30 Vragen en antwoorden over fosfaat in relatie tot landbouw en milieu

Deze uitgave geeft een antwoord op veel gestelde vragen over fosfaat. Het betreft zowel algemene als landbouwkundige en milieukundige vragen. Deze publicatie is opgesteld voor beleidsmedewerkers van de rijksoverheid en regionale overheden (provincies, waterschappen), maatschappelijke organisaties en voor landbouwers en hun organisaties. In feite voor allen die met fosfaatbeleid te maken hebben. Van nature zit er weinig fosfor in de bodem, zo’n 0,01 tot 0,1%. Fosfor wordt aangevoerd via veevoer en kunstmest. In Nederland wordt meer fosfaat aangevoerd dan afgevoerd. Er is dan ook sprake van een overschot aan fosfaat. Het overgrote deel van het overschot komt op landbouwgronden terecht. De fosfaatophoping in de bodem varieerde in de afgelopen decennia tussen de 80 en 40 miljoen kilo per jaar. Door uit- en afspoeling van fosfaten uit de bodem ontstaan negatieve effecten voor waterecosystemen, zoals een sterke groei van fytoplankton ("algenbloei”). Als gevolg hiervan verdwijnen waterplanten door lichtgebrek en sterven vissen door zuurstofgebrek. Blauwalgen halen zelfs regelmatig de media vanwege de giftige stoffen die zij afscheiden. Het terugdringen van het fosfaatoverschot is dan ook een van de hoofddoelen van het Nederlandse mestbeleid

Description of an Institutional Cohort of Myeloid Neoplasms Carrying ETV6-Locus Deletions or ETV6 Rearrangements.

The gene encoding for transcription factor ETV6 presents recurrent lesions in hematologic neoplasms, most notably the ETV6-RUNX1 rearrangement in childhood B-ALL. The role of ETV6 for normal hematopoiesis is unknown, but loss of its function probably participates in oncogenic procedures. In myeloid neoplasms, ETV6-locus (12p13) deletions are rare but recurrent; ETV6 translocations are even rarer, but those reported seem to have phenotype-defining consequences. We herein describe the genetic and hematologic profile of myeloid neoplasms with ETV6 deletions (10 cases), or translocations (4 cases) diagnosed in the last 10 years in our institution. We find complex caryotype to be the most prevalent cytogenetics among patients with 12p13 deletion (8/10 patients), with most frequent coexisting anomalies being monosomy 7 or deletion 7q32 (5/10), monosomy 5 or del5q14-15 (5/10), and deletion/inversion of chromosome 20 (5/10), and most frequent point mutation being TP53 mutation (6/10 patients). Mechanisms of synergy of these lesions are unknown. We describe the entire genetic profile and hematologic phenotype of cases with extremely rare ETV6 translocations, confirming the biphenotypic T/myeloid nature of acute leukemia associated to ETV6-NCOA2 rearrangement, the association of t (1;12) (p36; p13) and of the CHIC2-ETV6 fusion with MDS/AML, and the association of the ETV6-ACSL6 rearrangement with myeloproliferative neoplasm with eosinophilia. Mutation of the intact ETV6 allele was present in two cases and seems to be subclonal to the chromosomal lesions. Decoding the mechanisms of disease related to ETV6 haploinsufficiency or rearrangements is important for the understanding of pathogenesis of myeloid neoplasms and fundamental research must be guided by observational cues

Laboratory Genetic Testing in Clinical Practice 2016.

WOS: 000392526600001PubMed ID: 2813360

Evolution of Genetic Techniques: Past, Present, and Beyond.

Genetics is the study of heredity, which means the study of genes and factors related to all aspects of genes. The scientific history of genetics began with the works of Gregor Mendel in the mid-19th century. Prior to Mendel, genetics was primarily theoretical whilst, after Mendel, the science of genetics was broadened to include experimental genetics. Developments in all fields of genetics and genetic technology in the first half of the 20th century provided a basis for the later developments. In the second half of the 20th century, the molecular background of genetics has become more understandable. Rapid technological advancements, followed by the completion of Human Genome Project, have contributed a great deal to the knowledge of genetic factors and their impact on human life and diseases. Currently, more than 1800 disease genes have been identified, more than 2000 genetic tests have become available, and in conjunction with this at least 350 biotechnology-based products have been released onto the market. Novel technologies, particularly next generation sequencing, have dramatically accelerated the pace of biological research, while at the same time increasing expectations. In this paper, a brief summary of genetic history with short explanations of most popular genetic techniques is given

Laboratory genetic testing in clinical practice 2014.

WOS: 000352434200001PubMed ID: 2587902

Daratumumab and venetoclax in combination with chemotherapy provide sustained molecular remission in relapsed/refractory CD19, CD20, and CD22 negative acute B lymphoblastic leukemia with KMT2A-AFF1 transcript.

Relapsed/refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL) has a very poor prognosis with a median overall survival of four to nine months. Achieving a complete molecular response is most often required to obtain a sustained leukemia-free survival after allogeneic hematopoietic stem cell transplantation. Immunotherapies targeting CD19, CD20, or CD22 are very efficient in achieving this goal. However, in the absence of the expression of these immunotherapeutic targets by lymphoblasts, treatment options are extremely scarce. We report the successful treatment of a 26-year-old man who suffered R/R, CD19, CD20, and CD22 negative B-ALL targeting Bcl-2 and CD38 by combining venetoclax and daratumumab with chemotherapy

Differential expression analysis with global network adjustment

<p>Background: Large-scale chromosomal deletions or other non-specific perturbations of the transcriptome can alter the expression of hundreds or thousands of genes, and it is of biological interest to understand which genes are most profoundly affected. We present a method for predicting a gene’s expression as a function of other genes thereby accounting for the effect of transcriptional regulation that confounds the identification of genes differentially expressed relative to a regulatory network. The challenge in constructing such models is that the number of possible regulator transcripts within a global network is on the order of thousands, and the number of biological samples is typically on the order of 10. Nevertheless, there are large gene expression databases that can be used to construct networks that could be helpful in modeling transcriptional regulation in smaller experiments.</p> <p>Results: We demonstrate a type of penalized regression model that can be estimated from large gene expression databases, and then applied to smaller experiments. The ridge parameter is selected by minimizing the cross-validation error of the predictions in the independent out-sample. This tends to increase the model stability and leads to a much greater degree of parameter shrinkage, but the resulting biased estimation is mitigated by a second round of regression. Nevertheless, the proposed computationally efficient “over-shrinkage” method outperforms previously used LASSO-based techniques. In two independent datasets, we find that the median proportion of explained variability in expression is approximately 25%, and this results in a substantial increase in the signal-to-noise ratio allowing more powerful inferences on differential gene expression leading to biologically intuitive findings. We also show that a large proportion of gene dependencies are conditional on the biological state, which would be impossible with standard differential expression methods.</p> <p>Conclusions: By adjusting for the effects of the global network on individual genes, both the sensitivity and reliability of differential expression measures are greatly improved.</p&gt

t(15;21) translocations leading to the concurrent downregulation of RUNX1 and its transcription factor partner genes SIN3A and TCF12 in myeloid disorders.

Through a combined approach integrating RNA-Seq, SNP-array, FISH and PCR techniques, we identified two novel t(15;21) translocations leading to the inactivation of RUNX1 and its partners SIN3A and TCF12. One is a complex t(15;21)(q24;q22), with both breakpoints mapped at the nucleotide level, joining RUNX1 to SIN3A and UBL7-AS1 in a patient with myelodysplasia. The other is a recurrent t(15;21)(q21;q22), juxtaposing RUNX1 and TCF12, with an opposite transcriptional orientation, in three myeloid leukemia cases. Since our transcriptome analysis indicated a significant number of differentially expressed genes associated with both translocations, we speculate an important pathogenetic role for these alterations involving RUNX1