the entire breadth of current medical knowledge to bear on each patient in real time. It may also unearth otherwise unreachable knowledge in the attempt to integrate knowledge and research across disciplines. In this review, we discuss two complementary aspects of artificial intelligence deep learning and knowledge representation. Deep learning recognizes and predicts patterns. Knowledge representation structures and interprets those patterns or predictions. We frame this review around how deep learning and knowledge representation might expand the reach of Poison Control Centers and enhance syndromic surveillance from social media.Patients are turning into herbs for the management of diabetes, which cause increasing in the demand of plant-based alternative medicines. Ficus deltoidea or locally known as "Mas Cotek" in Malaysia is a famous herbal plant. However, many varieties of F. deltoidea existed with varied antidiabetic activities inspire us to evaluate in vivo antidiabetic activity of the most available varieties of F. deltoidea. Therefore, antihyperglycemic effect of different varieties of F. deltoidea at dose 250 mg/kg was evaluated on streptozotocin-nicotinamide-induced diabetic rats and further assessed their urinary metabolites using proton nuclear magnetic resonance (1H-NMR). The hyperglycemic blood level improved towards normoglycemic state after 30 days of treatment with standardized extracts of F. deltoidea var. trengganuensis, var.  https://www.selleckchem.com/products/ki16198.html  kunstleri, and var. intermedia. The extracts also significantly managed the biochemical parameters in diabetic rats. Metabolomics results showed these varieties were able to manage the altered metabolites of diabetic rats by shifting some of the metabolites back to their normal state. This knowledge might be very important in suggesting the use of these herbs in long-term treatment for diabetes. The most potential variety can be recommended, which may be useful for further pharmacological studies and herbal authentication processes.