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Context: In extensive grazing sheep systems, pregnant ewes undergo periods of undernutrition because gestation coincides with winter when natural pasture is of lowest quantity and poorest quality. The lamb's weight and thermoregulatory capacity, and the ewe–lamb bond at birth, may be compromised. Maternal melatonin treatment during gestation may reverse these effects. Aim: The aim was to determine the effects of melatonin treatment of single-lambing, undernourished ewes during the last third of gestation on lamb birthweights and body temperatures, and on ewe–lamb interactive behaviour after birth. Methods: At Day 100 of gestation, 39 single-bearing ewes received a subcutaneous melatonin implant, and 54 ewes served as controls with no implant. Throughout gestation, the ewes remained under extensive conditions grazing on natural pasture. Measurements were made of lamb birthweight, body temperatures (surface temperature by infrared thermography and rectal temperature), and ewe–lamb behaviours during a handling test at 6–17 h after lambing. Key results: There was no effect of melatonin treatment on lamb birthweight or rectal temperature, or on ewe–lamb interaction behaviours. Hip minimum surface temperature was greater in lambs from melatonin-treated ewes than lambs from control ewes (21.2°C ± 0.9°C vs 18.8°C ± 0.8°C; P = 0.05), and there was a similar trend for hip mean surface temperature (24.6°C ± 0.9°C vs 22.3°C ± 0.7°C; P = 0.06). Rump surface temperatures were greater in male than female lambs: maximum (27.9°C ± 1.2°C vs 22.9°C ± 1.2°C; P = 0.01), minimum (22.2°C ± 1.5°C vs 16.7°C ± 1.5°C; P = 0.02) and mean (25.4°C ± 1.3°C vs 20.5°C ± 1.3°C; P = 0.02). Conclusion: Melatonin treatment during the last third of ewe pregnancy slightly enhanced the surface temperature of lambs at birth but did not influence ewe–lamb interaction behaviour after birth (i.e. after establishment of the ewe–lamb bond). Implications: Further study in more depth is warranted into the possible effects of maternal supplementation with commercial melatonin implants on lamb development, thermoregulatory capacity, behaviour and survival rates in extensive grazing systems, including the effect on ewe–lamb behaviours immediately after birth for both singletons and twins. In sheep extensive production systems, pasture availability decreases in winter; thus, ewes are undernourished during gestation. Maternal melatonin treatment could mitigate intrauterine growth restriction induced by maternal undernutrition, enhancing bodyweight at birth and body temperature of lambs, and improving ewe–lamb behaviours at birth. In this study, only lamb hip surface temperature was enhanced after birth, whereas ewe–lamb interactions, lamb birthweight and rectal temperature were unaffected by melatonin treatment. [ABSTRACT FROM AUTHOR]

Melanoma, the most aggressive form of skin cancer, poses a substantial global health threat with increasing incidence rates. Although novel targeted therapies have improved melanoma treatment, challenges persist due to poor response rates and drug resistance. Plant-derived compounds have been crucial in anticancer drug discovery, with many natural products demonstrating the ability to target molecular pathways involved in tumor development. In this study, the anti-melanoma potential of essential oil extracted from the aerial parts of Lippia sidoides Cham. (EO-LS), composed mainly by the monoterpene thymol (96 %), was demonstrated. Obtained results demonstrated that EO-LS disrupted critical cancer hallmarks in A2058 melanoma cells harboring the BRAF V600E mutation. Specifically, EO-LS induced G1-phase cell cycle arrest and apoptosis, as assessed by annexin-V, caspase-3 activity, and TUNEL assays. EO-LS also inhibited cell migration and disrupted the AKT signaling pathway, which is a critical regulator of melanoma progression. Furthermore, a dose-dependent increase in reactive oxygen species (ROS) generation was observed, indicating pro-oxidant properties. These findings highlighted the significant in vitro anticancer properties of EO-LS suggesting its potential as a promising molecular scaffold for developing of novel anti-melanoma candidates., (© 2024 Wiley-VHCA AG, Zurich, Switzerland.)

Species phenology - the timing of key life events - is being altered by ongoing climate changes with yet underappreciated consequences for ecosystem stability. While flowering is generally occurring earlier, we know much less about other key processes such as the time of fruit ripening, largely due to the lack of comprehensive long-term datasets. Here we provide information on the exact date and site where seeds of 4,462 taxa were collected for the Index Seminum (seed exchange catalogue) of the Botanic Garden of the University of Coimbra, between 1926 and 2013. Seeds were collected from spontaneous and cultivated individuals across Portugal, including both native and introduced taxa. The database consists of 127,747 curated records with information on the species, or infraspecific taxa (including authority), and the day and site where seeds were collected. All records are georeferenced and provided with a confidence interval for the collection site. Taxonomy was first curated manually by in-house botanists and then harmonized according to the GBIF backbone taxonomy., (© 2024. The Author(s).)

Prioritizing watershed management interventions relies on delineating homogeneous precipitation regions. In this study, we identify these regions in the Brazilian Legal Amazon based on the magnitude of Sen's Slope trends using annual precipitation data from September to August, employing the Google Earth Engine platform. Utilizing the silhouette method, we determine four distinct clusters representing zones of homogeneous precipitation patterns. Cluster 0 exhibits a significant median increase in precipitation of 3.20 mm year -1 over the period from 1981 to 2020. Cluster 1 shows a notable increase of 8.13 mm year -1 , while Clusters 2 and 3 demonstrate reductions in precipitation of - 1.61 mm year -1 and - 3.87 mm year -1 , respectively, all statistically significant. Notably, the region known as the arc of deforestation falls within Cluster 2, indicating a concerning trend of reduced precipitation. Additionally, our analysis reveals significant correlations between Sea Surface Temperature (SST) in various oceanic regions and precipitation patterns over the Brazilian Legal Amazon. Particularly noteworthy is the strong positive correlation with SST in the South Atlantic, while negative correlations are observed with SST in the South Pacific and North Atlantic. These findings provide valuable insights for enhancing climate adaptation strategies in the Brazilian Legal Amazon region., (© 2024. The Author(s).)

Objective . This paper aims to investigate the possibility of detecting tonic-clonic seizures (TCSs) with behind-the-ear, two-channel wearable electroencephalography (EEG), and to evaluate its added value to non-EEG modalities in TCS detection. Methods . We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2. The wearable Sensor Dot (Byteflies) was used to measure behind-the-ear EEG, electromyography (EMG), electrocardiography, accelerometry (ACC) and gyroscope. We evaluated automatic unimodal detection of TCSs, using sensitivity, precision, false positive rate (FPR) and F1-score. Subsequently, we fused the different modalities and again assessed performance. Algorithm-labeled segments were then provided to two experts, who annotated true positive TCSs, and discarded false positives. Results . Wearable EEG outperformed the other single modalities with a sensitivity of 100% and a FPR of 10.3/24 h. The combination of wearable EEG and EMG proved most clinically useful, delivering a sensitivity of 97.7%, an FPR of 0.4/24 h, a precision of 43%, and an F1-score of 59.7%. The highest overall performance was achieved through the fusion of wearable EEG, EMG, and ACC, yielding a sensitivity of 90.9%, an FPR of 0.1/24 h, a precision of 75.5%, and an F1-score of 82.5%. Conclusions . In TCS detection with a wearable device, combining EEG with EMG, ACC or both resulted in a remarkable reduction of FPR, while retaining a high sensitivity. Significance . Adding wearable EEG could further improve TCS detection, relative to extracerebral-based systems., (© 2024 Institute of Physics and Engineering in Medicine.)

Introduction: Epilepsy affects around 50 million people worldwide and is associated with lower quality of life scores, an increased risk of premature death, and significant socio-economic implications. The lack of updated evidence on current epidemiology and patient characterization creates considerable uncertainty regarding the epilepsy burden in Portugal. The study aims to characterize and quantify the epilepsy patients who have been hospitalized, with medical or surgical procedures involved, and to analyze their associated comorbidities and mortality rates., Methods: A multicenter retrospective study was conducted using hospital production data of epilepsy patients. The study included all patients diagnosed with epilepsy-related International Classification of Diseases-9/10 codes between 2015 and 2018 in 57 Portuguese National Health Service (NHS) hospitals (n = 57 institutions). Patient characterization and quantification were done for all patients with an epilepsy diagnosis, with specific analyses focusing on those whose primary diagnosis was epilepsy. Baseline, demographic, and clinical characteristics were analyzed using descriptive statistics., Results: Between 2015 and 2018, a total of 80,494 hospital episodes (i.e., patient visit that generates hospitalization and procedures) were recorded, with 18 % to 19 % directly related to epilepsy. Among these epilepsy-related hospital episodes, 13.0 % led to short term hospitalizations (less than 24 h). Additionally, the average length of stay for all these epilepsy-related episodes was 8 days. A total of 49,481 patients were identified with epilepsy based on ICD-9/10 codes. The median age of patients was 64 years (min: 0; max: 104), with a distribution of 4.8 patients per 1,000 inhabitants. From the total of deaths (9,606) between 2015 and 2018, 14% were associated with patients whose primary diagnosis was epilepsy, with 545 of these being epilepsy-related deaths. Among patients with a primary diagnosis of epilepsy, the most common comorbidities were hypertension (24%) and psychiatric-related or similar comorbidities (15%), such as alcohol dependance, depressive and major depressive disorders, dementia and other convulsions., Conclusion: This study showed similar results to other European countries. However, due to methodological limitations, a prospective epidemiological study is needed to support this observation. Furthermore, the present study provides a comprehensive picture of hospitalized epilepsy patients in Portugal, their comorbidities, mortality, and hospital procedures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Background: The impact of coronavirus disease 2019 (COVID-19) on postoperative recovery from oncology surgeries should be understood for the clinical decision-making. Therefore, this study was designed to evaluate the postoperative cumulative 28-day mortality and the morbidity of surgical oncology patients during the COVID-19 pandemic., Methods: This retrospective cohort study included patients consecutively admitted to intensive care units (ICU) of three centres for postoperative care of oncologic surgeries between March to June 2019 (first phase) and March to June 2020 (second phase). The primary outcome was cumulative 28-day postoperative mortality. Secondary outcomes were postoperative organic dysfunction and the incidence of clinical complications. Because of the possibility of imbalance between groups, adjusted analyses were performed: Cox proportional hazards model (primary outcome) and multiple logistic regression model (secondary outcomes)., Results: After screening 328 patients, 291 were included. The proportional hazard of cumulative 28-day mortality was higher in the second phase than that in the first phase in the Cox model, with the adjusted hazard ratio of 4.35 (95% confidence interval [CI] 2.15-8.82). The adjusted incidences of respiratory complications (odds ratio [OR] 5.35; 95% CI 1.42-20.11) and pulmonary infections (OR 1.53; 95% CI 1.08-2.17) were higher in the second phase. However, the adjusted incidence of other infections was lower in the second phase (OR 0.78; 95% CI 0.67-0.91)., Conclusions: Surgical oncology patients who underwent postoperative care in the intensive care unit during the COVID-19 pandemic had higher hazard of 28-day mortality. Furthermore, these patients had higher odds of respiratory complications and pulmonary infections. Trials registration The study is registered in the Brazilian Registry of Clinical Trials under the code RBR-8ygjpqm, UTN code U1111-1293-5414., (© 2024. Society of Surgical Oncology.)

In twin pregnancies of discordant sex, the male fetus grows larger than the female co-twin. Our study aimed to determine the effect of the sex of co-twins on lambs' birth weight in ovine pregnancies developed under natural undernourishment. Additionally, we investigated whether the nutritional and/or antioxidant supplementation provided to ewes during pregnancy could modulate the potential effects associated with the sex of co-twins. Ninety-six birth records of twin pregnancies of sheep grazing the natural Patagonian prairies were analyzed. The animals were divided into four groups: control (no supplementation), N (concentrate supplementation, 100% NRC), A (antioxidant supplementation), and NA (concentrate + antioxidant supplementation). Supplementation occurred from day 35 of gestation onwards until lambing. There were no differences in female or male birth weight in the control undernourished group. However, in group N, females or males with sex-discordant co-twins had a higher birth weight than did those with co-twins of the same sex. Group A males with female co-twins had a higher birth weight compared to males whose co-twins were also males. In NA lambs, males had a higher birth weight compared to females, regardless of their co-twin's sex. Therefore, chronic undernutrition abolished the differences in birth weight due to fetal sex. Restoring maternal nutrition or antioxidant supplementation tends to normalize birth weight and restore the differences between females and males. This effect is enhanced with the combined supplementation of concentrated food and antioxidants.

N-carbamylglutamate (NCG) is postulated to improve fetal growth in nutrient-restricted gestations when supplemented from day 35 to 110 of gestation, but the effects of supplementation from 100 days of gestation to birth have not been evaluated. The aim of this study was to evaluate the effect of oral NCG supplementation from 100 days of gestation (dga) to term in naturally nutrient-restricted grazing twin-bearing ewes, on the maternal body weight (BW), body condition score (BCS), placental morphology, fetal body and organ weights and blood biochemistry and antioxidant status in the ewe and fetuses. Eighteen twin-bearing ewes maintained under grazing management were randomly allocated to either a treatment group (NCG; n = 10), orally dosed once daily with 60 mg/kg of NCG from day 100 until 140 dga, or an unsupplemented control group (CON; n = 8). At 140 dga, blood gases, redox status, maternal and fetal plasma and fetal biometrics were obtained after caesarian section. The serum concentration of NCG was increased 15-fold in the NCG ewes compared to the CON. No major effects on dam or fetal body weight nor on blood biochemistry or antioxidant parameters were observed. These results indicate that NCG supplementation in mid-to-late gestation to grazing ewes was unable to rescue the negative production effects of severe natural nutritional restriction on both the dam and fetuses.

Maternal nutrition during gestation plays an important role in colostrum production, postnatal growth, and survival of newborn lambs, especially in twin gestations. This research aimed to investigate the effects of chronic natural undernutrition on colostrum traits and early lamb's postnatal growth born from single and twin sheep pregnancies developed in a restrictive prairie, representative of southern Patagonia. Single- and twin-bearing ewes ( n  = 20 per group) were maintained grazing in a natural pasture. At 140 days of gestation, ewes were placed in individual pens for lambing control. Colostrum was collected immediately after delivery and at 12, 24, and 36 h postpartum, for determination of yield and composition. Maternal blood was obtained at 140 days of gestation and at lambing for plasma glucose, progesterone, 17β-estradiol, and IgG determination. Newborn lamb blood for determining glycaemia and IgG was collected at birth and at 12, 24, 36, and 120 h after birth. Lamb mortality and growth was assessed from birth until 30 days of life. No differences were observed in progesterone and 17β-estradiol. There were no differences in colostrum yields and fat components, however single- had higher values of protein and lactose than twin-bearing ewes ( p < 0.05 for both). Singletons had higher glycaemia than twins at 12 h postpartum (102.2 ± 32.8 vs. 73.4 ± 29.9 mg/dL, p < 0.05 ). Colostrum IgG content was similar at delivery but higher in single ewes at 12 and 24 h, reaching a similar values at 36 h (4.7 ± 9.7 and 5.8 ± 7.7 mg/mL in single and twin pregnancies, respectively). Newborn IgG was higher in singletons compared to twins at least until 48 h of life. Lams body weight was always superior in singleton than twins from birth until 30 days of life. Mortality did not differ during the first week of life, but it increased significantly only in twins until day 30 of life. Undernourishment in pregnant ewes affected colostrum quantity and quality, resulting in a lower postnatal growth and a higher mortality in twins. Alternative managements favoring fetal growth, birth weight and neonatal viability in twin sheep pregnancies are needed, when flocks are breed under harsh environments., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Turín, Sales, Peralta, De los Reyes, Borie, Carrasco, González-Bulnes and Parraguez.)

Perampanel is a promising antiepileptic drug (AED) for refractory epilepsy treatment due to its innovative mechanism of action. This study aimed to develop a population pharmacokinetic (PopPK) model to be further used in initial dose optimization of perampanel in patients diagnosed with refractory epilepsy. A total of seventy-two plasma concentrations of perampanel obtained from forty-four patients were analyzed through a population pharmacokinetic approach by means of nonlinear mixed effects modeling (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic profiles of perampanel. Interpatient variability (IPV) was entered on clearance (CL), while the residual error (RE) was modeled as proportional. The presence of enzyme-inducing AEDs (EIAEDs) and body mass index (BMI) were found as significant covariates for CL and volume of distribution (V), respectively. The mean (relative standard error) estimates for CL and V of the final model were 0.419 L/h (5.56%) and 29.50 (6.41%), respectively. IPV was 30.84% and the proportional RE was 6.44%. Internal validation demonstrated an acceptable predictive performance of the final model. A reliable population pharmacokinetic model was successfully developed, and it is the first enrolling real-life adults diagnosed with refractory epilepsy.

Many state-of-the-art methods for seizure prediction, using the electroencephalogram, are based on machine learning models that are black boxes, weakening the trust of clinicians in them for high-risk decisions. Seizure prediction concerns a multidimensional time-series problem that performs continuous sliding window analysis and classification. In this work, we make a critical review of which explanations increase trust in models' decisions for predicting seizures. We developed three machine learning methodologies to explore their explainability potential. These contain different levels of model transparency: a logistic regression, an ensemble of 15 support vector machines, and an ensemble of three convolutional neural networks. For each methodology, we evaluated quasi-prospectively the performance in 40 patients (testing data comprised 2055 hours and 104 seizures). We selected patients with good and poor performance to explain the models' decisions. Then, with grounded theory, we evaluated how these explanations helped specialists (data scientists and clinicians working in epilepsy) to understand the obtained model dynamics. We obtained four lessons for better communication between data scientists and clinicians. We found that the goal of explainability is not to explain the system's decisions but to improve the system itself. Model transparency is not the most significant factor in explaining a model decision for seizure prediction. Even when using intuitive and state-of-the-art features, it is hard to understand brain dynamics and their relationship with the developed models. We achieve an increase in understanding by developing, in parallel, several systems that explicitly deal with signal dynamics changes that help develop a complete problem formulation., (© 2023 The Authors. Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Introduction: Over recent decades, brain resection for drug-resistant epilepsy has proven to be a valuable treatment option. The histopathological classification was of paramount value for patient management. The aims of this study were to characterize our resective epilepsy surgical series including the histopathological diagnoses and to understand the differences in clinical practice between two different periods of our epilepsy surgical programme., Material and Methods: We performed a retrospective cohort study, including patients with drug-resistant epilepsy that underwent resective surgery between 1997 and 2021 in the Coimbra University Hospital Centre. Histopathological diagnoses were classified into seven major conventional categories. For comparison purposes, the cohort was divided into two consecutive periods of 12 years., Results: A total of 259 patients were included, from which 228 (88%) were adults at the time of surgery. The median disease duration prior to surgery was 14 (interquartile range 23) years. Fifty-five (21%) patients performed pre-surgical invasive work-up. The temporal lobe was the most frequently operated region (73%). Major and minor post-surgical complications were identified in 21 (8%) patients. A reduction in the number of antiepileptic drugs was possible in 96 (37%) patients after surgery. The most common histopathological diagnosis was hippocampal sclerosis, but among children it was long-term epilepsy associated tumour. Long-term epilepsy associated tumours, hippocampal sclerosis and vascular malformations had the best post-operative outcomes. Malformations of cortical development and glial scars had the worst outcomes. Regarding differences between the two periods, the absolute number of operated patients increased (119 versus 140), and the age at surgery was higher in the second period (p = 0.04). The number of malformations of cortical development increased (p = 0.01), but the number of other tumours (p = 0.01) and specimens with no lesion (p = 0.03) decreased in the same period., Conclusion: This study is in line with contemporaneous research, reinforcing the previous knowledge on the underlying structural aetiologies, clinical practice, and surgical outcomes over more than two decades of experience. Our data provide realistic expectations about epilepsy surgery and highlight the need for further improvements in diagnosis and treatment paradigm for people with chronic epilepsy.

Typical seizure prediction models aim at discriminating interictal brain activity from pre-seizure electrographic patterns. Given the lack of a preictal clinical definition, a fixed interval is widely used to develop these models. Recent studies reporting preictal interval selection among a range of fixed intervals show inter- and intra-patient preictal interval variability, possibly reflecting the heterogeneity of the seizure generation process. Obtaining accurate labels of the preictal interval can be used to train supervised prediction models and, hence, avoid setting a fixed preictal interval for all seizures within the same patient. Unsupervised learning methods hold great promise for exploring preictal alterations on a seizure-specific scale. Multivariate and univariate linear and nonlinear features were extracted from scalp electroencephalography (EEG) signals collected from 41 patients with drug-resistant epilepsy undergoing presurgical monitoring. Nonlinear dimensionality reduction was performed for each group of features and each of the 226 seizures. We applied different clustering methods in searching for preictal clusters located until 2 h before the seizure onset. We identified preictal patterns in 90% of patients and 51% of the visually inspected seizures. The preictal clusters manifested a seizure-specific profile with varying duration (22.9 ± 21.0 min) and starting time before seizure onset (47.6 ± 27.3 min). Searching for preictal patterns on the EEG trace using unsupervised methods showed that it is possible to identify seizure-specific preictal signatures for some patients and some seizures within the same patient., (© 2023. The Author(s).)

Low-grade neuroepithelial tumors (LNETs) represent an important group of central nervous system neoplasms, some of which may be associated to epilepsy. The concept of long-term epilepsy-associated tumors (LEATs) includes a heterogenous group of low-grade, cortically based tumors, associated to drug-resistant epilepsy, often requiring surgical treatment. LEATs entities can sometimes be poorly discriminated by histological features, precluding a confident classification in the absence of additional diagnostic tools. This study aimed to provide an updated review on the genomic findings and DNA methylation profiling advances in LNETs, including histological entities of LEATs. A comprehensive search strategy was conducted on PubMed, Embase, and Web of Science Core Collection. High-quality peer-reviewed original manuscripts and review articles with full-text in English, published between 2003 and 2022, were included. Results were screened based on titles and abstracts to determine suitability for inclusion, and when addressed the topic of the review was screened by full-text reading. Data extraction was performed through a qualitative content analysis approach. Most LNETs appear to be driven mainly by a single genomic abnormality and respective affected signaling pathway, including BRAF p.V600E mutations in ganglioglioma, FGFR1 abnormalities in dysembryoplastic neuroepithelial tumor, MYB alterations in angiocentric glioma, BRAF fusions in pilocytic astrocytoma, PRKCA fusions in papillary glioneuronal tumor, between others. However, these molecular alterations are not exclusive, with some overlap amongst different tumor histologies. Also, clustering analysis of DNA methylation profiles allowed the identification of biologically similar molecular groups that sometimes transcend conventional histopathological classification. The exciting developments on the molecular basis of these tumors reinforce the importance of an integrative histopathological and (epi)genetic classification, which can be translated into precision medicine approaches., (© 2022 Japanese Society of Neuropathology.)

Wildfire burn severity has important implications for postfire vegetation recovery and boundary-layer climate. We used a collection of Moderate Resolution Imaging Spectroradiometer (MODIS) datasets to investigate the impact of burn severity (relative differenced Normalized Burn Ratio, RdNBR) on vegetation recovery (Enhanced Vegetation Index, EVI), albedo change, and land surface temperature in seven California ecoregions, including: Southern California Mountains (SCM), Southern California Coast (SCC), Central California Foothills (CCF), Klamath (K), Cascades (C), Eastern Cascades (EC), and Sierra Nevada (SN). A statewide MODIS-derived RdNBR dataset was used to analyze the impact of burn severity on the five-year postfire early-summer averages of each biophysical variable between the years 2003-2020. We found that prefire EVI values were largest, and prefire albedo and temperature were lowest in the K, C, EC, and SN ecoregions. Furthermore, the largest changes between prefire and first-year postfire biophysical response tended to occur in the moderate and high burn severity classes across all ecoregions. First-year postfire albedo decreased in the K, C, EC, and SN but increased in the SCM, SCC, and CCF ecoregions. The greatest decreases, but most rapid recovery, of EVI occurred after high severity fires in all ecoregions. After five-years post-fire, EVI and land surface temperature did not return to prefire levels in any burn severity class in any ecoregion., Competing Interests: The authors have declared no competing interests exist.

Adherence to antiseizure drug treatment determines its effectiveness and safety, and consequently affects patients' quality of life. Herein, we assessed adherence to levetiracetam in Portuguese patients with refractory epilepsy ( n = 115), with resort to a pharmacokinetic drug monitoring approach. The pharmacokinetic parameters of levetiracetam in each patient were determined in steady-state while admitted to the hospital. Then, adherence was assessed by comparing the plasma concentration of the drug observed on the first day of hospitalization with the predicted plasma concentration, considering previously determined pharmacokinetic parameters. The rate of adherence was assessed according to gender, age, diagnosis, and antiseizure drug regimen. Among 115 enrolled patients, 49 (42.6%) were identified as non-adherent, 30 (26.1%) classified as under-consumers, and 19 (16.5%) as over-consumers. A relationship between adherence, daily dose and plasma concentrations was herein reported for the first time. Adherent patients received higher daily doses of levetiracetam [2500 (2000-3000) mg] than non-adherent over-consumers [1500 (1000-2000) mg] and non-adherent under-consumers [2000 (1500-3000) mg]. Higher average steady-state plasma concentrations of levetiracetam were found in non-adherent under-consumers [27.28 (15.33-36.36) mg/L], followed by adherent patients [22.05 (16.62-29.81) mg/L] and non-adherent over-consumers [17.50 (10.69-24.37) mg/L]. This study demonstrates that adherence (or lack thereof) influences the plasma concentrations of levetiracetam in steady-state and its pharmacological effects. Moreover, it emphasizes the importance of educating patients to encourage adherence to therapy. Otherwise, the risk of developing toxic and subtherapeutic concentrations is undeniable, compromising the therapeutic effect and safety of treatment.

Objectives: We aimed to investigate the antiepileptic effects of cathodal transcranial direct current stimulation (c-tDCS) and mechanisms of action based on its effects on the neurotransmitters responsible for the abnormal synchrony patterns seen in pharmacoresistant epilepsy. This is the first study to test the impact of neurostimulation on epileptiform interictal discharges (IEDs) and to measure brain metabolites in the epileptogenic zone (EZ) and control regions simultaneously in patients with pharmacoresistant epilepsy., Methods: This is a hypothesis-driven pilot prospective single-blinded repeated measure design study in patients diagnosed with pharmacoresistant epilepsy of temporal lobe onset. We included seven patients who underwent two sessions of c-tDCS (sham followed by real). The real tDCS session was 20 min in duration and had a current intensity of 1.5 mA delivered via two surface electrodes that had dimensions of 3 × 4 cm. The cathode electrode was placed at FT7 in the center whereas the anode at Oz in the center. After each session, we performed electroencephalographic recording to count epileptiform IEDs over 30 min. We also performed magnetic resonance spectroscopy (MRS) to measure brain metabolite concentrations in the two areas of interest (EZ and occipital region), namely, gamma-aminobutyric acid (GABA), glutamate (Glx), and glutathione. We focused on a homogenous sample where the EZ and antiepileptic medications are shared among patients., Results: Real tDCS decreased the number of epileptiform IEDs per min (from 9.46 ± 2.68 after sham tDCS to 5.37 ± 3.38 after real tDCS), p = 0.018, as compared to sham tDCS. GABA was decreased in the EZ after real c-tDCS stimulation as compared to sham tDCS (from 0.129 ± 0.019 to 0.096 ± 0.018, p = 0.02). The reduction in EZ GABA correlated with the reduction in the frequency of epileptiform IED per min (rho: 0.9, p = 0.003)., Conclusion: These results provide a window into the antiepileptic mechanisms of action of tDCS, based on local and remote changes in GABA and neural oscillatory patterning responsible for the generation of interictal epileptiform discharges., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Abuhaiba, Duarte, Castelhano, Dionísio, Sales, Edden and Castelo-Branco.)

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future., (Published by Oxford University Press on behalf of National Academy of Sciences 2022.)

Hypoxemia and oxidative stress, resulting in intrauterine growth restriction (IUGR) in undernourished twin sheep pregnancies, has been described in near-term studies. Our aim was to evaluate if the counteractive effects of maternal nutritional or antioxidant supplementation on the fetal redox status were evident before the accelerated fetal growth phase. Forty twin-bearing ewes grazing on natural Patagonian prairie were randomly assigned to four groups (n = 10 each; P: control ewes consuming mainly natural pasture; P+A: pasture plus antioxidants; P+C: pasture plus concentrate; P+A+C: pasture plus antioxidants and concentrate). Daily herbal antioxidants were supplemented in a feedstuff concentrate as a premix from day 35 until day 100 of gestation, when fetal venous cord blood samples and biometric measurements were obtained via cesarean section. The fetuses from group P were clearly hypoxemic. An analysis of variance showed that maternal antioxidant supplementation showed a trend of increased PO2, SatHb, and Ht, effects not observed in P+C fetuses. Antioxidants decreased the fetal MDA concentration (p < 0.05). Fetal TAC was increased by the antioxidants and concentrate (p < 0.05). Antioxidant supplementation showed a trend to increase fetal body weight but not biometry. The results suggest that negative effects of oxidative stress occur earlier than the overt growth arrest, and the maternal administration of antioxidants may constitute a good nutritional strategy for the early prevention of IUGR.

Seizure prediction may be the solution for epileptic patients whose drugs and surgery do not control seizures. Despite 46 years of research, few devices/systems underwent clinical trials and/or are commercialized, where the most recent state-of-the-art approaches, as neural networks models, are not used to their full potential. The latter demonstrates the existence of social barriers to new methodologies due to data bias, patient safety, and legislation compliance. In the form of literature review, we performed a qualitative study to analyze the seizure prediction ecosystem to find these social barriers. With the Grounded Theory, we draw hypotheses from data, while with the Actor-Network Theory we considered that technology shapes social configurations and interests, being fundamental in healthcare. We obtained a social network that describes the ecosystem and propose research guidelines aiming at clinical acceptance. Our most relevant conclusion is the need for model explainability, but not necessarily intrinsically interpretable models, for the case of seizure prediction. Accordingly, we argue that it is possible to develop robust prediction models, including black-box systems to some extent, while avoiding data bias, ensuring patient safety, and still complying with legislation, if they can deliver human- comprehensible explanations. Due to skepticism and patient safety reasons, many authors advocate the use of transparent models which may limit their performance and potential. Our study highlights a possible path, by using model explainability, on how to overcome these barriers while allowing the use of more computationally robust models., (© 2022 The Authors. Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Invasive brain recordings using many electrodes across a wide range of tasks provide a unique opportunity to study the role of oscillatory patterning and functional connectivity. We used large-scale recordings (stereo EEG) within and beyond the human hippocampus to investigate the role of distinct frequency oscillations during real-time execution of visual, attention and memory tasks in eight epileptic patients. We found that activity patterns in the hippocampus showed task and frequency dependent properties. Importantly, we found distinct connectivity signatures, in particular concerning parietal-hippocampal connectivity, thus revealing large scale synchronization of networks involved in memory tasks. Comparing the power per frequency band, across tasks and hippocampal regions (anterior/posterior) we confirmed a main effect of frequency band (p = 0.002). Gamma band activity was higher for visuo-spatial memory tasks in the anterior hippocampus. Further, we found that alpha and beta band activity in posterior hippocampus had larger modulation for high memory load visual tasks (p = 0.004). Three functional connectivity task related networks were identified: (dorsal) parietal-hippocampus (visual attention and memory), ventral stream- hippocampus and hippocampal-frontal connections (mainly tasks involving face recognition or object based search). These findings support the critical role of oscillatory patterning in the hippocampus during visual and memory tasks and suggests the presence of task related spectral and functional connectivity signatures. These results show that the use of large scale human intracranial recordings can validate the role of oscillatory and functional connectivity patterns across a broad range of cognitive domains., (© 2022. The Author(s).)