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Internet addiction (IA) refers to excessive internet use that causes cognitive impairment or distress. Understanding the neurophysiological mechanisms underpinning IA is crucial for enabling an accurate diagnosis and informing treatment and prevention strategies. Despite the recent increase in studies examining the neurophysiological traits of IA, their findings often vary. To enhance the accuracy of identifying key neurophysiological characteristics of IA, this study used the phase lag index (PLI) and weighted PLI (WPLI) methods, which minimize volume conduction effects, to analyze the resting-state electroencephalography (EEG) functional connectivity. We further evaluated the reliability of the identified features for IA classification using various machine learning methods.
Methods
Ninety-two participants (42 with IA and 50 healthy controls (HCs)) were included. PLI and WPLI values for each participant were computed, and values exhibiting significant differences between the two groups were selected as features for the subsequent classification task.
Results
Support vector machine (SVM) achieved an 83% accuracy rate using PLI features and an improved 86% accuracy rate using WPLI features. t-test results showed analogous topographical patterns for both the WPLI and PLI. Numerous connections were identified within the delta and gamma frequency bands that exhibited significant differences between the two groups, with the IA group manifesting an elevated level of phase synchronization.
Conclusions
Functional connectivity analysis and machine learning algorithms can jointly distinguish participants with IA from HCs based on EEG data. PLI and WPLI have substantial potential as biomarkers for identifying the neurophysiological traits of IA.
The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.
Methods
A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.
Results
Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.
Conclusions
These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.
For coherent systems with components and active redundancies having heterogeneous and dependent lifetimes, we prove that the lifetime of system with redundancy at component level is stochastically larger than that with redundancy at system level. In particular, in the setting of homogeneous components and redundancy lifetimes linked by an Archimedean survival copula, we develop sufficient conditions for the reversed hazard rate order, the hazard rate order and the likelihood ratio order between two system lifetimes, respectively. The present results substantially generalize some related results in the literature. Several numerical examples are presented to illustrate the findings as well.
This paper presents a three-stage E-band low-noise amplifier (LNA) fabricated in a 28-nm Complementary Metal Oxide Semiconductor High-Performance Compact Plus process. The proposed E-band LNA achieves a peak gain of 16.8 dB, exhibiting a gain variation of less than ±0.5 dB across the frequency range of 67.8–90.4 GHz. The measured 3-dB gain bandwidth spans from 64 to 93.8 GHz, and the minimum measured noise figure (NF) is 3.8 dB. By employing a one-stage common-source with a two-stage cascode topology, the proposed E-band LNA demonstrates competitiveness in terms of gain flatness and NF when compared to recently published E-band CMOS LNAs.
Reducing drag under high turbulence is a critical but challenging issue that has engendered great concern. This study utilizes hydrophilic tips in superhydrophobic (SHP) grooves to enhance the stability of plastron, which results in a considerable drag reduction ($DR$) up to 62 %, at Reynolds number ($Re$) reaching $2.79 \times 10^{4}$. The effect of the spacing width $w$ of the microgrooves on both $DR$ and flow structures is investigated. Experimental results demonstrate that $DR$ increases as either microgroove spacing $w$ or $Re$ increases. The velocity fields obtained using particle image velocimetry indicate that the air-filled SHP grooves induce a considerable wall slip. This slip significantly weakens the intensity of Taylor rolls, reduces local momentum transport, and consequently lowers drag. This phenomenon becomes more pronounced with increasing $w$. Furthermore, to quantify the multiscale relationship between global response and geometrical as well as driving parameters, $DR\sim (w, \phi _s, Re)$, a theoretical model is established based on angular momentum defect theory and magnitude estimate. It is demonstrated that a decrease in the surface solid fraction can reduce wall shear, and an increase in the groove width can weaken turbulence kinetic energy production, rendering enhanced slip and drag reduction. This research has implications for designing and optimizing turbulent-drag-reducing surfaces in various engineering applications, such as transportation and marine engineering.
This study aimed to understand the potassium voltage-gated channel KQT-like subfamily, member 1 gene polymorphism in a rural elderly population in a county in Guangxi and to explore the possible relationship between its gene polymorphism and blood sugar. The 6 SNP loci of blood DNA samples from 4355 individuals were typed using the imLDRTM Multiple SNP Typing Kit from Shanghai Tianhao Biotechnology Co. The data combining epidemiological information (baseline questionnaire and physical examination results) and genotyping results were statistically analyzed using GMDR0.9 software and SPSS22.0 software. A total of 4355 elderly people aged 60 years and above were surveyed in this survey, and the total abnormal rate of glucose metabolism was 16·11 % (699/4355). Among them, male:female ratio was 1:1·48; the age group of 60–69 years old accounted for the highest proportion, with 2337 people, accounting for 53·66 % (2337/4355). The results of multivariate analysis showed that usually not doing farm work (OR 1·26; 95 % CI 1·06, 1·50), TAG ≥ 1·70 mmol/l (OR 1·19; 95 % CI 1·11, 1·27), hyperuricaemia (OR 1·034; 95 % CI 1·01, 1·66) and BMI ≥ 24 kg/m2 (OR 1·06; 95 % CI 1·03, 1·09) may be risk factors for abnormal glucose metabolism. Among all participants, rs151290 locus AA genotype, A allele carriers (AA+AC) were 0.70 times more likely (0.54 to 0.91) and 0.82 times more likely (0.70 to 0.97) to develop abnormal glucose metabolism than CC genotype carriers, respectively. Carriers of the T allele at the rs2237892 locus (CT+TT) were 0.85 times more likely to have abnormal glucose metabolism than carriers of the CC genotype (0.72 to 0.99); rs2237897 locus CT gene. The possibility of abnormal glucose metabolism in the carriers of CC genotype, TT genotype and T allele (CT + TT) is 0·79 times (0·67–0·94), 0·74 times (0·55–0·99) and 0·78 times (0·66, 0·92). The results of multifactor dimensionality reduction showed that the optimal interaction model was a three-factor model consisting of farm work, TAG and rs2237897. The best model dendrogram found that the interaction between TAG and rs2237897 had the strongest effect on fasting blood glucose in the elderly in rural areas, and they were mutually antagonistic. Environment–gene interaction is an important factor affecting abnormal glucose metabolism in the elderly of a county in Hechi City, Guangxi.
As a photocatalyst with good prospects, TiO2 has the shortcomings of easy agglomeration and no catalytic performance under visible light. The purpose of the present study was to help solve these problems by employing muscovite as a carrier for N-doped TiO2 in a nanocomposite. The nanocomposites were prepared by a liquid precipitation-grinding method using muscovite as the matrix and urea as the nitrogen source. The crystal structures, chemical bonding, and micromorphology of the nanocomposites were analyzed by X-ray diffraction, infrared absorption spectrometry, and field emission scanning electron microscopy, respectively. Visible and ultraviolet (UV-Vis) light absorption of the nanocomposites was analyzed by solid ultraviolet diffuse reflectance spectroscopy. The photocatalytic effect of the nanocomposites was studied based on the degradation of rhodamine B (RhB) solution. The photocatalytic degradation product of RhB was detected by high-performance liquid chromatography-mass spectrometry, revealing that N-doping inhibits the growth of TiO2 nanoparticles. The photocatalytic performance of N-TiO2/muscovite composite nanomaterials decreased with increasing heat-treatment temperature. N-doped TiO2/muscovite nanocomposites that were heated at 400°C showed the best photocatalytic performance under visible-light illumination with an RhB degradation of 97%.
Xiaonanshan is an archaeological site dated to 16.5–13.5 cal kyr BP, situated beside the Ussuri River in China. The lithic assemblages feature microblade debitage, bifacial points and stone adzes, which provide important new materials for this project to explore Neolithisation in the Amur River basin of northeast Asia.
Dietary antioxidant indices (DAI) may be potentially associated with relative telomere length (RTL) of leucocytes. This study aimed to investigate the relationship between DAI and RTL. A cross-sectional study involving 1656 participants was conducted. A generalised linear regression model and a restricted cubic spline model were used to assess the correlation of DAI and its components with RTL. Generalised linear regression analysis revealed that DAI (β = 0·005, P = 0·002) and the intake of its constituents vitamin C (β = 0·043, P = 0·027), vitamin E (β = 0·088, P < 0·001), Se (β = 0·075, P = 0·003), and Zn (β = 0·075, P = 0·023) were significantly and positively correlated with RTL. Sex-stratified analysis showed that DAI (β = 0·006, P = 0·005) and its constituents vitamin E (β = 0·083, P = 0·012), Se (β = 0·093, P = 0·006), and Zn (β = 0·092, P = 0·034) were significantly and positively correlated with RTL among females. Meanwhile, among males, only vitamin E intake (β = 0·089, P = 0·013) was significantly and positively associated with RTL. Restricted cubic spline analysis revealed linear positive associations between DAI and its constituents’ (vitamin E, Se and Zn) intake and RTL in the total population. Sex-stratified analysis revealed a linear positive correlation between DAI and its constituents’ (vitamin E, Se and Zn) intake and RTL in females. Our study found a significant positive correlation between DAI and RTL, with sex differences.
By combining the technique of energy selective surface and frequency selective rasorber, an energy selective rasorber is proposed, which performs selective energy protection in the low communication frequency band (0.8–2 GHz) and wave-absorbing property in the high-frequency band (6–18 GHz). The design consists of two layers, of which the bottom one contains a lumped diode structure for energy selection function in the transmission band, while together with the top layer, they perform a wideband wave absorbing function. The simulated and measured results agree well with each other, and both show good absorption in 6–18 GHz and energy-selective property around 1.86 GHz. That is, when the incident power changes from −30 to 14 dBm, the reflection coefficient changes from below −22 dB to above −2 dB, while the transmission coefficient changes from above −3 dB to below −17 dB.
Despite rising incidences of global disasters, basic principles of disaster medicine training are barely taught in Singapore’s 3 medical schools. The aim of this study was to evaluate the current levels of emergency preparedness, attitudes, and perceptions of disaster medicine education among medical students in Singapore.
Methods:
The Emergency Preparedness Information Questionnaire (EPIQ) was provided to enrolled medical students in Singapore by means of an online form, from March 6, 2020, to February 20, 2021. A total of 635 (25.7%) responses were collated and analyzed.
Results:
Mean score for overall familiarity was low, at 1.50 ± 0.74, on a Likert scale of 1 for not familiar to 5 for very familiar. A total of 90.6% of students think that disaster medicine is an important facet of the curriculum, and 93.1% agree that training should be provided for medical students. Although 77.3% of respondents believe that they are unable to contribute to a disaster scenario currently, 92.8% believe that they will be able to contribute with formal training.
Conclusions:
Despite low levels of emergency preparedness knowledge, the majority of medical students in Singapore are keen for adaptation of disaster medicine into the current curriculum to be able to contribute more effectively. This can arm future health-care professionals with the confidence to respond to any potential emergency.
In the literature on active redundancy allocation, the redundancy lifetimes are usually postulated to be independent of the component lifetimes for the sake of technical convenience. However, this unrealistic assumption leads to a risk of inaccurately evaluating system reliability, because it overlooks the statistical dependence of lifetimes due to common stresses. In this study, for k-out-of-n:F systems with component and redundancy lifetimes linked by the Archimedean copula, we show that (i) allocating more homogeneous redundancies to the less reliable components tends to produce a redundant system with stochastically larger lifetime, (ii) the reliability of the redundant system can be uniformly maximized through balancing the allocation of homogeneous redundancies in the context of homogeneous components, and (iii) allocating a more reliable matched redundancy to a less reliable component produces a more reliable system. These novel results on k-out-of-n:F systems in which component and redundancy lifetimes are statistically dependent are more applicable to the complicated engineering systems that arise in real practice. Some numerical examples are also presented to illustrate these findings.
OBJECTIVES/GOALS: Childhood psychiatric symptoms are highly comorbid. Their co-occurrence and association with negative life outcomes is partially explained by deficits in executive control, or processes enabling self-regulation. Here, we test a novel executive neural target in three fMRI tasks and its relevance to shared psychopathology. METHODS/STUDY POPULATION: We studied 60 children [15 F/45 M; mean age (SD)=11.6 years (1.62)] with diverse diagnoses including attention deficit disorder (n=26) and autism spectrum disorder (n=22). We extracted a latent general factor of psychopathology using principal component analyses applied to parent-report Child Behavior Checklist syndrome scores. Subjects completed 3 executive control fMRI probes, tapping adaptive control, working memory, and inhibition. Correlational psychophysiological interaction (cPPI) analysis measured correlations between executive control-related modulations of activity in 414 network-affiliated parcels. We selected parcels exhibiting control-related cross-network correlations as well as control-related activity across all tasks and tested them for association with psychopathology. RESULTS/ANTICIPATED RESULTS: cPPI connectivity matrices were thresholded and graphs were identified using the Network-Based Statistic toolbox (p90th percentile PC) as well as control-related activation (>10% activated voxels; p DISCUSSION/SIGNIFICANCE: Our results examine cross-network interactions between brain regions during 3 fMRI tasks and their role in explaining individual variation in psychopathology. As executive control links to both comorbidity and life outcomes, identifying the clinically-relevant neural correlates of controlled behavior may lead to transdiagnostic treatments.
Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder defined by characteristic behavioral and cognitive features. Abnormal brain dynamic functional connectivity (dFC) has been associated with the disorder. The full spectrum of ADHD-related variation of brain dynamics and its association with behavioral and cognitive features remain to be established.
Methods
We sought to identify patterns of brain dynamics linked to specific behavioral and cognitive dimensions using sparse canonical correlation analysis across a cohort of children with and without ADHD (122 children in total, 63 with ADHD). Then, using mediation analysis, we tested the hypothesis that cognitive deficits mediate the relationship between brain dynamics and ADHD-associated behaviors.
Results
We identified four distinct patterns of dFC, each corresponding to a specific dimension of behavioral or cognitive function (r = 0.811–0.879). Specifically, the inattention/hyperactivity dimension was positively associated with dFC within the default mode network (DMN) and negatively associated with dFC between DMN and the sensorimotor network (SMN); the somatization dimension was positively associated with dFC within DMN and SMN; the inhibition and flexibility dimension and fluency and memory dimensions were both positively associated with dFC within DMN and between DMN and SMN, and negatively associated with dFC between DMN and the fronto-parietal network. Furthermore, we observed that cognitive functions of inhibition and flexibility mediated the relationship between brain dynamics and behavioral manifestations of inattention and hyperactivity.
Conclusions
These findings document the importance of distinct patterns of dynamic functional brain activity for different cardinal behavioral and cognitive features related to ADHD.
Wireless capsule endoscopes (WCEs) are pill-sized camera-embedded devices that can provide visualization of the gastrointestinal (GI) tract by capturing and transmitting images to an external receiver. Determination of the exact location of the WCE is crucial for the accurate navigation of the WCE through external guidance, tracking of the GI abnormality, and the treatment of the detected disease. Despite the enormous progress in the real-time tracking of the WCE, a well-calibrated analytical model is still missing for the accurate localization of WCEs by the measurements from different onboard sensing units. In this paper, a well-calibrated analytical model for the magnetic localization of the WCE was established by optimizing the magnetic moment in the magnetic dipole model. The Jacobian-based iterative method was employed to solve the position of the WCE. An error model was established and experimentally verified for the analysis and prediction of the localization errors caused by inaccurate measurements from the magnetic field sensor. The assessment of the real-time localization of the WCE was performed via experimental trials using an external permanent magnet (EPM) mounted on a robotic manipulator and a WCE equipped with a 3-axis magnetic field sensor and an inertial measurement unit (IMU). The localization errors were measured under different translational and rotational motion modes and working spaces. The results showed that the selection of workspace (distance relative to the EPM) could lead to different positioning errors. The proposed magnetic localization method holds great potential for the real-time localization of WCEs when performing complex motions during GI diagnosis.
Homeostasis of gut microbiota is a critical contributor to growth and health in weaned piglets. Fish oil is widely reported to benefit health of mammals including preventing intestinal dysfunction, yet its protective effect during suckling-to-weaning transition in piglets remains undetermined. Low (30 g/d) and high (60 g/d) doses of n-3-rich fish oil were supplemented in sows from late gestation to lactation. Serum indicators and gut microbiota were determined to evaluate the effects of maternal fish oil on growth performance, immunity and diarrhea of piglets. DHA and EPA in the colostrum as well as serum of suckling and 1-week post-wean piglets were significantly and linearly increased by maternal supplementation of fish oil (P < 0.05). IGF1 and T3 in nursing and weaned piglets were significantly elevated by maternal fish oil (P < 0.05), and the increase of IGF1 was concerning the dosage of fish oil. Colostrum IgG, plasma IgG, IgM in suckling piglets, IgG, IgM and IgA in weaned piglets were significantly increase as maternal replenishment of fish oil increased (P < 0.05). Additionally, cortisol was significantly reduced in weaned pigs (P < 0.05), regardless of dosage. 16S rRNA sequencing revealed that α-diversity of fecal microbiota in nursery piglets, and fecal Lactobacillus genus, positively correlated with post-weaning IgA, was significantly increased by high dosage. Collectively, maternal fish oil during late pregnancy and lactation significantly promoted growth, enhanced immunity, and reduced post-weaning diarrhea in piglets, therefore facilitated suckling-to-weaning transition in piglets, which may be partially due to the altered gut microbial community.
Apart from the psychiatric symptoms, cognitive deficits are also the core symptoms of schizophrenia. Brain network control theory provided information on the role of a specific brain region in the cognitive control process, helping understand the neural mechanism of cognitive impairment in schizophrenia.
Objectives
To characterize the control properties of functional brain network in first-episode untreated patients with schizophrenia and the relationships between controllability and psychiatric symptoms, as well as exploring the predictive value of controllability in differentiating patients from healthy controls (HCs).
Methods
Average and modal controllability of brain networks were calculated and compared between 133 first-episode untreated patients with schizophrenia and 135 HCs. The associations between controllability and clinical symptoms were evaluated using sparse canonical correlation analysis. Support vector machine (SVM) and SVM-recursive feature elimination combined with the controllability were performed to establish the individual prediction model.
Results
Compared to HCs, the patients with schizophrenia showed increased average controllability and decreased modal controllability in dorsal anterior cingulate cortex (dACC). Brain controllability predominantly in somatomotor, default mode, and visual networks was associated with the positive symptomatology of schizophrenia. The established model could identify patients with an accuracy of 0.68. Furthermore, the most discriminative features were located in dACC, medial prefrontal lobe, precuneus and superior temporal gyrus.
Conclusions
Altered controllability in dACC may play a critical role in the neuropathological mechanisms of cognitive deficit in schizophrenia, which could drive the brain function to different states to cope with varied cognitive tasks. As symptom-related biomarkers, controllability could be also beneficial to individual prediction in schizophrenia.
There is a growing consensus on brain networks that it is not immutable but rather a dynamic complex system for adapting environment. The neuroimaging research studying how brain regions work collaboratively with dynamic methods had demonstrated its effectiveness in revealing the neural mechanisms of schizophrenia.
Objectives
To investigate altered dynamic brain functional topology in first-episode untreated schizophrenia patients (SZs) and establish classification models to find objective brain imaging biomarkers.
Methods
Resting-state-functional magnetic resonance data for SZs and matched healthy controls were obtained(Table1).
Power-264-template was used to extract nodes and sliding-window approach was carried out to establish functional connectivity matrices. Functional topology was assessed by eigenvector centrality(EC) and node efficiency and its time-fluctuating was evaluated with coefficient of variation(CV). Group differences of dynamic topology and correlation analysis between Positive and Negative Syndrome Scale(PANSS) scores and topology indices showing group differences, which also were used in establishing classification models, was examed.
Results
The CV of node efficiency in angular and paracingulate gyrus was larger in SZs. There are 13 nodes assigned into several brain networks displaying altered CV of EC between groups(Figure1.A). Fluctuation of EC of the node in DMN, which was lower in SZs, showed negative correlation with PANSS total scores(Figure1.B). Dynamic functional topology of above nodes was used to train classification models and demonstrated 80% and 71% accuracy for support vector classification(SVC) and random forest(RF), respectively(Figure2).
Conclusions
Dynamic functional topology illustrated a capability in identifying SZs. Aberrated dynamics of DMN relevant to severity of patient’s symptoms could reveal the reason why it contributed to classification.
One of the most perplexing and characteristic symptoms of the schizophrenia (SZ) patients is hallucination. The occurrence of hallucinations to be associated with altered activity in the auditory and visual cortex but is not well understood from the brain functional network dynamics in SZ.
Objectives
To explore the brain abnormal basis of hallucinations in SZ with the dynamic functional connectivity (dFC).
Methods
Using magnetic resonance imaging for 83 SZ patients and 83 matched healthy controls and independent component analysis, 52 independent components (ICs) were identified as nodes and assigned into eight intrinsic connectivity networks (Figure 1A). Subsequently, we established dFC matrices and clustered them into four discrete states (Figure 1B) and three state transition metrics were obtained. To further explore the changes in the centrality of each component, eigenvector centrality (EC) was calculated and its time-varying was evaluated.
Results
Compared to controls with FDR correction, we found that patients had more mean dwell times and fractional time in state 1 (P=0.0081 and P=0.0018), mainly with hypoconnectivity between auditory and visual network and other networks and hyperconnectivity between language and default-mode network (DMN). While, patients had less dwell times and fractional time in state 3 (P=0.0018 and P=0.0009), and decreased FC between visual network and executive control network (ECN) and increased FC between ECN and DMN than controls (Figure 2).
EC statistics showed that SZs displayed increased temporal dynamics in visual-related regions (Figure 3).
Conclusions
SZ was mainly manifested as altered dFC and temporal variability of nodal centrality in auditory and visual networks.