Web-based artificial intelligence to predict cognitive impairment following stroke: A multicenter study.

BACKGROUND AND PURPOSE: Post-stroke cognitive impairment (PSCI) is highly prevalent in modern society. However, there is limited study implying an accurate and explainable machine learning model to predict PSCI. The aim of this study is to develop and validate a web-based artificial intelligence (AI) tool for predicting PSCI. METHODS: The retrospective cohort study design was conducted to develop and validate a web-based prediction model. Adults who experienced a stroke between January 1, 2004, and September 30, 2017, were enrolled, and patients with PSCI were followed up from the stroke index date until their last follow-up. The model's performance metrics, including accuracy, area under the curve (AUC), recall, precision, and F1 score, were compared. RESULTS: A total of 3209 stroke patients were included in the study. The model demonstrated an accuracy of 0.8793, AUC of 0.9200, recall of 0.6332, precision of 0.9664, and F1 score of 0.7651. In the external validation phase, the accuracy improved to 0.9039, AUC to 0.9094, recall to 0.7457, precision to 0.9168, and F1 score to 0.8224. The final model can be accessed at https://psci-calculator.my.id/. CONCLUSION: Our results are able to produce a user-friendly interface that is useful for health practitioners to perform early prediction on PSCI. These findings also suggest that the provided AI model is reliable and can serve as a roadmap for future studies using AI models in a clinical setting.

Detection of preceding sleep apnea using ECG spectrogram during CPAP titration night: A novel machine-learning and bag-of-features framework.

Obstructive sleep apnea (OSA) has a heavy health-related burden on patients and the healthcare system. Continuous positive airway pressure (CPAP) is effective in treating OSA, but adherence to it is often inadequate. A promising solution is to detect sleep apnea events in advance, and to adjust the pressure accordingly, which could improve the long-term use of CPAP treatment. The use of CPAP titration data may reflect a similar response of patients to therapy at home. Our study aimed to develop a machine-learning algorithm using retrospective electrocardiogram (ECG) data and CPAP titration to forecast sleep apnea events before they happen. We employed a support vector machine (SVM), k-nearest neighbour (KNN), decision tree (DT), and linear discriminative analysis (LDA) to detect sleep apnea events 30-90 s in advance. Preprocessed 30 s segments were time-frequency transformed to spectrograms using continuous wavelet transform, followed by feature generation using the bag-of-features technique. Specific frequency bands of 0.5-50 Hz, 0.8-10 Hz, and 8-50 Hz were also extracted to detect the most detected band. Our results indicated that SVM outperformed KNN, LDA, and DT across frequency bands and leading time segments. The 8-50 Hz frequency band gave the best accuracy of 98.2%, and a F1-score of 0.93. Segments 60 s before sleep events seemed to exhibit better performance than other pre-OSA segments. Our findings demonstrate the feasibility of detecting sleep apnea events in advance using only a single-lead ECG signal at CPAP titration, making our proposed framework a novel and promising approach to managing obstructive sleep apnea at home.

The effect of silica exposure on the risk of lung cancer: A meta-analysis.

Lung cancer is an incurable disease with an increased mortality rate caused by the inhalation of dust-containing crystalline silica particles. Silica exposure is one of the most important occupational hazards in the world. Whether the association between silica exposure and lung cancer is because of the fibrotic process or to the effect of respirable silica itself is unclear. The International Agency for Research on Cancer (IARC) classified silica as a human lung carcinogen. The opinion of lung cancer is a question that has been addressed in this review. Three electronic databases, including MEDLINE, Scopus, and Web of Science, were used to search for relevant literature from 2000 to 2022. To evaluate the relationship between exposure to silica and developing lung cancer, we performed a meta-analysis using the random-effects model. For each study, the overall odds ratio (OR), relative risk (RR) with 95% confidence intervals (CI), and p values were calculated. An extensive database search resulted in the selection of 20 (case-control and nested case-control studies were selected) out of 527 studies. Among the 20 selected studies, 7 studies showed a significant association between silica exposure and an increased risk of lung cancer. Further analysis showed that among the selected studies, six studies showed a significant correlation between combined exposure to silica and smoking with an increased risk of lung cancer. The data from the present study showed that smoking habits increased the impact of silica exposure on the initiation of lung carcinogenesis in exposed workers.

Psychometric properties of Indonesian version of sleep condition indicator for screening poststroke insomnia.

BACKGROUND: No study has examined the psychometric properties of the sleep condition indicator (SCI) for screening poststroke insomnia in the Indonesian population. We aimed to develop the Indonesian version of the sleep condition indicator (ISCI) and to examine its psychometric properties for screening adult patients in late sub-acute and chronic periods after stroke. METHODS: This was a cross-sectional study with two stages. In the first stage, the English version of the SCI was translated into the ISCI using standard procedures. The psychometric properties of the ISCI were tested in the second stage. Internal consistency and test-retest reliability of ISCI were used to evaluate reliability. A confirmatory factor analysis (CFA) was performed to test construct validity. To test concurrent and convergent validity, the Indonesian version of the insomnia severity index (ISI-INA), generalized anxiety disorder questionnaire (IGAD-7), and patient health questionnaire (IPHQ-9) were used. A receiver operating characteristic (ROC) analysis was conducted to calculate the optimal cutoff score of the ISCI on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for insomnia. RESULTS: A total of 160 adults with a diagnosis of stroke for more than 3 months were included (median age of 58.5 years, 31% met the DSM-5 criteria for insomnia). The ISCI had a satisfactory Cronbach's alpha of 0.89 and test-retest reliability of 0.78. The CFA revealed that the ISCI exhibited a satisfactory model fit and was associated with the ISI-INA, IGAD-7, and IPHQ-9 (r = -0.81, -0.32, and -0.52, respectively; all P < .001). The ROC test revealed that the optimal cutoff point of ≤23 yielded the highest sensitivity (94%) and specificity (97%). CONCLUSION: The study results revealed that the 8-item ISCI is a reliable and valid screening tool for detecting insomnia symptoms according to the DSM-5 criteria in the chronic period after stroke.

Post-Stroke Insomnia Increased the Risk of Cognitive Impairments: A Hospital-Based Retrospective Cohort Study.

OBJECTIVES/BACKGROUND: Insomnia is a common sleep complaint among patients who had a stroke and has been recognized as an independent risk factor for cognitive impairment. However, the relationship between poststroke insomnia and cognitive impairment over time is under-researched. Therefore, we examined the association between poststroke insomnia and the risk of cognitive impairment. PARTICIPANTS: Stroke participants who had a stroke and were 20 years and older. METHODS: This multicenter hospital-based retrospective cohort study with a 13-year follow-up period (2004-2017). The diagnosis of stroke, insomnia, and cognitive impairment was based on the International Classification of Diseases. The study participants who experienced a stroke were divided into two cohorts: those who also had insomnia and those who did not have insomnia. A Cox proportional-hazards regression model was used. RESULTS: A total of 1,775 patients with a mean age of 67.6 years were included. Of these patients, 146 and 75 patients were diagnosed with insomnia and cognitive impairment during the follow-up period, respectively. The cumulative incidence of cognitive impairment in the stroke with insomnia cohort was significantly lower than that in the stroke without insomnia cohort (log-rank test, P < .001). The adjusted hazard ratio and 95% confidence interval (CI) of the stroke with insomnia cohort indicated a higher risk of cognitive impairment compared with the stroke without insomnia cohort (adjusted hazard ratio: 2.38; 95% CI: 1.41-4.03). CONCLUSIONS: Patients who had a stroke and were diagnosed with insomnia exhibited a substantial increased risk of cognitive impairment over time.

Understanding Alkaline Hydrogen Oxidation Reaction on PdNiRuIrRh High-Entropy-Alloy by Machine Learning Potential.

High-entropy alloy (HEA) catalysts have been widely studied in electrocatalysis. However, identifying atomic structure of HEA with complex atomic arrangement is challenging, which seriously hinders the fundamental understanding of catalytic mechanism. Here, we report a HEA-PdNiRuIrRh catalyst with remarkable mass activity of 3.25 mA µg-1 for alkaline hydrogen oxidation reaction (HOR), which is 8-fold enhancement compared to that of commercial Pt/C. Through machine learning potential-based Monte Carlo simulation, we reveal that the dominant Pd-Pd-Ni/Pd-Pd-Pd bonding environments and Ni/Ru oxophilic sites on HEA surface are beneficial to the optimized adsorption/desorption of *H and enhanced *OH adsorption, contributing to the excellent HOR activity and stability. This work provides significant insights into atomic structure and catalytic mechanism for HEA and offers novel prospects for developing advanced HOR electrocatalysts.

Screening for Obstructive Sleep Apnea Risk by Using Machine Learning Approaches and Anthropometric Features.

Obstructive sleep apnea (OSA) is a global health concern and is typically diagnosed using in-laboratory polysomnography (PSG). However, PSG is highly time-consuming and labor-intensive. We, therefore, developed machine learning models based on easily accessed anthropometric features to screen for the risk of moderate to severe and severe OSA. We enrolled 3503 patients from Taiwan and determined their PSG parameters and anthropometric features. Subsequently, we compared the mean values among patients with different OSA severity and considered correlations among all participants. We developed models based on the following machine learning approaches: logistic regression, k-nearest neighbors, naïve Bayes, random forest (RF), support vector machine, and XGBoost. Collected data were first independently split into two data sets (training and validation: 80%; testing: 20%). Thereafter, we adopted the model with the highest accuracy in the training and validation stage to predict the testing set. We explored the importance of each feature in the OSA risk screening by calculating the Shapley values of each input variable. The RF model achieved the highest accuracy for moderate to severe (84.74%) and severe (72.61%) OSA. The level of visceral fat was found to be a predominant feature in the risk screening models of OSA with the aforementioned levels of severity. Our machine learning models can be employed to screen for OSA risk in the populations in Taiwan and in those with similar craniofacial structures.

Dynamic Prevalence of Sleep Disorders Following Stroke or Transient Ischemic Attack: Systematic Review and Meta-Analysis.

BACKGROUND AND PURPOSE: The exact prevalence of sleep disorders following stroke or transient ischemic attack (TIA) remains unclear. We aimed to determine the prevalence of sleep-disordered breathing, insomnia, periodic leg movement during sleep, and restless leg syndrome following stroke or TIA in acute, subacute, and chronic phases and examine the moderating effects of patient characteristics (eg, age) and methodological features (eg, study quality) on the prevalence. METHODS: We performed a systematic review and meta-analysis. Embase and PubMed were searched from inception to December 18, 2019. We included 64 047 adults in 169 studies (prospective, retrospective, case-control, and cross-sectional study designs) reporting the prevalence of sleep disorders following stroke or TIA. RESULTS: In the acute phase, the overall prevalence of mild, moderate, and severe sleep-disordered breathing was 66.8%, 50.3%, and 31.6% (95% CIs, 63.8-69.7, 41.9-58.7, and 24.9-39.1). In the subacute phase, the prevalence of mild, moderate, and severe sleep-disordered breathing was 65.5%, 44.3%, and 36.1% (95% CIs, 58.9-71.5, 36.1-52.8, and 22.2-52.8). In the chronic phase, the summary prevalence of mild, moderate, and severe sleep-disordered breathing was 66.2%, 33.1%, and 25.1% (95% CIs, 58.6-73.1, 24.8-42.6, and 10.9-47.6). The prevalence rates of insomnia in the acute, subacute, and chronic phases were 40.7%, 42.6%, and 35.9% (95% CIs, 31.8-50.3, 31.7-54.1, and 28.6-44.0). The pooled prevalence of periodic leg movement during sleep in the acute, subacute, and chronic phases was 32.0%, 27.3%, and 48.2% (95% CIs, 7.4-73.5, 11.6-51.7, and 33.1-63.5). The summary prevalence of restless leg syndrome in the acute and chronic phases was 10.4% and 13.7% (95 CIs, 6.4-16.4 and 2.3-51.8). Age, sex, comorbidities, smoking history, and study region had significant moderating effects on the prevalence of sleep disorders. CONCLUSIONS: Sleep disorders following stroke or TIA are highly prevalent over time. Our findings indicate the importance of early screening and treating sleep disorders following stroke or TIA.

Diphenyl pyrimidine exhibits protective effect on Staphylococcus aureus pneumonia in rat model by targeting NLRP3 expression.

Pneumonia is one of the most frequent disorder induced by S. aureus infection and accounts for 13.3% of the all the infections caused by staphylococcus. In the present study effect of diphenyl pyrimidine was investigated against Staphylococcus aureus (S. aureus) induced pneumonia in the rat model. The results demonstrated that diphenyl pyrimidine treatment of the rats effectively prevented S. aureus induced increase in mortality in dose-dependent manner. Diphenyl pyrimidine treatment inhibited histopathological changes in S. aureus infected rat lungs. Treatment of the rats with 1.25, 2.5, 5 and 10 mg/kg doses of diphenyl pyrimidine significantly (P < 0.05) reversed S. aureus infection induced increase in interleukin (IL)-1ß, IL-18 and tumor necrosis factor (TNF)-α levels. Treatment with 1.25, 2.5, 5 and 10 mg/kg doses of diphenyl pyrimidine significantly (P < 0.05) reversed S. aureus infection induced increase nucleotide-binding domain and leucine-rich repeat containing (NLR) protein (NLRP3), apoptosis-associated speck-like protein containing a C-terminal caspase recruitment domain (ASC) and caspase-1 protein expression in rat lungs in dose-dependent manner. The NLRP3, ASC and caspase-1 mRNA level in S. aureus infected rat pulmonary tissues was significantly (P < 0.05) reduced by diphenyl pyrimidine treatment in dose-dependent manner. Thus, diphenyl pyrimidine protects S. aureus-induced pneumonia through suppression of NLRP3 and inflammatory cytokine expression. Therefore, diphenyl pyrimidine can be of therapeutic importance for the treatment of S. aureus induced pneumonia.

A Wrist Sensor Sleep Posture Monitoring System: An Automatic Labeling Approach.

In the hospital, a sleep postures monitoring system is usually adopted to transform sensing signals into sleep behaviors. However, a home-care sleep posture monitoring system needs to be user friendly. In this paper, we present iSleePost-a user-friendly home-care intelligent sleep posture monitoring system. We address the labor-intensive labeling issue of traditional machine learning approaches in the training phase. Our proposed mobile health (mHealth) system leverages the communications and computation capabilities of mobile phones for provisioning a continuous sleep posture monitoring service. Our experiments show that iSleePost can achieve up to 85 percent accuracy in recognizing sleep postures. More importantly, iSleePost demonstrates that an easy-to-wear wrist sensor can accurately quantify sleep postures after our designed training phase. It is our hope that the design concept of iSleePost can shed some lights on quantifying human sleep postures in the future.

Comparison of Hospital-Based and Home-Based Obstructive Sleep Apnoea Severity Measurements with a Single-Lead Electrocardiogram Patch.

Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear. We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over three subsequent nights. Scores on OSA indices-namely, the apnoea-hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into three groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons, and their correlations were examined by Pearson's correlation coefficient. The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All three groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment, compared with the hospital-based assessment. The percentage of supine sleep time (∆Supine%) exhibited a significant but weak to moderate positive correlation with each of the OSA indices. A significant but weak-to-moderate correlation between the ∆Supine% and ∆Rx index was still observed among the patients with high sleep efficiency (≥80%), who could reduce the effect of short sleep duration, leading to underestimation of the patients' OSA severity. The high supine percentage of sleep may cause OSA indices' overestimation in the hospital-based examination. Sleep recording at home with patch-type wearable devices may aid in accurate OSA diagnosis.

Hexagonal RuSe2 Nanosheets for Highly Efficient Hydrogen Evolution Electrocatalysis.

Layered transition metal dichalcogenide (TMD) nanomaterials are promising alternatives to platinum (Pt) for the hydrogen evolution reaction (HER). However, the family of layered TMDs is mainly limited to Group IV-VII transition metals, while the synthesis of layered TMDs based on metals from other groups still remains a challenge. Herein, we demonstrate by atomic-resolution transmission electron microscopy that hexagonal RuSe2 (h-RuSe2 ) nanosheets with a mixture of 2H and 1T phases can be obtained by a facile bottom-up colloidal synthetic approach. The obtained h-RuSe2 , which can be transformed into the thermodynamically favorable phase of cubic RuSe2 (c-RuSe2 ) only after annealing at 600 °C, exhibits Pt-like HER performance, with a fivefold turnover frequency enhancement compared to the c-RuSe2 in alkaline media. Experimental results and density functional theory (DFT) calculations reveal that the enhanced adsorption free energies of H2 O (ΔG H 2 O * ), optimized adsorption free energies of H (ΔGH* ), and increased conductivity of h-RuSe2 contribute to its superior HER activity.

Disseminated cutaneous herpes zoster and multiple cerebral infarcts in an adult with diabetes mellitus.

Ischemic stroke is a rare complication of varicella-zoster virus (VZV) infection. We present the case of a patient with a medical history of type 2 diabetes mellitus (DM) who experienced disseminated cutaneous VZV infection followed by multiple cerebral infarcts associated with VZV vasculopathy. Brain magnetic resonance imaging revealed multiple hyperintense lesions over the bilateral deep white matter and basal ganglia. A skin biopsy revealed small-vessel leukocytoclastic vasculitis with neutrophilic, lymphocytic, and eosinophilic infiltration. This case report describes the rare finding of cutaneous leukocytoclastic vasculitis in VZV infection and highlights that VZV infection is an uncommon but critical etiology of cryptogenic stroke in patients with DM.

The Kidney Clock Contributes to Timekeeping by the Master Circadian Clock.

The kidney harbors one of the strongest circadian clocks in the body. Kidney failure has long been known to cause circadian sleep disturbances. Using an adenine-induced model of chronic kidney disease (CKD) in mice, we probe the possibility that such sleep disturbances originate from aberrant circadian rhythms in kidney. Under the CKD condition, mice developed unstable behavioral circadian rhythms. When observed in isolation in vitro, the pacing of the master clock, the suprachiasmatic nucleus (SCN), remained uncompromised, while the kidney clock became a less robust circadian oscillator with a longer period. We find this analogous to the silencing of a strong slave clock in the brain, the choroid plexus, which alters the pacing of the SCN. We propose that the kidney also contributes to overall circadian timekeeping at the whole-body level, through bottom-up feedback in the hierarchical structure of the mammalian circadian clocks.

Cerebral Microbleeds are Associated with Postural Instability and Gait Disturbance Subtype in People with Parkinson's Disease.

OBJECTIVES: The motor symptoms of Parkinson's disease (PD) vary among patients and have been categorized into 3 subtypes: tremor dominant, akinetic rigidity, and postural instability and gait disturbance (PIGD). Cerebral microbleed (CMB) is prevalent in people with PD and is associated with some nonmotor symptoms. The present study investigated the association between CMB and the motor subtypes of PD. MATERIALS AND METHODS: From 2009 to 2017, medical records and brain magnetic resonance imaging (MRI) reports of 134 Taiwanese people with early- and mid-stage PD were reviewed. CMBs were quantified according to the Microbleed Anatomical Rating Scale through susceptibility-weighted MRI. Motor subtypes were determined by medical chart review. Student's t test and multivariable logistic regression were used to analyze the association between the motor subtypes and CMB. Statistical analyses were performed using SPSS 19.0. RESULTS: Overall, 72 (53.7%) participants were women with a mean age of 69.5 ± 9.8 years. The prevalence of CMB was 33.6%, and lobar, deep, and infratentorial CMBs comprised 21.6, 19.4, and 11.9% of cases, respectively. PIGD subtype PD was associated with a significantly higher prevalence of any CMB as well as deep or lobar CMB. After adjustment for age and sex, the PIGD subtype was significantly positively associated with the presence of any, deep, and white matter (WM) and thalamic CMB. CONCLUSIONS: CMB was prevalent in Taiwanese people with early- and mid-stage PD, especially the PIGD subtype. Deep, especially thalamic and WM, CMBs exhibited the highest association with the PIGD subtype.

The Association of Apolipoprotein E Allele 4 Polymorphism with the Recovery of Sleep Disturbance after Mild Traumatic Brain Injury.

PURPOSE: Mild traumatic brain injury (mTBI) is a major public health concern. The apolipoprotein E (APOE) gene contains three polymorphisms, and the APOE4 polymorphism may affect several physiological states, such as the recovery from mTBI as well as sleep. This study aims to investigate the association between APOE4 with the recovery of sleep disturbance after mTBI. METHODS: From May 2012 to Aug 2015, 189 mTBI patients completed baseline (1st week post-mTBI) and follow-up (6th week post-mTBI) sleep assessments that involved using the Pittsburgh Sleep Quality Index (PSQI). APOE genotypes were determined by sequencing the products of polymerase chain reaction from genomic DNA. Statistical analyses were performed using the Wilcox signed-rank or chi-square test. RESULTS: Thirty-five (18.5%) participants were APOE4 carriers. At baseline, the demographic data and the severity of sleep disturbance were similar in both groups. APOE4 carriers demonstrated significant improvement in the overall PSQI score (8.34±3.9 at baseline and 7.43±3.99 at follow-up, p = 0.05) and scores of several PSQI subscales, including sleep disturbance, sleep latency, daytime dysfunction caused by sleepiness, and overall sleep quality, which was similar to APOE4 noncarriers. CONCLUSION: APOE4 is not associated with the recovery of sleep disturbance after mTBI.

Energy adaptive response during parthanatos is enhanced by PD98059 and involves mitochondrial function but not autophagy induction.

Parthanatos is a programmed necrotic demise characteristic of ATP (adenosine triphosphate) consumption due to NAD+ (nicotinamide adenine dinucleotide) depletion by poly(ADP-ribose) polymerase 1 (PARP1)-dependent poly(ADP-ribosyl)ation on target proteins. However, how the bioenergetics is adaptively regulated during parthanatos, especially under the condition of macroautophagy deficiency, remains poorly characterized. Here, we demonstrated that the parthanatic inducer N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) triggered ATP depletion followed by recovery in mouse embryonic fibroblasts (MEFs). Notably, Atg5-/- MEFs showed great susceptibility to MNNG with disabled ATP-producing capacity. Moreover, the differential energy-adaptive responses in wild-type (WT) and Atg5-/- MEFs were unequivocally worsened by inhibition ofAMP-activated protein kinase (AMPK), sirtuin 1 (SIRT1), and mitochondrial activity. Importantly, Atg5-/- MEFs disclosed diminished SIRT1 and mitochondrial activity essential to the energy restoration during parthanatos. Strikingly, however, parthanatos cannot be exasperated by bafilomycin A1 and MNNG neither provokes microtubule-associated protein 1A/1B-light chain 3 (LC3) lipidation and p62 elimination, suggesting that parthanatos does not induce autophagic flux. Intriguingly, we reported unexpectedly that PD98059, even at low concentration insufficient to inhibit MEK, can promote mitochondrial activity and facilitate energy-restoring process during parthanatos, without modulating DNA damage responses as evidenced by PARP1 activity, p53 expression, and gammaH2AX (H2A histone family, member X (H2AX), phosphorylated on Serine 139) induction. Therefore, we propose that Atg5 deficiency confers an infirmity to overcome the energy crisis during parthanatos and further underscore the deficits in mitochondrial quality control, but not incapability of autophagy induction, that explain the vulnerability in Atg5-deficient cells. Collectively, our results provide a comprehensive energy perspective for an improved treatment to alleviate parthanatos-related tissue necrosis and disease progression and also provide a future direction for drug development on the basis of PD98059 as an efficacious compound against parthanatos.

TAK1 inhibition-induced RIP1-dependent apoptosis in murine macrophages relies on constitutive TNF-α signaling and ROS production.

BACKGROUND: Transforming growth factor-ß (TGF-ß)-activated kinase 1 (TAK1) is a key regulator of signal cascades of TNF-α receptor and TLR4, and can induce NF-κB activation for preventing cell apoptosis and eliciting inflammation response. RESULTS: TAK1 inhibitor (TAKI) can decrease the cell viability of murine bone marrow-derived macrophages (BMDM), RAW264.7 and BV-2 cells, but not dermal microvascular endothelial cells, normal human epidermal keratinocytes, THP-1 monocytes, human retinal pigment epithelial cells, microglia CHME3 cells, and some cancer cell lines (CL1.0, HeLa and HCT116). In BMDM, TAKI-induced caspase activation and cell apoptosis were enhanced by lipopolysaccharide (LPS). Moreover, TAKI treatment increased the cytosolic and mitochondrial reactive oxygen species (ROS) production, and ROS scavengers NAC and BHA can inhibit cell death caused by TAKI. In addition, RIP1 inhibitor (necrostatin-1) can protect cells against TAKI-induced mitochondrial ROS production and cell apoptosis. We also observed the mitochondrial membrane potential loss after TAKI treatment and deterioration of oxygen consumption upon combination with LPS. Notably TNF-α neutralization antibody and inhibitor enbrel can decrease the cell death caused by TAKI. CONCLUSIONS: TAKI-induced cytotoxicity is cell context specific, and apoptosis observed in macrophages is dependent on the constitutive autocrine action of TNF-α for RIP1 activation and ROS production.

A Case Report of Japanese Encephalitis Focusing on MR Findings.

meningitis or encephalitis with or without neurological deficits. JEV typically attacks the thalamus, corpus striatum, brainstem and spinal cord. The laboratory diagnosis of JEV infection involves the detection of anti-JEV antibody IgMs using an enzyme-linked immunosorbent assay (ELISA), which has high sensitivity and specificity. Because of the lack of a specific antiviral therapy, JE is usually managed by symptomatic treatment and supportive care. We report a case of JE in a 34-year-old man. With a clinical presentation similar to herpes simplex virus encephalitis, the patient was finally diagnosed as having JE. The distinction of different viral encephalitides in MR findings is briefly reviewed.

Insomnia complaints correlated with higher risk of cognitive impairment in older adults following stroke: a National Representative Comparison Study.

Although associations among insomnia, cognitive impairment, and stroke have been demonstrated, whether insomnia increases the risk of cognitive impairment after stroke remains unclear. The aim of this study was to examine whether insomnia complaints moderated the association between stroke and cognitive impairment in older adults. This study was a secondary data analysis that used data from the National Health Interview Survey 2009. A total of 447 older adults with a mean age of 74.63 years (50.1% men) were included. Self-reported insomnia and stroke occurrence were determined using a questionnaire. Cognitive impairment was assessed using the Mini-Mental State Examination. We used multivariate logistic regression to analyze the association between insomnia complaints and cognitive impairment. Participants were categorized into four groups: those with stroke and insomnia (58), those with stroke without insomnia (91), those without stroke with insomnia (116), and those without stroke or insomnia (182). The prevalence of insomnia complaints was 38.9%, and the frequency of poststroke cognitive impairment was 50.3%. After controlling for potential confounders, participants with stroke (with or without insomnia) had a significantly higher risk of cognitive impairment than those without stroke or insomnia (adjusted odds ratios: 4.16 and 2.91, 95% confidence intervals: 1.91-9.07 and 1.56-5.43, respectively). Stroke with or without insomnia complaints was associated with a higher risk of cognitive impairment relative to older adults without stroke or insomnia. The risk of cognitive impairment was the highest among participants with both stroke and insomnia.