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Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome data from 702 neuroblastoma samples. Forty percent of samples harbor at least one recurrent driver gene alteration and most aberrations, including MYCN , ATRX , and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years. COSMIC mutational signature 18, previously associated with reactive oxygen species, is the most common cause of driver point mutations in neuroblastoma, including most ALK and Ras-activating variants. Signature 18 appears early and is continuous throughout disease evolution. Signature 18 is enriched in neuroblastomas with MYCN amplification, 17q gain, and increased expression of mitochondrial ribosome and electron transport-associated genes. Recurrent FGFR1 variants in six patients, and ALK N-terminal structural alterations in five samples, identify additional patients potentially amenable to precision therapy. Genomic analysis of neuroblastoma has revealed important disease etiology. In this study, the authors assembled whole genome, exome and transcriptome data from over 700 neuroblastomas and identified molecular signatures correlated with age, and rare, potentially targetable variants overlooked in smaller cohorts.

The use of dyes in food industrial processes is limited due to significant pollution in aquatic receptors from their wastewater. To address this issue, this study focused on evaluating the adsorption of dyes Allura Red (R40) and Brilliant blue FCF (B1) using cocoa shells (CS) as an absorbent. To achieve this, a pre-treatment was applied, which involved washing, grinding and drying at a temperature of 80 °C for 24 h, followed by a sieving process. The effect of the adsorbent dose was then analyzed and it was calculated that the optimal dose was 4 g/L. Additionally, the effect of contact time was studied through a kinetic analysis, all tests were carried out at a pH level of 2. The obtained data were fitted to kinetic models, which allowed us to conclude that the adsorption kinetics fit two different models depending on the initial solution conditions, in a range from 0 to 0.1512 mmol/L. Specifically, the Pseudo Second-Order (PSO) model fitted R40, while the Elovich model was appropriate for B1. In summary, CS was found to be a viable adsorbent for dyes in contaminated waters.

Currently, in the field of odor detection, there is generally a wider variation in limit of detections (LODs) for canines than instruments. The study presented in this paper introduces an improved protocol for the creation of controlled odor mimic permeation system (COMPS) devices for use as standards in canine training and discusses the canine detection thresholds of piperonal, a starting material for the illicit drug 3,4-methylenedioxymethamphetamine (MDMA), when exposed to these devices. Additionally, this paper describes the first-ever reported direct comparison of solid phase microextraction–ion mobility spectrometry (SPME–IMS) to canine detection for the MDMA odorant, piperonal. The research presented shows the reliability of COMPS devices as low cost field calibrants providing a wide range of odorant concentrations for biological and instrumental detectors. The canine LOD of piperonal emanating from the 100 ng s −1 COMPS was found to be 1 ng as compared to the SPME–IMS LOD of piperonal in a static, closed system at 2 ng, with a linear dynamic range from 2 ng to 11 ng. The utilization of the COMPS devices would allow for training that will reduce the detection variability between canines and maintain improved consistency for training purposes. Since both SPME and IMS are field portable technologies, it is expected that this coupled method will be useful as a complement to canine detection for the field detection of MDMA.

We developed cis-X, a computational method for discovering regulatory noncoding variants in cancer by integrating whole-genome and transcriptome sequencing data from a single cancer sample. cis-X first finds aberrantly cis -activated genes that exhibit allele-specific expression accompanied by an elevated outlier expression. It then searches for causal noncoding variants that may introduce aberrant transcription factor binding motifs or enhancer hijacking by structural variations. Analysis of 13 T-lineage acute lymphoblastic leukemias identified a recurrent intronic variant predicted to cis -activate the TAL1 oncogene, a finding validated in vivo by chromatin immunoprecipitation sequencing of a patient-derived xenograft. Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion that removes a CTCF-insulated neighborhood boundary. cis-X may be applied to pediatric and adult solid tumors that are aneuploid and heterogeneous. In contrast to existing approaches, which require large sample cohorts, cis-X enables the discovery of regulatory noncoding variants in individual cancer genomes. A new computational method integrates whole-genome sequencing and transcriptomic data to identify regulatory noncoding variants in an individual cancer genome.

What are the main findings? * Multilayer electrospun nanofibrous membranes based on polyacrylonitrile (PAN), chitosan (CS), and Nylon 6 (N6) were engineered and mechanically optimized for the adsorption of hexavalent chromium and cadmium from water. * The optimized CS–N6–PAN architecture achieved removal efficiencies above 80% for Cr[sup.6+] and approximately 79% for Cd[sup.2+] in synthetic solutions, while maintaining high performance in real river water. What are the main findings? Multilayer electrospun nanofibrous membranes based on polyacrylonitrile (PAN), chitosan (CS), and Nylon 6 (N6) were engineered and mechanically optimized for the adsorption of hexavalent chromium and cadmium from water. The optimized CS–N6–PAN architecture achieved removal efficiencies above 80% for Cr[sup.6+] and approximately 79% for Cd[sup.2+] in synthetic solutions, while maintaining high performance in real river water. What are the implications of these findings? * These multilayer electrospun membranes, particularly with chitosan as the outer functional layer, offer a robust and environmentally friendly platform for heavy metal remediation in contaminated waters. * The combination of high adsorption efficiency, mechanical stability, and effectiveness in real water matrices underscores their potential for scalable and sustainable water treatment applications. What are the implications of these findings? These multilayer electrospun membranes, particularly with chitosan as the outer functional layer, offer a robust and environmentally friendly platform for heavy metal remediation in contaminated waters. The combination of high adsorption efficiency, mechanical stability, and effectiveness in real water matrices underscores their potential for scalable and sustainable water treatment applications. This study presents the fabrication and performance analysis of multilayer membranes produced by electrospinning using polyacrylonitrile (PAN), chitosan (CS), and Nylon 6 (N6) for the removal of chromium (Cr) and cadmium (Cd) from water. The electrospun membranes were configured in six different multilayer structures. The morphological and mechanical properties of the membranes were evaluated using SEM and tensile testing. Adsorption experiments were performed using synthetic and real water samples from the Cutuchi River. The multilayer membranes demonstrated metal ion removal efficiencies up to 80.81% for Cr[sup.6+] and 78.98% for Cd[sup.2+] in synthetic water, and similar performance in real samples. These results validate the use of multilayer electrospun membranes as an effective, environmentally friendly method for water purification applications.

Nanofertilizers (NFs) and engineered nanoparticles (NPs) are increasingly used in agriculture, yet their environmental safety remains poorly understood. This study evaluated the comparative phytotoxicity of zinc oxide (ZnO), titanium dioxide (TiO2), and clinoptilolite nanoparticles, three commercial nanofertilizers, and potassium dichromate (K2Cr2O7) using Lactuca sativa seeds under adapted OECD-208 protocol conditions. Seeds were exposed to varying concentrations of each xenobiotic material (0.5–3% for NFs; 10–50% for NPs), with systematic assessment of seedling survival, root and hypocotyl length, dry biomass, germination index (GI), and median effective concentration (EC50) values. Nanofertilizers demonstrated significantly greater phytotoxicity than engineered nanoparticles despite lower application concentrations. The toxicity ranking was established as NF1 > NF3 > NF2 > NM2 > NM1 > NM3, with NF1 being most toxic (EC50 = 1.2%). Nanofertilizers caused 45–78% reductions in root length and 30–65% decreases in dry biomass compared with controls. GI values dropped to ≤70% in NF1 and NF3 treatments, indicating concentration-dependent growth inhibition. While nanofertilizers offer agricultural benefits, their elevated phytotoxicity compared with conventional nanoparticles necessitates rigorous pre-application safety assessment. These findings emphasize the critical need for standardized evaluation protocols incorporating both physiological and ecotoxicological endpoints to ensure safe xenobiotic nanomaterial deployment in agricultural systems.

Many different onset detection methods have been proposed over time, but other than for non-pitched percussive sounds, such as drums, there does not exist a general method that correctly identifies onsets with high accuracy. In this thesis, the domain is limited to pitched percussive sounds, particularly piano pieces. This thesis focuses on statistical-based onset detection models. When compared to probabilistic and learning-based models, they perform very well, are simpler, and run much faster since no training is involved, all of which are ideal for an online setting. These models have a common workflow of building a spectrogram, applying an onset detection function to create an activation curve, and using a peak picking algorithm to select candidate onsets. Even though they do not directly improve performance, pilot studies on the main stages of onset detection are described. This includes using a variable framerate spectrogram, an onset detection function that makes use of harmonic information, and dynamic peak picking thresholding using Otsu's method. These approaches touch on areas where onset detection can be improved and should be further investigated. Finally, a new method is proposed, combining many techniques shown to improve onset detection. This includes doubling the framerate of the spectrogram, preprocessing the spectrogram with a log-scale and adaptive magnitude, and widening the frame index difference. The preprocessed time-frequency representation, though more complex than previous algorithms, is effective, allowing the use of a simple onset detection function. This new method is able to outperform both original implementations and state-of-the-art statistical-based methods on a subset of the MIDI Aligned Piano Sounds dataset.

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

Xenografts are important models for cancer research and the presence of mouse reads in xenograft next generation sequencing data can potentially confound interpretation of experimental results. We present an efficient, cloud-based BAM-to-BAM cleaning tool called XenoCP to remove mouse reads from xenograft BAM files. We show application of XenoCP in obtaining accurate gene expression quantification in RNA-seq and tumor heterogeneity in WGS of xenografts derived from brain and solid tumors.

Where do marijuana co-ops get their marijuana? Is it purchased from legitimate drug dealers/growers or drug cartels? If so, who is paying the taxes on this multi-billion dollar industry? If the co-ops grow their own marijuana (beyond personal use), which state or federal laws allow that? Do the co-ops declare to the city or county where their marijuana farm is, so the proper health, agricultural and safety inspections can occur? If the co-ops are growing marijuana indoors are the local fire inspectors notified so safety standards are complied with?