Association of Localizing 18F-FDG-PET Hypometabolism and Outcome Following Epilepsy Surgery: Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Although commonly used in the evaluation of patients for epilepsy surgery, the association between the detection of localizing 18fluorine fluorodeoxyglucose PET (18F-FDG-PET) hypometabolism and epilepsy surgery outcome is uncertain. We conducted a systematic review and meta-analysis to determine whether localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery. METHODS: A systematic literature search was undertaken. Eligible publications included evaluation with 18F-FDG-PET before epilepsy surgery, with ≥10 participants, and those that reported surgical outcome at ≥12 months. Random-effects meta-analysis was used to calculate the odds of achieving a favorable outcome, defined as Engel class I, International League Against Epilepsy class 1-2, or seizure-free, with localizing 18F-FDG-PET hypometabolism, defined as concordant with the epilepsy surgery resection zone. Meta-regression was used to characterize sources of heterogeneity. RESULTS: The database search identified 8,916 studies, of which 98 were included (total patients n = 4,104). Localizing 18F-FDG-PET hypometabolism was associated with favorable outcome after epilepsy surgery for all patients with odds ratio (OR) 2.68 (95% CI 2.08-3.45). Subgroup analysis yielded similar findings for those with (OR 2.64, 95% CI 1.54-4.52) and without epileptogenic lesion detected on MRI (OR 2.49, 95% CI 1.80-3.44). Concordance with EEG (OR 2.34, 95% CI 1.43-3.83), MRI (OR 1.69, 95% CI 1.19-2.40), and triple concordance with both (OR 2.20, 95% CI 1.32-3.64) was associated with higher odds of favorable outcome. By contrast, diffuse 18F-FDG-PET hypometabolism was associated with worse outcomes compared with focal hypometabolism (OR 0.34, 95% CI 0.22-0.54). DISCUSSION: Localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery, irrespective of the presence of an epileptogenic lesion on MRI. The extent of 18F-FDG-PET hypometabolism provides additional information, with diffuse hypometabolism associated with worse surgical outcome than focal 18F-FDG-PET hypometabolism. These findings support the incorporation of 18F-FDG-PET into routine noninvasive investigations for patients being evaluated for epilepsy surgery to improve epileptogenic zone localization and to aid patient selection for surgery.

A systematic review of the impact of brain tumours on risk of motor vehicle crashes.

PURPOSE: Brain tumours are associated with neurocognitive impairments that are important for safe driving. Driving is vital to maintaining patient autonomy, despite this there is limited research on driving capacity amongst patients with brain tumours. The purpose of this review is to examine MVC risk in patients with brain tumours to inform development of clearer driving guidelines. METHODS: A systematic review was performed using Medline and EMBASE. Observational studies were included. The outcome of interest was MVC or measured risk of MVC in patients with benign or malignant brain tumours. Descriptive analysis and synthesis without meta-analysis were used to summarise findings. A narrative review of driving guidelines from Australia, United Kingdom and Canada was completed. RESULTS: Three studies were included in this review. One cohort study, one cross-sectional study and one case-control study were included (19,135 participants) across United States and Finland. One study evaluated the incidence of MVC in brain tumour patients, revealing no difference in MVC rates. Two studies measured MVC risk using driving simulation and cognitive testing. Patients found at higher risk of MVC had greater degrees of memory and visual attention impairments. However, predictive patient and tumour characteristics of MVC risk were heterogeneous across studies. Overall, driving guidelines had clear recommendations on selected conditions like seizures but were vague surrounding neurocognitive deficits. CONCLUSION: Limited data exists regarding driving behaviour and MVC incidence in brain tumour patients. Existing guidelines inadequately address neurocognitive complexities in this group. Future studies evaluating real-world data is required to inform development of more applicable driving guidelines. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO 2023 CRD42023434608.

Identifying epilepsy surgery referral candidates with natural language processing in an Australian context.

OBJECTIVE: Epilepsy surgery is known to be underutilized. Machine learning-natural language processing (ML-NLP) may be able to assist with identifying patients suitable for referral for epilepsy surgery evaluation. METHODS: Data were collected from two tertiary hospitals for patients seen in neurology outpatients for whom the diagnosis of "epilepsy" was mentioned. Individual case note review was undertaken to characterize the nature of the diagnoses discussed in these notes, and whether those with epilepsy fulfilled prespecified criteria for epilepsy surgery workup (namely focal drug refractory epilepsy without contraindications). ML-NLP algorithms were then developed using fivefold cross-validation on the first free-text clinic note for each patient to identify these criteria. RESULTS: There were 457 notes included in the study, of which 250 patients had epilepsy. There were 37 (14.8%) individuals who fulfilled the prespecified criteria for epilepsy surgery referral without described contraindications, 32 (12.8%) of whom were not referred for epilepsy surgical evaluation in the given clinic visit. In the prediction of suitability for epilepsy surgery workup using the prespecified criteria, the tested models performed similarly. For example, the random forest model returned an area under the receiver operator characteristic curve of 0.97 (95% confidence interval 0.93-1.0) for this task, sensitivity of 1.0, and specificity of 0.93. SIGNIFICANCE: This study has shown that there are patients in tertiary hospitals in South Australia who fulfill prespecified criteria for epilepsy surgery evaluation who may not have been referred for such evaluation. ML-NLP may assist with the identification of patients suitable for such referral. PLAIN LANGUAGE SUMMARY: Epilepsy surgery is a beneficial treatment for selected individuals with drug-resistant epilepsy. However, it is vastly underutilized. One reason for this underutilization is a lack of prompt referral of possible epilepsy surgery candidates to comprehensive epilepsy centers. Natural language processing, coupled with machine learning, may be able to identify possible epilepsy surgery candidates through the analysis of unstructured clinic notes. This study, conducted in two tertiary hospitals in South Australia, demonstrated that there are individuals who fulfill criteria for epilepsy surgery evaluation referral but have not yet been referred. Machine learning-natural language processing demonstrates promising results in assisting with the identification of such suitable candidates in Australia.

The impact of cognitive resource constraints on goal prioritization.

Many decisions we face daily entail deliberation about how to coordinate resources shared between multiple, competing goals. When time permits, people appear to approach these goal prioritization problems by analytically considering all goal-relevant information to arrive at a prioritization decision. However, it is not yet clear if this normative strategy extends to situations characterized by resource constraints such as when deliberation time is scarce or cognitive load is high. We evaluated the questions of how limited deliberation time and cognitive load affect goal prioritization decisions across a series of experiments using a gamified experimental task, which required participants to make a series of interdependent goal prioritization decisions. We fit several candidate models to experimental data to identify decision strategy adaptations at the individual subject-level. Results indicated that participants tended to opt for a simple heuristic strategy when cognitive resources were constrained rather than making a general tradeoff between speed and accuracy (e.g., the type of tradeoff that would be predicted by evidence accumulation models). The most common heuristic strategy involved disproportionately weighing information about goal deadlines compared to other goal-relevant information such as the goal's difficulty and the goal's subjective value.

Impact of contrasting poultry exposures on human, poultry, and wastewater antibiotic resistomes in Bangladesh.

IMPORTANCE: Through the use of DNA sequencing, our study shows that there is no significant difference in the antibiotic resistance genes found in stool samples taken from individuals with high exposure to poultry routinely fed antibiotics and those without such exposure. This finding is significant as it suggests limited transmission of antibiotic resistance genes between poultry and humans in these circumstances. However, our research also demonstrates that commercially reared poultry are more likely to possess resistance genes to antibiotics commonly administered on medium-sized farms. Additionally, our study highlights the under-explored potential of wastewater as a source of various antibiotic resistance genes, some of which are clinically relevant.

Ex-SPECTing Success: predictors of successful SPECT radiotracer injection during pre-surgical video-EEG admissions.

OBJECTIVES: To determine predictors of successful ictal Single Photon Emission Computed Tomography (SPECT) injections during Epilepsy Monitoring Unit (EMU) admissions for patients undergoing presurgical evaluation for drug resistant focal epilepsy. METHODS: In this retrospective study, consecutive EMU admissions were analysed at a single centre between 2019-2021. All seizures that occurred during the admission were reviewed. 'Injectable seizures' occurred during hours when the radiotracer was available. EMU-level data were analysed to identify factors predictive of an EMU admission with a successful SPECT injection (successful admission). Seizure-level data were analysed to identify factors predictive of an 'injectable seizure' receiving a SPECT injection during the ictal phase (successful injection). A multivariate generalised linear model was used to identify predictive variables. RESULTS: 125 EMU admissions involving 103 patients (median 37 years, IQR27.0-45.5) were analysed. 38.8% of seizures that were eligible for SPECT (n=134) were successfully injected; this represented 17.4% of all seizures (n=298) that occurred during admission. Unsuccessful admissions were most commonly due to a lack of seizures during EMU-SPECT (19.3%) or no 'injectable seizures' (62.3%). Successful EMU-SPECT was associated with baseline seizure frequency >1 per week (95%CI 2.1-3.0, p <0.001) and focal PET hypometabolism (95%CI 2.0-3.7, p <0.001). On multivariate analysis, the only factor associated with successful injection was patients being able to indicate they were having a seizure to staff (95%CI 1.0-4.4, p=0.038). SIGNIFICANCE: Completing a successful ictal SPECT study remains challenging. Baseline seizure frequency of >1 per-week, a PET hypometabolic focus and a patient's ability to indicate seizure onset were identified as predictors of success. These findings may assist EMUs in optimising their SPECT protocols, patient selection, and resource allocation.

An international survey of SEEG cortical stimulation practices.

OBJECTIVE: Cortical stimulation is an important component of stereoelectroencephalography (SEEG). Despite this, there is currently no standardized approach and significant heterogeneity in the literature regarding cortical stimulation practices. Via an international survey of SEEG clinicians, we sought to examine the spectrum of cortical stimulation practices to reveal areas of consensus and variability. METHODS: A 68-item questionnaire was developed to understand cortical stimulation practices including neurostimulation parameters, interpretation of epileptogenicity, functional and cognitive assessment and subsequent surgical decisions. Multiple recruitment pathways were pursued, with the questionnaire distributed directly to 183 clinicians. RESULTS: Responses were received from 56 clinicians across 17 countries with experience ranging from 2 to 60 years (M = 10.73, SD = 9.44). Neurostimulation parameters varied considerably, with maximum current ranging from 3 to 10 mA (M = 5.33, SD = 2.29) for 1 Hz and from 2 to 15 mA (M = 6.54, SD = 3.68) for 50 Hz stimulation. Charge density ranged from 8 to 200 µC/cm2 , with up to 43% of responders utilizing charge densities higher than recommended upper safety limits, i.e. 55 µC/cm2 . North American responders reported statistically significant higher maximum current (P < 0.001) for 1 Hz stimulation and lower pulse width for 1 and 50 Hz stimulation (P = 0.008, P < 0.001, respectively) compared to European responders. All clinicians evaluated language, speech, and motor function during cortical stimulation; in contrast, 42% assessed visuospatial or visual function, 29% memory, and 13% executive function. Striking differences were reported in approaches to assessment, classification of positive sites, and surgical decisions guided by cortical stimulation. Patterns of consistency were observed for interpretation of the localizing capacity of stimulated electroclinical seizures and auras, with habitual electroclinical seizures induced by 1 Hz stimulation considered the most localizing. SIGNIFICANCE: SEEG cortical stimulation practices differed vastly across clinicians internationally, highlighting the need for consensus-based clinical guidelines. In particular, an internationally standardized approach to assessment, classification, and functional prognostication will provide a common clinical and research framework for optimizing outcomes for people with drug-resistant epilepsy.

Identifying epilepsy surgery candidates with natural language processing: A systematic review.

INTRODUCTION: Epilepsy surgery is an underutilised, efficacious management strategy for selected individuals with drug-resistant epilepsy. Natural language processing (NLP) may aid in the identification of patients who are suitable to undergo evaluation for epilepsy surgery. The feasibility of this approach is yet to be determined. METHOD: In accordance with the PRISMA guidelines, a systematic review of the databases PubMed, EMBASE and Cochrane library was performed. This systematic review was prospectively registered on PROSPERO. RESULTS: 6 studies fulfilled inclusion criteria. The majority of included studies reported on datasets from only a single centre, with one study utilising data from two centres and one study six centres. The most commonly employed algorithms were support vector machines (5/6), with only one study utilising NLP strategies such as random forest models and gradient boosted machines. However, the results are promising, with all studies demonstrating moderate to high levels of performance in the identification of patients who may be suitable to undergo epilepsy surgery evaluation. Furthermore, multiple studies demonstrated that NLP could identify such patients 1-2 years prior to the treating clinicians instigating referral. However, no studies were identified that have evaluated the influence of implementing such algorithms on healthcare systems or patient outcomes. CONCLUSIONS: NLP is a promising approach to aid in the identification of patients that may be suitable to undergo epilepsy surgery evaluation. Further studies are required examining diverse datasets with additional analytical methodologies. Studies evaluating the impact of implementation of such algorithms would be beneficial.

Interruptions in healthcare: Modeling dynamic processes and effects at a team level.

Interruptions are associated with increases in medical errors amongst healthcare professionals, yet interventions to reduce interruptions have not been widely successful. While interruptions can be problematic for the interruptee, they may be necessary for the interrupter to maintain patient safety. To understand the emergent effects of interruptions within a dynamic environment, we develop a computational model that describes how nurses make decisions about interruptions and the effects those decisions have at a team level. Simulations reveal the dynamic interplay between urgency, task importance, the cost of being interrupted and team efficiency, depending on the consequences of clinical or procedural error, and shed light on the ways that the risks from interruptions can be better managed.

Abundance and phylogenetic distribution of eight key enzymes of the phosphorus biogeochemical cycle in grassland soils.

Grassland biomes provide valuable ecosystem services, including nutrient cycling. Organic phosphorus (Po) represents more than half of the total P in soils. Soil microorganisms release organic P through enzymatic processes, with alkaline phosphatases, acid phosphatases and phytases being the key P enzymes involved in the cycling of organic P. This study analysed 74 soil metagenomes from 17 different grassland biomes worldwide to evaluate the distribution and abundance of eight key P enzymes (PhoD, PhoX, PhoA, Nsap-A, Nsap-B, Nsap-C, BPP and CPhy) and their relationship with environmental factors. Our analyses showed that alkaline phosphatase phoD was the dataset's most abundant P-enzyme encoding genes, with a wide phylogenetic distribution. Followed by the acid phosphatases Nsap-A and Nsap-C showed similar abundance but a different distribution in their respective phylogenetic trees. Multivariate analyses revealed that pH, Tmax , SOC and soil moisture were associated with the abundance and diversity of all genes studied. PhoD and phoX genes strongly correlated with SOC and clay, and the phoX gene was more common in soils with low to medium SOC and neutral pH. In particular, P-enzyme genes tended to respond in a positively correlated manner among them, suggesting a complex relationship of abundance and diversity among them.

Impact of epilepsy surgery on quality of life: Systematic review and meta-analysis.

Improved quality of life (QoL) is an important outcome goal following epilepsy surgery. This study aims to quantify change in QoL for adults with drug-resistant epilepsy (DRE) who undergo epilepsy surgery, and to explore clinicodemographic factors associated with these changes. We conducted a systematic review and meta-analysis using Medline, Embase, and Cochrane Central Register of Controlled Trials. All studies reporting pre- and post-epilepsy surgery QoL scores in adults with DRE via validated instruments were included. Meta-analysis assessed the postsurgery change in QoL. Meta-regression assessed the effect of postoperative seizure outcomes on postoperative QoL as well as change in pre- and postoperative QoL scores. A total of 3774 titles and abstracts were reviewed, and ultimately 16 studies, comprising 1182 unique patients, were included. Quality of Life in Epilepsy Inventory-31 item (QOLIE-31) meta-analysis included six studies, and QOLIE-89 meta-analysis included four studies. Postoperative change in raw score was 20.5 for QOLIE-31 (95% confidence interval [CI] = 10.9-30.1, I2 = 95.5) and 12.1 for QOLIE-89 (95% CI = 8.0-16.1, I2 = 55.0%). This corresponds to clinically meaningful QOL improvements. Meta-regression demonstrated a higher postoperative QOLIE-31 score as well as change in pre- and postoperative QOLIE-31 score among studies of cohorts with higher proportions of patients with favorable seizure outcomes. At an individual study level, preoperative absence of mood disorders, better preoperative cognition, fewer trials of antiseizure medications before surgery, high levels of conscientiousness and openness to experience at the baseline, engagement in paid employment before and after surgery, and not being on antidepressants following surgery were associated with improved postoperative QoL. This study demonstrates the potential for epilepsy surgery to provide clinically meaningful improvements in QoL, as well as identifies clinicodemographic factors associated with this outcome. Limitations include substantial heterogeneity between individual studies and high risk of bias.

Arable soil nitrogen dynamics reflect organic inputs via the extended composite phenotype.

Achieving food security requires resilient agricultural systems with improved nutrient-use efficiency, optimized water and nutrient storage in soils, and reduced gaseous emissions. Success relies on understanding coupled nitrogen and carbon metabolism in soils, their associated influences on soil structure and the processes controlling nitrogen transformations at scales relevant to microbial activity. Here we show that the influence of organic matter on arable soil nitrogen transformations can be decoded by integrating metagenomic data with soil structural parameters. Our approach provides a mechanistic explanation of why organic matter is effective in reducing nitrous oxide losses while supporting system resilience. The relationship between organic carbon, soil-connected porosity and flow rates at scales relevant to microbes suggests that important increases in nutrient-use efficiency could be achieved at lower organic carbon stocks than currently envisaged.

Intrinsic and secondary epileptogenicity in focal cortical dysplasia type II.

OBJECTIVE: Favorable seizure outcome is reported following resection of bottom-of-sulcus dysplasia (BOSD). We assessed the distribution of epileptogenicity and dysplasia in and around BOSD to better understand this clinical outcome and the optimal surgical approach. METHODS: We studied 27 children and adolescents with magnetic resonance imaging (MRI)-positive BOSD who underwent epilepsy surgery; 85% became seizure-free postresection (median = 5.0 years follow-up). All patients had resection of the dysplastic sulcus, and 11 had additional resection of the gyral crown (GC) or adjacent gyri (AG). Markers of epileptogenicity were relative cortical hypometabolism on preoperative 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET), and spiking, ripples, fast ripples, spike-high-frequency oscillation cross-rate, and phase amplitude coupling (PAC) on preresection and postresection electrocorticography (ECoG), all analyzed at the bottom-of-sulcus (BOS), top-of-sulcus (TOS), GC, and AG. Markers of dysplasia were increased cortical thickness on preoperative MRI, and dysmorphic neuron density and variant allele frequency of somatic MTOR mutations in resected tissue, analyzed at similar locations. RESULTS: Relative cortical metabolism was significantly reduced and ECoG markers were significantly increased at the BOS compared to other regions. Apart from spiking and PAC, which were greater at the TOS compared to the GC, there were no significant differences in PET and other ECoG markers between the TOS, GC, and AG, suggesting a cutoff of epileptogenicity at the TOS rather than a tapering gradient on the cortical surface. MRI and tissue markers of dysplasia were all maximal in the BOS, reduced in the TOS, and mostly absent in the GC. Spiking and PAC reduced significantly over the GC after resection of the dysplastic sulcus. SIGNIFICANCE: These findings support the concept that dysplasia and intrinsic epileptogenicity are mostly limited to the dysplastic sulcus in BOSD and support resection or ablation confined to the MRI-visible lesion as a first-line surgical approach. 18 F-FDG PET and ECoG abnormalities in surrounding cortex seem to be secondary phenomena.

Evidence accumulation modelling in the wild: understanding safety-critical decisions.

Evidence accumulation models (EAMs) are a class of computational cognitive model used to understand the latent cognitive processes that underlie human decisions and response times (RTs). They have seen widespread application in cognitive psychology and neuroscience. However, historically, the application of these models was limited to simple decision tasks. Recently, researchers have applied these models to gain insight into the cognitive processes that underlie observed behaviour in applied domains, such as air-traffic control (ATC), driving, forensic and medical image discrimination, and maritime surveillance. Here, we discuss how this modelling approach helps researchers understand how the cognitive system adapts to task demands and interventions, such as task automation. We also discuss future directions and argue for wider adoption of cognitive modelling in Human Factors research.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Using cognitive modeling to examine the effects of competition on strategy and effort in races and tournaments.

We investigated the effects of two types of competition, races and tournaments (as well as an individual challenge and a do-your-best condition), on two different aspects of performance: effort and strategy. In our experiment, 100 undergraduate participants completed a simple cognitive task under four experimental conditions (in a repeated-measures design) based on different types of competitions and challenges. We used the Linear Ballistic Accumulator to quantify the effects of competition on strategy and effort. The results reveal that competition produced changes in strategy rather than effort, and that trait competitiveness had minimal impact on how people responded to competition. This suggests individuals are more likely to adjust their strategy in competitions, and the uncertainty created by different competition types influences the direction of these strategy adjustments.

Changes in affect during the pursuit of performance goals.

The aim of this article is to examine how affect changes when people are pursuing performance goals. We do this using the circumplex model of affect, in which a person's current affective state is represented as a point on a plane defined by the latent dimensions of pleasure and activation. We test competing hypotheses regarding the direction of changes within this 2-dimensional space. The first set of hypotheses are derived from Carver and Scheier's (1998) theory of self-regulation, which predicts that changes in the prospects of goal attainment should produce changes along axes offset 45° from the pleasure and activation dimensions. The second set of hypotheses are derived from the concept of core affect (Russell, 2003), which predicts that changes in the prospects of goal attainment should produce changes in pleasure, while changes in task demands should produce changes in activation. Two studies are reported in which participants provided ratings of momentary affect during goal pursuit. We developed a latent change model to estimate the direction and magnitude of changes in affect attributable to changes in the prospects of goal attainment and task demand. The results are more consistent with the hypotheses derived from the core affect account than with the hypotheses derived from the Carver and Scheier account. Theoretical and practical implications are discussed, with a focus on prospects for the development of an integrative theory, which accounts for both the motivational and affective components of goal pursuit. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

18F-FDG-PET hypometabolism as a predictor of favourable outcome in epilepsy surgery: protocol for a systematic review and meta-analysis.

INTRODUCTION: A substantial proportion of patients who undergo surgery for drug resistant focal epilepsy do not become seizure free. While some factors, such as the detection of hippocampal sclerosis or a resectable lesion on MRI and electroencephalogram-MRI concordance, can predict favourable outcomes in epilepsy surgery, the prognostic value of the detection of focal hypometabolism with 18F-fluorodeoxyglucose positive emission tomography (18F-FDG-PET) hypometabolism is uncertain. We propose a protocol for a systematic review and meta-analysis to examine whether localisation with 18F-FDG-PET hypometabolism predicts favourable outcomes in epilepsy surgery. METHODS AND ANALYSIS: A systematic literature search of Medline, Embase and Web of Science will be undertaken. Publications which include evaluation with 18F-FDG-PET prior to surgery for drug resistant focal epilepsy, and which report ≥12 months of postoperative surgical outcome data will be included. Non-human, non-English language publications, publications with fewer than 10 participants and unpublished data will be excluded. Screening and full-text review of publications for inclusion will be undertaken by two independent investigators, with discrepancies resolved by consensus or a third investigator. Data will be extracted and pooled using random effects meta-analysis, with heterogeneity quantified using the I2 analysis. ETHICS AND DISSEMINATION: Ethics approval is not required. Once complete, the systematic review will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42022324823.

Somatic Mosaic Mutation Gradient Detected in Trace Brain Tissue From Stereo-EEG Depth Electrodes.

BACKGROUND AND OBJECTIVES: Mosaic pathogenic variants restricted to brain are increasingly recognized as a cause of focal epilepsies. We aimed to identify a mosaic pathogenic variant and its anatomical gradient in brain DNA derived from trace tissue on explanted stereo-electroencephalography (SEEG) electrodes. MATERIAL AND METHODS: We studied a patient with non-lesional multifocal epilepsy undergoing pre-surgical evaluation with SEEG. Following explantation, electrodes were divided into 3 pools based on their brain location (right posterior quadrant, left posterior quadrant, hippocampus/temporal neocortex). Tissue from each pool was processed and DNA whole genome amplified prior to high-depth exome sequencing. Droplet digital PCR was performed to quantify mosaicism. Brain-specific GFAP protein assay enabled cell-of-origin analysis. RESULTS: We demonstrated a mosaic gradient for a novel pathogenic KCNT1 loss-of-function variant, c.530G>A, p.W177X, predicted to lead to nonsense-mediated decay. Strikingly, the mosaic gradient correlated strongly with the SEEG findings as the highest mutant allele fraction was in the right posterior quadrant, reflecting the most epileptogenic region on EEG studies. Elevated GFAP level indicated enrichment of brain-derived cells in SEEG cell suspension. CONCLUSIONS: This study demonstrates proof-of-concept that mosaic gradients of pathogenic variants can be established using trace tissue from explanted SEEG electrodes.

An overlooked mechanism underlying the attenuated temperature response of soil heterotrophic respiration.

Biogeochemical reactions occurring in soil pore space underpin gaseous emissions measured at macroscopic scales but are difficult to quantify due to their complexity and heterogeneity. We develop a volumetric-average method to calculate aerobic respiration rates analytically from soil with microscopic soil structure represented explicitly. Soil water content in the model is the result of the volumetric-average of the microscopic processes, and it is nonlinearly coupled with temperature and other factors. Since many biogeochemical reactions are driven by oxygen (O2) which must overcome various resistances before reaching reactive microsites from the atmosphere, the volumetric-average results in negative feedback between temperature and soil respiration, with the magnitude of the feedback increasing with soil water content and substrate quality. Comparisons with various experiments show the model reproduces the variation of carbon dioxide emission from soils under different water content and temperature gradients, indicating that it captures the key microscopic processes underpinning soil respiration. We show that alongside thermal microbial adaptation, substrate heterogeneity and microbial turnover and carbon use efficiency, O2 dissolution and diffusion in water associated with soil pore space is another key explanation for the attenuated temperature response of soil respiration and should be considered in developing soil organic carbon models.