Nodal Level Research Articles

IRINS: Implementing a Research Information Management System in Indian Higher Education Institutions

An increasing number of organizations are encouraging and accepting the research information management system in the institute level to assess the research progress of the organization and bring out a report on scholarly communication activities. Open and commercial product on the Current Research Information System (CRIS) is emerging in the last decade. The Directory of Current Research Information system listed 25 CRIS system across European countries. The European Current Research Information System (euroCRIS) support the CRIS thought the European countries through the conference, working group and pioneer in the advocacy since 2002. This paper considers the recent development in the CRIS related activities around the world and recent progress in India. This paper describes the various challenges to setting up the RIM for the higher education institutions including identification of nodal officers, collecting faculty profile information, retrieving scholarly communication activities from internal and external sources, etc. Also, discuss the training programme to the nodal officer level and institute level to promote the academic identities and their importance. The paper also discusses the impact of the IRINS in the higher education system in India and its use case with different stakeholders such as students, scholars, faculty members, scientists, research administrators, funding agencies and policymakers, etc.

Analysis of the Relevance of the Ultrasonographic Features of Papillary Thyroid Carcinoma and Cervical Lymph Node Metastasis on Conventional and Contrast-Enhanced Ultrasonography.

BackgroundPreoperative prediction of lymph node metastases has a major impact on prognosis and recurrence for patients with papillary thyroid carcinoma (PTC). Thyroid ultrasonography is the preferred inspection to guide the appropriate diagnostic procedure.PurposeTo investigate the relationship between PTC and cervical lymph node metastasis (CLNM, including central and lateral LNM) using both conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS).Material and MethodsOur study retrospectively analyzed 379 patients diagnosed with PTC confirmed by surgical pathology at our hospital who underwent US and CEUS examinations from October 2016 to March 2021. Individuals were divided into two groups: the lymph node metastasis group and the nonmetastasis group. The relationship between US and CEUS characteristics of PTC and CLNM was analyzed. Univariate and multivariable logistic regression methods were used to identify the high-risk factors and established a nomogram to predict CLNM in PTC. Furthermore, we explore the frequency of CLNM at each nodal level in PTC patients.ResultsUnivariate analysis indicated that there were significant differences in gender, age, tumor size, microcalcification, contact with the adjacent capsule, multifocality, capsule integrity and enhancement patterns in CEUS between the lymph node metastasis group and the nonmetastasis group (all P<0.05). Multivariate regression analysis showed that tumor size ≥1 cm, age ≤45 years, multifocality, and contact range of the adjacent capsule >50% were independent risk factors for CLNM in PTC, which determined the nomogram. The diagnostic model had an area under the curve (AUC) of 0.756 (95% confidence interval, 0.707-0.805). And calibration plot analysis shown that clinical utility of the nomogram. In 162 PTC patients, the metastatic rates of cervical lymph nodes at levels I-VI were 1.9%, 15.4%, 35.2%, 34.6%, 15.4%, 82.1%, and the difference was statistically significant (P<0.001).ConclusionOur study indicated that the characteristics of PTC on ultrasonography and CEUS can be used to predict CLNM as a useful tool. Preoperative analysis of ultrasonographical features has important value for predicting CLNM in PTCs. The risk of CLNM is greater when tumor size ≥1 cm, age ≤45 years, multifocality, contact range of the adjacent capsule >50% are present.

Analysis of lymph nodes metastasis in hypopharyngeal squamous cell carcinoma based on contrast‐enhanced computed tomography imaging

AbstractObjectiveTo investigate the frequency, distribution, and potential factors of lymphatic metastasis at each nodal level, and stratify the risk of lymph node metastasis in hypopharyngeal squamous cell carcinoma based on computed tomography.MethodsContrast‐enhanced computed tomography images of 176 patients with pathologically confirmed hypopharyngeal squamous cell carcinoma without any cancer‐related therapeutic history were analyzed retrospectively. The lymphatic metastasis ratio at each nodal level was determined. Potential factors that correlated with lymph node metastasis were identified using univariate and multivariate analyses.ResultsMetastatic lymph nodes were found in 145 (82.4%) of 176 patients. The lymphatic metastasis ratio was 0.6% (Ia), 4.0% (Ib), 67.6% (IIa), 43.8% (IIb), 45.5% (III), 13.1% (IV), 5.1% (Va), 1.7% (Vb), 1.7% (VIa), 12.5% (VIb), and 15.9% (VII) for each nodal level in the ipsilateral neck. In contrast, a lower lymphatic metastasis ratio was observed in the contralateral neck, with the highest measuring 18.2% at level IIa. Esophageal invasion was highly correlated with an increased risk of developing level VIb metastasis (P = 0.019). Furthermore, posterior pharyngeal wall invasion was highly correlated with an increased risk of level VII metastasis (P = 0.014).ConclusionIn general, nodal levels IIa, III, and IIb were highly susceptible to metastasis in the ipsilateral neck. Nodal levels IV, VIb, and VII in the ipsilateral neck, and IIa in the contralateral neck showed a moderate risk of metastasis. Levels I and V were considered low risk. The anatomical characteristics and infiltration of tumors in different subsites should also be considered in the delineation of the clinical target volume.

Shape optimization of the time-harmonic response of vibroacoustic devices using cut elements

This article presents a method for generalized shape optimization of time-harmonic vibroacoustic problems. The modeling approach utilizes an immersed boundary cut element method in conjunction with a level set representation of the geometry. The cut element method utilizes a fixed background mesh, a dimensionless contrast parameter and an integration scheme to realize complex geometries and obtain accurate physical solutions to the governing problem. The design parameterization is obtained using a nodal level set description, directly linked to the mathematical design variables, and the gradients of the objective and the constraints are obtained with the discrete adjoint approach. The framework is applied to the optimization of three 2D examples. A study on the effect of initial guess for the proposed optimization procedure is presented on a benchmark example of the design of an acoustic partitioner. Further optimization examples include design of a wave splitter to realize prescribed frequency dependent directivity for emitted acoustic waves and a suspension structure design to improve the performance of a simplified 2D model of a hearing instrument. The results demonstrate that, even though the final topology is strongly dictated by the initial design, modifying the shape allows for a significant improvement of the system behavior. • A generalized shape optimization methodology for 2D time-harmonic vibroacoustic problems using cut elements. • A simple, yet accurate, crisp interface cut element method without the need for stabilization. • A numerically stable level set based shape optimization procedure based on density methods. • Three numerical examples that demonstrate the strengths and weaknesses of the proposed method.

Real World Data Estimates of Contralateral Nodal Involvement Based on Clinical and Automatically Extracted Treatment Plan Features

To evaluate the association of contralateral nodal involvement (CNI) with automatically defined midline proximity in patients (pts) with head and neck cancer based on treatment planning (TP) real world data (RWD).All available TPs for head and neck cancer pts between 2010 and 2017 were analyzed in an automated data analysis pipeline where the pt's midline was determined objectively using their external contour and discounting distortion due to neck lymphadenopathy via linear modeling. Primary gross tumor volumes (GTVp) and nodal volumes (GTVn) were contoured by treating radiation oncologists. Objective tumor laterality (OTL) was calculated as the difference between the GTVp center of mass and the midline in the R/L direction. OTL accuracy compared to the clinically assigned laterality (when available) was assessed. Midline proximity (MP) was the difference between the medial edge of the GTVp bounding box to the patient midline with positive values representing progressively lateralized tumors and negative values representing tumors crossing midline. Nodal involvement (ipsilateral and contralateral levels 1-5 and retropharyngeal) was determined using the TP nodal target contours labeled by neck level as is standard practice at our institution during treatment planning. The primary endpoint, CNI, was defined based on these TP contours. Volumes of GTVp were calculated from the TP. Clinical variables including HPV status, age, smoking, disease site and subsite were used for model development. The factors predictive of CNI were assessed using logistic regression (LR).Of 2458 pts available for analysis, 2031 had a clinically assigned laterality. The accuracy of automatically assigned laterality was 0.91 when compared with the clinically assigned laterality. Using the automatically assigned laterality (n = 2458), the overall rate of CNI was 45% and varied by disease site and nodal level involved: oropharynx (55.1%, n = 629/1142), larynx (17.6%, n = 124/703), nasopharynx (79.7%, n = 231/290). Multivariable logistic regression (LR) including subsite, HPV status, GTVp, GTVp center of mass relative to midline, GTVp midline proximity, and ipsilateral nodal involvement was performed. In the oropharynx, multivariable LR demonstrated GTVp volume (P < 0.01) and ipsilateral nodes (P < 0.01) were associated with CNI. Neither HPV status or subsite (e.g., base of tongue) was significant on multivariable analysis. In the nasopharynx, GTVp and ipsilateral nodes were significantly associated with CNI on LR. In the larynx, GTVp, ipsilateral nodes, and midline position were all significantly associated with CLI. Nomograms estimating CLI were generated for each disease site based on significant features from the LRs.Automated TP analysis can be used to generate RWD-based predictions of CNI. CNI risk remains a critical radiotherapy endpoint and RWD may help determine CLI risk using combinations of anatomic and clinical features.

Patterns of Failure After IMRT and Proton Re-Irradiation for Patients With Recurrent Head and Neck Cancer

Patterns of Failure After IMRT and Proton Re-Irradiation for Patients With Recurrent Head and Neck Cancer

Aberrant large-scale brain modules in deficit and non-deficit schizophrenia

ObjectiveSchizophrenia is a heterogenous psychiatric disease, and deficit schizophrenia (DS) is a clinical subgroup with primary and enduring negative symptoms. Although previous neuroimaging studies have identified functional connectome alterations in schizophrenia, the modular organizations in DS and nondeficit schizophrenia (NDS) remain poorly understood. Therefore, this study aimed to investigate the modular-level alterations in DS patients compared with the NDS and healthy control (HC) groups. MethodsA previously collected dataset was re-analyzed, in which 74 chronic male schizophrenia patients (33 DS and 41 NDS) and 40 HC underwent resting-state functional magnetic resonance imaging with eyes closed in a Siemens 3 T scanner (scanning duration = 8 min). Modular- (intramodule and intermodule connectivity) and nodal- [normalized within-module degree (Zi) and participation coefficient (PCi)] level graph theory properties were computed and compared among the three groups. Receiver operating characteristic curve (ROC) analyses were performed to examine the classification ability of these measures, and partial correlations were conducted between network measures and symptom severity. Validation analyses on head motion, network sparsity, and parcellation scheme were also performed. ResultsBoth schizophrenia subgroups showed decreased intramodule connectivity in salience network (SN), somatosensory-motor network (SMN), and visual network (VN), and increased intermodule connectivity in SMN-default mode network (DMN) and SMN-frontoparietal network (FPN). Compared with NDS patients, DS patients showed weaker intramodule connectivity in SN and stronger intermodule connectivity in SMN-FPN and SMN-VN. At the nodal level, the schizophrenia-related alterations were distributed in SN, SMN, VN, and DMN, and 7 DS-specific nodal alterations were identified. Intramodule connectivity of SN, intermodule connectivity of SMN-VN, and Zi of left precuneus successfully distinguished the three groups. Partial correlational analyses revealed that these measures were related to negative symptoms, general psychiatric symptoms, and neurocognitive function. ConclusionOur findings suggest that functional connectomes, especially SN, SMN, and VN, may capture the distinct and common disruptions of DS and NDS. These findings may help to understand the neuropathology of negative symptoms of schizophrenia and inform targets for treating different schizophrenia subtypes.

Disrupted intrinsic functional brain topology in patients with major depressive disorder

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Altered Brain Functional Network Topology in Lung Cancer Patients After Chemotherapy.

Purpose: This study aimed to explore the topological features of brain functional network in lung cancer patients before and after chemotherapy using graph theory.Methods: Resting-state functional magnetic resonance imaging scans were obtained from 44 post-chemotherapy and 46 non-chemotherapy patients as well as 49 healthy controls (HCs). All groups were age- and gender-matched. Then, the topological features of brain functional network were assessed using graph theory analysis.Results: At the global level, compared with the HCs, both the non-chemotherapy group and the post-chemotherapy group showed significantly increased values in sigma (p < 0.05), gamma (p < 0.05), and local efficiency, Eloc (p < 0.05). The post-chemotherapy group and the non-chemotherapy group did not differ significantly in the above-mentioned parameters. At the nodal level, when non-chemotherapy or post-chemotherapy patients were compared with the HCs, abnormal nodal centralities were mainly observed in widespread brain regions. However, when the post-chemotherapy group was compared with the non-chemotherapy group, significantly decreased nodal centralities were observed primarily in the prefrontal–subcortical regions.Conclusions: These results indicate that lung cancer and chemotherapy can disrupt the topological features of functional networks, and chemotherapy may cause a pattern of prefrontal–subcortical brain network abnormality. As far as we know, this is the first study to report that altered functional brain networks are related to lung cancer and chemotherapy.

Disrupted Small-world Networks are Associated with Decreased Vigilant Attention after Total Sleep Deprivation

Sleep deprivation critically affects vigilant attention. Previous neuroimaging studies have revealed altered inter-regional functional connectivity after sleep deprivation, which may disrupt topological properties of brain functional networks. However, little is known about alterations in the topology of intrinsic connectivity and its involvement in attention performance after sleep deprivation. In the current study, we investigated the topological properties of brain networks derived from resting-state functional magnetic resonance imaging of 26 healthy men in rested wakefulness (RW) state and after 36 h of total sleep deprivation (TSD). In the predefined sparsity threshold range, both global and nodal network properties were evaluated based on graph theory analysis. Vigilant attention was assessed using the psychomotor vigilance test (PVT) before and after TSD. Furthermore, Pearson’s correlation analyses were conducted to explore the association between altered network properties and changed PVT performance after TSD. At the global level, the brain functional networks in the TSD state showed a significantly lower small-world coefficient than RW, with decreased global efficiency. At the nodal level, the altered regions were selectively distributed in frontoparietal networks, sensorimotor networks, temporal regions, and salience networks. More specifically, the altered clustering coefficient in the posterior superior temporal sulcus (pSTS) and insula, and altered local efficiency in pSTS were further associated with PVT performance after TSD. Our results suggest that the topological properties of brain functional networks are disrupted, and aberrant topology of temporal networks and salience networks may act as neural signatures underlying the vigilant attention impairments after TSD.

Progressive Brain Degeneration From Subjective Cognitive Decline to Amnestic Mild Cognitive Impairment: Evidence From Large-Scale Anatomical Connection Classification Analysis.

People with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are both at high risk for Alzheimer’s disease (AD). Behaviorally, both SCD and aMCI have subjective reports of cognitive decline, but the latter suffers a more severe objective cognitive impairment than the former. However, it remains unclear how the brain develops from SCD to aMCI. In the current study, we aimed to investigate the topological characteristics of the white matter (WM) network that can successfully identify individuals with SCD or aMCI from healthy control (HC) and to describe the relationship of pathological changes between these two stages. To this end, three groups were recruited, including 22 SCD, 22 aMCI, and 22 healthy control (HC) subjects. We constructed WM network for each subject and compared large-scale topological organization between groups at both network and nodal levels. At the network level, the combined network indexes had the best performance in discriminating aMCI from HC. However, no indexes at the network level can significantly identify SCD from HC. These results suggested that aMCI but not SCD was associated with anatomical impairments at the network level. At the nodal level, we found that the short-path length can best differentiate between aMCI and HC subjects, whereas the global efficiency has the best performance in differentiating between SCD and HC subjects, suggesting that both SCD and aMCI had significant functional integration alteration compared to HC subjects. These results converged on the idea that the neural degeneration from SCD to aMCI follows a gradual process, from abnormalities at the nodal level to those at both nodal and network levels.

Disrupted Topological Organization in White Matter Networks in Unilateral Sudden Sensorineural Hearing Loss.

Sudden sensorineural hearing loss (SSNHL) is a sudden-onset hearing impairment that rapidly develops within 72 h and is mostly unilateral. Only a few patients can be identified with a defined cause by routine clinical examinations. Recently, some studies have shown that unilateral SSNHL is associated with alterations in the central nervous system. However, little is known about the topological organization of white matter (WM) networks in unilateral SSNHL patients in the acute phase. In this study, 145 patients with SSNHL and 91 age-, gender-, and education-matched healthy controls were evaluated using diffusion tensor imaging (DTI) and graph theoretical approaches. The topological properties of WM networks, including global and nodal parameters, were investigated. At the global level, SSNHL patients displayed decreased clustering coefficient, local efficiency, global efficiency, normalized clustering coefficient, normalized characteristic path length, and small-worldness and increased characteristic path length (p < 0.05) compared with healthy controls. At the nodal level, altered nodal centralities in brain regions involved the auditory network, visual network, attention network, default mode network (DMN), sensorimotor network, and subcortical network (p < 0.05, Bonferroni corrected). These findings indicate a shift of the WM network topology in SSNHL patients toward randomization, which is characterized by decreased global network integration and segregation and is reflected by decreased global connectivity and altered nodal centralities. This study could help us understand the potential pathophysiology of unilateral SSNHL.

Topological Aberrance of Structural Brain Network Provides Quantitative Substrates of Post-Traumatic Brain Injury Attention Deficits in Children.

Background: Traumatic brain injury (TBI)-induced attention deficits are among the most common long-term cognitive consequences in children. Most of the existing studies attempting to understand the neuropathological underpinnings of cognitive and behavioral impairments in TBI have utilized heterogeneous samples and resulted in inconsistent findings. The current research proposed to investigate topological properties of the structural brain network in children with TBI and their relationship with post-TBI attention problems in a more homogeneous subgroup of children who had severe post-TBI attention deficits (TBI-A). Materials and Methods: A total of 31 children with TBI-A and 35 group-matched controls were involved in the study. Diffusion tensor imaging-based probabilistic tractography and graph theoretical techniques were used to construct the structural brain network in each subject. Network topological properties were calculated in both global level and regional (nodal) level. Between-group comparisons among the topological network measures and analyses for searching brain-behavioral were all corrected for multiple comparisons using Bonferroni method. Results: Compared with controls, the TBI-A group showed significantly higher nodal local efficiency and nodal clustering coefficient in left inferior frontal gyrus and right transverse temporal gyrus, whereas significantly lower nodal clustering coefficient in left supramarginal gyrus and lower nodal local efficiency in left parahippocampal gyrus. The temporal lobe topological alterations were significantly associated with the post-TBI inattentive and hyperactive symptoms in the TBI-A group. Conclusion: The results suggest that TBI-related structural re-modularity in the white matter subnetworks associated with temporal lobe may play a critical role in the onset of severe post-TBI attention deficits in children. These findings provide valuable input for understanding the neurobiological substrates of post-TBI attention deficits, and have the potential to serve as quantitatively measurable criteria guiding the development of more timely and tailored strategies for diagnoses and treatments to the affected individuals. Impact statement This study provides a new insight into the neurobiological substrates associated with post-traumatic brain injury attention deficits (TBI-A) in children, by evaluating topological alterations of the structural brain network. The results demonstrated that relative to group-matched controls, the children with TBI-A had significantly altered nodal local efficiency and nodal clustering coefficient in temporal lobe, which strongly linked to elevated inattentive and hyperactive symptoms in the TBI-A group. These findings suggested that white matter structural re-modularity in subnetworks associated with temporal lobe may serve as quantitatively measurable biomarkers for early prediction and diagnosis of post-TBI attention deficits in children.

Disrupted Brain Network Topology in Drug-naïve Essential Tremor Patients with and Without Depression : AResting State Functional Magnetic Resonance Imaging Study.

This study was carried out to investigate brain functional connectome and its potential relationships with the disease severity and emotion function in patients with essential tremor with and without depressive symptoms by using resting-state functional magnetic resonance imaging and graph theory approaches. In this study 33 essential tremor patients with depression, 45 essential tremor patients without depression and 79age and gender-matched healthy controls were recruited to undergo a3.0‑T imaging scan. The whole brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions, and the topologic properties were analyzed by using graph theory approaches and network-based statistic approaches. Nonparametric permutation test was also used for group comparisons of topological metrics. Correlation analyses between topographic features and the clinical characteristics were performed. The functional connectome in both essential tremor patients with and without depression showed abnormalities at the global level (decrease in clustering coefficient, global efficiency, and local efficiency but increase in characteristic path length) and at the nodal level (decrease nodal centralities in the cerebellum, motor cortex, prefrontal-limbic regions, default mode network) (p < 0.05, false discovery rate corrected). Moreover, essential tremor patients with depression showed higher node efficiency in superior frontal gyrus and posterior cingulate gyrus compared to essential tremor without depression. Our results may provide insights into the underlying pathophysiology of essential tremor patients with and without depression and aid the development of some potential biomarkers of the depressive symptoms in patients with essential tremor.

Planning for resilience in power distribution networks: A multi‐objective decision support

Power grid response against high-impact low-probability (HILP) events could be enhanced by (a) hardening mechanisms to boost its structural resilience and (b) corrective recovery and mitigation analytics to improve its operational resilience. Planning for structural resilience and attempts to find the optimal location of the Tie switches in radially operated power distribution networks that enable harnessing the network topology for maximised resilience against HILP disasters are focussed. This goal is achieved through a novel resilience-oriented multi-objective decision making platform, which employs a k-PEM based probabilistic power flow (PPF) algorithm. The proposed framework offers a decision making analytic embedded with the fuzzy satisfying method (FSM) that characterises the system resilience features, such as robustness, restoration agility, load criticality, and recovered capacity, to assess different network reconfiguration options and select the optimal solution for implementation. The aforementioned resilience features are formulated in nodal level and then aggregated over the entire system to characterise the system-level objective functions. The performance of the suggested framework is analysed on the IEEE 33-Bus test system under a designated HILP event, and the applicability on larger networks has been verified on the IEEE 69-bus test system. The results demonstrate the efficacy and applicability of the proposed framework in boosting the network resilience against future extremes.

Aberrant brain network topology in the frontoparietal-limbic circuit in bipolar disorder: a graph-theory study.

Characterizing the properties of brain networks across mood states seen in bipolar disorder (BP) can provide a deeper insight into the mechanisms involved in this type of affective disorder. In this study, graph theoretical methods were used to examine global, modular and nodal brain network topology in the resting state using functional magnetic resonance imaging data acquired from 95 participants, including those with bipolar depression (BPD; n = 30) and bipolar mania (BPM; n = 39) and healthy control (HC) subjects (n = 26). The threshold value of the individual subjects' connectivity matrix varied from 0.15 to 0.30 with steps of 0.01. We found that: (1) at the global level, BP patients showed a significantly increased global efficiency and synchronization and a decreased path length; (2) at the nodal level, BP patients showed impaired nodal parameters, predominantly within the frontoparietal and limbic sub-network; (3) at the module level, BP patients were characterized by denser FCs (edges) between Module III (the front-parietal system) and Module V (limbic/paralimbic systems); (4) at the nodal level, the BPD and BPM groups showed state-specific differences in the orbital part of the left superior-frontal gyrus, right putamen, right parahippocampal gyrus and left fusiform gyrus. These results revealed abnormalities in topological organization in the whole brain, especially in the frontoparietal-limbic circuit in both BPD and BPM. These deficits may reflect the pathophysiological processes occurring in BP. In addition, state-specific regional nodal alterations in BP could potentially provide biomarkers of conversion across different mood states.

Mixed formulation for geometric and material nonlinearity of shear-critical reinforced concrete columns

This study presents a new beam element formulation following a Hellinger-Reissner variational principle for shear critical reinforced concrete members, and considering large displacement and rotation effects. The corotational formulation is used to describe the large displacement at the element nodal level and degenerated Green-Lagrange strain measures are used at the basic element level. A new displacement shape function has been developed considering section kinematics and compatibility conditions to satisfy stability criteria. New explicit equations for the internal geometric stiffness matrix to consider large deformation effect has been developed. A robust state determination algorithm for the large deformation mixed-based formulation is proposed. The Timoshenko beam theory has been adopted to consider shear deformations in deriving the section kinematics equations. The multi-axial stress state in reinforced concrete fibre has been simulated through the fixed crack smeared softened membrane model. The developed shear fibre beam element is capable of accurately reproducing the experimentally-observed large displacement effect on the post-peak shear strength degradation in the softening region. The accuracy and efficiency of the mixed-based formulation was evaluated by examining the responses at local and global levels for both monotonic and reverse cyclic loading conditions along with the process of reproducing experimentally-observed failure modes.

On the Correlation Between Nodal and Nonzero Level Sets for Random Spherical Harmonics

We study the correlation between the nodal length of random spherical harmonics and the length of a nonzero level set. We show that the correlation is asymptotically zero, while the partial correlation after removing the effect of the random L^2-norm of the eigenfunctions is asymptotically one.

Aberrant basal ganglia-thalamo-cortical network topology in juvenile absence epilepsy: A resting-state EEG-fMRI study

PurposeThe underlying pathophysiology of juvenile absence epilepsy (JAE) is unclear. Since cortical and subcortical brain regions are thought to be altered in genetic generalized epilepsy, the present study examined the resting-state functional network topology of the same regions in JAE. MethodsElectroencephalography and functional magnetic resonance imaging (EEG-fMRI) were performed on 18 JAE patients and 28 healthy controls (HCs). The topology of functional networks was analyzed using the graph-theoretic method. Both global and nodal network parameters were calculated, and parameters differing significantly between the two groups were correlated with clinical variables. ResultsBoth JAE patients and HCs had small-world functional network topological architectures. However, JAE patients showed higher values for the global parameters of clustering coefficient (Cp) and normalized characteristic path length (Lambda). At the nodal level, patients exhibited greater centrality at widespread cortices, including the left superior parietal gyrus, right superior temporal gyrus, right orbital part of middle frontal gyrus and bilateral supplementary motor area. Conversely, patients showed decreased nodal centrality predominantly in the limbic network, left thalamus and right caudate nucleus. Degree centrality in the right hippocampus and betweenness centrality in the right caudate nucleus positively correlated with epilepsy duration. ConclusionThe global functional network of JAE shows small-world properties, but tends to be regular with higher segregation and lower integration. Regions in the basal ganglia-thalamo-cortical network have aberrant nodal centrality. The hippocampus and caudate nucleus may reorganize as epilepsy progresses. Our findings indicate the pathogenesis and compensatory mechanisms to seizure attacks and cognitive deficits of JAE.

FDG-PET/CT and Pathology in Newly Diagnosed Head and Neck Cancer: ACRIN 6685 Trial, FDG-PET/CT cN0.

FDG-PET/CT (fluorodeoxyglucose-positron emission tomography/computed tomography) is effective to assess for occult neck nodal disease. We report risks and patterns of nodal disease based on primary site and nodal level from data on the dissected cN0 per the results from ACRIN 6685. Prospective nonrandomized enrollment included participants with first-time head and neck squamous cell carcinoma and at least 1 cN0 neck side to be dissected. Twenty-four ACRIN-certified centers internationally (American College of Radiology Imaging Network). A total of 287 participants were enrolled. Preoperative FDG-PET/CT findings were centrally reviewed and compared with pathology. Incidence, relative risk, pattern of lymph node involvement, and impact upon neck dissection were reported. An overall 983 nodal levels were dissected (n = 261 necks, n = 203 participants). The highest percentages of ipsilateral positive nodes by primary location and nodal level were oral cavity (level I, 17/110, 15.5%), pharynx (level II, 6/30, 20.0%), and larynx (level VI, 1/3, 33.3%). Levels at greatest risk for nodal disease in cN0 in terms of ipsilateral neck dissection are level I (oral cavity), II (pharynx), and VI (larynx). These data should be considered when treating patients presenting with cN0. This is the first study to comprehensively report the incidence, location, and risk of metastases in cN0 in the FDG-PET/CT era.