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Purpose: This study aims to create a reference model for the national Financial Literacy movement by finding a Financial Control model for Generation Z of Surabaya, which is 0.03% of the total in Indonesia. Therefore, the researchers made it the subject of research. Design/methodology/approach: In determining the minimum number of samples, the researcher used the Slovin formula. The research instrument used was a questionnaire. Findings: The study results show that the model relates to the Marketplace and financial literacy. Here, Marketplace has a significant impact and weak influence on Financial Control. At the same time, Financial Literacy has a substantial and robust effect on Financial Control. While Marketplace on Financial Control through Financial Literacy has a significant impact and a reasonably vital influence role. The findings are that 53% of research subjects think the literacy movement with animated video models through digital media is more attractive than others. Originality/value: This paper is original Paper type: Research article

Medulloblastoma is one of the most common types of brain tumors in children. During and after treatment with surgery, chemotherapy, and/or radiotherapy, children with this disease are monitored with imaging and cerebrospinal fluid analysis for the detection of tumor cells. These methods are not always sensitive or specific enough to confirm or rule out residual disease. Here, we develop a laboratory test based on the genetic makeup of medulloblastomas in 12 children. We analyze liquid biopsies (cerebrospinal fluid and blood plasma) for specific genetic fragments leaking from the individual tumors and find molecular traces of disease in 75% (9/12) of children overall. None of the children had malignant cells in the cerebrospinal fluid. We propose that this test could open up new technical possibilities to track measurable residual disease in children with medulloblastoma in order to further risk-adapt treatment, but first, larger studies of the approach at standardized time points are warranted.Medulloblastoma is a malignant embryonal tumor of the central nervous system (CNS) that mainly affects infants and children. Prognosis is highly variable, and molecular biomarkers for measurable residual disease (MRD) detection are lacking. Analysis of cell-free DNA (cfDNA) in cerebrospinal fluid (CSF) using broad genomic approaches, such as low-coverage whole-genome sequencing, has shown promising prognostic value. However, more sensitive methods are needed for MRD analysis. Here, we show the technical feasibility of capturing medulloblastoma-associated structural variants and point mutations simultaneously in cfDNA using multiplexed droplet digital PCR (ddPCR). Assay sensitivity was assessed with a dilution series of tumor in normal genomic DNA, and the limit of detection was below 100 pg of input DNA for all assays. False positive rates were zero for structural variant assays. Liquid biopsies (CSF and plasma, n = 47) were analyzed from 12 children with medulloblastoma, all with negative CSF cytology. MRD was detected in 75% (9/12) of patients overall. In CSF samples taken before or within 21 days of surgery, MRD was detected in 88% (7/8) of patients with localized disease and in one patient with the metastasized disease. Our results suggest that this approach could expand the utility of ddPCR and complement broader analyses of cfDNA for MRD detection.

Risk-adapted treatment in acute lymphoblastic leukemia (ALL) relies on genetic information and measurable residual disease (MRD) monitoring. In this proof of concept study, DNA from diagnostic bone marrow (BM) of six children with ALL, without stratifying genetics or central nervous system (CNS) involvement, underwent whole-genome sequencing (WGS) to identify structural variants (SVs) in the leukemic blasts. Unique sequences generated by SVs were targeted with patient-specific droplet digital PCR (ddPCR) assays. Genomic DNA (gDNA) from BM and cell-free DNA (cfDNA) from plasma and cerebrospinal fluid (CSF) were analyzed longitudinally. WGS with 30× coverage enabled target identification in all cases. Limit of quantifiability (LoQ) and limit of detection (LoD) for the ddPCR assays (n = 15) were up to 10

Background: Sarcomas are rare tumours with heterogeneous clinical behaviour including varying rates of metastasis. Clinical treatment and follow-up rely on crude grading systems with uncertain accuracy for individual patients. Whole genome sequencing (WGS) detects both structural variation and single nucleotide variants and may thus add important diagnostic/prognostic information. Liquid biopsies (LB) may potentially identify hematogenous spread and treatment response rate but further evaluation in sarcomas is needed. Methods: In this study we explore the performance of individualized LB in four patients with different types of sarcomas. Fresh frozen tumour tissue was sequenced using WGS and whole transcriptome sequencing. Three putative driver variants or one fusion gene were selected per case and custom digital droplet PCR (ddPCR) assays were designed, evaluated on tumour DNA and used to assess levels of cell free tumour DNA in plasma taken prior to surgery. Results: In LB, ddPCR identified three variants in one patient with metastatic disease. The remaining three patients had negative LBs and were without disease at follow-up (>18 months after surgery). Conclusions: WGS is a powerful tool to detect all types of genetic changes in sarcoma and can facilitate clinical diagnosis/classification while custom LB may add prognostic information.