Intradental mechano-nociceptors serve as sentinels that prevent tooth damage.

Pain is the anticipated output of the trigeminal sensory neurons that innervate the tooth's vital interior 1,2 ; however, the contribution of intradental neurons to healthy tooth sensation has yet to be defined. Here, we employ in vivo Ca 2+ imaging to identify and define a population of myelinated high-threshold mechanoreceptors (intradental HTMRs) that detect superficial structural damage of the tooth and initiate jaw opening to protect teeth from damage. Intradental HTMRs remain inactive when direct forces are applied to the intact tooth but become responsive to forces when the structural integrity of the tooth is compromised, and the dentin or pulp is exposed. Their terminals collectively innervate the inner dentin through overlapping receptive fields, allowing them to monitor the superficial structures of the tooth. Indeed, intradental HTMRs detect superficial enamel damage and encode its degree, and their responses persist in the absence of either PIEZO2 or Na v 1.8 3,4 . Optogenetic activation of intradental HTMRs triggers a rapid, jaw opening reflex via contraction of the digastric muscle. Taken together, our data indicate that intradental HTMRs serve as sentinels that guard against mechanical threats to the tooth, and their activation results in physical tooth separation to minimize irreversible structural damage. Our work provides a new perspective on the role of intradental neurons as protective rather than exclusively pain-inducing and illustrates additional diversity in the functions of interoreceptors.

Identification of Nonfunctional Alternatively Spliced Isoforms of STING in Human Acute Myeloid Leukemia.

Lack of robust activation of Stimulator of Interferon Genes (STING) pathway and subsequent induction of type I IFN responses is considered a barrier to antitumor immunity in acute myeloid leukemia (AML). Using common human AML cell lines as in vitro tools to evaluate the efficacy of novel STING agonists, we found most AML lines to be poor producers of IFNs upon exposure to extremely potent agonists, suggesting cell-intrinsic suppression of STING signaling may occur. We observed unexpected patterns of response that did not correlate with levels of STING pathway components or of known enzymes associated with resistance. To identify a genetic basis for these observations, we cloned and sequenced STING from the cDNA of human AML cell lines and found both frequent mutations and deviations from normal RNA splicing. We identified two novel spliced isoforms of STING in these lines and validated their expression in primary human AML samples. When transduced into reporter cells, these novel STING isoforms exhibited complete insensitivity to agonist stimulation. These observations identify alternative splicing as a mechanism of STING pathway suppression and suggest that most AML silences the STING pathway through direct modification rather than through engagement of external inhibitory factors. SIGNIFICANCE: We find that AML acquires resistance to innate immune activation via the STING pathway through aberrant splicing of the STING transcript including two novel forms described herein that act as dominant negatives. These data broaden understanding of how cancers evolve STING resistance, and suggest that the AML tumor microenvironment, not the cancer cell, should be the target of therapeutic interventions to activate STING.

Availability of Internet-Based Cognitive-Behavioral Therapies for Depression: A Systematic Review.

We examined the availability and components of internet-based cognitive-behavioral therapies (iCBTs) for depression tested in randomized-controlled trials (RCTs). The objectives of this literature review were to determine the extent to which research-validated iCBTs were available to the public, as well as to determine their therapeutic content. A literature review of RCTs for iCBTs was conducted on July 30, 2021. For each iCBT, interventions were rated by content and compared to commercially available smartphone apps. Our search yielded 80 studies using 41 unique iCBTs. Of these, only 6 (15%) were completely available to the public, more than half were not publicly available (46%), and the remaining 39% were available to the public with some restrictions (e.g., those based on the user's geographical location). When comparing iCBTs evaluated in RCTs to commercially available smartphone apps, we found that iCBTs were more likely to contain psychoeducation, cognitive restructuring, behavioral activation, problem solving, and interpersonal communication components. iCBTs from RCTs contain evidence-based content but few are available to the public. Extending beyond efficacy, attention should be paid to the dissemination of iCBTs.

Mental Health Apps for Children and Adolescents: A Clinician-Friendly Review.

Mobile apps for mental health and wellness (MH apps) have the potential to support youth mental health, expanding access to the large proportion of youth with mental health concerns who do not access formal treatment. Survey data suggest that young people are highly interested in MH apps, with minoritized youth (eg, LGBTQ individuals) and youth with elevated depressive symptoms reporting especially high rates of downloading MH apps.1 In addition, systematic reviews and meta-analyses suggest that MH apps can be effective.2 Although many popular MH apps do not have direct empirical evidence supporting their efficacy,3 they often include elements of empirically supported treatments for children and adolescents.4 The MH app space moves at a fast pace, making it difficult to stay up-to-date. More than 10,000 MH apps exist, with hundreds released each year.5 Even interested clinicians may, understandably, not have time to sort through the large number of apps, scientific papers, and app directories. Furthermore, these resources are rarely designed to offer clear, actionable advice for clinicians. Clinicians could benefit from information and guidance to help patients safely navigate MH apps and to best use MH apps in treatment. Here, we provide 3 key points about youth MH apps ("takeaways"), each with an actionable implication for clinicians ("action items"). We also provide examples of specific questions for clinicians to support their use of MH apps with children and adolescents (Table 1). More information regarding where we derived these recommendations is available in Supplement 1, available online.

iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.

OBJECTIVE: Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. METHODS: We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. RESULTS: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. SIGNIFICANCE: iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

Disparities in lung cancer short- and long-term outcomes after surgery: Analysis from the national cancer database.

INTRODUCTION: Social determinants of health are particularly important in lung cancer epidemiology. Previous studies have primarily associated social determinants with long-term outcomes, such as survival, but fail to include short-term outcomes after surgery. The National Cancer Database (NCDB) was used to draw associations between social factors of patients with lung cancer and short-term post-surgical outcomes, while comparing them to prognostic factors, including stage at diagnosis and survival. METHODS: The 2004-17 NCDB was queried for patients with primary epithelial tumor, squamous cell carcinoma, or adenocarcinoma of the lung treated with curative intent. Linear, binary logistic, Kaplan-Meier, and Cox proportional hazards regression models were utilized. RESULTS: On logistic regression modeling, male gender, low income, lacking insurance, and facility in the central United States were associated with poor short-term outcomes (<0.05). Increased age, White race, and Black race were associated with increased length of hospital stay and mortality, but negatively correlated with readmission rates (<0.05). Medicare and Medicaid were associated with increased length of stay and mortality, respectively (<0.05). Similar patterns were observed for higher stage at diagnosis (<0.05). Hazard ratios were elevated with increased age, male gender, White race, lacking insurance, Medicaid, and facility in the central United States (<0.05). CONCLUSION: Many social factors previously associated with poor prognosis after lung cancer diagnosis are also associated with poor short-term outcomes after surgery. This study implies that healthcare providers treating lung cancer should proceed with care while aware that patients with the discussed social factors are predisposed to complicated recoveries.

The seizure severity score: a quantitative tool for comparing seizures and their response to therapy.

Objective.Epilepsy is a neurological disorder characterized by recurrent seizures which vary widely in severity, from clinically silent to prolonged convulsions. Measuring severity is crucial for guiding therapy, particularly when complete control is not possible. Seizure diaries, the current standard for guiding therapy, are insensitive to the duration of events or the propagation of seizure activity across the brain. We present a quantitative seizure severity score that incorporates electroencephalography (EEG) and clinical data and demonstrate how it can guide epilepsy therapies.Approach.We collected intracranial EEG and clinical semiology data from 54 epilepsy patients who had 256 seizures during invasive, in-hospital presurgical evaluation. We applied an absolute slope algorithm to EEG recordings to identify seizing channels. From this data, we developed a seizure severity score that combines seizure duration, spread, and semiology using non-negative matrix factorization. For validation, we assessed its correlation with independent measures of epilepsy burden: seizure types, epilepsy duration, a pharmacokinetic model of medication load, and response to epilepsy surgery. We investigated the association between the seizure severity score and preictal network features.Main results.The seizure severity score augmented clinical classification by objectively delineating seizure duration and spread from recordings in available electrodes. Lower preictal medication loads were associated with higher seizure severity scores (p= 0.018, 97.5% confidence interval = [-1.242, -0.116]) and lower pre-surgical severity was associated with better surgical outcome (p= 0.042). In 85% of patients with multiple seizure types, greater preictal change from baseline was associated with higher severity.Significance.We present a quantitative measure of seizure severity that includes EEG and clinical features, validated on gold standard in-patient recordings. We provide a framework for extending our tool's utility to ambulatory EEG devices, for linking it to seizure semiology measured by wearable sensors, and as a tool to advance data-driven epilepsy care.

Quantifying interictal intracranial EEG to predict focal epilepsy.

Introduction: Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials. Methods: We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the "5 Sense Score (5SS)," a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians' choice of therapeutic intervention and the patient outcome. Results: The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information. Conclusions: Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.

Phytochemical characterization, antioxidant and antibacterial activities of crude extracts of Anisomeles malabarica and Coldenia procumbens.

The aim of this study was to determine the phytochemical profile, antibacterial and antioxidant activities of crude aqueous leaf extracts of Anisomeles malabarica and Coldenia procumbens. The predominant components present in these crude extracts of test plants identified using gas chromatography-mass spectrometry (GC-MS) analysis in both plant extracts were phytochemicals including flavonoids, tannins, terpenoids, and phenols. The antibacterial activity of crude extracts of these plants against bacterial pathogens including Escherichia coli, Bacillus subtilis, Shigella sp., Salmonella paratyphi A and B, Proteus mirabilis, Proteus vulgaris, Pseudomonas sp. Klebsiella pneumoniae, and Staphylococcus aureus were examined. Data demonstrated that the extracts of A. malabarica and C. procumbens exhibited significant antibacterial activity against B.subtilis and P.vulgaris at the concentration of 50 mg/ml. A. malabarica aqueous extract displayed significant antioxidant activity on 2,2-diphenyl-1-picrylhydrazl (DPPH), fluorescence recovery after photobleaching (FRAP) and hydrogen peroxide (H2O2) free radicals at the concentration of 90 mg/ml. The antioxidant activity was significantly higher with A. malabarica than extract of C. procumbens. Evidence indicates that both plant extracts may possess significant pharmaceutical potential as antibacterial and antioxidant agents.

iEEG-recon: A Fast and Scalable Pipeline for Accurate Reconstruction of Intracranial Electrodes and Implantable Devices.

Background: Collaboration between epilepsy centers is essential to integrate multimodal data for epilepsy research. Scalable tools for rapid and reproducible data analysis facilitate multicenter data integration and harmonization. Clinicians use intracranial EEG (iEEG) in conjunction with non-invasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. These tasks are still performed manually in many epilepsy centers. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. Methods: We created iEEG-recon, a scalable electrode reconstruction pipeline for semi-automatic iEEG annotation, rapid image registration, and electrode assignment on brain MRIs. Its modular architecture includes three modules: a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon, and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. Results: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography (ECoG) and stereoelectroencephalography (SEEG) cases with a 10 minute running time per case, and ~20 min for semi-automatic electrode labeling. iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and post-implant T1-MRI visual inspections. Our use of ANTsPyNet deep learning approach for brain segmentation and electrode classification was consistent with the widely used Freesurfer segmentation. Discussion: iEEG-recon is a valuable tool for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting efficient data analysis, and integration into clinical workflows. The tool's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide. Comprehensive documentation is available at https://ieeg-recon.readthedocs.io/en/latest/.

Depression and anxiety symptoms, subjective well-being, and happiness among Indian high school students.

Background: Mental health problems cause significant distress and impairment in adolescents worldwide. One-fifth of the world's adolescents live in India, and much remains to be known about their mental health and wellbeing. Aim: In this preregistered study, we aimed to estimate the rates of depressive and anxiety symptoms, examine their relationship with indicators of wellbeing, and identify correlates of mental health among Indian adolescents. Methods: We administered self-report measures of depressive symptoms (PHQ-9), anxiety symptoms (GAD-7), wellbeing (WEMWBS), and happiness (SHS) to 1,213 Indian adolescents (52.0% male; Mage = 14.11, SDage = 1.48). Results: Findings from the PHQ-9 (M = 8.08, SD = 5.01) and GAD-7 (M = 7.42, SD = 4.78) indicated high levels of depressive symptoms and anxiety symptoms. Thirty seven percent of the sample scored above the clinical cutoff for depressive symptoms, and 30.6% scored above the cutoff for anxiety symptoms. Although measures of mental health symptoms (PHQ-9 and GAD-7) were associated with measures of wellbeing and happiness (WEMWBS and SHS), these associations were only modest (Correlation < 0.45). Female students reported higher symptoms (and worse wellbeing) compared to male students, and older students reported higher symptoms (and worse wellbeing and happiness) compared to younger students. Conclusion: This study highlights the high prevalence of depressive symptoms and anxiety symptoms among Indian high school students. Symptom measures correlated only modestly with measures of wellbeing and happiness, suggesting that wellbeing and happiness reflect more than the absence of internalizing symptoms. Future research is needed to identify effective and appropriate ways to promote mental health and wellness among Indian students.

Designing a TiO2-MoO3-BMIMBr nanocomposite by a solvohydrothermal method using an ionic liquid aqueous mixture: an ultra high sensitive acetaminophen sensor.

This study shows a simplistic, efficient procedure to synthesize TiO2-MoO3-BMIMBr nanocomposites. Powder X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy have all been used to completely analyse the materials. The detection of acetaminophen (AC) has been examined at a modified glassy carbon electrode with TiO2-MoO3-BMIMBr nanocomposites. Moreover, the electrochemical behavior of the nanocomposite modified electrode has been studied by cyclic voltammetry (CV), differential pulse voltammetry (DPV), chronoamperometry and electrochemical impedance spectroscopy (EIS). The linear response of AC was observed in the range 8.26-124.03 nM. The sensitivity and detection limits (S/N = 3) were found to be 1.16 µA L mol-1 cm-2 and 11.54 nM by CV and 24 µA L mol-1 cm-2 and 8.16 nM by DPV respectively.

The effects of sport, setting, and demographics on sunscreen use and education in young athletes.

Participation in outdoor sports increases exposure to ultraviolet radiation, necessitating mitigation through sunscreen use. This prospective study examined the effects of sport, setting (practice vs. competition), gender, age and geographic location on sunscreen use and education among youth athletes in various sports. Six hundred and twelve athletes ≤18 years old completed an online survey on sunscreen education and use during competitions and practices. Regardless of sport, reported sunscreen use was higher during practices than competition (p < 0.0001). Sunscreen was used most by swimmers/divers (odds ratio: OR ≥ 1.9, p < 0.001) and least by American football players (OR ≤ 0.57, p ≤ 0.001). Coaches mentioned sunscreen use the most in track and field (OR 1.84, p = 0.001) and the least in American football (OR 0.67, p = 0.03). Athletes used sunscreen more if they were female (OR ≥ 1.9 1.38, p ≤ 0.06) and younger (age OR ≤ 0.88, p < 0.001). In conclusion, youth athletes differ in sunscreen use by sport and setting, highlighting the need for continued photoprotective education.

Radiological Diagnosis and Surgical Treatment of Gallstone Ileus.

We report on the diagnosis and treatment of a patient who presented with a small bowel obstruction due to gallstone ileus. This condition is an infrequent complication of cholelithiasis that presents with non-specific and intermittent findings, including bloating, early satiety, constipation, nausea, and vomiting. Contrast-enhanced CT features the classic imaging finding, called Rigler's triad, which includes small bowel distension, gas in the gallbladder, and an ectopic gallstone. Laparoscopic enterolithotomy is employed to prevent further erosion through the gallbladder wall and into the adjacent gastrointestinal structures. The early diagnosis and treatment of gallstone ileus results in decreased morbidity and mortality.

Radiological Manifestations of Rhino-Orbito-Cranial Mucormycosis in COVID-19 Patients Correlated With Pathological and Clinical Outcomes and Emphasis on Magnetic Resonance Imaging-Based Scoring System.

There was tremendous increase in the number of cases of mucormycosis among patients affected by coronavirus disease 2019 (COVID-19) during the second wave of pandemic in South Asian countries. This invasive fungal infection primarily affects paranasal sinuses and can have orbito-facial and intracranial extension. We are presenting the radiological findings of invasive mucormycosis with pathological and clinical outcome correlation. It is important for radiologists to have the knowledge of various presentations of this opportunistic infection for early diagnosis and helping clinicians in planning the appropriate line of management. The study also emphasizes on the correlation between the extent of involvement with clinical outcome and we proposed a magnetic resonance imaging (MRI) based scoring system to standardize and prognosticate the patients affected with mucormycosis. MATERIALS AND METHODS: We utilized GE 1.5 tesla, 16-channeled MRI machine for scanning the clinically suspected mucormycosis patients and did plain and contrast study of the paranasal sinuses, orbito-facial study and included brain as and when required. Images were acquired in axial, coronal, and sagittal planes using T1, T2, and fat-saturated short tau inversion recovery sequences (STIR), fat-saturated contrast sequences for better evaluation of the extent of the disease. Diffusion-weighted sequence was also acquired to detect ischemic changes in optic nerve or brain parenchyma. Contrast study was used to detect any major vessel occlusion or cavernous sinus thrombosis in the study population. RESULTS: Total number of cases (n) included in the study were 32. The mean age group was 41-50 years with the median age was 47 years. Out of 32 cases (n=32), in 16 cases (50%) the disease was limited only to the paranasal sinuses and in remaining 16 (50%) cases, disease has spread to other regions such as orbits, facial soft tissues, optic nerve, and brain parenchyma. All the 18 cases with Mild score (MRI ROCM score 1-3) survived and all those with severe score (2 cases) (MRI ROCM score 7-10) did not survive. CONCLUSION: During the second wave of COVID-19 pandemic, we observed a significant rise in acute invasive mucormycosis infection primarily involving the paranasal sinuses and spread to orbito-facial, cerebral parenchyma causing related complications and hence increased morbidity and death. Radiologically, using MRI, it was effectively possible to detect early extrasinonasal spread and other fatal complications thereby guiding the physicians and surgeons in the proper early aggressive management of the disease. Here, we have described the radiological characteristics of paranasal sinus mucormycosis and its spread to other regions. We also proposed an MRI-based Scoring System for standardized assessment of the disease severity. We observed in our study that the extent of disease on MRI is directly correlating with mortality.

The Value of Programmed Ventricular Extrastimuli From the Right Ventricular Basal Septum During Supraventricular Tachycardia.

BACKGROUND: The difference between the right ventricular (RV) apical stimulus-atrial electrogram (SA) interval during resetting of supraventricular tachycardia (SVT) versus the ventriculoatrial (VA) interval during SVT (ΔSA-VAapex) is an established technique for discerning SVT mechanisms but is limited by a significant diagnostic overlap. OBJECTIVES: This study hypothesized that the difference between the RV SA interval during resetting of SVTs versus the VA interval during SVTs (ΔSA-VA) would yield a more robust differentiation of atrioventricular nodal re-entrant tachycardia (AVNRT) from atrioventricular reciprocating tachycardia (AVRT) when using the RV basal septal stimulation (ΔSA-VAbase) as compared to the RV apical stimulation (ΔSA-VAapex). Moreover, it was predicted that the ΔSA-VAbase might distinguish septal from free wall accessory pathways (APs) effectively. METHODS: In this prospective study, 105 patients with AVNRTs (age 48 ± 20 years, 44% male) and 130 with AVRTs (age 26 ± 18 years, 54% male) underwent programmed ventricular extrastimuli delivered from both the RV basal septum and RV apex. The ΔSA-VA values were compared between the 2 sites. RESULTS: The ΔSA-VAbase was shorter than the ΔSA-VAapex during AVRT (44 ± 30 ms vs 58 ± 29 ms; P < 0.001), and the opposite occurred during AVNRT (133 ± 31 ms vs 125 ± 25 ms; P = 0.03). A ΔSA-VAbase of ≧85 milliseconds had a sensitivity of 97% and specificity of 96% for identifying AVNRT. Furthermore, a ΔSA-VAbase of 45-85 milliseconds identified AVRT with left free wall APs (sensitivity 86%, specificity 95%), 20-45 milliseconds for posterior septal APs (sensitivity 72%, specificity 96%), and <20 milliseconds for right free wall or anterior/mid septal APs (sensitivity 86%, specificity 98%). CONCLUSIONS: The ΔSA-VAbase during programmed ventricular extrastimuli produced a robust differentiation between AVNRT and AVRT regardless of the AP location with ≧85 milliseconds as an excellent cutoff point. This straightforward technique further allowed localizing 4 general AP sites.

A pharmacokinetic model of antiseizure medication load to guide care in the epilepsy monitoring unit.

OBJECTIVE: Evaluating patients with drug-resistant epilepsy often requires inducing seizures by tapering antiseizure medications (ASMs) in the epilepsy monitoring unit (EMU). The relationship between ASM taper strategy, seizure timing, and severity remains unclear. In this study, we developed and validated a pharmacokinetic model of total ASM load and tested its association with seizure occurrence and severity in the EMU. METHODS: We studied 80 patients who underwent intracranial electroencephalographic recording for epilepsy surgery planning. We developed a first order pharmacokinetic model of the ASMs administered in the EMU to generate a continuous metric of overall ASM load. We then related modeled ASM load to seizure likelihood and severity. We determined the association between the rate of ASM load reduction, the length of hospital stay, and the probability of having a severe seizure. Finally, we used modeled ASM load to predict oncoming seizures. RESULTS: Seizures occurred in the bottom 50th percentile of sampled ASM loads across the cohort (p < .0001, Wilcoxon signed-rank test), and seizures requiring rescue therapy occurred at lower ASM loads than seizures that did not require rescue therapy (logistic regression mixed effects model, odds ratio = .27, p = .01). Greater ASM decrease early in the EMU was not associated with an increased likelihood of having a severe seizure, nor with a shorter length of stay. SIGNIFICANCE: A pharmacokinetic model can accurately estimate ASM levels for patients in the EMU. Lower modeled ASM levels are associated with increased seizure likelihood and seizure severity. We show that ASM load, rather than ASM taper speed, is associated with severe seizures. ASM modeling has the potential to help optimize taper strategy to minimize severe seizures while maximizing diagnostic yield.

Spike patterns surrounding sleep and seizures localize the seizure-onset zone in focal epilepsy.

OBJECTIVE: Interictal spikes help localize seizure generators as part of surgical planning for drug-resistant epilepsy. However, there are often multiple spike populations whose frequencies change over time, influenced by brain state. Understanding state changes in spike rates will improve our ability to use spikes for surgical planning. Our goal was to determine the effect of sleep and seizures on interictal spikes, and to use sleep and seizure-related changes in spikes to localize the seizure-onset zone (SOZ). METHODS: We performed a retrospective analysis of intracranial electroencephalography (EEG) data from patients with focal epilepsy. We automatically detected interictal spikes and we classified different time periods as awake or asleep based on the ratio of alpha to delta power, with a secondary analysis using the recently published SleepSEEG algorithm. We analyzed spike rates surrounding sleep and seizures. We developed a model to localize the SOZ using state-dependent spike rates. RESULTS: We analyzed data from 101 patients (54 women, age range 16-69). The normalized alpha-delta power ratio accurately classified wake from sleep periods (area under the curve = .90). Spikes were more frequent in sleep than wakefulness and in the post-ictal compared to the pre-ictal state. Patients with temporal lobe epilepsy had a greater wake-to-sleep and pre- to post-ictal spike rate increase compared to patients with extra-temporal epilepsy. A machine-learning classifier incorporating state-dependent spike rates accurately identified the SOZ (area under the curve = .83). Spike rates tended to be higher and better localize the seizure-onset zone in non-rapid eye movement (NREM) sleep than in wake or REM sleep. SIGNIFICANCE: The change in spike rates surrounding sleep and seizures differs between temporal and extra-temporal lobe epilepsy. Spikes are more frequent and better localize the SOZ in sleep, particularly in NREM sleep. Quantitative analysis of spikes may provide useful ancillary data to localize the SOZ and improve surgical planning.

Meta-analysis: The Effectiveness of Youth Psychotherapy Interventions in Low- and Middle-Income Countries.

OBJECTIVE: Because most youth psychotherapies are developed and tested in high-income countries, relatively little is known about their effectiveness or moderators in low- and middle-income countries (LMICs). To address this gap, we conducted a meta-analysis of randomized controlled trials (RCTs) testing psychotherapies for youth with multiple psychiatric conditions in LMICs, and we tested candidate moderators. METHOD: We searched 9 international databases for RCTs of youth psychotherapies in LMICs published through January 2021. The RCTs targeted elevated symptoms of youth anxiety (including posttraumatic stress disorder [PTSD] and obsessive-compulsive disorder), depression, conduct problems, and attention problems. Using robust variance estimation, we estimated the pooled effect sizes (Hedges g) at posttreatment and follow-up for intervention vs control conditions. RESULTS: Of 5,145 articles identified, 34 articles (with 43 treatment-control comparisons and 4,176 participants) met methodological standards and were included. The overall pooled g with winsorized outliers was 1.01 (95% CI = 0.72-1.29, p < .001) at posttreatment and 0.68 (95% CI = 0.29-1.07, p = .003) at follow-up. Interventions delivered by professional clinicians significantly outperformed those delivered by lay providers (g = 1.59 vs 0.53), but all interventions for conduct problems were delivered by professionals, and the difference for interventions targeting internalizing problems (g = 1.33 vs .53) was not significant. Interventions developed non-locally were more effective if they were not adapted to local contexts than if they were adapted locally (g = 2.31 vs 0.66), highlighting a need for further research on effective adaptations. Significant risk of bias was identified. CONCLUSION: Overall, pooled effects of youth psychotherapies in LMICs were markedly larger than those in recent comparable non-LMIC meta-analyses, which have shown small-to-medium effects for youth psychotherapies. Findings highlight the potential benefits of youth psychotherapies in LMICs, as well as a need for more RCTs and improved study quality. STUDY PREREGISTRATION INFORMATION: Effectiveness of Youth Psychotherapy Interventions in Low- and Middle-Income Countries (LMICs): A Systematic Review and Meta-Analysis of Randomized Clinical Trials; https://www.crd.york.ac.uk/PROSPERO/; CRD42021240031.

Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy.

Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data is captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal (between-seizure) intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-center study for model development; two-center study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using interictal EEG. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. 47 patients (30 women; ages 20-69; 20 left-sided, 10 right-sided, and 17 bilateral seizure onsets) were analyzed for model development and internal validation. 19 patients (10 women; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analyzed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome.