Multiple sclerosis and COVID-19: a northern China survey.

BACKGROUND: There is insufficient data on severe acute respiratory syndrome coronavirus type-2 (SARS-CoV-2) infection in Chinese patients with multiple sclerosis (pwMS). This study aims to explore the manifestation of pwMS during the Coronavirus disease 2019 (COVID-19) pandemic and the effect of SARS-CoV-2 infection on the prognosis of MS in northern China. METHODS: In this cross-sectional study, an online self-administered questionnaire and telephone interviews were conducted among pwMS of northern China. Clinical correlation of SARS-CoV-2 infection since the onset of the COVID-19 pandemic in northern China was analyzed. RESULTS: 164 patients with an average age of 38.9 ± 12.2 years were included, of which 57.3% had a disease course ≤ 5 years. 33.5% of the patients were COVID-19 vaccinated. 87.2% received disease-modifying therapy (DMT), and the average immunotherapy duration was 1.9 ± 1.6 years. 83.5% were SARS-CoV-2 infected, 14.6% reported worsening of their original condition after infection, and 5.1% had a relapse of MS. Shorter disease course was independently related to infection risk (P = 0.046), whereas increasing age was related to aggravated behavioral symptoms (P = 0.008). However, gender, vaccination, and DMT were not associated with susceptibility or poor prognosis. CONCLUSION: A shorter disease course is independently associated with an increased risk of SARS-CoV-2 infection, and age is associated with worsening disability. It seems to be safe and necessary to use DMT during the pandemic, however, the use of B cell-depletion agents should be approached with caution.

Impact of Preseason Climate Factors on Vegetation Photosynthetic Phenology in Mid-High Latitudes of the Northern Hemisphere.

During the period preceding the vegetation growing season (GS), temperature emerges as the pivotal factor determining phenology in northern terrestrial ecosystems. Despite extensive research on the impact of daily mean temperature (Tmean) during the preseason period, the influence of diurnal temperature range (DTR) on vegetation photosynthetic phenology (i.e., the impact of the plant photosynthetic cycle on seasonal time scale) has largely been neglected. Using a long-term vegetation photosynthetic phenology dataset and historical climate data, we examine vegetation photosynthetic phenology dynamics and responses to climate change across the mid-high latitudes of the Northern Hemisphere from 2001 to 2020. Our data reveal an advancing trend in the start of the GS (SOS) by -0.15 days per year (days yr-1), affecting 72.1% of the studied area. This is particularly pronounced in western Canada, Alaska, eastern Asia, and latitudes north of 60°N. Conversely, the end of the GS (EOS) displays a delaying trend of 0.17 days yr-1, impacting 62.4% of the studied area, especially northern North America and northern Eurasia. The collective influence of an earlier SOS and a delayed EOS has resulted in the notably prolonged length of the GS (LOS) by 0.32 days yr-1 in the last two decades, affecting 70.9% of the studied area, with Eurasia and western North America being particularly noteworthy. Partial correlation coefficients of the SOS with preseason Tmean, DTR, and accumulated precipitation exhibited negative values in 98.4%, 93.0%, and 39.2% of the study area, respectively. However, there were distinct regional variations in the influence of climate factors on the EOS. The partial correlation coefficients of the EOS with preseason Tmean, DTR, and precipitation were positive in 58.6%, 50.1%, and 36.3% of the region, respectively. Our findings unveil the intricate mechanisms influencing vegetation photosynthetic phenology, holding crucial significance in understanding the dynamics of carbon sequestration within terrestrial ecosystems amidst climate change.

The multifaceted role of RNA-based regulation in plant stress memory.

Plants have evolved interconnected regulatory pathways which enable them to respond and adapt to their environments. In plants, stress memory enhances stress tolerance through the molecular retention of prior stressful experiences, fostering rapid and robust responses to subsequent challenges. Mounting evidence suggests a close link between the formation of stress memories and effective future stress responses. However, the mechanism by which environmental stressors trigger stress memory formation is poorly understood. Here, we review the current state of knowledge regarding the RNA-based regulation on stress memory formation in plants and discuss research challenges and future directions. Specifically, we focus on the involvement of microRNAs (miRNAs), small interfering RNAs (siRNAs), long non-coding RNAs (lncRNAs), and alternative splicing (AS) in stress memory formation. miRNAs regulate target genes via post-transcriptional silencing, while siRNAs trigger stress memory formation through RNA-directed DNA methylation (RdDM). lncRNAs guide protein complexes for epigenetic regulation, and AS of pre-mRNAs is crucial to plant stress memory. Unraveling the mechanisms underpinning RNA-mediated stress memory formation not only advances our knowledge of plant biology but also aids in the development of improved stress tolerance in crops, enhancing crop performance and global food security.

Anti-Hu antibody associated paraneoplastic neurological syndrome in a child with ganglioneuroblastoma: A rare case report and literature review.

RATIONALE: Paraneoplastic neurological syndrome with anti-Hu antibody (Hu-PNS) is a neurological disorder that occur in patients with malignancy. The syndrome has a wide range of presentations and can present before diagnosis of primary malignancy. Familiarity with these paraneoplastic neurological syndromes can help early recognition and take appropriate regimens. PATIENTS CONCERNS: Diagnosis and treatment of Hu-PNS. DIAGNOSES: This is retrospective study that analyzed the clinical data of this case. Through retrospective analysis and targeted antibody screening, serum anti-Hu antibody was detected. Subsequent spinal imaging revealed a mass in the paraspinal region, which was confirmed as ganglioneuroblastoma by pathologic examination. INTERVENTIONS: The child was treated with a course of intravenous immunoglobulin and radical surgical operation without chemotherapy. OUTCOMES: The neurological symptoms were gradually improved and no signs indicate disease progression or tumor recurrence. LESSONS: Hu-PNS has rarely been reported in children with ganglioneuroblastomas. They can mimic non-neoplastic processes, making detection and diagnosis difficult. Serum and/or cerebrospinal fluid onconeural antibody can strongly indicate occult cancers. Early detection of paraneoplastic neurological syndromes can help take appropriate regimens and improve prognosis.

Interrelationships among abnormal P-wave axis, metabolic syndrome and its components, and mortality in US adults.

BACKGROUND: Metabolic syndrome (MetS) is associated with increased rates of cardiovascular disease and mortality and is linked to abnormal electrocardiogram (ECG) parameters. We aimed to explore the relationships and interactions among MetS and its components, abnormal P-wave axis (aPWA), and mortality rates. METHODS: We analyzed data from 7526 adult participants with sinus rhythm recruited from the National Health and Nutrition Examination Survey III. MetS was classified based on the NCEP ATP III-2005 definition. aPWA included all P-wave axis outside 0-75°. The National Death Index was utilized to identify survival status. Hazard ratios (HRs) and 95% confidence intervals (CIs) categorized by aPWA, MetS, and their components were analyzed using Cox proportional hazards models to investigate all-cause and cardiovascular mortalities. RESULTS: Within a median follow-up period of 20.76 years, 4686 deaths were recorded, of which 1414 were attributable to cardiovascular disease. Participants with both MetS and aPWA had higher all-cause (HR: 1.45, 95% CI: 1.29-1.64, interaction P = 0.043) and cardiovascular (HR: 1.36, 95% CI: 1.02-1.79, interaction P-value = 0.058) mortality rates than participants without MetS and with a normal P-wave axis. Participants with the greatest number of MetS components and aPWA had a higher risk of all-cause mortality (HR: 1.70, 95% CI: 1.13-2.55, P = 0.011). CONCLUSIONS: Individuals with both aPWA and MetS have a higher risk of mortality, and those with a greater number of MetS components and aPWA have a higher risk of all-cause mortality. These findings highlight the significance of integrating ECG characteristics with metabolic health status in clinical assessment.

Macrophage based drug delivery: Key challenges and strategies.

As a natural immune cell and antigen presenting cell, macrophages have been studied and engineered to treat human diseases. Macrophages are well-suited for use as drug carriers because of their biological characteristics, such as excellent biocompatibility, long circulation, intrinsic inflammatory homing and phagocytosis. Meanwhile, macrophages' uniquely high plasticity and easy re-education polarization facilitates their use as part of efficacious therapeutics for the treatment of inflammatory diseases or tumors. Although recent studies have demonstrated promising advances in macrophage-based drug delivery, several challenges currently hinder further improvement of therapeutic effect and clinical application. This article focuses on the main challenges of utilizing macrophage-based drug delivery, from the selection of macrophage sources, drug loading, and maintenance of macrophage phenotypes, to drug migration and release at target sites. In addition, corresponding strategies and insights related to these challenges are described. Finally, we also provide perspective on shortcomings on the road to clinical translation and production.

SLC15A3 is transcriptionally regulated by HIF1α and p65 to worsen neuroinflammation in experimental ischemic stroke.

Systemic inflammatory stimulus is a risk factor for the incidence of ischemic stroke and contributes to poorer clinical outcomes. Solute carrier 15A3 (SLC15A3) is a peptide/histidine transporter that is implicated in regulating inflammatory responses. However, whether SLC15A3 affects the progression of ischemic stroke associated with systemic inflammation is unclear. The transient middle cerebral artery occlusion (tMCAO) mice with LPS administration (LPS/tMCAO) were prepared as an in vivo model, and LPS-induced BV2 cells under oxygen-glucose deprivation (OGD) exposure were utilized as an in vitro model. We found that SLC15A3 was highly expressed in the ischemic penumbra of LPS/tMCAO mice, and its inhibition reduced infarct area, attenuated neurological deficit, recovered motor function, and mitigated apoptotic neurons. Knockdown of SLC15A3 suppressed the proinflammatory M1-type markers and promoted the levels of M2-associated genes. The in vitro results confirmed that SLC15A3 overexpression promoted microglia polarizing towards M1 subtypes, while SLC15A3 inhibition exerted an opposite effect. In addition, we demonstrated that the p65 signaling pathway and HIF1α were activated by LPS/OGD. Luciferase reporter assay showed that inhibiting p65 using its specific inhibitor BAY 11-7082 or silencing HIF1α using siRNAs reduced the transcriptional activity of SLC15A3 in LPS/OGD-induced BV2 cells. Results in NIH 3T3 cells also confirmed that p65 and HIF1α directly bound to the SLC15A3 promoter to activate SLC15A3 transcription. In conclusion, this work shows that SLC15A3, transcriptionally activated by p65 and HIF1α, contributes to poor outcomes in ischemic stroke associated with systemic inflammation by promoting microglial cells polarizing towards M1 types.

Cognitive diagnostic assessment: A Q-matrix constraint-based neural network method.

Cognitive diagnosis is a crucial element of intelligent education that aims to assess the proficiency of specific skills or traits in students at a refined level and provide insights into their strengths and weaknesses for personalized learning. Researchers have developed numerous cognitive diagnostic models. However, previous studies indicate that diagnostic accuracy can be significantly influenced by the appropriateness of the model and the sample size. Thus, designing a general model that can adapt to different assumptions and sample sizes remains a considerable challenge. Artificial neural networks have been proposed as a promising approach in some studies. In this paper, we propose a cognitive diagnosis model of a neural network constrained by a Q-matrix and named QNN. Specifically, we employ the Q-matrix to determine the connections between neurons and the width and depth of the neural network. Moreover, to reduce the human effort in the training algorithm, we designed a self-organizing map-based cognitive diagnosis training framework called SOM-NN, which enables the QNN to be trained unsupervised. Extensive experimental results on simulated and real datasets demonstrate that our approaches are effective in both accuracy and interpretability. Notably, under unsupervised conditions, our approach has significant advantages on small sample datasets with high levels of guessing and slipping, especially on the pattern-wise agreement rates. This work bridges the gap between psychometrics and machine learning and provides a realistic and implementable reference solution for classroom instructional assessment and the cold start of personalized and adaptive assessment systems.

Lung adenocarcinoma patients with ROS1-rearranged tumors by sex and smoking intensity.

Background: ROS1 rearrangements (ROS1+) define a distinct molecular subset of lung adenocarcinomas. ROS1 + tumors are known to occur more in never-smokers, but the frequency and outcome of ROS1 positivity by sex and smoking intensity are not clearly documented. Patients and methods: This patient cohort study included all never- (<100 cigarettes lifetime) and light- (100 cigarettes-20 pack-years) smokers, and a sample of heavy-smokers. ROS1 + rates by sex and smoking intensity were compared within and beyond our study. Survival outcomes were analyzed using Kaplan-Meier curves and Cox proportional hazards models. Results: Of the 571 total patients, ROS1 + was detected in 24 (4.2%): 6.4% in men and 3.0% in women; 5.1% in never-, 5.7% in light-, and 1.8% in heavy-smokers (P=0.05). Among the 209 stage IIIB-IV patients, men had much higher ROS1 + rate (11.1%) not only than women (1.7%, P=0.004) in our study, but also than men (0.4%-1.8%) in 8 published studies (Ps = 0.0019-0.0001). ROS1+ rates were similar between never- (9.3%) and light-smokers (8.1%) and significantly lower in heavy-smokers (1.2%, P=0.017), a finding confirmed by 6 published studies (Ps = 0.041-0.0001). Overall survival of ROS1 + patients were significantly better than the ROS1- (P=0.023) mainly due to targeted therapy. Among patients who exhibited resistance to crizotinib, follow-up treatment of entrectinib and lorlatinib showed remarkable survival benefits. Conclusions: The ROS1 + rates were higher in men than in women, and similar in never- and light-smokers, more pronounced in stage IIIB-IV patients. Newer-generation ALK/ROS1-targeted drugs showed efficacy in a cohort of crizotinib resistant ROS1 + patients. These results, when validated, could assist efficiently accruing ROS1 + patients.

Identifying SLC2A6 as the novel protective factor in breast cancer by TP53-related genes affecting M1 macrophage infiltration.

The high heterogeneity of breast cancer (BC) caused by pathogenic gene mutations poses a challenge to immunotherapy, but the underlying mechanism remains unknown. The difference in the infiltration of M1 macrophages induced by TP53 mutations has a significant impact on BC immunotherapy. The aim of this study was to develop a TP53-related M1 macrophage infiltration molecular typing risk signature in BC and evaluate the biological functions of the key gene to find new immunotherapy biomarkers. Weighted correlation network analysis (WGCNA) and negative matrix factorization (NMF) were used for distinguishing BC subtypes. The signature and the nomogram were both constructed and evaluated. Biological functions of the novel signature gene SLC2A6 were confirmed through in vitro and in vivo experiments. RNA-Sequencing and protein profiling were used for detecting the possible mechanism of SLC2A6. The results suggested that four BC subtypes were distinguished by TP53-related genes that affect M1 macrophage infiltration. The signature constructed by molecular typing characteristics could evaluate BC's clinical features and tumor microenvironment. The nomogram could accurately predict the prognosis. The signature gene SLC2A6 was found to have an abnormally low expression in tumor tissues. Overexpression of SLC2A6 could inhibit proliferation, promote mitochondrial damage, and result in apoptosis of tumor cells. The HSP70 family member protein HSPA6 could bind with SLC2A6 and increase with the increased expression of SLC2A6. In summary, the risk signature provides a reference for BC risk assessment, and the signature gene SLC2A6 could act as a tumor suppressor in BC.

Iron biology.

Iron is a fundamental element for biological life, starting from bacteria till humans. Iron is essential for cell function and survival, energy production and metabolism, whereas increased levels cause oxidative stress. It is also a constituent of haemoglobin and thus it is necessary for oxygen transportation through the body. Given these multiple functions, the regulation of iron metabolism is complex and tight coupled with oxygen homeostasis at tissue and cellular levels, thanks to the interaction with the hypoxia inducible factor (HIF) system. In patients with chronic kidney disease (CKD), iron deficiency significantly contributes to anaemia development. This frequently overlaps with chronic inflammation, causing iron- restricted erythropoiesis. To add further complexity, metabolic hyperferritinemia may, on one side, increase the risk for CKD and, on the other, overlaps with functional iron deficiency. Excessive intracellular iron in certain cell types during CKD can also mediate cellular death (called ferroptosis), and contribute to the pathogenesis of kidney damage, atherosclerosis and vascular calcifications. This review is aimed at broadening the perspective of iron metabolism in the setting of CKD not just as a contributor to anaemia in CKD patients, but also as an important player with an impact on cell metabolism, renal fibrosis, and the cardiovascular system.

A long non-coding RNA functions as a competitive endogenous RNA to modulate TaNAC018 by acting as a decoy for tae-miR6206.

Increasing evidence indicates a strong correlation between the deposition of cuticular waxes and drought tolerance. However, the precise regulatory mechanism remains elusive. Here, we conducted a comprehensive transcriptome analysis of two wheat (Triticum aestivum) near-isogenic lines, the glaucous line G-JM38 rich in cuticular waxes and the non-glaucous line NG-JM31. We identified 85,143 protein-coding mRNAs, 4,485 lncRNAs, and 1,130 miRNAs. Using the lncRNA-miRNA-mRNA network and endogenous target mimic (eTM) prediction, we discovered that lncRNA35557 acted as an eTM for the miRNA tae-miR6206, effectively preventing tae-miR6206 from cleaving the NAC transcription factor gene TaNAC018. This lncRNA-miRNA interaction led to higher transcript abundance for TaNAC018 and enhanced drought-stress tolerance. Additionally, treatment with mannitol and abscisic acid (ABA) each influenced the levels of tae-miR6206, lncRNA35557, and TaNAC018 transcript. The ectopic expression of TaNAC018 in Arabidopsis also improved tolerance toward mannitol and ABA treatment, whereas knocking down TaNAC018 transcript levels via virus-induced gene silencing in wheat rendered seedlings more sensitive to mannitol stress. Our results indicate that lncRNA35557 functions as a competing endogenous RNA to modulate TaNAC018 expression by acting as a decoy target for tae-miR6206 in glaucous wheat, suggesting that non-coding RNA has important roles in the regulatory mechanisms responsible for wheat stress tolerance.

IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning.

BACKGROUND: The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses. FINDINGS: We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals. CONCLUSIONS: IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.

Predicting left ventricular remodeling post-MI through coronary physiological measurements based on computational fluid dynamics.

Early detection of left ventricular remodeling (LVR) is crucial. While cardiac magnetic resonance (CMR) provides valuable information, it has limitations. Coronary angiography-derived fractional flow reserve (caFFR) and index of microcirculatory resistance (caIMR) offer viable alternatives. 157 patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention were prospectively included. 23.6% of patients showed LVR. Machine learning algorithms constructed three LVR prediction models: Model 1 incorporated clinical and procedural parameters, Model 2 added CMR parameters, and Model 3 included echocardiographic and functional parameters (caFFR and caIMR) with Model 1. The random forest algorithm showed robust performance, achieving AUC of 0.77, 0.84, and 0.85 for Models 1, 2, and 3. SHAP analysis identified top features in Model 2 (infarct size, microvascular obstruction, admission hemoglobin) and Model 3 (current smoking, caFFR, admission hemoglobin). Findings indicate coronary physiology and echocardiographic parameters effectively predict LVR in patients with STEMI, suggesting their potential to replace CMR.

HRCL: Hierarchical Relation Contrastive Learning for Low-Resource Relation Extraction.

Low-resource relation extraction (LRE) aims to extract the relationships between given entities from natural language sentences in low-resource application scenarios, which has been an incredibly challenging task due to the limited annotated corpora. Existing studies either leverage self-training schemes to expand the scale of labeled data, while the error accumulation of pseudo-labels' selection bias provoke the gradual drift problem in subsequent relation prediction, or utilize the instance-wise contrastive learning that fails to distinguish those sentence pairs with similar semantics. To alleviate these defects, this article introduces a novel contrastive learning framework called hierarchical relation contrastive learning (HRCL) for LRE. HRCL leverages task-related instruction description and schema-constrained as prompts to generate high-level relation representations. To enhance the efficacy of contrastive learning, we further employ hierarchical affinity propagation clustering (HiPC) to derive hierarchical signals from relational feature space with a hierarchy cross-attention (HCA) mechanism and effectively optimize pair-level relation features through relation-wise contrastive learning. Exhaustive experiments have been conducted on five public relation extraction (RE) datasets in low-resource settings. The results demonstrate the effectiveness and robustness of HRCL and outperform the current state-of-the-art (SOTA) model by 6.56% on average in terms of B3F1 . Our source code is publicly available at https://github.com/Phevos75/HRCLRE.

Emerging concern on air pollution and health: Trade-off between air pollution exposure and physical activity.

Air pollution is a major contributor to the global disease burden, especially affecting respiratory and cardiovascular health. However, physical activity is associated with improved lung function, a slower decline in lung function, and lower mortality. The public is more likely to be exposed to air pollution during outdoor physical activity. However, studies on how long-term and short-term exposure to air pollution interacts with physical activity yield inconsistent results, and the thresholds for air pollution and physical activity remain unclear. Thus, more studies are needed to provide sufficient evidence to guide the public to safely engage in outdoor physical activity when exposed to air pollution.

Mechanisms of norcantharidin against renal tubulointerstitial fibrosis.

Renal tubulointerstitial fibrosis (RTIF) is a common feature and inevitable consequence of all progressive chronic kidney diseases, leading to end-stage renal failure regardless of the initial cause. Although research over the past few decades has greatly improved our understanding of the pathophysiology of RTIF, until now there has been no specific treatment available that can halt the progression of RTIF. Norcantharidin (NCTD) is a demethylated analogue of cantharidin, a natural compound isolated from 1500 species of medicinal insect, the blister beetle (Mylabris phalerata Pallas), traditionally used for medicinal purposes. Many studies have found that NCTD can attenuate RTIF and has the potential to be an anti-RTIF drug. This article reviews the recent progress of NCTD in the treatment of RTIF, with emphasis on the pharmacological mechanism of NCTD against RTIF.

Obstructive sleep apnea in relation to beat-to-beat, reading-to-reading, and day-to-day blood pressure variability.

We investigated blood pressure (BP) variability as assessed by beat-to-beat, reading-to-reading and day-to-day BP variability indices in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). In 786 hospitalized hypertensives (mean age, 53.2 years; 42.2% women), we performed 10-min beat-to-beat (n = 705), 24-h ambulatory (n = 779), and 7-day home BP (n = 445) measurements and the full overnight polysomnography. Mild, moderate and severe OSAHS were defined as an apnea-hypopnea index of 5-14, 15-29, and ≥ 30 events per hour, respectively. BP variability indices including variability independent of the mean (VIM), average real variability (ARV), and maximum-minimum difference (MMD), were compared across the OSAHS severity groups. In univariate analysis, beat-to-beat systolic VIM and MMD, reading-to-reading asleep systolic and diastolic ARV and MMD increased from patients without OSAHS, to patients with mild, moderate and severe OSAHS. This increasing trend for beat-to-beat systolic VIM and MMD remained statistically significant after adjustment for confounders (P ≤ 0.047). There was significant (P ≤ 0.039) interaction of the presence and severity of OSAHS with age and body mass index in relation to the beat-to-beat systolic VIM and MMD and with the presence of diabetes mellitus in relation to asleep systolic ARV. The association was stronger in younger (age < 50 years) and obese (body mass index ≥ 28 kg/m²) and diabetic patients. None of the day-to-day BP variability indices reached statistical significance (P ≥ 0.16). BP variability, in terms of beat-to-beat systolic VIM and MMD and asleep reading-to-reading asleep systolic ARV, were higher with the more severe OSAHS, especially in younger and obese and diabetic patients.

Variability of large timescale functional networks in patients with disorders of consciousness.

Objective: Most brain function assessments for disorders of consciousness (DOC) utilized quantified characteristics, measured only once, ignoring the variation of patients' brain states. The study aims to investigate the brain activities of patients with DOC from a new perspective: variability of a large timescale functional network. Methods: Forty-nine patients were enrolled in this study and performed a 1-week behavioral assessment. Subsequently, each patient received electroencephalography (EEG) recordings five times daily at 2-h intervals. Functional connectivity and networks were measured by weighted phase lag index and complex network parameters (characteristic path length, cluster coefficient, and betweenness centrality). The relative coefficient of variation (CV) of network parameters was measured to evaluate functional network variability. Results: Functional networks of patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS) showed significantly higher segregation (characteristic path length) and lower centrality (betweenness centrality) than emerging from the minimal conscious state (EMCS) and minimal conscious state (MCS), as well as lower integration (cluster coefficient) than MCS. The functional networks of VS/UWS patients consistently presented the highest variability in segregation and integration (i.e., highest CV values of characteristic path length and cluster coefficient) on a larger time scale than MCS and EMCS. Moreover, the CV values of characteristic path length and cluster coefficient showed a significant inverse correlation with the Coma Recovery Scale-Revised scores (CRS-R). The CV values of network betweenness centrality, particularly of the cento-parietal region, showed a positive correlation with the CRS-R. Conclusion: The functional networks of VS/UWS patients present the most invariant segregation and integration but divergent centrality on the large time scale networks than MCS and EMCS. Significance: The variations observed within large timescale functional networks significantly correlate with the degree of consciousness impairment. This finding augments our understanding of the neurophysiological mechanisms underpinning disorders of consciousness.

New-onset hypertension as a contributing factor to the incidence of atrial fibrillation in the elderly.

Hypertension and atrial fibrillation are closely related. However, hypertension is already prevalent in young adults, but atrial fibrillation usually occurs in the elderly. In the present analysis, we investigated incident atrial fibrillation in relation to new-onset hypertension in an elderly Chinese population. Our study participants were elderly (≥65 years) hypertensive residents, recruited from community health centers in the urban Shanghai (n = 4161). Previous and new-onset hypertension were defined as the use of antihypertensive medication or elevated systolic/diastolic blood pressure (≥140/90 mmHg), respectively, at entry and during follow-up on ≥ 2 consecutive clinic visits. Atrial fibrillation was detected by a 30-s single-lead electrocardiography (ECG, AliveCor® Heart Monitor) and further evaluated with a regular 12-lead ECG. During a median of 2.1 years follow-up, the incidence rate of atrial fibrillation was 7.60 per 1000 person-years in all study participants; it was significantly higher in patients with new-onset hypertension (n = 368) than those with previous hypertension (n = 3793, 15.76 vs. 6.77 per 1000 person-years, P = 0.02). After adjustment for confounding factors, the hazard ratio for the incidence of atrial fibrillation was 2.21 (95% confidence interval 1.15-4.23, P = 0.02) in patients with new-onset hypertension versus those with previous hypertension. The association was even stronger in those aged ≥ 75 years (hazard ratio 2.70, 95% confidence interval 1.11-6.56, P = 0.03). In patients with previous hypertension, curvilinear association (P for non-linear trend = 0.04) was observed between duration of hypertension and the risk of incident atrial fibrillation, with a higher risk in short- and long-term than mid-term duration of hypertension. Our study showed a significant association between new-onset hypertension and the incidence of atrial fibrillation in elderly Chinese. In an elderly Chinese population with previous and new-onset hypertension, we found that the new-onset hypertension during follow-up, compared with previous hypertension, was associated with a significantly higher risk of incident atrial fibrillation. In patients with previous hypertension, curvilinear association was observed between duration of hypertension and the risk of incident atrial fibrillation, with a higher risk in short- and long-term than mid-term duration of hypertension.