Objective Although the prognosis of posterior reversible encephalopathy syndrome (PRES) is usually favourable and most patients wholly recover, the disorder can result in death in some patients. To date, the data on clinical features and risk factors for death are still lacking; therefore, we aim to investigate the clinical features and long-term prognostic risk factors of PRES in the present study. Methods The patients with PRES were identified from the First Affiliated Hospital of Zhengzhou University from June 2011 to June 2020. Clinical characteristics, laboratory tests, magnetic resonance imaging examinations, and treatment of all patients were analyzed retrospectively. All patients were followed up by telephone. Finally, the patients were divided into the survival group and death group for prognosis analysis. Results A total of 92 patients with PRES were included; 84.8% of whom were female, with an average age of 25.4 (5–66) years at the onset of PRES. Epilepsy was the main clinical manifestation (72.8%). The in-hospital mortality rate was 2.17%. The 3-year all-cause survival rate for PRES patients was 86%. In univariate analysis, patients with systemic lupus erythematosus (P = 0.027) and blood transfusion history within 1 month before onset (P = 0.027), need for dialysis (P ≤ 0.001), nephritis (P = 0.010), stroke (P = 0.016), and heart failure (P = 0.016) were associated with death. In multivariate analysis, we found that heart failure (OR = 0.095, 95% CI 0.020 to 0.441) and stroke (OR = 0.033, 95% CI 0.002 to 0.467) were independent risk factors for death in PRES patients, while pregnancy was a protective factor for death in PRES patients (OR = 7.978, 95% CI 1.446 to 44.006). Conclusions Our results indicate that PRES could be considered as a sign of a very high-risk patient. We also demonstrated that heart failure and stroke were independent risk factors for death in patients with PRES; moreover, pregnancy was a protective factor.

Aromatic L-amino acid decarboxylase (AADC) deficiency is a rare congenital autosomal recessive metabolic disorder caused by pathogenic homozygous or compound heterozygous variants in the dopa decarboxylase (DDC) gene. Adeno-associated viral vector-mediated gene transfer of the human AADC gene into the putamina has become available. This systematic review on PubMed, Scopus databases, and other sources is aimed at describing the AADC whole phenotypic spectrum in order to facilitate its early diagnosis. Literature reviews, original articles, retrospective and comparative studies, large case series, case reports, and short communications were considered. A database was set up using Microsoft Excel to collect clinical, molecular, biochemical, and therapeutic data. By analysing 261 patients from 41 papers with molecular and/or biochemical diagnosis of AADC deficiency for which individuality could be determined with certainty, we found symptom onset to occur in the first 6 months of life in 93% of cases. Hypotonia and developmental delay are cardinal signs, reported as present in 73.9% and 72% of cases, respectively. Oculogyric crises were seen in 67% of patients while hypokinesia in 42% and ptosis in 26%. Dysautonomic features have been revealed in 53% and gastrointestinal symptoms in 19% of cases. With 37% and 30% of patients reported being affected by sleep and behavioural disorders, it seems to be commoner than previously acknowledged. Although reporting bias cannot be excluded, there is still a need for comprehensive clinical descriptions of symptoms at onset and during follow-up. In fact, our review suggests that most of the neurological and extraneurological symptoms and signs reported, although quite frequent in this condition, are not pathognomonic, and therefore, ADCC deficiency can remain an underdiscovered disorder.

The purpose of this study was to discuss the effect of voluntary wheel running on striatal dopamine levels and anxiety-like behavior in rats with global cerebral ischemia. The male Sprague-Dawley rats were signed on in this study and randomly divided into following 4 groups: Control group (C group), Sham group (S group), ischemia group (I group), and 3 weeks physical exercise before ischemia group (3RI group). The rats in the 3RI group were placed in a voluntary running wheel for three weeks to exercise. Then, the rats in I and 3RI groups received bilateral carotid artery ligation (2-VO) operation. The C and S group did not perform voluntary running exercise and the bilateral common carotid arteries of S group were exposed without ligation. In vivo microdialysis was used in conjunction with high performance liquid chromatography (HPLC) and electrochemical detection to ascertain the level of dopamine in the striatum. Elevated plus maze (EPM) and open field (OF) were used to test anxiety status at 24 hours and 7days after 2-VO cerebral ischemia. Meanwhile, gait and motor coordination evaluations were carried out to eliminate the influence of non-specific motor problems. The results indicated that cerebral ischemia instigate the increase of striatal dopamine in I group rats during acute cerebral ischemia. A 3-week voluntary wheel running significantly enhances the striatal dopamine before ischemia and obstructs a further increase of dopamine during acute cerebral ischemia in 3RI group rats. At 24 hours after ischemia, striatal dopamine returned to pre-ischemic levels in 3RI group. Striatal dopamine in I group were less than pre-ischemic levels at 7 days. Behavioral data indicated that 3-week voluntary wheel running promoted recovery of anxiety-like behavior and gait were not affected by 2-VO cerebral ischemia at 24 hours post-ischemia rats. Therefore, it can be concluded that 3-week physical exercise significantly increased the striatal dopamine and improved anxiety-like behavior by inhibiting the increase of dopamine during acute cerebral ischemia and suppressing the decrease of dopamine after 24 hours and 7 days cerebral ischemia.

Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

Methods All rats were randomly divided into four groups, namely, control, CUMS, CUMS + CUR, and CUMS + CUR + SR18292 (PGC-1α inhibitor). Behavioral tests were conducted to assess the antidepressant-like effects of CUR. The expressions of PGC-1α, estrogen-related receptor alpha (ERRα), FNDC5, and BDNF were determined to investigate the regulatory effects of CUR on the PGC-1α/FNDC5/BDNF pathway. The PGC-1α inhibitor SR18292 was used to explore the role of PGC-1α in the induction of BDNF by CUR. Results Daily gavage of 100 mg/kg CUR successfully attenuated the abnormal behaviors induced by CUMS and effectively prevented CUMS-induced reduction of PGC-1α, ERRα, FNDC5, and BDNF expressions. CUR also enhanced PGC-1α and ERRα translocation from cytoplasm to nucleus. Furthermore, we found that CUR supplementation effectively promoted neurocyte proliferation and suppressed neuronal apoptosis induced by CUMS. Of note, the PGC-1α inhibitor SR18292 remarkably reversed the beneficial effects of CUR on depressed rats, indicating an important role of PGC-1α in the antidepressant-like effects of CUR. Conclusion Collectively, our data evaluating the neuroprotective action of CUR in the CUMS rats highlights the involvement of the PGC-1α/FNDC5/BDNF pathway in the antidepressant-like effects of CUR.

E-shopping is a rapidly growing phenomenon among different individuals who intend to shop online. However, a trust deficit in the E-shopping environment has always been a critical issue in the brick-and-click mode of shopping, being one of the main reasons for E-cart abandonment in E-commerce. This empirical study is aimed at investigating the perceived effect of website trust on E-shopping intentions and behaviour, drawing upon the theory of planned behaviour (TPB). Data were collected through self-administered questionnaires from working adults who shop for garments online. Structural equation modelling was used to evaluate the model fit and assumptions. Our findings suggest that website trust and E-shopping attitude play substantial roles in building E-shopping intentions and actual behaviours. Both are the significant predictors of the behaviour mediated by E-shopping intentions. However, E-shopping intentions did not mediate between subjective norms and E-shopping behaviour, when working adults decide to purchase garments online.

Cognitive science is a technology which focuses on analyzing the human brain using the application of DM. The databases are utilized to gather and store the large volume of data. The authenticated information is extracted using measures. This research work is based on detecting the sarcasm from the text data. This research work introduces a scheme to detect sarcasm based on PCA algorithm, K-means algorithm, and ensemble classification. The four ensemble classifiers are designed with the objective of detecting the sarcasm. The first ensemble classification algorithm (SKD) is the combination of SVM, KNN, and decision tree. In the second ensemble classifier (SLD), SVM, logistic regression, and decision tree classifiers are combined for the sarcasm detection. In the third ensemble model (MLD), MLP, logistic regression, and decision tree are combined, and the last one (SLM) is the combination of MLP, logistic regression, and SVM. The proposed model is implemented in Python and tested on five datasets of different sizes. The performance of the models is tested with regard to various metrics.

Patient behavioral analysis is the key factor for providing treatment to patients who may suffer from various difficulties including neurological disease, head trauma, and mental disease. Analyzing the patient's behavior helps in determining the root cause of the disease. In traditional healthcare, patient behavioral analysis has lots of challenges that were much more difficult. The patient behavior can be easily analyzed with the development of smart healthcare. Information technology plays a key role in understanding the concept of smart healthcare. A new generation of information technologies including IoT and cloud computing is used for changing the traditional healthcare system in all ways. Using Internet of Things in the healthcare institution enhances the effectiveness as well as makes it more personalized and convenient to the patients. The first thing that will be discussed in the article is the technologies that have been used to support the smart class, and further, there will be a discussion on the existing problems with the smart healthcare system and how these problems can be solved. This study can provide essential information about the role of smart healthcare and IoT in maintaining behavior of patent. Various biomarkers are maintained properly with the help of these technologies. This study can provide effective information about importance of smart health system. This smart healthcare is conducted with the involvement of proper architecture. This is treated as effective energy efficiency architecture. Artificial intelligence is used increasingly in healthcare to maintain diagnosis and other important factors of healthcare. This application is also used to maintain patient engagement, which is also included in this study. Major hardware components are also included in this technology such as CO sensor and CO2 sensor.

Objective To assess association between congenital cytomegalovirus (CMV) infection and brain injury in neonates. Methods The literatures from inception to November 4, 2020, were searched through PubMed, Embase, Cochrane Library, and Web of Science. Heterogeneity test was conducted for each indicator and measured by I2 statistics. If I2 ≥ 50%, the random effects model was applied; otherwise, the fixed effects model was used. Sensitivity analysis was performed for all models. Weighed mean difference (WMD) was used as the effect size for measurement data, and risk ratio (RR) was as the effect indicator. Results A total of 13 studies, including 4,262 congenital CMV infection neonates, were enrolled in this study. Our results showed that the rate of hearing impairment (RR: 2.105, 95% CI: (1.115, 3.971), P = 0.002), sensorineural hearing loss (SNHL) (RR: 17.051, 95% CI: (6.201, 46.886), P < 0.001), and microcephaly (RR: 2.283, 95% CI: (1.325, 3.935), P =0.003) in neonates infected congenital CMV was higher than that in control group. Conclusion The risks of hearing impairment, SNHL, and microcephaly in neonates during childhood may be associated with congenital CMV infection. It is necessary to establish neonatal screening programs and comprehensive diagnostic tests for patients to reduce the risk of adverse brain damage to the congenital CMV infection as early as possible and to improve the prognosis of the newborn.

Objective To evaluate whether hemodynamic factors are risk factors for prognosis in moyamoya disease (MMD). Materials and Methods The retrospective study reviewed a single-center MMD cohort in Huashan Hospital from August 2017 to January 2020. Stroke events in 30 days and follow-up modified Rankin Scale (mRS) grade were recorded. Systematic assessments with perioperative mean arterial pressure (MAP), red blood cell (RBC) parameters, and fluid management were also conducted. Logistic regressions were applied to evaluate the predictors of worse outcomes. Data was analyzed using SPSS 24.0. Results Admission to neurological intensive care unit (NICU) totalled about 347 after revascularization surgery. The result showed that the higher the postoperative MAP level (favorable group 95.7 ± 11.4 mmHg vs. unfavorable group 103.6 ± 10.4 mmHg, p < 0.001) and the greater the MAP variability (favorable group 0.26 ± 13.2 vs. unfavorable group 7.2 ± 13.5, p = 0.006) were, the higher the patient's follow-up mRS grade was. What is more, a higher early postoperative Hb level also seemed to predict a worse long-term clinical outcome (favorable group 116.9 ± 17.1 g/L vs. unfavorable group 123.7 ± 13.0 g/L, p = 0.03), but the difference disappeared after adjusting sex and age. Logistic regression analyses showed that a higher level of postoperative MAP (β = 0.024, 95% CI (0.004, 0.044), and p = 0.02) within the first 24 h in NICU might be the short-term risk factor. For long-term outcome, a higher level (β = 1.058, 95% CI (1.022, 1.096), and p = 0.001) and a greater variability (β = 30.982, 95% CI (2.112, 454.414), and p = 0.01) of postoperative MAP might be the negative predictors of mRS grade. Conclusions The early postoperative hemodynamic management might be extremely critical for patients with MMD. Both high postoperative MAP levels and large MAP variability might affect the prognosis. What is more, we also found that a higher postoperative Hb level might be related with a worse outcome.