Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy

Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

Generalizable Links Between Borderline Personality Traits and Functional Connectivity

BACKGROUND

Symptoms of borderline personality disorder (BPD) often manifest during adolescence, but the underlying relationship between these debilitating symptoms and the development of functional brain networks is not well understood. Here, we aimed to investigate how multivariate patterns of functional connectivity are associated with borderline personality traits in large samples of young adults and adolescents.

METHODS

We used functional magnetic resonance imaging data from young adults and adolescents from the HCP-YA (Human Connectome Project Young Adult) (n = 870, ages 22-37 years, 457 female) and the HCP-D (Human Connectome Project Development) (n = 223, ages 16-21 years, 121 female). A previously validated BPD proxy score was derived from the NEO Five-Factor Inventory. A ridge regression model with cross-validation and nested hyperparameter tuning was trained and tested in HCP-YA to predict BPD scores in unseen data from regional functional connectivity. The trained model was further tested on data from HCP-D without further tuning. Finally, we tested how the connectivity patterns associated with BPD aligned with age-related changes in connectivity.

RESULTS

Multivariate functional connectivity patterns significantly predicted out-of-sample BPD scores in unseen data in young adults (HCP-YA ppermuted = .001) and older adolescents (HCP-D ppermuted = .001). Regional predictive capacity was heterogeneous; the most predictive regions were found in functional systems relevant for emotion regulation and executive function, including the ventral attention network. Finally, regional functional connectivity patterns that predicted BPD scores aligned with those associated with development in youth.

CONCLUSIONS

Individual differences in functional connectivity in developmentally sensitive regions are associated with borderline personality traits.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Methods for decoding cortical gradients of functional connectivity

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.

Framewise multi-echo distortion correction for superior functional MRI

Functional MRI (fMRI) data are severely distorted by magnetic field (B0) inhomogeneities which currently must be corrected using separately acquired field map data. However, changes in the head position of a scanning participant across fMRI frames can cause changes in the B0 field, preventing accurate correction of geometric distortions. Additionally, field maps can be corrupted by movement during their acquisition, preventing distortion correction altogether. In this study, we use phase information from multi-echo (ME) fMRI data to dynamically sample distortion due to fluctuating B0 field inhomogeneity across frames by acquiring multiple echoes during a single EPI readout. Our distortion correction approach, MEDIC (Multi-Echo DIstortion Correction), accurately estimates B0 related distortions for each frame of multi-echo fMRI data. Here, we demonstrate that MEDIC's framewise distortion correction produces improved alignment to anatomy and decreases the impact of head motion on resting-state functional connectivity (RSFC) maps, in higher motion data, when compared to the prior gold standard approach (i.e., TOPUP). Enhanced framewise distortion correction with MEDIC, without the requirement for field map collection, furthers the advantage of multi-echo over single-echo fMRI.

Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity

The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.

XCP-D: A Robust Pipeline for the post-processing of fMRI data

Functional neuroimaging is an essential tool for neuroscience research. Pre-processing pipelines produce standardized, minimally pre-processed data to support a range of potential analyses. However, post-processing is not similarly standardized. While several options for post-processing exist, they tend not to support output from disparate pre-processing pipelines, may have limited documentation, and may not follow BIDS best practices. Here we present XCP-D, which presents a solution to these issues. XCP-D is a collaborative effort between PennLINC at the University of Pennsylvania and the DCAN lab at the University at Minnesota. XCP-D uses an open development model on GitHub and incorporates continuous integration testing; it is distributed as a Docker container or Singularity image. XCP-D generates denoised BOLD images and functional derivatives from resting-state data in either NifTI or CIFTI files, following pre-processing with fMRIPrep, HCP, and ABCD-BIDS pipelines. Even prior to its official release, XCP-D has been downloaded >3,000 times from DockerHub. Together, XCP-D facilitates robust, scalable, and reproducible post-processing of fMRI data.

Acculturative Orientations Among Hispanic/Latinx Caregivers in the ABCD Study: Associations With Caregiver and Youth Mental Health and Youth Brain Function

Background

Population-based neuroscience offers opportunities to examine important but understudied sociocultural factors such as acculturation. Acculturation refers to the extent to which an individual retains their cultural heritage and/or adopts the receiving society's culture and is particularly salient among Hispanic/Latinx immigrants. Specific acculturative orientations have been linked to vulnerability to substance use, depression, and suicide and are known to influence family dynamics between caregivers and their children.

Methods

Using data from first- and second-generation Hispanic/Latinx caregivers in the Adolescent Brain Cognitive Development (ABCD) Study (N = 1057), we examined how caregivers' acculturative orientation affects their mental health, as well as the mental health and brain function of their children. Neuroimaging analyses focused on regions associated with self- and affiliation-based social processing (ventromedial prefrontal cortex, insula, and temporoparietal junction).

Results

We identified 2 profiles of caregiver acculturation: bicultural (retains heritage culture while adopting U.S. culture) and detached (discards heritage culture and rejects U.S. culture). Bicultural caregivers exhibited fewer internalizing and externalizing problems than detached caregivers; furthermore, youth exhibited similar internalizing effects across caregiver profiles. In addition, youth with bicultural caregivers displayed increased resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations and regional homogeneity) in the left insula, which has been linked to psychopathology; however, differences in long-range functional connectivity were not significant.

Conclusions

Caregiver acculturation is an important familial factor that has been linked to significant differences in youth mental health and insula activity. Future work should examine sociocultural and neurodevelopmental changes across adolescence to assess health outcomes and determine whether localized, corticolimbic brain effects are ultimately translated into long-range connectivity differences.

Task-based attentional and default mode connectivity associated with science and math anxiety profiles among university physics students

PURPOSE

Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students.

PROCEDURES

Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task.

FINDINGS

No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity.

CONCLUSIONS

These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.

Generalizable links between symptoms of borderline personality disorder and functional connectivity

Background |

Symptoms of borderline personality disorder (BPD) often manifest in adolescence, yet the underlying relationship between these debilitating symptoms and the development of functional brain networks is not well understood. Here we aimed to investigate how multivariate patterns of functional connectivity are associated with symptoms of BPD in a large sample of young adults and adolescents.

Methods |

We used high-quality functional Magnetic Resonance Imaging (fMRI) data from young adults from the Human Connectome Project: Young Adults (HCP-YA; N = 870, ages 22-37 years, 457 female) and youth from the Human Connectome Project: Development (HCP-D; N = 223, age range 16-21 years, 121 female). A previously validated BPD proxy score was derived from the NEO Five Factor Inventory (NEO-FFI). A ridge regression model with 10-fold cross-validation and nested hyperparameter tuning was trained and tested in HCP-YA to predict BPD scores in unseen data from regional functional connectivity, while controlling for in-scanner motion, age, and sex. The trained model was further tested on data from HCP-D without further tuning. Finally, we tested how the connectivity patterns associated with BPD aligned with age-related changes in connectivity.

Results |

Multivariate functional connectivity patterns significantly predicted out-of-sample BPD proxy scores in unseen data in both young adults (HCP-YA; pperm = 0.001) and older adolescents (HCP-D; pperm = 0.001). Predictive capacity of regions was heterogeneous; the most predictive regions were found in functional systems relevant for emotion regulation and executive function, including the ventral attention network. Finally, regional functional connectivity patterns that predicted BPD proxy scores aligned with those associated with development in youth.

Conclusion |

Individual differences in functional connectivity in developmentally-sensitive regions are associated with the symptoms of BPD.

A reproducible and generalizable software workflow for analysis of large-scale neuroimaging data collections using BIDS Apps

Neuroimaging research faces a crisis of reproducibility. With massive sample sizes and greater data complexity, this problem becomes more acute. Software that operates on imaging data defined using the Brain Imaging Data Structure (BIDS) - BIDS Apps - have provided a substantial advance. However, even using BIDS Apps, a full audit trail of data processing is a necessary prerequisite for fully reproducible research. Obtaining a faithful record of the audit trail is challenging - especially for large datasets. Recently, the FAIRly big framework was introduced as a way to facilitate reproducible processing of large-scale data by leveraging DataLad - a version control system for data management. However, the current implementation of this framework was more of a proof of concept, and could not be immediately reused by other investigators for different use cases. Here we introduce the BIDS App Bootstrap (BABS), a user-friendly and generalizable Python package for reproducible image processing at scale. BABS facilitates the reproducible application of BIDS Apps to large-scale datasets. Leveraging DataLad and the FAIRly big framework, BABS tracks the full audit trail of data processing in a scalable way by automatically preparing all scripts necessary for data processing and version tracking on high performance computing (HPC) systems. Currently, BABS supports jobs submissions and audits on Sun Grid Engine (SGE) and Slurm HPCs with a parsimonious set of programs. To demonstrate its scalability, we applied BABS to data from the Healthy Brain Network (HBN; n=2,565). Taken together, BABS allows reproducible and scalable image processing and is broadly extensible via an open-source development model.

Graded functional organisation in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity

The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include that the LIFG underpins a domain-general function or, alternatively, that it is characterized by functional differentiation, which might occur in either a discrete or a graded pattern. The aim of the present study was to explore the topographical organisation of the LIFG using a bimodal data-driven approach. To this end, we extracted functional connectivity (FC) gradients from 1) the resting-state fMRI time-series of 150 participants (77 female), and 2) patterns of co-activation derived meta-analytically from task data across a diverse set of cognitive domains. We then sought to characterize the FC differences driving these gradients with seed-based resting-state FC and meta-analytic co-activation modelling analyses. Both analytic approaches converged on an FC profile that shifted in a graded fashion along two main organisational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior LIFG) to being more tightly coupled with perceptually-driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal LIFG), and with the semantic network, on the other (ventral). These results provide novel insights into a graded functional organisation of the LIFG underpinning both task-free and task-constrained mental states, and suggest that the LIFG is an interface between distinct large-scale functional networks.

Neural systems underlying RDoC social constructs: An activation likelihood estimation meta-analysis

Neuroscientists have sought to identify the underlying neural systems supporting social processing that allow interaction and communication, forming social relationships, and navigating the social world. Through the use of NIMH's Research Domain Criteria (RDoC) framework, we evaluated consensus among studies that examined brain activity during social tasks to elucidate regions comprising the "social brain". We examined convergence across tasks corresponding to the four RDoC social constructs, including Affiliation and Attachment, Social Communication, Perception and Understanding of Self, and Perception and Understanding of Others. We performed a series of coordinate-based meta-analyses using the activation likelihood estimate (ALE) method. Meta-analysis was performed on whole-brain coordinates reported from 864 fMRI contrasts using the NiMARE Python package, revealing convergence in medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, temporoparietal junction, bilateral insula, amygdala, fusiform gyrus, precuneus, and thalamus. Additionally, four separate RDoC-based meta-analyses revealed differential convergence associated with the four social constructs. These outcomes highlight the neural support underlying these social constructs and inform future research on alterations among neurotypical and atypical populations.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies

BACKGROUND

Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact.

METHODS

We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks.

RESULTS

Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal).

CONCLUSIONS

These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

Extended functional connectivity of convergent structural alterations among individuals with PTSD: a neuroimaging meta-analysis

Background

Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated.

Methods

Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations.

Results

We observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes.

Conclusions

Consensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12993-022-00196-2.

qMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data

The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several neuroimaging modalities. Traditionally, BIDS had a strong focus on functional magnetic resonance imaging (MRI) datasets and lacked guidance on how to store multimodal structural MRI datasets. Here, we present and describe the BIDS Extension Proposal 001 (BEP001), which adds a range of quantitative MRI (qMRI) applications to the BIDS. In general, the aim of qMRI is to characterize brain microstructure by quantifying the physical MR parameters of the tissue via computational, biophysical models. By proposing this new standard, we envision standardization of qMRI through multicenter dissemination of interoperable datasets. This way, BIDS can act as a catalyst of convergence between qMRI methods development and application-driven neuroimaging studies that can help develop quantitative biomarkers for neural tissue characterization. In conclusion, this BIDS extension offers a common ground for developers to exchange novel imaging data and tools, reducing the entrance barrier for qMRI in the field of neuroimaging.

Altered large-scale brain network interactions associated with HIV infection and error processing

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

Risky decision-making strategies mediate the relationship between amygdala activity and real-world financial savings among individuals from lower income households: A pilot study

Lower financial savings among individuals experiencing adverse social determinants of health (SDoH) increases vulnerabilities during times of crisis. SDoH including low socioeconomic status (low-SES) influence cognitive abilities as well as health and life outcomes that may perpetuate poverty and disparities. Despite evidence suggesting a role for financial growth in minimizing SDoH-related disparities and vulnerabilities, neurobiological mechanisms linked with financial behavior remain to be elucidated. As such, we examined the relationships between brain activity during decision-making (DM), laboratory-based task performance, and money savings behavior. Participants (N = 24, 14 females) from low-SES households (income<$20,000/year) underwent fMRI scanning while performing the Balloon Analogue Risk Task (BART), a DM paradigm probing risky- and strategic-DM processes. Participants also completed self-report instruments characterizing relevant personality characteristics and then engaged in a community outreach financial program where amount of money saved was tracked over a 6-month period. Regarding BART-related brain activity, we observed expected activity in regions implicated in reward and emotional processing including the amygdala. Regarding brain-behavior relationships, we found that laboratory-based BART performance mediated the impact of amygdala activity on real-world behavior. That is, elevated amygdala activity was linked with BART strategic-DM which, in turn, was linked with more money saved after 6 months. In exploratory analyses, this mediation was moderated by emotion-related personality characteristics such that, only individuals reporting lower alexithymia demonstrated a relationship between amygdala activity and savings. These outcomes suggest that DM-related amygdala activity and/or emotion-related personality characteristics may provide utility as an endophenotypic marker of individual's financial savings behavior.

HIV infection is linked with reduced error-related default mode network suppression and poorer medication management abilities

OBJECTIVE

Brain activity linked with error processing has rarely been examined among persons living with HIV (PLWH) despite importance for monitoring and modifying behaviors that could lead to adverse health outcomes (e.g., medication non-adherence, drug use, risky sexual practices). Given that cannabis (CB) use is prevalent among PLWH and impacts error processing, we assessed the influence of HIV serostatus and chronic CB use on error-related brain activity while also considering associated implications for everyday functioning and clinically-relevant disease management behaviors.

METHODS

A sample of 109 participants, stratified into four groups by HIV and CB (HIV+/CB+, n = 32; HIV+/CB-, n = 27; HIV-/CB+, n = 28; HIV-/CB-, n = 22), underwent fMRI scanning while completing a modified Go/NoGo paradigm called the Error Awareness Task (EAT). Participants also completed a battery of well-validated instruments including a subjective report of everyday cognitive failures and an objective measure of medication management abilities.

RESULTS

Across all participants, we observed expected error-related anterior insula (aI) activation which correlated with better task performance (i.e., less errors) and, among HIV- participants, fewer self-reported cognitive failures. Regarding awareness, greater insula activation as well as greater posterior cingulate cortex (PCC) deactivation were notably linked with aware (vs. unaware) errors. Regarding group effects, unlike HIV- participants, PLWH displayed a lack of error-related deactivation in two default mode network (DMN) regions (i.e., PCC, medial prefrontal cortex [mPFC]). No CB main or interaction effects were detected. Across all participants, reduced error-related PCC deactivation correlated with reduced medication management abilities and PCC deactivation mediated the effect of HIV on such abilities. More lifetime CB use was linked with reduced error-related mPFC deactivation among HIV- participants and poorer medication management across CB users.

CONCLUSIONS

These results demonstrate that insufficient error-related DMN suppression linked with HIV infection, as well as chronic CB use among HIV- participants, has real-world consequences for medication management behaviors. We speculate that insufficient DMN suppression may reflect an inability to disengage task irrelevant mental operations, ultimately hindering error monitoring and behavior modification.

The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug and natural reward-related stimuli

The cue-reactivity paradigm is a widely adopted neuroimaging probe engendering brain activity linked with attentional, affective, and reward processes following presentation of appetitive stimuli. Given the multiple mental operations invoked, we sought to decompose cue-related brain activity into constituent components employing emergent meta-analytic techniques when considering drug and natural reward-related cues. We conducted coordinate-based meta-analyses delineating common and distinct brain activity convergence across cue-reactivity studies (N = 196 articles) involving drug (n = 133) or natural (n = 63) visual stimuli. Across all studies, convergence was observed in limbic, cingulate, insula, and fronto-parieto-occipital regions. Drug-distinct convergence was observed in posterior cingulate, dorsolateral prefrontal, and temporo-parietal regions, whereas distinct-natural convergence was observed in thalamic, insular, orbitofrontal, and occipital regions. We characterized connectivity profiles of identified regions by leveraging task-independent and task-dependent MRI datasets, grouped these profiles into subnetworks, and linked each with putative mental operations. Outcomes suggest multifaceted brain activity during cue-reactivity can be decomposed into elemental processes and indicate that while drugs of abuse usurp the brain's natural-reward-processing system, some regions appear distinct to drug cue-reactivity.

MMP8 increases tongue carcinoma cell-cell adhesion and diminishes migration via cleavage of anti-adhesive FXYD5

Matrix metalloproteinases (MMPs) modify bioactive factors via selective processing or degradation resulting in tumour-promoting or tumour-suppressive effects, such as those by MMP8 in various cancers. We mapped the substrates of MMP8 to elucidate its previously shown tumour-protective role in oral tongue squamous cell carcinoma (OTSCC). MMP8 overexpressing (+) HSC-3 cells, previously demonstrated to have reduced migration and invasion, showed enhanced cell-cell adhesion. By analysing the secretomes of MMP8 + and control cells with terminal amine isotopic labelling of substrates (TAILS) coupled with liquid chromatography and tandem mass spectrometry (LC-MS/MS), we identified 36 potential substrates of MMP8, including FXYD domain-containing ion transport regulator 5 (FXYD5). An anti-adhesive glycoprotein FXYD5 has been previously shown to predict poor survival in OTSCC. Cleavage of FXYD5 by MMP8 was confirmed using recombinant proteins. Furthermore, we detected a loss of FXYD5 levels on cell membrane of MMP8 + cells, which was rescued by inhibition of the proteolytic activity of MMP8. Silencing (si) FXYD5 increased the cell-cell adhesion of control but not that of MMP8 + cells. siFXYD5 diminished the viability and motility of HSC-3 cells independent of MMP8 and similar effects were seen in another tongue cancer cell line, SCC-25. FXYD5 is a novel substrate of MMP8 and reducing FXYD5 levels either with siRNA or cleavage by MMP8 increases cell adhesion leading to reduced motility. FXYD5 being a known prognostic factor in OTSCC, our findings strengthen its potential as a therapeutic target.

Effective Self-Management for Early Career Researchers in the Natural and Life Sciences

Early career researchers (ECRs) are faced with a range of competing pressures in academia, making self-management key to building a successful career. The Organization for Human Brain Mapping undertook a group effort to gather helpful advice for ECRs in self-management.

Multiple large-scale neural networks underlying emotion regulation

Recent models suggest emotion generation, perception, and regulation rely on multiple, interacting large-scale brain networks. Despite the wealth of research in this field, the exact functional nature and different topological features of these neural networks remain elusive. Here, we addressed both using a well-established data-driven meta-analytic grouping approach. We applied k-means clustering to a large set of previously published experiments investigating emotion regulation (independent of strategy, goal and stimulus type) to segregate the results of these experiments into large-scale networks. To elucidate the functional nature of these distinct networks, we used functional decoding of metadata terms (i.e. task-level descriptions and behavioral domains). We identified four large-scale brain networks. The first two were related to regulation and functionally characterized by a stronger focus on response inhibition or executive control versus appraisal or language processing. In contrast, the second two networks were primarily related to emotion generation, appraisal, and physiological processes. We discuss how our findings corroborate and inform contemporary models of emotion regulation and thereby significantly add to the literature.

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Ontological Dimensions of Cognitive-Neural Mappings

The growing literature reporting results of cognitive-neural mappings has increased calls for an adequate organizing ontology, or taxonomy, of these mappings. This enterprise is non-trivial, as relevant dimensions that might contribute to such an ontology are not yet agreed upon. We propose that any candidate dimensions should be evaluated on their ability to explain observed differences in functional neuroimaging activation patterns. In this study, we use a large sample of task-based functional magnetic resonance imaging (task-fMRI) results and a data-driven strategy to identify these dimensions. First, using a data-driven dimension reduction approach and multivariate distance matrix regression (MDMR), we quantify the variance among activation maps that is explained by existing ontological dimensions. We find that 'task paradigm' categories explain more variance among task-activation maps than other dimensions, including latent cognitive categories. Surprisingly, 'study ID', or the study from which each activation map was reported, explained close to 50% of the variance in activation patterns. Using a clustering approach that allows for overlapping clusters, we derived data-driven latent activation states, associated with re-occurring configurations of the canonical frontoparietal, salience, sensory-motor, and default mode network activation patterns. Importantly, with only four data-driven latent dimensions, one can explain greater variance among activation maps than all conventional ontological dimensions combined. These latent dimensions may inform a data-driven cognitive ontology, and suggest that current descriptions of cognitive processes and the tasks used to elicit them do not accurately reflect activation patterns commonly observed in the human brain.

Brain activity links performance in science reasoning with conceptual approach

Understanding how students learn is crucial for helping them succeed. We examined brain function in 107 undergraduate students during a task known to be challenging for many students-physics problem solving-to characterize the underlying neural mechanisms and determine how these support comprehension and proficiency. Further, we applied module analysis to response distributions, defining groups of students who answered by using similar physics conceptions, and probed for brain differences linked with different conceptual approaches. We found that integrated executive, attentional, visual motion, and default mode brain systems cooperate to achieve sequential and sustained physics-related cognition. While accuracy alone did not predict brain function, dissociable brain patterns were observed when students solved problems by using different physics conceptions, and increased success was linked to conceptual coherence. Our analyses demonstrate that episodic associations and control processes operate in tandem to support physics reasoning, offering potential insight to support student learning.

Sex differences in brain correlates of STEM anxiety

Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning.

Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit

Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naïve Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs.

Non-curative treatment of patients with oral tongue squamous-cell carcinoma

Purpose

Late-stage OTSCC is associated with poor overall survival (OS). Non-curative treatment approach aims to improve quality of life and prolong survival of patients deemed incurable. The purpose of this study was to investigate the used non-curative treatment modalities for OTSSC and patient survival.

Methods

All patients diagnosed with OTSCC and treated with non-curative intent at the HUS Helsinki University Hospital (Helsinki, Finland) during the 12-year period of 2005–2016 were included. Survival analysis after the non-curative treatment decision was conducted using the Kaplan–Meier method in this population-based study.

Results

Eighty-two patients were identified. A non-curative treatment decision was made at presentation without any previous treatment in 26 patients (7% of all patients diagnosed with OTSCC during the study period). Palliative radiotherapy was administered to 24% of all patients. The average survival time after the non-curative treatment decision was 3.7 months (median 2 and range 0–26).

Conclusions

Due to the short mean survival time after decision for treatment with non-curative intent, and the notable symptom burden in this patient population, a prompt initiation of all non-curative measures is warranted.

Myofibroblasts in oral potentially malignant disorders: Is it related to malignant transformation?

In oral cancer, acquisition of α-smooth muscle actin (α-SMA)-positive fibroblasts, known as myofibroblasts or carcinoma-associated fibroblasts (CAF), is an important event for progression and metastasis. However, the contribution of myofibroblasts in oral potentially malignant disorders (OPMD) remains controversial. This systematic review provides evidence that immunodetection of myofibroblasts may identify oral submucous fibrosis (OSMF) with high risk of malignant transformation, but does not represent an auxiliary tool to predict the malignant potential of leukoplakia and erythroplakia, the most common OPMD.

Meta-analytic evidence for a core problem solving network across multiple representational domains

Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development.

Toward a Neurobiological Basis for Understanding Learning in University Modeling Instruction Physics Courses

Modeling Instruction (MI) for University Physics is a curricular and pedagogical approach to active learning in introductory physics. A basic tenet of science is that it is a model-driven endeavor that involves building models, then validating, deploying, and ultimately revising them in an iterative fashion. MI was developed to provide students a facsimile in the university classroom of this foundational scientific practice. As a curriculum, MI employs conceptual scientific models as the basis for the course content, and thus learning in a MI classroom involves students appropriating scientific models for their own use. Over the last 10 years, substantial evidence has accumulated supporting MI's efficacy, including gains in conceptual understanding, odds of success, attitudes toward learning, self-efficacy, and social networks centered around physics learning. However, we still do not fully understand the mechanisms of how students learn physics and develop mental models of physical phenomena. Herein, we explore the hypothesis that the MI curriculum and pedagogy promotes student engagement via conceptual model building. This emphasis on conceptual model building, in turn, leads to improved knowledge organization and problem solving abilities that manifest as quantifiable functional brain changes that can be assessed with functional magnetic resonance imaging (fMRI). We conducted a neuroeducation study wherein students completed a physics reasoning task while undergoing fMRI scanning before (pre) and after (post) completing a MI introductory physics course. Preliminary results indicated that performance of the physics reasoning task was linked with increased brain activity notably in lateral prefrontal and parietal cortices that previously have been associated with attention, working memory, and problem solving, and are collectively referred to as the central executive network. Critically, assessment of changes in brain activity during the physics reasoning task from pre- vs. post-instruction identified increased activity after the course notably in the posterior cingulate cortex (a brain region previously linked with episodic memory and self-referential thought) and in the frontal poles (regions linked with learning). These preliminary outcomes highlight brain regions linked with physics reasoning and, critically, suggest that brain activity during physics reasoning is modifiable by thoughtfully designed curriculum and pedagogy.

Extracellular vesicles from oral squamous carcinoma cells display pro- and anti-angiogenic properties

BACKGROUND

A new intercellular communication mode established by neoplastic cells and tumor microenvironment components is based on extracellular vesicles (EVs). However, the biological effects of the EVs released by tumor cells on angiogenesis are not completely understood. Here, we aimed to understand the biological effects of EVs isolated from two cell lines of oral squamous cell carcinoma (OSCC) (SCC15 and HSC3) on endothelial cell tubulogenesis.

METHODS

OSCC-derived EVs were isolated with a polymer-based precipitation method, quantified using nanoparticle tracking analysis and verified for EV markers by dot blot. Functional assays were performed to assess the angiogenic potential of the OSCC-derived EVs.

RESULTS

The results showed that EVs derived from both cell lines displayed typical spherical-shaped morphology and expressed the EV markers CD63 and Annexin II. Although the average particle concentration and size were quite similar, SCC15-derived EVs promoted a pronounced tubular formation associated with significant migration and apoptosis rates of the endothelial cells, whereas EVs derived from HSC3 cells inhibited significantly endothelial cell tubulogenesis and proliferation.

CONCLUSION

The findings of this study reveal that EVs derived from different OSCC cell lines by a polymer-based precipitation method promote pro- or anti-angiogenic effects.

Topical tacrolimus, triamcinolone acetonide, and placebo in oral lichen planus: a pilot randomized controlled trial

OBJECTIVE

To carry out a double-blind randomized controlled trial (RCT) to compare the effectiveness of topical tacrolimus (TAC), triamcinolone acetonide (TRI), and placebo (PLA) in symptomatic oral lichen planus (OLP).

SUBJECTS AND METHODS

A clinical score (CS, range 0-130) was developed to measure the clinical signs and symptoms of OLP. Twenty-seven OLP patients with a CS of ≥20 were randomly allocated to receive 0.1% TAC ointment (n = 11), 0.1% TRI paste (n = 7), or Orabase^® paste as PLA (n = 9) for 3 weeks. If the CS dropped ≥20% (interpreted as response), the patients continued the same medication for another 3 weeks. If the CS dropped <20% or increased (non-response), the patients were switched to TAC for 6 weeks. A 6-month follow-up period ensued. The primary outcome variable was the change in CS from baseline to week 3. In primary outcome analysis, CS values between the treatment arms were compared.

RESULTS

Tacrolimus and TRI were more effective (P = 0.012 and 0.031, respectively) than PLA in reducing the CS at week 3. No difference in the efficacy was noted between TAC and TRI (P = 0.997).

CONCLUSIONS

This pilot RCT provides evidence for the effectiveness of TAC and TRI over PLA in the management of OLP.

Distinct neural correlates for attention lapses in patients with schizophrenia and healthy participants

Momentary lapses in attention are common in healthy populations. This phenomenon has recently received increased investigation, particularly in relationship to the default mode network (DMN). Previous research has suggested that these lapses may be due to intrusive task-irrelevant thoughts. The study of this phenomenon in schizophrenia, which is characterized by a wide variety of cognitive deficits including deficits in attention, has not previously been explored. We used the AX Continuous Performance Task to investigate attention lapses in healthy participants as well as patients with schizophrenia. We found distinct patterns of network activation between these two groups. Lapses in healthy participants were associated with DMN activation, while in patients, the same behavioral phenomenon was associated with deactivations in frontal-parietal control network (FPCN) regions. When considered in contrast to the results observed in healthy participants, these results suggest an additional origin of attention lapses in patients derived from a loss of task-related context, rather than intrusive task-irrelevant thoughts.

The prognostic value of histopathological grading systems in oral squamous cell carcinomas

OBJECTIVE

This study evaluated the association of four histopathological grading systems (WHO grading system, malignancy grading of the deep invasive margins (MG), histological risk (HR) model, and tumor budding and depth of invasion (BD) model) with clinicopathological parameters and outcome of 113 oral squamous cell carcinomas to identify their roles in prognosis.

METHODS

Demographic and clinical features were obtained from patients' records. Sections from all paraffin-embedded blocks were evaluated according to the four grading systems. Demographic and clinical associations were analyzed using chi-square test, and correlations between the grading systems were established with the Spearman's rank correlation test. Survival curves were performed with Kaplan-Meier method, and multivariate analysis based on Cox proportional hazard model was calculated.

RESULTS

Significant associations with survival were observed for WHO grading system and BD model in the univariate analysis, but only the BD model was significantly associated with disease outcome as an independent prognostic marker. Age, tumor size, and presence of regional metastasis were also independent markers of reduced survival.

CONCLUSION

A significant association between the BD model and outcome of OSCC patients was observed, indicating this new histopathological grading system as a possible prognostic tool.

Phosphorus in manure and sewage sludge more recyclable than in soluble inorganic fertilizer

Phosphorus (P) flow from deposits through agriculture to waterways leads to eutrophication and depletion of P reserves. Therefore, P must be recycled. Low and unpredictable plant availability of P in residues is considered to be a limiting factor for recycling. We identified the determinants for the plant-availability of P in agrifood residues. We quantified P in Italian ryegrass (Lolium multiflorum) and in field soil fractions with different plant availabilities of P as a response to manure and sewage sludge with a range of P capture and hygienization treatments. P was more available in manure and in sludge, when it was captured biologically or with a moderate iron (Fe)/P (1.6), than in NPK. Increasing rate of sludge impaired P recovery and high Fe/P (9.8) prevented it. Anaerobic digestion (AD) reduced plant-availability at relevant rates. The recovery of P was increased in AD manure via composting and in AD sludge via combined acid and oxidizer. P was not available to plants in the sludge hygienized with a high calcium/P. Contrary to assumed knowledge, the recyclability of P in appropriately treated residues can be better than in NPK. The prevention of P sorption in soil by organic substances in fertilizers critically enhances the recyclability of P.

Role of dentin MMPs in caries progression and bond stability

Dentin can be described as a biological composite with collagen matrix embedded with nanosized hydroxyapatite mineral crystallites. Matrix metalloproteinases (MMPs) and cysteine cathepsins are families of endopeptidases. Enzymes of both families are present in dentin and collectively capable of degrading virtually all extracellular matrix components. This review describes these enzymes and their presence in dentin, mainly focusing on their role in dentin caries pathogenesis and loss of collagen in the adhesive hybrid layer under composite restorations. MMPs and cysteine cathepsins present in saliva, mineralized dentin, and/or dentinal fluid may affect the dentin caries process at the early phases of demineralization. Changes in collagen and noncollagenous protein structure may participate in observed decreases in mechanical properties of caries-affected dentin and reduce the ability of caries-affected dentin to remineralize. These endogenous enzymes also remain entrapped within the hybrid layer during the resin infiltration process, and the acidic bonding agents themselves (irrespective of whether they are etch-and-rinse or self-etch) can activate these endogenous protease proforms. Since resin impregnation is frequently incomplete, denuded collagen matrices associated with free water (which serves as a collagen cleavage reagent for these endogenous hydrolase enzymes) can be enzymatically disrupted, finally contributing to the degradation of the hybrid layer. There are multiple in vitro and in vivo reports showing that the longevity of the adhesive interface is increased when nonspecific enzyme-inhibiting strategies are used. Different chemicals (i.e., chlorhexidine, galardin, and benzalkonium chloride) or collagen cross-linker agents have been successfully employed as therapeutic primers in the bonding procedure. In addition, the incorporation of enzyme inhibitors (i.e., quaternary ammonium methacrylates) into the resin blends has been recently promoted. This review will describe MMP functions in caries and hybrid layer degradation and explore the potential therapeutic role of MMP inhibitors for the development of improved intervention strategies for MMP-related oral diseases.

[Nutraceuticals in the combat against oral cancer]

Head and neck squamous cell carcinoma (HNSCC), the eighth most common cancer worldwide, accounts for approximately 600,000 new cases per year. The mobile tongue is the most common site for oral cancer and is associated with a poorer survival than other HNSCC sites. Standard therapeutic strategies have failed to significantly improve survival rates that have remained around 50% over the past four decades. In the last decade intense investigations on oral cancer highlighted the mandatory role of the tumor microenvironment (TME), in addition to the genetic aberrations and molecular biology changes within the cancer cells. Furthermore, the molecular crosstalk between cancer cells and TME components (i.e., cancer-associated fibroblasts, inflammatory pro-tumorigenic cells, etc.) has a crucial role in growth, invasion, spread and metastases of the cancer cells and consequently leads to poor prognosis. Recent studies suggest that plant-derived dietary agents nutraceuticals, especially curcumin and green tea, have the advantage to combat both malignant cells and TME components, unlike standard anti-cancer protocols that target only cancer cells. However, due to a very low bioavailability, nutraceuticals do not currently constitute an integral part of these protocols. Ongoing developments in nanotechnology for improved delivery are expected to overcome their challenging pharmacokinetics.

Clinicopathological prognostic factors of oral tongue squamous cell carcinoma: a retrospective study of 202 cases

Although several histopathological parameters and grading systems have been described as predictive of the treatment response and outcome of oral squamous cell carcinoma (OSCC), none is universally accepted. A new scoring system, the histological risk model, was recently described to be a powerful predictive tool for recurrence and overall survival in OSCC. The aim of this study was to verify the predictive role of the histological risk model in a cohort of 202 patients at all stages of oral/mobile tongue squamous cell carcinoma (OTSCC). Demographic and clinical data were collected from the medical records and the tumours were evaluated using the histological risk model. Statistical analyses were performed using the χ(2) test, the Kaplan-Meier method, and the Cox regression model. The histological risk model showed no statistical correlation with demographic or clinical parameters and did not Predict the outcome of the OTSCC patients. However, multivariate regression analysis revealed a significant correlation of the clinical disease stage with the disease outcome. Despite major efforts to identify new predictive parameters and histological systems, clinical features are still the most reliable prognostic factors for patients with OTSCC.

Sodium fluoride inhibits MMP-2 and MMP-9

The importance of fluoride (F) in preventing dental caries by favorably interfering in the demineralization-remineralization processes is well-established, but its ability to inhibit matrix metalloproteinases (MMPs), which could also help to prevent dentin caries, has not been investigated. This study assessed the ability of F to inhibit salivary and purified human gelatinases MMPs-2 and -9. Saliva was collected from 10 healthy individuals. Pooled saliva was centrifuged, and supernatants were incubated for 1 hr at 37°C and subjected to zymography. Sodium fluoride (50-275 ppm F) was added to the incubation buffer. The reversibility of the inhibition of MMPs-2 and -9 by NaF was tested by the addition of NaF (250-5,000 ppm F) to the incubation buffer, after which an additional incubation was performed in the absence of F. F decreased the activities of pro- and active forms of salivary and purified human MMPs in a dose-response manner. Purified gelatinases were completely inhibited by 200 ppm F (IC50 = 100 and 75 ppm F for MMPs-2 and -9, respectively), and salivary MMP-9 by 275 ppm F (IC50 = 200 ppm F). Inhibition was partially reversible at 250-1,500 ppm F, but was irreversible at 5,000 ppm F. This is the first study to describe the ability of NaF to inhibit MMPs completely.