Single-cell genomics details the maturation block in BCP-ALL and identifies therapeutic vulnerabilities in DUX4-r cases.

B cell progenitor acute lymphoblastic leukemia (BCP-ALL) is the most common childhood malignancy, driven by multiple genetic alterations that cause maturation arrest and accumulation of abnormal progenitor B cells. Current treatment protocols with chemotherapy have led to favorable outcomes but are associated with significant toxicity and risk of side effects, highlighting the necessity for highly effective, less toxic, targeted drugs, even in subtypes with a favorable outcome. Here, we used multimodal single-cell sequencing to delineate the transcriptional, epigenetic, and immunophenotypic characteristics of 23 childhood BCP-ALLs, belonging to the BCR::ABL1-positive, ETV6::RUNX1-positive, high hyperdiploid, and recently discovered DUX4-rearranged (DUX4-r) subtypes. Projection of the ALL cells along the normal hematopoietic differentiation axis revealed a diversity in the maturation pattern between the different BCP-ALL subtypes. Whereas the BCR::ABL1-, ETV6::RUNX1-positive, and high hyperdiploidy cells mainly showed similarities to normal pro-B cells, the DUX4-r ALL cells also displayed transcriptional signatures resembling mature B cells. Focusing on the DUX4-r subtype, we found that the blast population displayed multilineage priming toward non-hematopoietic cells, myeloid, and T cell lineages, but also an activation of PI3K/AKT signaling that sensitized the cells to PI3K inhibition in vivo. Given the multilineage priming of the DUX4-r blasts with aberrant expression of the myeloid marker CD371 (CLL-1), we generated chimeric antigen receptor T cells, which effectively eliminated DUX4-r ALL cells in vivo. These results provide a detailed characterization of BCP-ALL at the single-cell level and reveal therapeutic vulnerabilities in the DUX4-r subtype with implications for the understanding of ALL biology and new therapeutic strategies.

Treatment outcomes of childhood PICALM::MLLT10 acute leukaemias.

The prognostic impact of PICALM::MLLT10 status in childhood leukaemia is not well described. Ten International Berlin Frankfurt Münster-affiliated study groups and the Children's Oncology Group collaborated in this multicentre retrospective study. The presence of the PICALM::MLLT10 fusion gene was confirmed by fluorescence in situ hybridization and/or RNA sequencing at participating sites. Ninety-eight children met the study criteria. T-cell acute lymphoblastic leukaemia (T-ALL) and acute myeloid leukaemia (AML) predominated 55 (56%) and 39 (40%) patients, respectively. Most patients received a chemotherapy regimen per their disease phenotype: 58% received an ALL regimen, 40% an AML regimen and 1% a hybrid regimen. Outcomes for children with PICALM::MLLT10 ALL were reasonable: 5-year event-free survival (EFS) 67% and 5-year overall survival (OS) 76%, but children with PICALM::MLLT10 AML had poor outcomes: 5-year EFS 22% and 5-year OS 26%. Haematopoietic stem cell transplant (HSCT) did not result in a significant improvement in outcomes for PICALM::MLLT10 AML: 5-year EFS 20% for those who received HSCT versus 23% for those who did not (p = 0.6) and 5-year OS 37% versus 36% (p = 0.7). In summary, this study confirms that PICALM::MLLT10 AML is associated with a dismal prognosis and patients cannot be salvaged with HSCT; exploration of novel therapeutic options is warranted.

Poor Subjective Sleep Quality Predicts Symptoms in Irritable Bowel Syndrome Using the Experience Sampling Method.

INTRODUCTION: Sleep quality may affect symptom experience in irritable bowel syndrome (IBS). Our aim was to investigate the relationship between sleep quality and gastrointestinal (GI) symptoms using actigraphy and the experience sampling method. METHODS: Patients with IBS were recruited from a tertiary Neurogastroenterology clinic and the community. GI symptoms and mood were recorded on a smartphone application, 10 times per day, over 7 consecutive days. Subjective sleep quality was recorded every morning to reflect the night before. Objective measures of sleep quality were estimated from wrist-worn actigraphy. Cross-lagged structural equation models were built to assess the directionality of sleep-symptom relationships over time. RESULTS: Eighty patients with IBS completed the study (mean age: 37 years [range 20-68], 89% female, 78% community). Approximately 66% had a Pittsburgh Sleep Quality Index score ≥ 8, indicating a clinically significant sleep disturbance. Approximately 82% (95% CI: 72-90) screened positive for a sleep disorder, most commonly insomnia. In cross-lagged analysis, poor subjective sleep quality predicted next-day abdominal pain (0.036 < P < 0.040) and lower GI symptoms (0.030 < P < 0.032), but not vice versa. No significant relationship with GI symptoms was found for any objective sleep measure using actigraphy. DISCUSSION: Poor subjective sleep quality was associated with higher next-day lower GI symptom levels, but not vice versa. Objective sleep measures did not predict next-day abdominal symptoms, potentially supporting the conclusion that it is the perception of sleep quality that is most influential. This study may be used to guide future research into the effect of sleep interventions on GI symptoms.

Overuse of EEG and ECG in children with breath-holding spells and its implication for the management of the spells.

AIM: Breath-holding spells (BHS) are common in children, but evidence-based clinical guidelines are lacking. We investigated a large population-based cohort of BHS patients, to propose a refined description of typical BHS and guidelines for its management. METHODS: In a cross-sectional retrospective study, patients diagnosed with BHS in Southern Sweden 2004-2018 were recruited. Disease characteristics and diagnostic data were collected from patient medical records. RESULTS: In total, 519 patients, mean age at diagnosis 19.8 ± 13.8 months with equal gender distribution, were included. In 48.3%, BHS had already been diagnosed after one spell. During spells, 78.0% of patients were unresponsive. For 71.5%, atonic, tonic, tonic-clonic or myoclonic seizures were reported, and 78.0% of patients had a spell lasting less than 1 min. Electroencephalography was conducted in 30.4% and Electrocardiography in 45.1%. Six children (3.8%) had a pathological electroencephalogram, four of which had concomitant epilepsy and only 0.9% of children had electrocardiogram findings suggesting pathology, none showing long QT syndrome. CONCLUSION: Children with BHS were frequently subjected to unnecessary diagnostic interventions. We characterise a typical presentation of BHS and propose a management-algorithm, which is expected to reduce unnecessary usage of electroencephalography and electrocardiography.

Characteristics and outcome of primary resistant disease in paediatric acute myeloid leukaemia.

A significant proportion of events in paediatric acute myeloid leukaemia (AML) are caused by resistant disease (RD). We investigated clinical and biological characteristics in 66 patients with RD from 1013 children with AML registered and treated according to the NOPHO-AML 93, NOPHO-AML 2004, DB AML-01 and NOPHO-DBH AML 2012 protocols. Risk factors for RD were age10 years or older and a white-blood-cell count (WBC) of 100 × 109 /L or more at diagnosis. The five-year overall survival (OS) was 38% (95% confidence interval [CI]: 28%-52%). Of the 63 children that received salvage therapy with chemotherapy, 59% (N = 37) achieved complete remission (CR) with OS 57% (95% CI: 42%-75%) compared to 12% (95% CI: 4%-35%) for children that did not achieve CR. Giving more than two salvage chemotherapy courses did not increase CR rates. OS for all 43 patients receiving allogeneic haematopoietic stem cell transplantation (HSCT) was 49% (95% CI: 36%-66%). Those achieving CR and proceeding to HSCT had an OS of 56% (95% CI: 41%-77%, N = 30). This study showed that almost 40% of children with primary resistant AML can be cured with salvage therapy followed by HSCT. Children that did not achieve CR after two salvage courses with chemotherapy did not benefit from additional chemotherapy.

An International Survey of Allogeneic Hematopoietic Cell Transplantation for X-Linked Agammaglobulinemia.

PURPOSE: X-linked agammaglobulinemia (XLA) is an inborn error of immunity caused by variants in Bruton's tyrosine kinase (BTK). XLA patients require lifelong immunoglobulin replacement therapy (IgRT). Only few XLA patients are indicated for allogeneic hematopoietic cell transplantation (HCT) because of severe complications. Accordingly, the published transplantation experience in XLA is minimal. We aimed to collect clinical data of XLA patients who received HCT in an international framework and to establish appropriate transplantation criteria and methods for XLA patients. METHODS: XLA patients were recruited through a questionnaire and a literature review. The data are on patient characteristics and transplantation methods and outcomes. RESULTS: In this study, twenty-two XLA patients who underwent HCT were recruited. The indication for HCT was recurrent or life-threatening infection in sixteen patients, malignancy in three, and other factors in three. A myeloablative conditioning, reduced toxicity myeloablative conditioning (RT-MAC), and reduced intensity conditioning (RIC) were selected in four, ten, and eight patients, respectively. Engraftment was achieved in 21 patients (95%). In all patients, 2-year overall survival (OS) and event-free survival (EFS) were 86% and 77%, respectively. In patients who received RT-MAC or RIC using treosulfan, busulfan, or melphalan, 2-year OS and EFS were 82% and 71%, respectively. Finally, twenty-one patients (95%) obtained complete or stable high-level mixed chimerism (50-95%), and the 1-year discontinuation rate of IgRT was 89%. CONCLUSION: Based on the concept in which IgRT is the standard treatment for XLA, HCT may be an effective and safe alternative treatment option for XLA patients, and IgRT can be discontinued following transplantation. It is ideal to perform HCT in XLA patients for whom transplantation is indicated before they develop organ damage.

Inhaled Δ9-tetrahydrocannabinol does not enhance oxycodone-induced respiratory depression: randomised controlled trial in healthy volunteers.

BACKGROUND: In humans, the effect of cannabis on ventilatory control is poorly studied, and consequently, the effect of Δ9-tetrahydrocannabinol (THC) remains unknown, particularly when THC is combined with an opioid. We studied the effect of THC on breathing without and with oxycodone pretreatment. We hypothesised that THC causes respiratory depression, which is amplified when THC and oxycodone are combined. METHODS: In this randomised controlled crossover trial, healthy volunteers were administered inhaled Bedrocan® 100 mg (Bedrocan International B.V., Veendam, The Netherlands), a pharmaceutical-grade high-THC cannabis variant (21.8% THC; 0.1% cannabidiol), after placebo or oral oxycodone 20 mg pretreatment; THC was inhaled 1.5 and 4.5 h after placebo or oxycodone intake. The primary endpoint was isohypercapnic ventilation at an end-tidal Pco2 of 55 mm Hg or 7.3 kPa (VE55), measured at 1-h intervals for 7 h after placebo/oxycodone intake. RESULTS: In 18 volunteers (age 22 yr [3]; 9 [50%] female), oxycodone produced a 30% decrease in VE55, whereas placebo was without effect on VE55. The first cannabis inhalation resulted in VE55 changing from 20.3 (3.1) to 23.8 (2.4) L min-1 (P=0.06) after placebo, and from 11.8 (2.8) to 13.0 (3.9) L min-1 (P=0.83) after oxycodone. The second cannabis inhalation also had no effect on VE55, but slightly increased sedation. CONCLUSIONS: In humans, THC has no effect on ventilatory control after placebo or oxycodone pretreatment. CLINICAL TRIAL REGISTRATION: 2021-000083-29 (EU Clinical Trials Register.).

Evaluating a clinical decision support point of care instrument in low resource setting.

BACKGROUND: Clinical pathways are one of the main tools to manage the health care's quality and concerned with the standardization of care processes. They have been used to help frontline healthcare workers by presenting summarized evidence and generating clinical workflows involving a series of tasks performed by various people within and between work environments to deliver care. Integrating clinical pathways into Clinical Decision Support Systems (CDSSs) is a common practice today. However, in a low-resource setting (LRS), this kind of decision support systems is often not readily accessible or even not available. To fill this gap, we developed a computer aided CDSS that swiftly identifies which cases require a referral and which ones may be managed locally. The computer aided CDSS is designed primarily for use in primary care settings for maternal and childcare services, namely for pregnant patients, antenatal and postnatal care. The purpose of this paper is to assess the user acceptance of the computer aided CDSS at the point of care in LRSs. METHODS: For evaluation, we used a total of 22 parameters structured in to six major categories, namely "ease of use, system quality, information quality, decision changes, process changes, and user acceptance." Based on these parameters, the caregivers from Jimma Health Center's Maternal and Child Health Service Unit evaluated the acceptability of a computer aided CDSS. The respondents were asked to express their level of agreement using 22 parameters in a think-aloud approach. The evaluation was conducted in the caregiver's spare-time after the clinical decision. It was based on eighteen cases over the course of two days. The respondents were then asked to score their level of agreement with some statements on a five-point scale: strongly disagree, disagree, neutral, agree, and strongly agree. RESULTS: The CDSS received a favorable agreement score in all six categories by obtaining primarily strongly agree and agree responses. In contrast, a follow-up interview revealed a variety of reasons for disagreement based on the neutral, disagree, and strongly disagree responses. CONCLUSIONS: Though the study had a positive outcome, it was limited to the Jimma Health Center Maternal and Childcare Unit, and hence a wider scale evaluation and longitudinal measurements, including computer aided CDSS usage frequency, speed of operation and impact on intervention time are needed.

Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms.

Background Inclusion of mammographic breast density (BD) in breast cancer risk models improves accuracy, but accuracy remains modest. Interval cancer (IC) risk prediction may be improved by combining assessments of BD and an artificial intelligence (AI) cancer detection system. Purpose To evaluate the performance of a neural network (NN)-based model that combines the assessments of BD and an AI system in the prediction of risk of developing IC among women with negative screening mammography results. Materials and Methods This retrospective nested case-control study performed with screening examinations included women who developed IC and women with normal follow-up findings (from January 2011 to January 2015). An AI cancer detection system analyzed all studies yielding a score of 1-10, representing increasing likelihood of malignancy. BD was automatically computed using publicly available software. An NN model was trained by combining the AI score and BD using 10-fold cross-validation. Bootstrap analysis was used to calculate the area under the receiver operating characteristic curve (AUC), sensitivity at 90% specificity, and 95% CIs of the AI, BD, and NN models. Results A total of 2222 women with IC and 4661 women in the control group were included (mean age, 61 years; age range, 49-76 years). AUC of the NN model was 0.79 (95% CI: 0.77,0.81), which was higher than AUC of the AI cancer detection system or BD alone (AUC, 0.73 [95% CI: 0.71, 0.76] and 0.69 [95% CI: 0.67, 0.71], respectively; P < .001 for both). At 90% specificity, the NN model had a sensitivity of 50.9% (339 of 666 women; 95% CI: 45.2, 56.3) for prediction of IC, which was higher than that of the AI system (37.5%; 250 of 666 women; 95% CI: 33.0, 43.7; P < .001) or BD percentage alone (22.4%; 149 of 666 women; 95% CI: 17.9, 28.5; P < .001). Conclusion The combined assessment of an artificial intelligence detection system and breast density measurements enabled identification of a larger proportion of women who would develop interval cancer compared with either method alone. Published under a CC BY 4.0 license.

Improved automated early detection of breast cancer based on high resolution 3D micro-CT microcalcification images.

BACKGROUND: The detection of suspicious microcalcifications on mammography represents one of the earliest signs of a malignant breast tumor. Assessing microcalcifications' characteristics based on their appearance on 2D breast imaging modalities is in many cases challenging for radiologists. The aims of this study were to: (a) analyse the association of shape and texture properties of breast microcalcifications (extracted by scanning breast tissue with a high resolution 3D scanner) with malignancy, (b) evaluate microcalcifications' potential to diagnose benign/malignant patients. METHODS: Biopsy samples of 94 female patients with suspicious microcalcifications detected during a mammography, were scanned using a micro-CT scanner at a resolution of 9 µm. Several preprocessing techniques were applied on 3504 extracted microcalcifications. A high amount of radiomic features were extracted in an attempt to capture differences among microcalcifications occurring in benign and malignant lesions. Machine learning algorithms were used to diagnose: (a) individual microcalcifications, (b) samples. For the samples, several methodologies to combine individual microcalcification results into sample results were evaluated. RESULTS: We could classify individual microcalcifications with 77.32% accuracy, 61.15% sensitivity and 89.76% specificity. At the sample level diagnosis, we achieved an accuracy of 84.04%, sensitivity of 86.27% and specificity of 81.39%. CONCLUSIONS: By studying microcalcifications' characteristics at a level of details beyond what is currently possible by using conventional breast imaging modalities, our classification results demonstrated a strong association between breast microcalcifications and malignancies. Microcalcification's texture features extracted in transform domains, have higher discriminating power to classify benign/malignant individual microcalcifications and samples compared to pure shape-features.

Does minimal central nervous system involvement in childhood acute lymphoblastic leukemia increase the risk for central nervous system toxicity?

Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) implicates enhanced intrathecal chemotherapy, which is related to CNS toxicity. Whether CNS involvement alone contributes to CNS toxicity remains unclear. We studied the occurrence of all CNS toxicities, seizures, and posterior reversible encephalopathy syndrome (PRES) in children with ALL without enhanced intrathecal chemotherapy with CNS involvement (n = 64) or without CNS involvement (n = 256) by flow cytometry. CNS involvement increased the risk for all CNS toxicities, seizures, and PRES in univariate analysis and, after adjusting for induction therapy, for seizures (hazard ratio [HR] = 3.33; 95% confidence interval [CI]: 1.26-8.82; p = 0.016) and PRES (HR = 4.85; 95% CI: 1.71-13.75; p = 0.003).

Assessment of formats and completeness of paper-based referral letters among urban hospitals in Rwanda: a retrospective baseline study.

BACKGROUND: Patient referral is a process in which a healthcare provider decides to seek assistance due to the limitations of available skills, resources and services offered locally. Paper-based referrals predominantly used in low-income countries hardly follow any procedure. This causes a major gap in communication, coordination, and continuity of care between primary and specialized levels, leading to poor access, delay, duplication and unnecessary costs. The goal of this study is to assess the formats and completeness of existing paper-based referral letters in order to improve health information exchange, coordination, and continuity of care. METHODS: A retrospective exploratory research was conducted in eight public and three private healthcare facilities in the city of Kigali from May to October 2021. A purposive sampling method was used to select hospitals and referral letters from patients' files. A data capture sheet was designed according to the contents of the referral letters and the resulting responses were analyzed descriptively. RESULTS: In public hospitals, five types of updated referral letters were available, in total agreement with World Health Organization (WHO) standards of which two (neonatal transfer form and patient monitoring transfer form) were not used. There was also one old format that was used by most hospitals and another format designed and used by a district hospital (DH) separately. Three formats were designed and used by private hospitals (PH) individually. A total of 2,304 referral letters were perused and the results show that "external transfer" forms were completed at 58.8%; "antenatal, delivery, and postnatal external transfer" forms at 47.5%; "internal transfer" forms at 46.6%; "Referral/counter referral" forms at 46.0%; district hospital referrals (DH2) at 73.4%. Referrals by private hospitals (PH1, PH2 and PH3) were completed at 97.7%, 70.7%, and 0.0% respectively. The major completeness deficit was observed in counter referral information for all hospitals. CONCLUSION: We observed inconsistencies in the format of the available referral letters used by public hospitals, moreover some of them were incompatible with WHO standards. Additionally, there were deficits in the completeness of all types of paper-based referral letters in use. There is a need for standardization and to disseminate the national patient referral guideline in public hospitals with emphasis on referral feedback, referral registry, triage, archiving and a need for regular training in all organizations.

Real-Time Analysis of Hand Gesture Recognition with Temporal Convolutional Networks.

In recent years, the successful application of Deep Learning methods to classification problems has had a huge impact in many domains. (1) Background: In biomedical engineering, the problem of gesture recognition based on electromyography is often addressed as an image classification problem using Convolutional Neural Networks. Recently, a specific class of these models called Temporal Convolutional Networks (TCNs) has been successfully applied to this task. (2) Methods: In this paper, we approach electromyography-based hand gesture recognition as a sequence classification problem using TCNs. Specifically, we investigate the real-time behavior of our previous TCN model by performing a simulation experiment on a recorded sEMG dataset. (3) Results: The proposed network trained with data augmentation yields a small improvement in accuracy compared to our existing model. However, the classification accuracy is decreased in the real-time evaluation, showing that the proposed TCN architecture is not suitable for such applications. (4) Conclusions: The real-time analysis helps in understanding the limitations of the model and exploring new ways to improve its performance.

A Systematic Literature Review of the Successors of "NeuroEvolution of Augmenting Topologies".

NeuroEvolution (NE) refers to a family of methods for optimizing Artificial Neural Networks (ANNs) using Evolutionary Computation (EC) algorithms. NeuroEvolution of Augmenting Topologies (NEAT) is considered one of the most influential algorithms in the field. Eighteen years after its invention, a plethora of methods have been proposed that extend NEAT in different aspects. In this article, we present a systematic literature review (SLR) to list and categorize the methods succeeding NEAT. Our review protocol identified 232 papers by merging the findings of two major electronic databases. Applying criteria that determine the paper's relevance and assess its quality, resulted in 61 methods that are presented in this article. Our review article proposes a new categorization scheme of NEAT's successors into three clusters. NEAT-based methods are categorized based on 1) whether they consider issues specific to the search space or the fitness landscape, 2) whether they combine principles from NE and another domain, or 3) the particular properties of the evolved ANNs. The clustering supports researchers 1) understanding the current state of the art that will enable them, 2) exploring new research directions or 3) benchmarking their proposed method to the state of the art, if they are interested in comparing, and 4) positioning themselves in the domain or 5) selecting a method that is most appropriate for their problem.

Data Augmentation of Surface Electromyography for Hand Gesture Recognition.

The range of applications of electromyography-based gesture recognition has increased over the last years. A common problem regularly encountered in literature is the inadequate data availability. Data augmentation, which aims at generating new synthetic data from the existing ones, is the most common approach to deal with this data shortage in other research domains. In the case of surface electromyography (sEMG) signals, there is limited research in augmentation methods and quite regularly the results differ between available studies. In this work, we provide a detailed evaluation of existing (i.e., additive noise, overlapping windows) and novel (i.e., magnitude warping, wavelet decomposition, synthetic sEMG models) strategies of data augmentation for electromyography signals. A set of metrics (i.e., classification accuracy, silhouette score, and Davies-Bouldin index) and visualizations help with the assessment and provides insights about their performance. Methods like signal magnitude warping and wavelet decomposition yield considerable increase (up to 16%) in classification accuracy across two benchmark datasets. Particularly, a significant improvement of 1% in the classification accuracy of the state-of-the-art model in hand gesture recognition is achieved.

Gain-of-function SAMD9L mutations cause a syndrome of cytopenia, immunodeficiency, MDS, and neurological symptoms.

Several monogenic causes of familial myelodysplastic syndrome (MDS) have recently been identified. We studied 2 families with cytopenia, predisposition to MDS with chromosome 7 aberrations, immunodeficiency, and progressive cerebellar dysfunction. Genetic studies uncovered heterozygous missense mutations in SAMD9L, a tumor suppressor gene located on chromosome arm 7q. Consistent with a gain-of-function effect, ectopic expression of the 2 identified SAMD9L mutants decreased cell proliferation relative to wild-type protein. Of the 10 individuals identified who were heterozygous for either SAMD9L mutation, 3 developed MDS upon loss of the mutated SAMD9L allele following intracellular infections associated with myeloid, B-, and natural killer (NK)-cell deficiency. Five other individuals, 3 with spontaneously resolved cytopenic episodes in infancy, harbored hematopoietic revertant mosaicism by uniparental disomy of 7q, with loss of the mutated allele or additional in cisSAMD9L truncating mutations. Examination of 1 individual indicated that somatic reversions were postnatally selected. Somatic mutations were tracked to CD34+ hematopoietic progenitor cell populations, being further enriched in B and NK cells. Stimulation of these cell types with interferon (IFN)-α or IFN-γ induced SAMD9L expression. Clinically, revertant mosaicism was associated with milder disease, yet neurological manifestations persisted in 3 individuals. Two carriers also harbored a rare, in trans germ line SAMD9L missense loss-of-function variant, potentially counteracting the SAMD9L mutation. Our results demonstrate that gain-of-function mutations in the tumor suppressor SAMD9L cause cytopenia, immunodeficiency, variable neurological presentation, and predisposition to MDS with -7/del(7q), whereas hematopoietic revertant mosaicism commonly ameliorated clinical manifestations. The findings suggest a role for SAMD9L in regulating IFN-driven, demand-adapted hematopoiesis.

Acute myeloid leukemia (AML) with t(7;12)(q36;p13) is associated with infancy and trisomy 19: Data from Nordic Society for Pediatric Hematology and Oncology (NOPHO-AML) and review of the literature.

The t(7;12)(q36;p13) (MNX1/ETV6) is not included in the WHO classification but has been described in up to 30% of acute myeloid leukemia (AML) in children <2 years and associated with a poor prognosis. We present the clinical and cytogenetics characteristics of AML cases with t(7;12)(p36;p13). A literature review identified 35 patients with this translocation, published between 2000 and 2015. Outcome data were available in 22 cases. The NOPHO-AML (Nordic Society for Pediatric Hematology and Oncology) database contained 651 patients with AML from 1993 to 2014 and seven (1.1%) had the translocation. The t(7;12) was only present in patients <2 years of age (median age 6 months) but none was diagnosed as newborn. These patients constituted 4.3% of the patients <2 years of age. There was a strong association with trisomy 19 (literature: 86%, NOPHO: 100%) and +8 (literature: 19%, NOPHO: 14%). Seventeen of 22 patients from the literature with t(7;12) and four of seven patients from the NOPHO database suffered from relapse. The patients with t(7;12) had a 3-year event free survival of 24% (literature) vs. 43% (NOPHO) and a 3-year overall survival of 42% (literature) vs. 100% (NOPHO). None of the NOPHO patients was treated with hematopoietic stem cell transplantation (HSCT) in first complete remission. Relapse was frequent but the salvage rate using HSCT was high. We conclude that t(7;12)(q36;13) is a unique subgroup of childhood AML with presentation before 2 years of age with most cases being associated with +19.

Meditation is associated with increased brain network integration.

INTRODUCTION: This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration. METHODS: Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4-8 Hz), alpha (8-13 Hz) and lower beta (13-20 Hz) frequency bands. RESULTS: Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands. CONCLUSION: These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using neurophenomenology experiments.

Large-scale network organization of EEG functional connectivity in newborn infants.

The organization of functional brain networks changes across human lifespan. The present study analyzed functional brain networks in healthy full-term infants (N = 139) within 1-6 days from birth by measuring neural synchrony in EEG recordings during quiet sleep. Large-scale phase synchronization was measured in six frequency bands with the Phase Lag Index. Macroscopic network organization characteristics were quantified by constructing unweighted minimum spanning tree graphs. The cortical networks in early infancy were found to be significantly more hierarchical and had a more cost-efficient organization compared with MST of random control networks, more so in the theta and alpha than in other frequency bands. Frontal and parietal sites acted as the main hubs of these networks, the topological characteristics of which were associated with gestation age (GA). This suggests that individual differences in network topology are related to cortical maturation during the prenatal period, when functional networks shift from strictly centralized toward segregated configurations. Hum Brain Mapp 38:4019-4033, 2017. © 2017 Wiley Periodicals, Inc.