Eigenvector PageRank difference as a measure to reveal topological characteristics of the brain connectome for neurosurgery.

PURPOSE: Applying graph theory to the human brain has the potential to help prognosticate the impacts of intracerebral surgery. Eigenvector (EC) and PageRank (PR) centrality are two related, but uniquely different measures of nodal centrality which may be utilized together to reveal varying neuroanatomical characteristics of the brain connectome. METHODS: We obtained diffusion neuroimaging data from a healthy cohort (UCLA consortium for neuropsychiatric phenomics) and applied a personalized parcellation scheme to them. We ranked parcels based on weighted EC and PR, and then calculated the difference (EP difference) and correlation between the two metrics. We also compared the difference between the two metrics to the clustering coefficient. RESULTS: While EC and PR were consistent for top and bottom ranking parcels, they differed for mid-ranking parcels. Parcels with a high EC centrality but low PR tended to be in the medial temporal and temporooccipital regions, whereas PR conferred greater importance to multi-modal association areas in the frontal, parietal and insular cortices. The EP difference showed a weak correlation with clustering coefficient, though there was significant individual variation. CONCLUSIONS: The relationship between PageRank and eigenvector centrality can identify distinct topological characteristics of the brain connectome such as the presence of unimodal or multimodal association cortices. These results highlight how different graph theory metrics can be used alone or in combination to reveal unique neuroanatomical features for further clinical study.

Unexpected hubness: a proof-of-concept study of the human connectome using pagerank centrality and implications for intracerebral neurosurgery.

INTRODUCTION: Understanding the human connectome by parcellations allows neurosurgeons to foretell the potential effects of lesioning parts of the brain during intracerebral surgery. However, it is unclear whether there exist variations among individuals such that brain regions that are thought to be dispensable may serve as important networking hubs. METHODS: We obtained diffusion neuroimaging data from two healthy cohorts (OpenNeuro and SchizConnect) and applied a parcellation scheme to them. We ranked the parcellations on average using PageRank centrality in each cohort. Using the OpenNeuro cohort, we focused on parcellations in the lower 50% ranking that displayed top quartile ranking at the individual level. We then queried whether these select parcellations with over 3% prevalence would be reproducible in the same manner in the SchizConnect cohort. RESULTS: In the OpenNeuro (n = 68) and SchizConnect cohort (n = 195), there were 27.9% and 43.1% of parcellations, respectively, in the lower half of all ranks that displayed top quartile ranks. We noted three outstanding parcellations (L_V6, L_a10p, and L_7PL) in the OpenNeuro cohort that also appeared in the SchizConnect cohort. In the larger Schizconnect cohort, L_V6, L_a10p, and L_7PL had unexpected hubness in 3.08%, 5.13%, and 8.21% of subjects, respectively. CONCLUSIONS: We demonstrated that lowly-ranked parcellations may serve as important hubs in a subset of individuals, highlighting the importance of studying parcellation ranks at the personalized level in planning supratentorial neurosurgery.

An agile, data-driven approach for target selection in rTMS therapy for anxiety symptoms: Proof of concept and preliminary data for two novel targets.

INTRODUCTION: Data-driven approaches to transcranial magnetic stimulation (TMS) might yield more consistent and symptom-specific results based on individualized functional connectivity analyses compared to previous traditional approaches due to more precise targeting. We provide a proof of concept for an agile target selection paradigm based on using connectomic methods that can be used to detect patient-specific abnormal functional connectivity, guide treatment aimed at the most abnormal regions, and optimize the rapid development of new hypotheses for future study. METHODS: We used the resting-state functional MRI data of 28 patients with medically refractory generalized anxiety disorder to perform agile target selection based on abnormal functional connectivity patterns between the Default Mode Network (DMN) and Central Executive Network (CEN). The most abnormal areas of connectivity within these regions were selected for subsequent targeted TMS treatment by a machine learning based on an anomalous functional connectivity detection matrix. Areas with mostly hyperconnectivity were stimulated with continuous theta burst stimulation and the converse with intermittent theta burst stimulation. An image-guided accelerated theta burst stimulation paradigm was used for treatment. RESULTS: Areas 8Av and PGs demonstrated consistent abnormalities, particularly in the left hemisphere. Significant improvements were demonstrated in anxiety symptoms, and few, minor complications were reported (fatigue (n = 2) and headache (n = 1)). CONCLUSIONS: Our study suggests that a left-lateralized DMN is likely the primary functional network disturbed in anxiety-related disorders, which can be improved by identifying and targeting abnormal regions with a rapid, data-driven, agile aTBS treatment on an individualized basis.

Using a ResNet-18 Network to Detect Features of Alzheimer's Disease on Functional Magnetic Resonance Imaging: A Failed Replication. Comment on Odusami et al. Analysis of Features of Alzheimer's Disease: Detection of Early Stage from Functional Brain Changes in Magnetic Resonance Images Using a Finetuned ResNet18 Network. Diagnostics 2021, 11, 1071.

There is considerable interest in developing effective tools to detect Alzheimer's Disease (AD) early in its course, prior to clinical progression [...].

A connectivity model of the anatomic substrates underlying Gerstmann syndrome.

The Gerstmann syndrome is a constellation of neurological deficits that include agraphia, acalculia, left-right discrimination and finger agnosia. Despite a growing interest in this clinical phenomenon, there remains controversy regarding the specific neuroanatomic substrates involved. Advancements in data-driven, computational modelling provides an opportunity to create a unified cortical model with greater anatomic precision based on underlying structural and functional connectivity across complex cognitive domains. A literature search was conducted for healthy task-based functional MRI and PET studies for the four cognitive domains underlying Gerstmann's tetrad using the electronic databases PubMed, Medline, and BrainMap Sleuth (2.4). Coordinate-based, meta-analytic software was utilized to gather relevant regions of interest from included studies to create an activation likelihood estimation (ALE) map for each cognitive domain. Machine-learning was used to match activated regions of the ALE to the corresponding parcel from the cortical parcellation scheme previously published under the Human Connectome Project (HCP). Diffusion spectrum imaging-based tractography was performed to determine the structural connectivity between relevant parcels in each domain on 51 healthy subjects from the HCP database. Ultimately 102 functional MRI studies met our inclusion criteria. A frontoparietal network was found to be involved in the four cognitive domains: calculation, writing, finger gnosis, and left-right orientation. There were three parcels in the left hemisphere, where the ALE of at least three cognitive domains were found to be overlapping, specifically the anterior intraparietal area, area 7 postcentral (7PC) and the medial intraparietal sulcus. These parcels surround the anteromedial portion of the intraparietal sulcus. Area 7PC was found to be involved in all four domains. These regions were extensively connected in the intraparietal sulcus, as well as with a number of surrounding large-scale brain networks involved in higher-order functions. We present a tractographic model of the four neural networks involved in the functions which are impaired in Gerstmann syndrome. We identified a 'Gerstmann Core' of extensively connected functional regions where at least three of the four networks overlap. These results provide clinically actionable and precise anatomic information which may help guide clinical translation in this region, such as during resective brain surgery in or near the intraparietal sulcus, and provides an empiric basis for future study.

Machine Learning Decomposition of the Anatomy of Neuropsychological Deficit in Alzheimer's Disease and Mild Cognitive Impairment.

Objective: Alzheimer's Disease (AD) is a progressive condition characterized by cognitive decline. AD is often preceded by mild cognitive impairment (MCI), though the diagnosis of both conditions remains a challenge. Early diagnosis of AD, and prediction of MCI progression require data-driven approaches to improve patient selection for treatment. We used a machine learning tool to predict performance in neuropsychological tests in AD and MCI based on functional connectivity using a whole-brain connectome, in an attempt to identify network substrates of cognitive deficits in AD. Methods: Neuropsychological tests, baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 149 MCI, and 85 AD patients; and 140 cognitively unimpaired geriatric participants. A novel machine learning tool, Hollow Tree Super (HoTS) was utilized to extract feature importance from each machine learning model to identify brain regions that were associated with deficit and absence of deficit for 11 neuropsychological tests. Results: 11 models attained an area under the receiver operating curve (AUC-ROC) greater than 0.65, while five models had an AUC-ROC ≥ 0.7. 20 parcels of the Human Connectome Project Multimodal Parcelation Atlas matched to poor performance in at least two neuropsychological tests, while 14 parcels were associated with good performance in at least two tests. At a network level, most parcels predictive of both presence and absence of deficit were affiliated with the Central Executive Network, Default Mode Network, and the Sensorimotor Networks. Segregating predictors by the cognitive domain associated with each test revealed areas of coherent overlap between cognitive domains, with the parcels providing possible markers to screen for cognitive impairment. Conclusion: Approaches such as ours which incorporate whole-brain functional connectivity and harness feature importance in machine learning models may aid in identifying diagnostic and therapeutic targets in AD.

Using Quicktome for Intracerebral Surgery: Early Retrospective Study and Proof of Concept.

BACKGROUND: Neurosurgeons have limited tools in their armamentarium to visualize critical brain networks during surgical planning. Quicktome was designed using machine-learning to generate robust visualization of important brain networks that can be used with standard neuronavigation to minimize those deficits. We sought to see whether Quicktome could help localize important cerebral networks and tracts during intracerebral surgery. METHODS: We report on all patients who underwent keyhole intracranial surgery with available Quicktome-enabled neuronavigation. We retrospectively analyzed the locations of the lesions and determined functional networks at risks, including chief executive network, default mode network, salience, corticospinal/sensorimotor, language, neglect, and visual networks. We report on the postoperative neurologic outcomes of the patients and retrospectively determined whether the outcomes could be explained by Quicktome's functional localizations. RESULTS: Fifteen high-risk patients underwent craniotomies for intra-axial tumors, with the exception of one meningioma and one case of leukoencephalopathy. Eight patients were male. The median age was 49.6 years. Quicktome was readily integrated in our existing navigation system in every case. New postoperative neurologic deficits occurred in 8 patients. All new deficits, except for one resulting from a postoperative stroke, were expected and could be explained by preoperative findings by Quicktome. In addition, in those who did not have new neurologic deficits, Quicktome offered explanations for their outcomes. CONCLUSIONS: Quicktome helps to visualize complex functional connectomic networks and tracts by seamlessly integrating into existing neuronavigation platforms. The added information may assist in reducing neurological deficits and offer explanations for postsurgical outcomes.

Parcellation-based anatomic model of the semantic network.

INTRODUCTION: The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task-based fMRI studies, we built a neuroanatomical model of this network. METHODS: One hundred and fifty-five task-based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network. RESULTS: The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model. CONCLUSIONS: We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application.

The development of industry-specific odor impact criteria for feedlots using models.

Emissions from feedlot operations are known to vary by environmental conditions and few if any techniques or models exist to predict the variability of odor emission rates from feedlots. The purpose of this paper is to outline and summarize unpublished reports that are the result of a collective effort to develop industry-specific odor impact criteria for Australian feedlots. This effort used over 250 olfactometry samples collected with a wind tunnel and past research to develop emission models for pads, sediment basins, holding ponds, and manure storage areas over a range of environmental conditions and tested using dynamic olfactometry. A process was developed to integrate these emission models into odor dispersion modeling for the development of impact criteria. The approach used a feedlot hydrology model to derive daily feedlot pad moisture, temperature, and thickness. A submodel converted these daily data to hourly data. A feedlot pad emissions model was developed that predicts feedlot pad emissions as a function of temperature, moisture content, and pad depth. Emissions from sediment basins and holding ponds were predicted using a basin emissions model as a function of days since rain, inflow volume, inflow ratio (pond volume), and temperature. This is the first attempt to model all odor source emissions from a feedlot as variable hourly emissions on the basis of climate, management, and site-specific conditions. Results from the holding pond, sediment basin, and manure storage emission models performed well, but additional work on the pad emissions model may be warranted. This methodology mimics the variable odor emissions and odor impact expected from feedlots due to climate and management effects. The main outcome of the work is the recognition that an industry-specific odor impact criterion must be expressed in terms of all of the components of the assessment methodology.

Susceptibility of gnotobiotic transgenic mice (Tgepsilon26) with combined deficiencies in natural killer cells and T cells to wild-type and hyphal signalling-defective mutants of Candida albicans.

Germfree transgenic epsilon 26 mice (Tgepsilon26), deficient in natural killer cells and T cells, were colonized (alimentary tract) with Candida albicans wild-type or each of two hyphal transcription factor signalling mutant strains (efg1/efg1, efg1/efg1 cph1/cph1). Each Candida strain colonized the alimentary tract, infected keratinized gastric tissues to a similar extent, and induced a granulocyte-dominated inflammatory response in infected tissues. Both wild-type and mutant strains formed hyphae in vivo and were able to elicit an increase in cytokine [tumour necrosis factor alpha, interleukin (IL)-10 and IL-12] and chemokine (KC and macrophage inflammatory protein-2] mRNAs in infected tissues; however, administration of the wild-type strain was lethal for the Tgepsilon26 mice, whereas the mice colonized with the mutant strains survived. Death of the Tgepsilon26-colonized mice appeared to be due to occlusive oesophageal candidiasis, and not to disseminated candidiasis of endogenous origin. In contrast, the mutant strains exhibited a significantly reduced capacity to infect (frequency and severity) oro-oesophageal (tongue and oesophagus) tissues. Therefore, the two hyphal signalling-defective mutants were less able to infect oro-oesophageal tissues and were non-lethal, but retained their ability to colonize the alimentary tract with yeast and hyphae, infect keratinized gastric tissues, and evoke an inflammatory response in orogastric tissues.

Candida glabrata and Candida albicans; dissimilar tissue tropism and infectivity in a gnotobiotic model of mucosal candidiasis.

Germ-free transgenic epsilon 26 (Tgepsilon26) mice, deficient in both natural killer (NK)- and T-cells, were inoculated (orally) with each of two Candida glabrata (BG2 or BG1003) or Candida albicans (CAF2-1 or SC5314) strains. Candida glabrata- or C. albicans-colonized mice exhibited similar numbers of viable Candida in the alimentary tract. Neither C. glabrata nor C. albicans caused systemic candidiasis of endogenous (alimentary tract) origin. Candida albicans invaded oroesophageal (tongue, palate, esophagus) and keratinized gastric tissues, evoked hyperkeratosis and a prominent, chronic, granulocyte-dominated, inflammatory response in all infected tissues, stimulated the production of splenic granulocytes and was lethal for the mice within 3-5 weeks after oral colonization. The two C. glabrata strains colonized the alimentary tract and penetrated into the keratinized (cardia-antrum) gastric tissues, but in contrast to C. albicans, were unable to infect oroesophageal tissues. Furthermore, C. glabrata strains were not lethal for the Tgepsilon26 mice, and did not evoke an inflammatory response in colonized gastric tissues or stimulate the production of splenic granulocytes. This 'stealth-like' behavior could explain the ability of C. glabrata to persist in infected tissues and survive as a commensal in the alimentary tract.

Susceptibility of germfree phagocyte oxidase- and nitric oxide synthase 2-deficient mice, defective in the production of reactive metabolites of both oxygen and nitrogen, to mucosal and systemic candidiasis of endogenous origin.

Mice deficient for phagocyte oxidase (Phox) and nitric oxide synthase 2 (NOS2) (gp91phox-/-/NOS2-/-), defective in the production of both reactive oxygen intermediates (ROI) and reactive nitrogen intermediates (RNI), were used to investigate the role of phagocytic cells during mucosal and systemic candidiasis of endogenous origin. The alimentary tracts of germfree mice were colonized with Candida albicans wild type or each of two hyphal signaling-defective mutants (efg1/efg1 and efg1/efg1 cph1/cph1). All Candida-colonized gp91phox-/-/NOS2-/- mice were moribund within 12 to 15 days after oral inoculation. C. albicans wild-type and mutant strains colonized the alimentary tracts equally well and were able to translocate, most likely via Peyer's patches and mesenteric lymph nodes, to the internal organs and trigger the formation of abscesses; however, the wild-type and mutant strains did not survive in the abscessed murine tissues. Surprisingly, there was no significant difference in the ability of peritoneal exudate cells from gp91phox-/-/NOS2-/-, NOS2-/-, gp91phox-/-, or immunocompetent C57BL/6 mice to kill C. albicans in vitro. This suggests that anti-Candida factors other than ROI and RNI can control the growth of C. albicans and that gp91phox-/-/NOS2-/- mice die due to the inability of the host to control its inflammatory response to Candida. Correspondingly, reverse transcription-PCR analysis showed increased expression of the cytokines gamma interferon, tumor necrosis factor alpha, and the chemokines MIP-2 and KC at the site of infection, while interleukin-15 expression remained relatively unchanged between germfree and infected tissues. These studies indicate that defects in ROI and RNI enabled C. albicans to translocate and disseminate to the internal organs, resulting in an uncontrolled immune response, severe pathology, and death; however, ROI and RNI were not required for the killing of phagocytized C. albicans, indicating that other anti-Candida factors either compensate or are sufficient for the killing of phagocytized Candida.

Detection of Candida albicans mRNA from formalin-fixed, paraffin-embedded mouse tissues by nested reverse transcription-PCR.

Histopathology archives represent a vast source of infectious disease specimens that can be used to elucidate important disease processes. In this report, we describe a method to detect Candida albicans gene expression from infected, formalin-fixed, paraffin-embedded mouse tissue. By use of glass beads to break open the fungal cells and proteinase K treatment, RNA was extracted routinely from tissue sections that had been fixed for up to 72 h. Upon reverse transcription of the RNA and nested PCR, the procedure detected C. albicans "housekeeping" and putative virulence genes.

Hydrolytic gene expression during oroesophageal and gastric candidiasis in immunocompetent and immunodeficient gnotobiotic mice.

To investigate whether host immunocompetence influences hydrolytic gene expression, we compared secretory aspartyl proteinase gene (SAP) and phospholipase B gene (PLB) expression during gastric candidiasis in immunocompetent and defined immunodeficient gnotobiotic mice, by reverse-transcription polymerase chain reaction. The use of immunodeficient gnotobiotic mice with combined defects in T cells and natural killer cells enabled a comprehensive study of virulence gene expression in various mucosal sites during lethal oroesophageal (tongue, palate, and esophagus) and gastric candidiasis. All 10 SAP and both PLB genes were expressed in both immunocompetent and specific immunodeficient mice, which suggests that the absence of important components of the host defense did not alter gene expression during gastric candidiasis. Although similar patterns of gene expression were evident in different oral tissues, we detected specific differences between Candida albicans-infected oroesophageal and gastric tissues and differences at various time points during the progression of gastric candidiasis.