Predicting Serious Bacterial Infections Among Hypothermic Infants in the Emergency Department.

BACKGROUND: There is insufficient evidence to guide the initial evaluation of hypothermic infants. We aimed to evaluate risk factors for serious bacterial infections (SBI) among hypothermic infants presenting to the emergency department (ED). METHODS: We conducted a multicenter case-control study among hypothermic (rectal temperature <36.5°C) infants ≤90 days presenting to the ED who had a blood culture collected. Our outcome was SBI (bacteremia, bacterial meningitis, and/or urinary tract infection). We performed 1:2 matching. Historical, physical examination and laboratory covariables were determined based on the literature review from febrile and hypothermic infants and used logistic regression to identify candidate risk factors. RESULTS: Among 934 included infants, 57 (6.1%) had an SBI. In univariable analyses, the following were associated with SBI: age > 21 days, fever at home or in the ED, leukocytosis, elevated absolute neutrophil count, thrombocytosis, and abnormal urinalysis. Prematurity, respiratory distress, and hypothermia at home were negatively associated with SBI. The full multivariable model exhibited a c-index of 0.91 (95% confidence interval: 0.88-0.94). One variable (abnormal urinalysis) was selected for a reduced model, which had a c-index of 0.82 (95% confidence interval: 0.75-0.89). In a sensitivity analysis among hypothermic infants without fever (n = 22 with SBI among 116 infants), leukocytosis, absolute neutrophil count, and abnormal urinalysis were associated with SBI. CONCLUSIONS: Historical, examination, and laboratory data show potential as variables for risk stratification of hypothermic infants with concern for SBI. Larger studies are needed to definitively risk stratify this cohort, particularly for invasive bacterial infections.

High-rate leading spikes in propagating spike sequences predict seizure outcome in surgical patients with temporal lobe epilepsy.

Inter-ictal spikes aid in the diagnosis of epilepsy and in planning surgery of medication-resistant epilepsy. However, the localizing information from spikes can be unreliable because spikes can propagate, and the burden of spikes, often assessed as a rate, does not always correlate with the seizure onset zone or seizure outcome. Recent work indicates identifying where spikes regularly emerge and spread could localize the seizure network. Thus, the current study sought to better understand where and how rates of single and coupled spikes, and especially brain regions with high-rate and leading spike of a propagating sequence, informs the extent of the seizure network. In 37 patients with medication-resistant temporal lobe seizures, who had surgery to treat their seizure disorder, an algorithm detected spikes in the pre-surgical depth inter-ictal EEG. A separate algorithm detected spike propagation sequences and identified the location of leading and downstream spikes in each sequence. We analysed the rate and power of single spikes on each electrode and coupled spikes between pairs of electrodes, and the proportion of sites with high-rate, leading spikes in relation to the seizure onset zone of patients seizure free (n = 19) and those with continuing seizures (n = 18). We found increased rates of single spikes in mesial temporal seizure onset zone (ANOVA, P < 0.001, η2 = 0.138), and increased rates of coupled spikes within, but not between, mesial-, lateral- and extra-temporal seizure onset zone of patients with continuing seizures (P < 0.001; η2 = 0.195, 0.113 and 0.102, respectively). In these same patients, there was a higher proportion of brain regions with high-rate leaders, and each sequence contained a greater number of spikes that propagated with a higher efficiency over a longer distance outside the seizure onset zone than patients seizure free (Wilcoxon, P = 0.0172). The proportion of high-rate leaders in and outside the seizure onset zone could predict seizure outcome with area under curve = 0.699, but not rates of single or coupled spikes (0.514 and 0.566). Rates of coupled spikes to a greater extent than single spikes localize the seizure onset zone and provide evidence for inter-ictal functional segregation, which could be an adaptation to avert seizures. Spike rates, however, have little value in predicting seizure outcome. High-rate spike sites leading propagation could represent sources of spikes that are important components of an efficient seizure network beyond the clinical seizure onset zone, and like the seizure onset zone these, too, need to be removed, disconnected or stimulated to increase the likelihood for seizure control.

Interictal Gamma Event Connectivity Differentiates the Seizure Network and Outcome in Patients after Temporal Lobe Epilepsy Surgery.

Studies of interictal EEG functional connectivity in the epileptic brain seek to identify abnormal interactions between brain regions involved in generating seizures, which clinically often is defined by the seizure onset zone (SOZ). However, there is evidence for abnormal connectivity outside the SOZ (NSOZ), and removal of the SOZ does not always result in seizure control, suggesting, in some cases, that the extent of abnormal connectivity indicates a larger seizure network than the SOZ. To better understand the potential differences in interictal functional connectivity in relation to the seizure network and outcome, we computed event connectivity in the theta (4-8 Hz, ThEC), low-gamma (30-55 Hz, LGEC), and high-gamma (65-95 Hz, HGEC) bands from interictal depth EEG recorded in surgical patients with medication-resistant seizures suspected to begin in the temporal lobe. Analysis finds stronger LGEC and HGEC in SOZ than NSOZ of seizure-free (SF) patients (p = 1.10e-9, 0.0217), but no difference in not seizure-free (NSF) patients. There were stronger LGEC and HGEC between mesial and lateral temporal SOZ of SF than NSF patients (p = 0.00114, 0.00205), and stronger LGEC and ThEC in NSOZ of NSF than SF patients (p = 0.0089, 0.0111). These results show that event connectivity is sensitive to differences in the interactions between regions in SOZ and NSOZ and SF and NSF patients. Patients with differential strengths in event connectivity could represent a well-localized seizure network, whereas an absence of differences could indicate a larger seizure network than the one localized by the SOZ and higher likelihood for seizure recurrence.

Warning Labels and High-Powered Magnet Exposures.

BACKGROUND AND OBJECTIVES: High-powered magnets are among the most dangerous childhood foreign bodies. Consumer advocates and physicians have called for these products to be effectively banned, but manufacturers assert warning labels would sufficiently mitigate risk. METHODS: Subjects from Injuries, Morbidity, and Parental Attitudes Concerning Tiny High-powered Magnets (IMPACT of Magnets), a retrospective, multicenter study of children with high-powered magnet exposures (ie, ingestion or bodily insertion), were contacted. Consenting participants responded to a standardized questionnaire regarding the presence and utility of warning labels, magnet product manufacturer, and attitudes around risk. RESULTS: Of 596 patients in the IMPACT study, 173 parents and 1 adult patient were reached and consented to participate. The median age was 7.5 years. Subjects reported not knowing if a warning label was present in 60 (53.6%) cases, whereas 25 (22.3%) stated warnings were absent. Warnings were present in 28 (24.1%) cases but only 13 (46.4%) reported reading them. A manufacturer was identified by families in 28 (16.1%) exposures; 25 of these were domestic and 27 had warnings. Subjects reported knowing magnets were dangerous in 58% of the cases, although 44.3% believed they were children's toys and only 6.9% knew high-powered magnets were previously removed from the United States market. CONCLUSIONS: Over 90% of subjects from the IMPACT study didn't know if warning labels were present or failed to read them if they were, whereas almost half believed high-powered magnets were children's toys. Warning labels on high-powered magnet products are, therefore, unlikely to prevent injuries in children.

Variability in emergency department management of hypothermic infants ≤90 days of age.

OBJECTIVES: Hypothermic infants are at risk for serious bacterial and herpes simplex virus infections, but there are no evidence-based guidelines for managing these patients. We sought to characterize variations and trends in care for these infants in the emergency department (ED). METHODS: We conducted a retrospective cross-sectional study of infants under 90 days old presenting to 32 pediatric EDs from 2009 through 2019 with an International Classification of Diseases diagnosis code for hypothermia. We characterized variation in diagnostic testing, antimicrobial treatment, and disposition of children in three age groups (≤30 days, 31-60 days, and 61-90 days old) and analyzed care trends. RESULTS: Of 7828 ED encounters meeting inclusion criteria, most (81%) were ≤ 30 days of age. Infants in the 0-30 days old age group, compared to 61-90 days old age group, had a higher proportion of blood (75% vs. 68%), urine (72% vs. 64%), and cerebrospinal fluid (CSF; 35% vs. 22%) cultures obtained (p < 0.01) and greater antimicrobial use (81% vs. 68%; p < 0.01) in the ED. From 2009 to 2019, C-reactive protein (CRP), and procalcitonin usage steadily increased, from 25% to 40% and 0% to 30% respectively, while antibiotic use (83% to 77%), CSF testing (53% to 44%), and chest radiography (47% to 34%) decreased. Considerable interhospital variation was noted in testing and treatment, including CSF testing (14-70%), inflammatory markers (CRP and procalcitonin; 8-88%), and antibiotics (56-92%). CONCLUSION: Substantial hospital-level variation exists for managing hypothermic infants in the ED. Long-term trends are notable for changing practice over time, particularly with increased use of inflammatory markers. Prospective studies are needed to risk stratify and optimize care for this population.

High-Powered Magnet Exposures in Children: A Multi-Center Cohort Study.

BACKGROUND AND OBJECTIVES: High-powered magnets were effectively removed from the US market by the Consumer Product Safety Commission (CPSC) in 2012 but returned in 2016 after federal court decisions. The United States Court of Appeals for the 10th Circuit cited imprecise data among other reasons as justification for overturning CPSC protections. Since then, incidence of high-powered magnet exposure has increased markedly, but outcome data are limited. In this study, we aim to describe the epidemiology and outcomes in children seeking medical care for high-powered magnets after reintroduction to market. METHODS: This is a multicenter, retrospective cohort study of patients aged 0 to 21 years with a confirmed high-powered magnet exposure (ie, ingestion or insertion) at 25 children's hospitals in the United States between 2017 and 2019. RESULTS: Of 596 patients with high-powered magnet exposures identified, 362 (60.7%) were male and 566 (95%) were <14 years of age. Nearly all sought care for magnet ingestion (n = 574, 96.3%), whereas 17 patients (2.9%) presented for management of nasal or aural magnet foreign bodies, 4 (0.7%) for magnets in their genitourinary tract, and 1 patient (0.2%) had magnets in their respiratory tract. A total of 57 children (9.6%) had a life-threatening morbidity; 276 (46.3%) required an endoscopy, surgery, or both; and 332 (55.7%) required hospitalization. There was no reported mortality. CONCLUSIONS: Despite being intended for use by those >14 years of age, high-powered magnets frequently cause morbidity and lead to high need for invasive intervention and hospitalization in children of all ages.

Dendritic and parallel processing of visual threats in the retina control defensive responses.

Approaching predators cast expanding shadows (i.e., looming) that elicit innate defensive responses in most animals. Where looming is first detected and how critical parameters of predatory approaches are extracted are unclear. In mice, we identify a retinal interneuron (the VG3 amacrine cell) that responds robustly to looming, but not to related forms of motion. Looming-sensitive calcium transients are restricted to a specific layer of the VG3 dendrite arbor, which provides glutamatergic input to two ganglion cells (W3 and OFFα). These projection neurons combine shared excitation with dissimilar inhibition to signal approach onset and speed, respectively. Removal of VG3 amacrine cells reduces the excitation of W3 and OFFα ganglion cells and diminishes defensive responses of mice to looming without affecting other visual behaviors. Thus, the dendrites of a retinal interneuron detect visual threats, divergent circuits downstream extract critical threat parameters, and these retinal computations initiate an innate survival behavior.

Quantum thermodynamics from the nonequilibrium dynamics of open systems: Energy, heat capacity, and the third law.

In a series of papers, we intend to take the perspective of open quantum systems and examine from their nonequilibrium dynamics the conditions when the physical quantities, their relations, and the laws of thermodynamics become well defined and viable for quantum many-body systems. We first describe how an open-system nonequilibrium dynamics (ONEq) approach is different from the closed combined system +  environment in a global thermal state (CGTs) setup. Only after the open system equilibrates will it be amenable to conventional thermodynamics descriptions, thus quantum thermodynamics (QTD) comes at the end rather than assumed in the beginning. The linkage between the two comes from the reduced density matrix of ONEq in that stage having the same form as that of the system in the CGTs. We see the open-system approach having the advantage of dealing with nonequilibrium processes as many experiments in the near future will call for. Because it spells out the conditions of QTD's existence, it can also aid us in addressing the basic issues in quantum thermodynamics from first principles in a systematic way. We then study one broad class of open quantum systems where the full nonequilibrium dynamics can be solved exactly, that of the quantum Brownian motion of N strongly coupled harmonic oscillators, interacting strongly with a scalar-field environment. In this paper, we focus on the internal energy, heat capacity, and the third law. We show for this class of physical models, amongst other findings, the extensive property of the internal energy, the positivity of the heat capacity, and the validity of the third law from the perspective of the behavior of the heat capacity toward zero temperature. These conclusions obtained from exact solutions and quantitative analysis clearly disprove claims of negative specific heat in such systems and dispel allegations that in such systems the validity of the third law of thermodynamics relies on quantum entanglement. They are conceptually and factually unrelated issues. Entropy and entanglement will be the main theme of our second paper on this subject matter.

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity.

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function.

A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection.

We develop an integrative Bayesian predictive modeling framework that identifies individual pathological brain states based on the selection of fluoro-deoxyglucose positron emission tomography (PET) imaging biomarkers and evaluates the association of those states with a clinical outcome. We consider data from a study on temporal lobe epilepsy (TLE) patients who subsequently underwent anterior temporal lobe resection. Our modeling framework looks at the observed profiles of regional glucose metabolism in PET as the phenotypic manifestation of a latent individual pathologic state, which is assumed to vary across the population. The modeling strategy we adopt allows the identification of patient subgroups characterized by latent pathologies differentially associated to the clinical outcome of interest. It also identifies imaging biomarkers characterizing the pathological states of the subjects. In the data application, we identify a subgroup of TLE patients at high risk for post-surgical seizure recurrence after anterior temporal lobe resection, together with a set of discriminatory brain regions that can be used to distinguish the latent subgroups. We show that the proposed method achieves high cross-validated accuracy in predicting post-surgical seizure recurrence.

Functional MRI Correlates of Resting-State Temporal Theta and Delta EEG Rhythms.

PURPOSE: The EEG rhythms demonstrate changes in frequency and power with spontaneous changes in behavioral state that do not have well-understood metabolic correlates within the brain. To investigate this question and compare the temporal lobe theta and delta rhythms, resting-state functional MRI was obtained with simultaneous EEG. METHODS: Simultaneous EEG-functional MRI was recorded from 14 healthy sleep-deprived subjects in awake and drowsy states. Scalp electrodes corresponding to bilateral temporal lobes were used to calculate delta and theta band power. The resulting time series was used as input in a general linear model, and the final power curves were convolved with the standard hemodynamic response function. Resulting images were thresholded at Z > 2.0. RESULTS: Positive and negative correlations for unilateral theta and delta rhythms were present bilaterally in different structures and with differing correlation signs. Theta rhythm positive correlation was present in hindbrain, peri-opercular, and frontoparietal regions and subcortical gray structures, whereas negative correlation was present in parietooccipital cortex. Delta rhythm positive correlation was present in parietooccipital cortex, and negative correlation roughly resembled positive correlations for the theta rhythm. CONCLUSIONS: Temporal lobe theta and delta rhythms are correlated with functional MRI signal in an almost mutually exclusive distribution. The different distributions indicate different corresponding networks. These normal findings supplement the understanding of theta and delta rhythm significance.

Bayesian vector autoregressive model for multi-subject effective connectivity inference using multi-modal neuroimaging data.

In this article a multi-subject vector autoregressive (VAR) modeling approach was proposed for inference on effective connectivity based on resting-state functional MRI data. Their framework uses a Bayesian variable selection approach to allow for simultaneous inference on effective connectivity at both the subject- and group-level. Furthermore, it accounts for multi-modal data by integrating structural imaging information into the prior model, encouraging effective connectivity between structurally connected regions. They demonstrated through simulation studies that their approach resulted in improved inference on effective connectivity at both the subject- and group-level, compared with currently used methods. It was concluded by illustrating the method on temporal lobe epilepsy data, where resting-state functional MRI and structural MRI were used. Hum Brain Mapp 38:1311-1332, 2017. © 2016 Wiley Periodicals, Inc.

Time-dependence of graph theory metrics in functional connectivity analysis.

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations.

Functional connectivity homogeneity correlates with duration of temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) is often associated with progressive changes to seizures, memory, and mood during its clinical course. However, the cerebral changes related to this progression are not well understood. Because the changes may be related to changes in brain networks, we used functional connectivity MRI (fcMRI) to determine whether brain network parameters relate to the duration of TLE. Graph theory-based analysis of the sites of reported regions of TLE abnormality was performed on resting-state fMRI data in 48 subjects: 24 controls, 13 patients with left TLE, and 11 patients with right TLE. Various network parameters were analyzed including betweenness centrality (BC), clustering coefficient (CC), path length (PL), small-world index (SWI), global efficiency (GE), connectivity strength (CS), and connectivity diversity (CD). These were compared for patients with TLE as a group, compared to controls, and for patients with left and right TLE separately. The association of changes in network parameters with epilepsy duration was also evaluated. We found that CC, CS, and CD decreased in subjects with TLE compared to control subjects. Analyzed according to epilepsy duration, patients with TLE showed a progressive reduction in CD. In conclusion, we found that several network parameters decreased in patients with TLE compared to controls, which suggested reduced connectivity in TLE. Reduction in CD associated with epilepsy duration suggests a homogenization of connections over time in TLE, indicating a reduction of the normal repertoire of stronger and weaker connections to other brain regions.

Epidemiology, disease burden and outcomes of cirrhosis in a large secondary care hospital in South Auckland, New Zealand.

BACKGROUND: Liver cirrhosis is an important cause of morbidity and mortality; however, little is known about its impact in New Zealand. AIMS: We aim to determine the disease burden, epidemiology and outcomes of cirrhotic patients. METHODS: This is a retrospective study of cirrhosis patients under secondary public hospital care in a geographically defined region, between the years 2000 and 2011. Cirrhosis complications and mortality was recorded. Poisson log-linear regression analysis was performed for incidence rate ratio (IRR) and Cox regression analysis was used to analyse time-related events. RESULTS: Seven hundred and forty-six cirrhotic patients were analysed; most were European/Other (39.9%), Pacific islanders (21.6%), Southeast Asian/Chinese (17.8%) and Maori (12.3%). 68.4% were male. The common primary aetiologies for cirrhosis were chronic hepatitis B (CHB) cirrhosis (37.3%), alcoholic liver disease (ALD) cirrhosis (24.1%), chronic hepatitis C (CHC) cirrhosis (22.3%) and non-alcoholic fatty liver disease (NAFLD) cirrhosis (16.4%). The hepatocellular carcinoma (HCC) mortality rates were highest in NAFLD and CHB cirrhosis groups (3.0 and 3.1 per 100 patient-year respectively), compared with ALD and CHC groups (2.2 and 1.4 per 100 patient-year, all P < 0.05 respectively). Patients with ALD and NAFLD cirrhosis had the highest all-cause and non-HCC mortality rate compared with viral hepatitis cirrhosis groups. The IRR for HCC incidence, liver-related mortality and HCC mortality were 1.087, 1.098 and 1.114, respectively (all P < 0.001), suggesting increasing incidence and disease burden over the study period. CONCLUSION: The number of cirrhotic patients in secondary care is increasing steadily. Cirrhosis complications and mortality rates are also rising, particularly the incidence and mortality of HCC.

Distinct gene expression profiles of proximal and distal colorectal cancer: implications for cytotoxic and targeted therapy.

Colorectal cancer (CRC) is a heterogeneous disease with genetic profiles and clinical outcomes dependent on the anatomic location of the primary tumor. How location has an impact on the molecular makeup of a tumor and how prognostic and predictive biomarkers differ between proximal versus distal colon cancers is not well established. We investigated the associations between tumor location, KRAS and BRAF mutation status, and the messenger RNA (mRNA) expression of proteins involved in major signaling pathways, including tumor growth (epidermal growth factor receptor (EGFR)), angiogenesis (vascular endothelial growth factor receptor 2 (VEGFR2)), DNA repair (excision repair cross complement group 1 (ERCC1)) and fluoropyrimidine metabolism (thymidylate synthase (TS)). Formalin-fixed paraffin-embedded tumor specimens from 431 advanced CRC patients were analyzed. The presence of seven different KRAS base substitutions and the BRAF V600E mutation was determined. ERCC1, TS, EGFR and VEGFR2 mRNA expression levels were detected by reverse transcriptase-PCR. BRAF mutations were significantly more common in the proximal colon (P<0.001), whereas KRAS mutations occurred at similar frequencies throughout the colorectum. Rectal cancers had significantly higher ERCC1 and VEGFR2 mRNA levels compared with distal and proximal colon tumors (P=0.001), and increased TS levels compared with distal colon cancers (P=0.02). Mutant KRAS status was associated with lower ERCC1, TS, EGFR and VEGFR2 gene expression in multivariate analysis. In a subgroup analysis, this association remained significant for all genes in the proximal colon and for VEGFR2 expression in rectal cancers. The mRNA expression patterns of predictive and prognostic biomarkers, as well as associations with KRAS and BRAF mutation status depend on primary tumor location. Prospective studies are warranted to confirm these findings and determine the underlying mechanisms.

Network analysis of the default mode network using functional connectivity MRI in Temporal Lobe Epilepsy.

Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal fluctuations over time. Temporal Lobe Epilepsy (TLE) is the most common type of adult epilepsy and involves multiple brain networks. The default mode network (DMN) is involved in conscious, resting state cognition and is thought to be affected in TLE where seizures cause impairment of consciousness. The DMN in epilepsy was examined using seed based fcMRI. The anterior and posterior hubs of the DMN were used as seeds in this analysis. The results show a disconnection between the anterior and posterior hubs of the DMN in TLE during the basal state. In addition, increased DMN connectivity to other brain regions in left TLE along with decreased connectivity in right TLE is revealed. The analysis demonstrates how seed-based fcMRI can be used to probe cerebral networks in brain disorders such as TLE.

Metabolic syndrome delays HBeAg seroclearance in Chinese patients with hepatitis B.

BACKGROUND: Delayed hepatitis B e antigen (HBeAg) seroclearance increases the risk of cirrhosis and hepatocellular carcinoma (HCC). The effect of metabolic syndrome (MetS) on HBeAg seroclearance in chronic hepatitis B (CHB) patients remains unclear. AIMS: To examine the effect of MetS on HBeAg seroclearance. METHODS: A prospective cohort of 413 treatment-naïve HBeAg-positive CHB patients from 2005 to 2012 was studied. Clinical, virological and histological parameters were evaluated. The patients were classified into three groups according to the metabolic characteristics; normal, pre-MetS and MetS based on the International Diabetes Federation criteria. The primary outcome was age at HBeAg seroclearance. RESULTS: The overall HBeAg seroclearance rate was 11.4% per annum during 19 351 patient-months of follow-up with no difference in HBeAg seroclearance rates between 162 treatment-free and 251 patients receiving nucleos(t)ide analogues. Patients with pre-MetS and MetS were older when HBeAg seroclearance occurred (44 ± 12 and 53 ± 7 years, respectively) than the normal patients (37 ± 9 years, all P < 0.01). Patients with pre-MetS and MetS had more advanced liver fibrosis (33.0% and 53.1%, respectively) than the normal patients (18.4%, all P < 0.05). By the age of 50, 59.3% of the metabolic normal patients, 42.1% of the pre-MetS and 18.7% of the MetS patients had achieved HBeAg seroclearance (all P < 0.05, except P = 0.07 for pre-MetS vs. MetS). In multivariate analysis, MetS and type II diabetes at baseline were predictors of delayed HBeAg seroclearance after adjusting for viral load, anti-viral therapy and necroinflammatiom. CONCLUSION: Chinese patients with chronic hepatitis B and with pre-metabolic syndrome or metabolic syndrome have delayed HBeAg seroclearance.

Functional connectivity of hippocampal networks in temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) affects brain areas beyond the temporal lobes due to connections of the hippocampi and other temporal lobe structures. Using functional connectivity magnetic resonance imaging (MRI), we determined the changes of hippocampal networks in TLE to assess for a more complete distribution of abnormality. METHODS: Regions of interest (ROIs) were defined in the right and left hippocampi in three groups of participants: left TLE (n = 13), right TLE (n = 11), and healthy controls (n = 16). Brain regions functionally connected to these ROIs were identified by correlating resting-state low-frequency functional MRI (fMRI) blood oxygenation level-dependent (BOLD) signal fluctuations. The grouped results were compared using independent sample t-test. RESULTS: TLE was associated with increased hippocampal connectivity involving several key areas of the limbic network (temporal lobe, insula, thalamus), frontal lobes, angular gyrus, basal ganglia, brainstem, and cerebellum, along with reduced connectivity involving areas of the sensorimotor cortex (visual, somatosensory, auditory, primary motor) and the default mode network (precuneus). Left TLE had more marked connectivity changes than right TLE. SIGNIFICANCE: The observed connectivity changes in TLE indicate dysfunctional networks that underlie widespread brain involvement in TLE. There are identifiable differences in the connectivity of the hippocampi between left and right TLE.