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The aim of this study is to perform the first meta-meta-analysis on the effectiveness of parent-based interventions for children with externalizing behavior problems. Even though parent-based interventions are considered as effective treatments the effects reported in meta-analyses are heterogeneous and the implementation in clinical practice is suboptimal. Recapitulative valid effect predictions are required to close the still existing gap between research findings and clinical practice. The meta-meta-analytic results on changes in child behavior shall result in a clear signal for clinical practice. This meta-meta-analysis encompasses 26 meta-analyses identified via search in electronic databases (PsycINFO, Medline, PubMed). Meta-analyses had to report effects of parent-based interventions on child behavior and focus on children under the age of 13 years with externalizing behavior problems in a clinical setting. Analyses were based on random-effects models. To combine results, the effect estimates of the meta-analyses were transformed to SMD and weighted to correct for primary study overlap. The meta-meta-analysis is registered on PROSPERO, registration number CRD42016036486 and was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA). The results indicate a significant moderate overall effect for child behavior (SMD = 0.46) as well as for parent reports (SMD = 0.51) and observational data (SMD = 0.62). Further analyses focusing on child externalizing behavior yielded significant and moderate effects (SMD = 0.45). All effects remained stable to follow-up. Considerable heterogeneity was observed within results. Parent-based interventions are shown to be effective in improving behavior in children with externalizing behavior problems, as assessed using parent reports and observational measures. The present results should encourage health care providers to apply evidence-based parent-based interventions.

This manuscript describes the Child Health and Mortality Prevention Surveillance (CHAMPS) network approach to pathologic evaluation of minimally invasive tissue sampling (MITS) specimens, including guidelines for histopathologic examination and further diagnostics with special stains, immunohistochemistry, and molecular testing, as performed at the CHAMPS Central Pathology Laboratory (CPL) at the Centers for Disease Control and Prevention, as well as techniques for virtual discussion of these cases (telepathology) with CHAMPS surveillance locations. Based on review of MITS from the early phase of CHAMPS, the CPL has developed standardized histopathology-based algorithms for achieving diagnoses from MITS and telepathology procedures in conjunction with the CHAMPS sites, with the use of whole slide scanners and digital image archives, for maximizing concurrence and knowledge sharing between site and CPL pathologists. These algorithms and procedures, along with lessons learned from initial implementation of these approaches, guide pathologists at the CPL and CHAMPS sites through standardized diagnostics of MITS cases, and allow for productive, real-time case discussions and consultations.

Postmortem minimally invasive tissue sampling (MITS) is a potential alternative to the gold standard complete diagnostic autopsy for identifying specific causes of childhood deaths. We investigated the utility of MITS, interpreted with available clinical data, for attributing underlying and immediate causes of neonatal deaths. This prospective, observational pilot study enrolled neonatal deaths at Chris Hani Baragwanath Academic Hospital in Soweto, South Africa. The MITS included needle core-biopsy sampling for histopathology of brain, lung, and liver tissue. Microbiological culture and/or molecular tests were performed on lung, liver, blood, cerebrospinal fluid, and stool samples. The \"underlying\" and \"immediate\" causes of death (CoD) were determined for each case by an international panel of 12-15 medical specialists. We enrolled 153 neonatal deaths, 106 aged 3-28 days. Leading underlying CoD included \"complications of prematurity\" (52.9%), \"complications of intrapartum events\" (15.0%), \"congenital malformations\" (13.1%), and \"infection related\" (9.8%). Overall, infections were the immediate or underlying CoD in 57.5% (n = 88) of all neonatal deaths, including the immediate CoD in 70.4% (58/81) of neonates with \"complications of prematurity\" as the underlying cause. Overall, 74.4% of 90 infection-related deaths were hospital acquired, mainly due to multidrug-resistant Acinetobacter baumannii (52.2%), Klebsiella pneumoniae (22.4%), and Staphylococcus aureus (20.9%). Streptococcus agalactiae was the most common pathogen (5/15 [33.3%]) among deaths with \"infections\" as the underlying cause. MITS has potential to address the knowledge gap on specific causes of neonatal mortality. In our setting, this included the hitherto underrecognized dominant role of hospital-acquired multidrug-resistant bacterial infections as the leading immediate cause of neonatal deaths.

We present one of the first case studies demonstrating the use of distributed acoustic sensing deployed on regional unlit fiber-optic telecommunication infrastructure (dark fiber) for broadband seismic monitoring of both near-surface soil properties and earthquake seismology. We recorded 7 months of passive seismic data on a 27 km section of dark fiber stretching from West Sacramento, CA to Woodland, CA, densely sampled at 2 m spacing. This dataset was processed to extract surface wave velocity information using ambient noise interferometry techniques; the resulting V S profiles were used to map both shallow structural profiles and groundwater depth, thus demonstrating that basin-scale variations in hydrological state could be resolved using this technique. The same array was utilized for detection of regional and teleseismic earthquakes and evaluated for long period response using records from the M8.1 Chiapas, Mexico 2017, Sep 8th event. The combination of these two sets of observations conclusively demonstrates that regionally extensive fiber-optic networks can effectively be utilized for a host of geoscience observation tasks at a combination of scale and resolution previously inaccessible.

One-dimensional (1D) zinc oxide (ZnO) nanostructures have been extensively and intensively studied for several decades not only for their extraordinary chemical and physical properties, but also for their current and future different electronic and optoelectronic device applications. This review provides a brief overview of the progress of different synthesis methods and applications of 1D-ZnO nanostructures. Morphology of ZnO nanostructures grown by various methods and progress in the optical properties are briefly described. Using low-temperature photoluminescence (LTPL) study, detailed informations about the defect states and impurity of such nanostructures are reported. Improvement of field emission properties by modifying the edge of 1D-ZnO nanostructures is briefly discussed. Applications such as different sensors, field effect transistor, light-emitting diodes (LEDs), and photodetector are briefly reviewed. ZnO has large exciton binding energy (60 meV) and wide band gap (3.37 eV), which could lead to lasing action based on exciton recombination. As semiconductor devices are being aggressively scaled down, ZnO 1D nanostructures based resistive switching (RS) memory (resistance random access memory) is very attractive for nonvolatile memory applications. Switching properties and mechanisms of Ga-doped and undoped ZnO nanorods/NWs are briefly discussed. The present paper reviews the recent activities of the growth and applications of various 1D-ZnO nanostructures for sensor, LED, photodetector, laser, and RS memory devices.

The geometric structure of a single-particle energy band in a solid is fundamental for a wide range of many-body phenomena and is uniquely characterized by the distribution of Berry curvature over the Brillouin zone. We realize an atomic interferometer to measure Berry flux in momentum space, in analogy to an Aharonov-Bohm interferometer that measures magnetic flux in real space. We demonstrate the interferometer for a graphene-type hexagonal optical lattice loaded with bosonic atoms. By detecting the singular π Berry flux localized at each Dirac point, we establish the high momentum resolution of this interferometric technique. Our work forms the basis for a general framework to fully characterize topological band structures.

Many interventions targeting executive function (EF) development in the preschool period, where malleability might be particularly high, have been created and evaluated. We conducted a meta-analysis of randomized controlled trials (RCTs) on the effects of these interventions on (a) EFs in preschool children from the general population as well as preschool children with (symptoms of) attention-deficit hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD), and (b) ADHD and ODD symptoms in preschool children with ADHD/ODD (symptoms). Literature search yielded 35 RCTs. Risk of bias of the individual studies was assessed. A random-effects model was used. Moderator effects were tested using mixed model analyses. The overall effects on EFs were: d = 0.46 (95% CI 0.30–0.61) for working memory (WM), d = 0.30 (95% CI 0.21–0.38) for inhibitory control (IC), d = 0.33 (95% CI − 0.04 to 0.71) for reward-related IC, and d = 0.47 (95% CI 0.28–0.66) for flexibility. In children with ADHD/ODD, mean effects were d = 0.64 (95% CI 0.31–0.96) for WM and d = 0.46 (95% CI 0.07–0.84) for IC. Studies on reward-related IC and FL were lacking. Effects on ODD and ADHD symptoms were d = 0.40 (95% CI − 0.23 to 1.03) and d = 0.28 (95% CI − 0.08 to 0.64), respectively. Interventions targeting multiple EFs and using interpersonal cognitive scaffolding approaches showed large and statistically significant effects on ADHD and ODD symptoms. In preschool children of the general population and in those with ADHD/ODD (symptoms), interventions led to an improvement of EF performance. In children with ADHD and ODD, cognitive scaffolding interventions were most effective in terms of reducing ADHD and ODD symptoms. However, more well-controlled studies need to be conducted before any firm conclusions can be drawn.

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits. A genome-wide association study for attention deficit/hyperactivity disorder (ADHD) identifies 12 loci and implicates neurodevelopmental pathways and conserved regions of the genome as being involved in underlying ADHD biology.

In 2011, the “ADHD-200 Global Competition” was held with the aim of identifying biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic resonance imaging (rs-fMRI) and structural MRI (s-MRI) data collected on 973 individuals. Statisticians and computer scientists were potentially the most qualified for the machine learning aspect of the competition, but generally lacked the specialized skills to implement the necessary steps of data preparation for rs-fMRI. Realizing this barrier to entry, the Neuro Bureau prospectively collaborated with all competitors by preprocessing the data and sharing these results at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) (http://www.nitrc.org/frs/?group_id=383). This “ADHD-200 Preprocessed” release included multiple analytical pipelines to cater to different philosophies of data analysis. The processed derivatives included denoised and registered 4D fMRI volumes, regional time series extracted from brain parcellations, maps of 10 intrinsic connectivity networks, fractional amplitude of low frequency fluctuation, and regional homogeneity, along with grey matter density maps. The data was used by several teams who competed in the ADHD-200 Global Competition, including the winning entry by a group of biostaticians. To the best of our knowledge, the ADHD-200 Preprocessed release was the first large public resource of preprocessed resting-state fMRI and structural MRI data, and remains to this day the only resource featuring a battery of alternative processing paths. •Processed derivatives generated from structural and resting-state fMRI in 973 individuals.•The sample includes 585 typically developing children, 362 children with ADHD, and 26 with unknown diagnostic status.•Functional MRI volumes were denoised and aligned using two alternative processing pipelines.•Derivatives include regional time series, grey matter segmentation and variants of functional connectivity mapping.•These resources are freely available, with minimal access requirements.