Evolution And Religion The Disconnection - 2016 Words

Evolution and Religion: The Disconnection For years, theologians and scientists have debacled as to which theories could be categorized as correct as opposed to incorrect theologies. On a larger scale, these individuals debate the question of the universe’s origin, as well as the origin of life itself. Some of the most contemplated questions theologians face are those that include thoughts regarding the creation of all living things. Whether or not all things that currently inhabit the world are derived from a single act that has yet to be defined, or if it perhaps the result of a combination of random, yet coinciding, events? The theory of Intelligent Design is perceived to be hold credible withstanding for approximately 50% of people†¦show more content†¦However, Young Earth believers also say that because of their beliefs, literal interpretation would lead people to believe that God is the Great Deceiver. Under this presumption, referring to God as the Great Deceiv er, it means that God has lied or tried to test â€Å"us† as individual believers of the faith, with fossils situated in different layers in the crust and areas around the globe. While some would explain these tests evolution, Young Earth creationist expel this idea and consider those who follow Darwin’s theory of evolution a failure to their faith in God’s creation. As an accepted scientific theory, evolution is the change in allele frequency in a population over time. It is in my opinion, irrefutable to argue the ideology of Young Earth creationism. It is a readily accepted scientific fact that alleles, genes, undergo minute mutations from generation to generation directly depending on what organisms of that species lived; survival of the fittest. Otherwise known as Natural Selection, Survival of fittest is the idea that only the organisms best adapted to the ecosystem may survive. This process, defined by Charles Darwin, is said to be a main constituent effec ting evolution. For example, if the ground and a mouse is white, it will most likely to be killed and or eaten based on the sole fact that it stands out against its darker counterparts. In continuation, if an animal of prey is slower than the rest of its pack,

Essay about Analysis of Wordsworth’s Surprised by Joy

Analysis of Wordsworth’s Surprised by Joy Death, like ink dropped in a glass of water, taints ones perception of life by coloring every experience with a sad shade of grief. In his poem, Surprised by Joy, William Wordsworth relates how a moment of joy caused him to remember the death of his four-year-old daughter, Catharine. The memory effectively crushed any positive feelings he had during his encounter with joy and replaced them with quilt and sadness. This sonnet, though Italian in rhyme scheme, abandons the typical conflict-to-resolution form of argument for one which begins with the desired end-result and progresses towards the heart of the problem. Throughout the sonnet, Wordsworth shifts from expressing raw emotions†¦show more content†¦However, his action is stopped short after the word transport with a caesuric dash and the exclamation, [o]h! with whom (2). The distressed Oh! and the accented whom give the end of the line just enough lift to suggest the question with whom? The answer, of course, is his daug hter whom he proceeds to address in line 3: [b]ut thee, deep buried in the silent tomb. Wordsworth expresses helpless disappointment in this statement because his daughter, the first person with whom he instinctively wants to share his joy, is dead. The enjambment of the lines rushes us to But thee where a caesura, combined with the repetition of the long, extended e sound in thee, deep buried, gives a sense of depth and finality to her death and effectively halts the energetic free-thought flow of the previous lines with its ominous tones. The unspoken b in tomb and swallowed t in silent contrast the power of the spondaic deep buried with a softer, sadder image of her grave state. Wordsworth adds that she is in [t]hat spot which no vicissitude can find (4). The word vicissitude, meaning a change in fortune for the worse, is an ironic description of her grave considering that death itself is one of the worst kinds of fortunes to befall a person. The fricative v sound followed by the hissing s sound in vicissitude give the word a sinister spin which implies, along with its misplaced polysyllabic elegance, his bitter and ironicShow MoreRelatedAmbiguity in Robert Frosts Works2796 Words   |  12 Pagesfeels doubtful whether or not he chose the best one. Frost travels into the human mind in this poem, portraying how his speaker is an unreliable narrator to compensate for his anxiety. For means of comparison, the speaker in William Wordsworth’s poem, â€Å"Surprised by Joy†, can safely be assumed to be Wordsworth himself because the loss of his daughter, seen in the poem, was an unfortunate reality for the poet. Frost’s â€Å"The Road Not Taken†, in addition to many of his other works, provides no such indicationRead MoreFrankenstein Study Guide14107 Words   |  57 Pagesengineering †¢ Approaches to Teaching Shelley’s Frankenstein, edited by Stephen C. Behrendt, 1990. Classroom-tested methods for teaching Shelley’s novel For the Student †¢ Mary Shelley’s Monster: The Story of Frankenstein by Martin Tropp, 1976. Engaging analysis of all facets of the novel including related literature and films (Photographs) Be sure to preview all media links to determine whether or not the material is appropriate for your class. Frankenstein Study Guide For the Teacher 3 Teaching

SNP/CGH Microarray Based Genomic Testing in Myelodysplastic Syndrome

Question: Describe about the SNP/CGH Microarray Based Genomic Testing in Myelodysplastic Syndrome. Answer: Introduction: Myelodysplastic syndrome (MDS) is a progressive disease characterised by ineffective haematopoiesis, peripheral blood cytopenias, abnormal cellular morphology and variable risk of progression to acute leukaemia. Myelodysplastic syndromes (MDS) are the clonal disorders of an immature hematopoietic progenitor cell. MDS hematopoiesis is categorised by irregular progenitor proliferation and impaired cellular differentiation and maturation. As a result, the bulk of MDS patients have a plodding evolution in the direction of progressive bone marrow failure and leukemic transformation. The hard work made by numerous research assemblies during past few years have assisted to unknot the complex that forms the fundamentals of the pathogenesis of MDS. In this review, we will focus on the major molecular abnormalities and cytogenetic involved in MDS beginning and disease development. Moreover, we will deliberate the impact of the marrow microenvironment on proliferation and survival of hematopoie tic progenitors in MDS. It is one of the commonest haematological disorders worldwide accounting for 1.3% of all cancers in New Zealand [31]. Approximately 86-87% cases of MDS in Australia and New Zealand were reported to be diagnosed in individuals of above 60 years of age [31]. The MDS pathogenesis is not understood very well but as being a neoplasm, it involves the accumulative acquisition of oncogenic driver mutations. MDS is generally considered a clonal process that is thought to develop from a single transformed hematopoietic progenitor cell [47]. The recent improvement in the detection of recurring chromosomal abnormalities and mutations has provided better understanding of the pathogenesis of MDS. The investigation gone through the Three decades into the pathophysiology of the myelodysplastic syndromes (MDS) have established the heterogenicity of MDS and emphasised the intricacy in disease biology. Recent improvements in technology have yielded stimulating observations. The aim and objective of this review is to assimilate laboratory and clinical findings into a functioning hypothesis for the advancement of idiopathic MDS, distinguish idiopathic MDS from SAA, and propose latest therapeutic strategies. Understanding of data from MDS studies still remains challenging. Without a dependable disease marker, here can be a questions about the exactness of an MDS analysis. Supplementary problems ascend the minute patients with incongruent biologies are made compared. Patients who are possessing MDS may have noticeable single or multiple clonal chromosomal variations at the time of analysis or gain them later through the course of the disease which may pave the way of transformation into acute myeloid leukaemia (AML). Simple chromosome changes may involve a numerical change which may be monosomy or trisomy, a structural abnormality like inversion and interstitial deletion that involve only one chromosome and very rarely a balanced translocation which involve two chromosomes. Complex karyotyping with multiple abnormalities approximately more three can also be detected in advanced cases [29]. A large MDS series of 1029 patients was studied by Pozdnyakova and his colleagues, found 44% of cases with MDS to have clonal cytogenetic abnormalities evident by standard metaphase karyotyping at diagnosis [33] [29]. Del(5q) was the most common and seen in 18% of cases followed by complex karyotype in 6% of cases. Trisomy 8 and Del(20q) were present in 4%, and 3%, respectively [29]. Trisomy 8 increases the risk of leukemic transformation which is predominant in male and causes oral ulceration. Loss of the Y chromosome is known to be one of the good prognostic markers in MDS, however, it is generally thought to be an age related phenomenon [46]. The analysis of MDS relies mainly on the detection of clonal genetic abnormalities in the appropriate clinical context as well as the identification of significant morphological dysplasia on peripheral blood film and/or bone marrow. There are certain cytogenetic abnormalities considered as a presumptive evidence of MDS even in the absence of morphological dysplasia. The presence of these specific cytogenetic abnormalities confirms the MDS diagnosis in cases with absent or very little morphologic dysplasia. Similarly, the diagnosis of AML can sometimes be established in the presence of certain cytogenetic abnormalities regardless of blast count. An amazing development in the understanding of the leukemogenesisis made conceivable by the methodological improvements in the cytogenetic field. The cytogenetic irregularities that have usually provided the molecular basis for the finding of the genes that are engaged into the mechanism of the leukemogenesis. Numerous study illustrates that t he cytogenetic turned out is one of the most significant prognostic factor and so it was integrated into the statistical model which aims for the improvement of the forecast the procedures of the individual prognosis. The identification of clonal chromosomal abnormalities is not only important in establishing the MDS diagnosis but also aids in the classification of MDS, prognostic stratification and treatment planning [33], [14]. The impact of cytogenetics is clearly demonstrated in its role in determining the International Prognostic Scoring System (IPSS). The conventional metaphase cytogenetics is the standard genetic test routinely performed in evaluating MDS cases in most laboratories. Sometime the traditional cytogenetic analysis and routine chromosome analysis is mentioned to as karyotyping. These kinds of studies are used to identify numerical and structural chromosome irregularities in metaphase cells. Routine chromosome analyses involves sterile viable tissue samples. The removal of the long arm of the chromosome 5, del (5q) is the most frequently occurring chromosomal abnormalities found in the patient diagnosed with MDS. The lenalidomide developed as the effective targeted therapy for the little and intermediate risk of MDS with a del 5(q) has increased the importance of karyotyping in disease management. This test has a number of limitations including the low resolution and the need for high quality metaphases and cell division within the abnormal cells. In view of those limitations, new methodology with much higher resoluti on such as Single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) microarray analysis were incorporated in the evaluation of MDS cases. Genomic Micro-Array Studies: The main principle present behind the microarrays is the hybridization between two strands of DNA , the property by which complementary sequences of the nucleic acid exactly pairs with complementary nucleotide bases by forming hydrogen bonds among each other. A large number of complementary base pairs in a nucleotide sequence means more tight non-covalent bonding among the two strands. Subsequently washing off non-specific bonding sequences, only toughly paired strands will remain hybridized. Fluorescently labeled target sequences which bind to a probe sequence will help to produce a signal which is dependent on the hybridization circumstances (such as temperature), and perform washing after the hybridization. The total strong point of the signal, from a spot (feature), rest on the quantity of target sample binded to the probes that are present on the spot. The Microarrays uses comparative quantitation in which the intensity of a feature is compared to the intensity of the same featu re under several different condition, and the distinctiveness of the feature is recognised by its situation. Both SNP and CGH array are basically high resolution DNA microarray tools that can detect genomic gains or deletions associated with copy number changes down to a level of 5 KB of DNA [28], [30]. SNP arrays however have the additional advantage of its ability to detect copy-neutral loss of heterozygosity (LOH) or uniparental disomy (UPD). The basic components of SNP and CGH arrays include: DNA hybridization of immobilized allele -specific oligonucleotide (ASO) probes with target DNA sequences labelled with florescent dyes [7]. ASO probes are generally designed and selected from a representative pool of healthy individuals [7]. The use of fluorescence microscopy and a solid surface DNA capture system that picks up and interprets hybridization signals [35] [7]. The differences in the fluorescence intensities reflects copy numbers changes in DNA sequences. This indicates the presence of either loss or a gain mutation. Despite of the high resolution of SNP/CGH microarray analysis, it has important limitations. Those limitations are: Inability to detect genomic abnormalities that do not result in copy number changes such as balanced translocations. Inability to detect genomic abnormalities in the settings of small clone sizes. Microarray analysis in MDS: Mohamedali study showed that the use of SNP microarray analysis in MDS cases resulted in a much higher detection rate of genomic abnormalities up to 75% compared to 50% using conventional metaphase cytogenetics alone. Some of these detected cryptic genomic lesions were shown to have prognostic implications [22]. Essentially similar results were demonstrated in Tius study of 430 patients with MDS disorders. It concluded that combining both the metaphase cytogenetics and SNP array together led to a higher diagnostic yield of chromosomal defects (74% vs 44%, P .0001), compared metaphase cytogenetics alone [40, 41 42]. It also demonstrated that some of the newly detected SNP array defects contributed to poorer prognosis. Some of these new SNP array detected chromosomal lesions were independent predictors of overall and event-free survival [41]. Both Heinrichs and Volkert studies evaluated the use of SNP/CGH microarray on MDS cases with normal metaphase cytogenetics [16, 43]. In both studies the SNP/CGH microarray detected cryptic genomic lesions in 11-15% of cases respectively [16, 43]. Heinrichs study showed that most of these genetic lesions resulted from segmental uniparental disomies (UPD). The study also showed that UPD affecting chromosome 7q are associated with a progressive course and worse outcome regardless of their low-risk International Prognostic Scoring System score [16]. In Volkert study, the majority of CGH array identified genetic lesions were sub-microscopic copy number changes (4% gains and 7% losses) [43]. Compared to sub-microscopic gains, more than half of the sub-microscopic deletions were recurrent and involved the genes TET2, DNMT3A, ETV6, NF1, RUNX1 and STAG2 [43]. The presence of sub-microscopic deletions was associated with lower overall survival rates compared to those without deletions [43]. SNP/ CGH microarray analysis with its superb resolution in detecting genomic abnormalities resulting from copy number changes, is expected to be particularly useful in MDS. This is supported by two factors; firstly, the fact that the vast majority of cytogenetic abnormalities in MDS are characterised by copy number changes and secondly, because balanced translocations are not common in MDS. Overall SNP/CGH microarray analysis appears to be a good complementary method to conventional metaphase cytogenetics analysis in MDS cases, with its own unique prognostic information The use of SNP/CGH microarray analysis in MDS related disorders has been evaluated in this study by comparing its results with standard metaphase cytogenetics. AIM: The overall objective of this study is to demonstrate the ability of SNP/CGH microarray in 1- Improving the diagnostic yield of suspected MDS cases by detecting clonal genetic lesions in cases with either normal or non-informative conventional metaphase cytogenetics. 2- Providing higher resolution genetic testing capable of accurately guiding both prognostic stratification scoring system and therapy. 3- Providing early detection of micro genetic abnormalities that can potentially be associated with a progressive course and hence prioritising early bone marrow transplant therapy in transplant eligible patients. 4- Effectively replacing or complementing the conventional metaphase cytogenetic testing in our local practice in evaluating MDS cases. Methodology: We hypothesized that the combination of standard metaphase cytogenetics and SNP/CGH microarray could potentially enhance both the diagnosis and prognostic stratification of MDS related disorders. We also evaluated the possibility that MDS cases with either normal or non-informative metaphase cytogenetics could potentially harbour cryptic chromosomal lesions with possible prognostic implications that can only be detected by SNP/CGH microarray analysis. A total of 28 cases (14 women and 14 men) with a mean age of 68.4 years (range 2287 years) were included in the study. Out of those 28 cases, A total 17/28 cases including 15 cases with normal metaphase cytogenetics and 2 cases with failed metaphase cytogenetics were randomly selected for the study (Table 1a). A total of 11/28 cases with previously detected genetic abnormalities by metaphase cytogenetics were preselected for the study. Those 11 cases have wide range of chromosomal abnormalities ranging from simple numerical changes (ie, monosomy or trisomy), structural chromosomal abnormalities such as interstitial deletion, translocation involving two chromosomes and complex karyotypes with multiple abnormalities. The 28 cases included in the study are 18 cases of confirmed MDS, five suspected cases of MDS with borderline morphologic dysplasia, three cases of AML with myelodysplasia related changes, one case of Chronic myelomonocytic leukaemia (CMML) and one case of Myelodysplastic syndrome / Myeloproliferative neoplasm overlap unclassifiable (MDS/MPN u) (Table 1b). According to the bone marrow morphological assessment and the WHO classification, the cohort comprised of the following MDS subtypes: refractory cytopenia with multilineage dysplasia (RCMD, n=7), refractory cytopenia with multilineage dysplasia with ring sideroblasts (RCMD-RS, n=3), refractory anaemia with ring sideroblasts (RARS, n=4), refractory anaemia (RA, n=1), refractory anaemia with excess blasts ( RAEB-1, n=1; RAEB-2:n=1). All cases had their bone marrow samples submitted to our regional laboratory within the period from March 2014 to April 2016 for evaluation of cytopenias and/or clinical suspicion of MDS related disorders. The cytomorphological examination and assessment was performed in Auckland regional laboratory and MDS diagnosis reported according the world health organisation (WHO) Classification criteria 2008. Samples were also referred to IGENZ laboratory for further cytogenetic testing. These laboratories are IANZ accredited. Metaphase cytogenetic analysis was carried out on marrow samples according to standard methods. Chromosome preparations were G-banded using trypsin and Giemsa (GTG) and karyotypes were reported according to the International System for Human Cytogenetic Nomenclature (ISCN). SNP/CGH microarray analysis was performed using an Agilent 8 x 60K SUREPRINT G3 custom CGH/SNP array platform according to the manufacturer instructions and with a practical resolution of ~180kb. Data was analysed using Agilent Cytogenomic Software v3.0 using human genomic build 19. The sample was hybridised against a commercially produced reference DNA obtained from Agilent. The research project has been registered and approved by the local Middlemore hospital research office and adhered to the national HDEC guidelines where formal ethics approval was deemed not required. The study cohort was subdivided in to two main groups (Group A Group B) and one small group (Group C). Group A included the randomly selected 15 cases with normal karyotype by conventional metaphase cytogenetics analysis. Group B included the preselected eleven cases with wide range of chromosomal abnormalities detected by metaphase cytogenetics. Group C however is comprised of two cases with failed conventional metaphase cytogenetics. The detection rate of genomic abnormalities was compared between metaphase cytogenetics analysis and SNP/CGH microarray analysis across the three groups. Further analysis including IPSS scores, survival data and disease outcome was performed on the 18 cases with confirmed MDS diagnosis. The standard metaphase cytogenetics based IPSS scores were compared to the SNP/CGH microarray based IPSS scores. (Table 2). Table 1a. Result showing the Standard metaphase cytogenetic and SNP/CGH microarray analysis of 28 patients Case # AGE Gender Diagnosis Metaphase cytogenetics SNP/CGH microarray 1 70 Male AML-with-MDS-related-changes Normal Normal 2 73 Male AML-with-MDS-related-changes Normal Normal 3 78 Female RARS Normal Normal 4 80 Female RCMD -20 dic (17;20) 5 72 Male RAEB-2 -7 -7 6 52 Female MDS/MPN-unclassifiable Complex Complex 7 76 Male RCMD-RS Del(20q)+t(4;7) Del(20q) 8 78 Female RCMD Del(20q) Del(20q) 9 82 Male Possible MDS -y -y 10 58 Female RCMD+RS Normal Normal 11 67 Female Possible MDS Normal Normal 12 83 Female RCMD Normal Normal 13 87 Female RCMD and Myeloma Normal Del(20q) 14 73 Female RARS Normal Normal 15 22 Male RCMD Normal Normal 16 53 Female Hypoplastic MDS and Myeloma Normal Del(13q) 17 71 Male Possible MDS +20 Normal 18 72 Male AML-with-MDS-related-changes Complex Complex 19 72 Male RARS karyotype-failed -y 20 34 Female Possible MDS karyotype-failed Normal 21 74 Male RAEB-1 Complex Complex+additional 22 77 Male RARS Normal Complex 23 78 Female RCMD Del(20q) Del(20q) 24 56 Female RA Normal Normal 25 79 Male Possible MDS Normal Del(5q13.2) 26 75 Male CMML2 Normal Del(17q11.2) 27 65 Male RCMD+RS Normal Normal 28 57 Female RCMD Del(7q) Complex (including Del(7q) RCMD = refractory cytopenia with multilineage dysplasia, RCMD-RS = refractory cytopenia with multilineage dysplasia with ring sideroblasts. RARS = refractory anaemia with ring sideroblasts, RA = refractory anaemia, RAEB-1 or 2 = refractory anaemia with excess blasts 1 or 2. Results: The SNP/CGH microarray analysis results were compared with metaphase cytogenetics in the three groups. Table1a(i). Results which are considered in Group A Case # AGE Gender Diagnosis Metaphase cytogenetics SNP/CGH microarray 1 70 Male AML-with-MDS-related-changes Normal Normal 2 73 Male AML-with-MDS-related-changes Normal Normal 3 78 Female RARS Normal Normal 10 58 Female RCMD+RS Normal Normal 11 67 Female Possible MDS Normal Normal 12 83 Female RCMD Normal Normal 13 87 Female RCMD and Myeloma Normal Del(20q) 14 73 Female RARS Normal Normal 15 22 Male RCMD Normal Normal 16 53 Female Hypoplastic MDS and Myeloma Normal Del(13q) 22 77 Male RARS Normal Complex 24 56 Female RA Normal Normal 25 79 Male Possible MDS Normal Del(5q13.2) 26 75 Male CMML2 Normal Del(17q11.2) 27 65 Male RCMD+RS Normal Normal In group A there are 15 cases with normal metaphase cytogenetics but SNP/CGH microarray analysis was able to detect a wide spectrum of cryptic genomic abnormalities in 5 cases out of 15 cases that I one third of cases. Among those five cases, there is only one case with a very little morphological dysplasia and the rest of the four cases had a confirmed MDS diagnosis with significant morphological dysplasia. Those five cases with only positive SNP/CGH microarray findings are: 1) CMML case where SNP/CGH microarray analysis detected a 521 kb loss in the long arm of chromosome 17 [Del(17q11.2)]. 2) A case of suspected MDS with borderline dysplasia. The SNP/CGH microarray detected Del(5q13.2) characterised by a 2.2 Mb deletion in the long arm of chromosome 5. 3) A case of confirmed MDS diagnosis WHO subtype RARS, the SNP/CGH microarray detected complex cytogenetics abnormalities (5p+, 19q+, 21q+) in the form of three small chromosomal gains in 5p13.3-p15.1, 19q13.2-q13.3 and 21q21.1-q21.2. 4) A case of Hypoplastic MDS and myeloma, the SNP/CGH microarray detected Del(13q) characterised by 30Mb deletion in the long arm of chromosome 13 at band q21.31 - q31.3. 5) A case with established MDS and RCMD WHO subtype, the SNP/CGH array identified the presence of Del(20q). Table1a(ii). Results which are considered in Group B Case # AGE Gender Diagnosis Metaphase cytogenetics SNP/CGH microarray 4 80 Female RCMD -20 dic (17;20) 5 72 Male RAEB-2 -7 -7 6 52 Female MDS/MPN-unclassifiable Complex Complex 7 76 Male RCMD-RS Del(20q)+t(4;7) Del(20q) 8 78 Female RCMD Del(20q) Del(20q) 9 82 Male Possible MDS -y -y 17 71 Male Possible MDS +20 Normal 18 72 Male AML-with-MDS-related-changes Complex Complex 21 74 Male RAEB-1 Complex Complex+additional 23 78 Female RCMD Del(20q) Del(20q) 28 57 Female RCMD Del(7q) Complex (including Del(7q) In group B there were 11 cases with already established chromosomal abnormalities by metaphase cytogenetics. However, the SNP/CGH microarray showed a wide spectrum of findings that correlated quite well with most of the already established metaphase cytogenetics results. However, the microarray managed to reveal additional significant cryptic genomic abnormalities in three out of the eleven cases (27.2%) that were not apparent by metaphase cytogenetics. Some of those additional SNP/CGH array abnormalities have shown significant prognostic implication. On the other hand, metaphase cytogenetics were superior to SNP/CGH microarray in two out of the eleven cases (18.2%), where the SNP/CGH microarray failed to detect some of the already established chromosomal abnormalities by metaphase cytogenetics. The three cases where the SNP/CGH microarray detected additional genetic abnormalities are: 80-year-old female with confirmed diagnosis of MDS WHO subtype refractory cytopenia with multiline age dysplasia (RCMD) and presented with moderate anaemia and thrombocytopenia. Conventional metaphase cytogenetics identified -20 as a sole cytogenetic abnormality. The SNP/CGH microarray analysis however revealed a serious cryptic genomic abnormality, dic(17;20) with both 17p and 20q deletions. 74-year-old male with a confirmed diagnosis of MDS WHO subtype refractory anaemia with excess blast -1 (RAEB-1). Metaphase cytogenetics analysis established a complex karyotype (+19, Del(20q), +21). The SNP/CGH microarray however confirmed the complex abnormalities with an additional abnormality of +8. A 57-year-old female with established diagnosis of MDS, WHO subtype RCMD. She presented with moderate anaemia and neutropenia. Metaphase cytogenetics analysis revealed Del (7q) only. The SNP/CGH microarray analysis however confirmed the presence of Del(7q) and showed two additional cryptic genomic lesions; Del(7p) and gain of 21. This confirmed the presence of complex cytogenetics. The two cases with higher detection of chromosomal lesions by metaphase cytogenetics than SNP/CGH microarray analysis are: 71-year-old male with suspected diagnosis of MDS and borderline dysplasia. Initial conventional metaphase cytogenetic revealed the presence of trisomy 20. The SNP/CGH microarray analysis failed to detect the trisomy 20. 76-Year-old male with confirmed diagnosis of MDS WHO subtype refractory cytopenia with multilineage dysplasia and ring sideroblast (RCMD+RS). Conventional metaphase cytogenetics identified the presence of two clonal abnormalities; t(4;7) and Del(20q). The SNP+CGH microarray analysis was able to accurately detect the presence of Del(20q) but failed to identify the presence of t(4;7). Table1a(iii). Results which are considered in Group C Case # AGE Gender Diagnosis Metaphase cytogenetics SNP/CGH microarray 19 72 Male RARS karyotype-failed -y 20 34 Female Possible MDS karyotype-failed Normal The group C consist of two cases with failed metaphase cytogenetics analysis and the SNP/CGH microarray detected Y chromosome in the first case of 72-year-old male with established morphologic diagnosis of MDS and RARS subtype. The second case is a suspected MDS case and the SNP/CGH microarray did not reveal any genomic abnormality. Table 1b. Frequency and Percentage of diseases Frequency Percent AML-with-MDS-related-changes 3 10.7 CMML2 1 3.6 Hypoplastic MDS 1 3.6 MDS/MPN-unclassifiable 1 3.6 Possible MDS 5 17.9 RA 1 3.6 RAEB-1 1 3.6 RAEB-2 1 3.6 RARS 4 14.3 RCMD 7 25.0 RCMD+RS 3 10.7 Total 28 100.0 AML= acute myeloid leukaemia, CMML2 = chronic myelomonocytic leukaemia2, MDS, MDS = myelodysplastic syndrome, RCMD = refractory cytopenia with multilineage dysplasia, RCMD-RS = refractory cytopenia with multilineage dysplasia with ring sideroblasts. RARS = refractory anaemia with ring sideroblasts, RA = refractory anaemia, RAEB-1 or 2 = refractory anaemia with excess blasts 1 or 2. Table 2. Result showing IPSS score analysis of 18 cases Diagnosis (MDS subtype) Metaphase cytogenetics Microarray Metaphase cytogenetics based IPSS score Microarray based IPSS score Patient outcome. Survival in months Time to transformation to AML. RARS Normal Normal 0.0 (Low) 0.0 (Low) Alive 23M No transformation RCMD -20 Dic(17;20) 0.5 (INT-1) 0.5 (INT-1) Dead 14M 11 M RAEB-2 -7 -7 2.5 (High) 2.5 (High) Dead 28M 2M RCMD+rs Del(20q), t(4;7) Del(20q) 0.5 (INT-1) 0.0 (Low) Alive 29M No transformation RCMD Del(20q) Del(20q) 0.0 (Low) 0.0 (low) Alive 20M No Transformation RCMD+rs Normal Normal 0.0 (Low) 0.0 (Low) Alive 5M No Transformation RCMD Normal Normal 0.0 (Low) 0.0 (Low) Alive 22M No Transformation RCMD Normal Del(20q) 0.0 (Low) 0.0 (Low) Alive 34M No Transformation RARS Normal Normal 0.0 (Low) 0.0 (Low) Alive 15M No Transformation RCMD Normal Normal 0.0 (Low) 0.0 (Low) Alive 24M No Transformation Hypoplastic MDS Normal Del(13q) 0.0 (Low) 0.0 (Low) Alive 24M No Transformation RARS Failed -Y - 0.0 (Low) Alive 9M No Transformation RAEB-1 Complex Complex + Additional 1.5 (INT-2) 1.5 (INT-2) Alive 31M No Transformation RARS Normal Complex (undetermined clinical significance) 0.0 (Low) 0.0 (Low) Alive 29M No Transformation RCMD Del(20q) Del(20q) 0.0 (Low) 0.0 (Low) Alive 20M No Transformation RA Normal Normal 0.0 (Low) 0.0 (Low) Alive 276M No Transformation RCMD+rs Normal Normal 0.0 (Low) 0.0 (Low) Alive 3M No Transformation RCMD Del(7q) Complex 1.5 (INT-2) 1.5 (INT-2) Alive 2M No Transformation. AML= acute myeloid leukaemia, MDS = myelodysplastic syndrome, RCMD = refractory cytopenia with multilineage dysplasia, RCMD-RS = refractory cytopenia with multilineage dysplasia with ring sideroblasts. RARS = refractory anaemia with ring sideroblasts, RA = refractory anaemia, RAEB-1 or 2 = refractory anaemia with excess blasts 1 or 2. M= month, IPSS= international prognostic scoring system, INT-1 or 2 Intermediate 1 or 2. The IPSS score analysis on the 18 cases with confirmed MDS cases diagnosis showed that the microarray based IPSS scores correlated quite well with conventional metaphase cytogenetics based IPSS scores. In a total of 7/18 cases, the SNP/CGH microarray detected more genomic abnormalities than metaphase cytogenetics. In all of these 7/18 cases with newly microarray detected additional genomic abnormalities, there has been no change in the IPSS score following the microarray compared to the conventional metaphase cytogenetics based IPSS score. On the other hand the metaphase cytogenetics was superior to microarray in one case with confirmed MDS diagnosis (1/18), where the Array failed to identify the balanced translocation t(4;7). This resulted in the case being inappropriately categorised into a lower risk category with the microarray based IPSS score of 0.0, compared to standard metaphase cytogenetics based IPSS score of 0.5 consistent with Intermediate-1 risk category. The 18 cases with confirmed MDS diagnosis have a median survival 22.5 months from time of diagnosis (range 2-276 months). Two cases progressed into AML and died, while the rest of the 16 cases are still alive with no transformation to AML . Discussion: The application of SNP/CGH microarray analysis has the potential to greatly enhance the diagnostic and prognostic stratification processes for MDS cases especially when conventional metaphase cytogenetics is not informative. In group A 15 cases were found with normal metaphase cytogenetics, the SNP/CGH microarray analysis was able to detect cryptic chromosomal lesions in 5 cases put of 15 that means 33.3% of cases were having normal standard metaphase cytogenetics. This can be attributed to the higher resolution of SNP/CGH microarray analysis and the ability to reliably detect sub-microscopic chromosomal lesions. Relatively similar results have been demonstrated in other studies such as in Volkert study where the microarray identified copy number changes in 11% of total 520 MDS cases with confirmed normal karyotyping by metaphase cytogenetics [43]. Similarly, Mohamedali showed SNP array detected 10% cytogenetically cryptic deletions and 8% gains in low-risk MDS cases [22]. Our result of 33.3% is slightly higher than those studies, this can be attributed to sample size differences and also to patient selection. Those microarray identified chromosomal abnormalities are; Del(20q), Del(5q13.2), Del(17q11.2), complex (5p+, 19q+, 21q+) and Del(13q). Some of them helped determining the exact underlying gene mutation as Del(17q11.2) in the CMML-2 case where a 521 kb loss was identified in the long arm of chromosome 17. This abnormality had been previously described by Kolquist and thought to be encompassing NF1 tumour suppressor gene which has a possible role as a negative regulator of the RAS pathway [18]. This gene has also been shown to have some prognostic implications as per Franks study showing relatively increased incidence of NF1 mutation as the MDS disease progresses to acute leukaemia [34]. This was particularly relevant in our case as the patient had a relatively high risk CMML-2 with high blast count. The detection of Del(5q13.2) in a suspected case of MDS with borderline dysplasia also supports the hypothesis of enhanced diagnostic yield of SNP/CGH microarray analysis in suspected MDS cases with normal metaphase cytogenetics. This chromosomal lesion is different from the common 5q- and has been reported to be related to the gene RAD17 which have been previously identified in MDS by Starczynowski and others [36]. This clonal abnormality however will support the diagnosis of either MDS or clonal cytopenia of undetermined significance in the right clinical context. The detection of Del(20q) by the microarray in the case with established MDS diagnosis, will help in supporting the MDS diagnosis, given that it is very well known to be MDS related. The new identified microarray complex cytogenetics abnormalities; (5p+, 19q+, 21q+) and Del(13q) are not known to be specifically MDS related lesion. However, they may well indicate clonality and further support the MDS diagnosis in the right clinical context. Overall, it is worth highlighting the diagnostic yield of the SNP/CGH microarray as it helped in supporting the diagnosis of either MDS or Clonal Cytopenia of Undetermined Significance (CCUS) in 5/15 cases (33.3%) by detecting either known MDS cytogenetic abnormalities or clonal lesions. In group C (the two cases with failed metaphase cytogenetics analysis), SNP/CGH microarray however was normal in the case with inconclusive MDS diagnosis and only detected Y in the other established case of MDS. Given that Y may not be considered as a clonal abnormality in the elderly the utility of SNP/CGH array has not been accurately analysed in this context. A study by Arenillas showed that SNP array was able to detect cytogenetic abnormalities in 50% patients with failed metaphase cytogenetics. It also demonstrated some prognostic implications related to copy number alterations detected by the array [2]. In the Group B results it was found that 11 cases with already established chromosomal abnormalities by metaphase cytogenetics. The SNP/CGH microarray analysis showed good correlation characterised by the detection of majority of chromosomal abnormalities identified by standard metaphase cytogenetics. It also managed to reveal additional cryptic genomic lesion in 3 cases out of 11 cases which is 27.2% of the total cases. Some of those novel SNP/CGH array additionally identified genomic lesions s were noted to have major prognostic implications. This has been demonstrated clearly in the case of the 80-year-old lady with an established diagnosis of MDS RCMD subtype. Her conventional metaphase cytogenetics identified monosomy 20 as a sole cytogenetic abnormality and as a result of that her case had been categorised into the intermediate-1 risk category according to standard IPSS scoring system. Subsequent the SNP/CGH microarray analysis however revealed a seriously hidden cryptic genomic abnormality characterised by unbalanced dicentric (17;20), resulting in loss of 17p (including TP53) and 20q. Although dic(17;20) is a rare abnormality it has been reported in MDS cases by Tirado and Campbell and has been shown to be associated with disease progression and worse outcome [39]. Moreover, the SNP/CGH microarray in this case has also suggested the presence of TP53 mutation which is one of the known mutations associated with MDS and AML. The presence of this mutation has been shown to be of great clinical significance and associated with poor survival even after bone marrow transplant [4,5,6 11]. Some studies also showed that TP53 mutations have a major and unique prognostic value independent of the current IPSS score system for patients with MDS. [4,6 17]. This was consistent with our patients progressive course with early transformation to acute leukaemia in 11 months time. The Array results however did not lead to change in the IPSS score for this patient. This will support the hypothesis that large-scale genetic and molecular profiling is needed for further sub-classification and prognostic stratification in MDS patients [15]. The other two cases with the SNP/CGH microarray showing additional clonal chromosomal lesions, have already confirmed MDS diagnosis at the high risk category based on the metaphase cytogenetics based IPSS score. The additional clonal abnormalities identified by the SNP/CGH microarray however in those cases did not indicate significant change in the disease outcome or prognostic risk stratification. The combined SNP+CGH microarray analysis however did not identify a couple of chromosomal lesions previously detected by metaphase cytogenetics analysis in 2/11 (18%) of cases with abnormal karyotype. In one case due to low level of the abnormal clone of 10%, the SNP/CGH microarray was unable to detect the presence of trisomy 20. This is one of the known limitation of SNP/CGH microarray analysis in detecting low clone size less than 30%. Given that microarray was reported as normal in this particular case, this could potentially lead to a reduction on its diagnostic yield. The array result in this case did not result in change in the IPSS score, given that trisomy 20 is one of the low risk clonal genetic abnormality. In the second case the SNP/CGH microarray analysis failed to detect the presence of a likely balanced translocation t(4;7), however it managed to detect the presence of Del(20q). This can be explained by the known limitation of the SNP/CGH microarray analysis in detectin g balanced translocations. This could potentially lead to inappropriately stratifying the patient into a lower risk group, if karyotyping has not been performed. The IPSS score analysis on the 18 cases with confirmed MDS cases showed that the Array based IPSS scores correlated quite well with the conventional karyotyping based IPSS score (Table 3). There has been no significant change in IPSS score following the SNP/CGH microarray in the 7/18 cases with higher detection of genomic abnormalities by the SNP/CGH microarray compared to conventional metaphase cytogenetics. This could possibly be explained by three factors: 1) The fact that some of these SNP/CGH microarray detected genomic lesions were of not known to be MDS related such as Del(13q) and (5p+, 19q+, 21q+). As a result of that those newly detected genomic lesions are not included in the standard IPSS score assessment. 2) Despite of the SNP/CGH microarray ability to detect certain poor prognostic genetic mutations, most of these mutations act as an independent risk factor regardless of the IPSS score. 3) Those Array identified good prognostic chromosomal abnormalities (e.g. Del(20q) and -Y) were mostly detected in the low risk group with already established low standard metaphase cytogenetics based IPSS score. On the other hand, the SNP/CGH microarray identified poor prognostic genomic abnormalities were also mostly detected in high risk group with already high IPSS score based on conventional metaphase cytogenetics. This has resulted in the IPSS score to essentially remain unchanged following the SNP/CGH microarray analysis results. Overall in this small study the conventional metaphase cytogenetic appears to be slightly better than the microarray analysis in guiding the IPSS scoring system. This was particularly demonstrated in the case with the balanced translocation t(4;7) missed by the SNP/CGH microarray. There is no enough follow up period to reliably assess the presence of survival differences among the group with new or additional microarray identified genomic abnormalities. However, only one case with unique cryptic genomic abnormalities detected only by the array demonstrated progressive course with early transformation to AML and death. This case showed that certain genomic abnormalities (Del(17p) /TP53 gene mutation) have extremely poor prognosis independent of the IPSS score. This is consistent with other studies by Bejar and Horiike [4,5, 6 17]. Conclusion: This pilot study has demonstrated that the combination of SNP/CGH microarray and conventional G banding analysis enhances the diagnostic yield and provides additional prognostic information in the assessment of MDS cases. The SNP/CGH microarray analysis was able to detect some cryptic genomic lesions which are of utmost clinical and prognostic significance. It was also able to identify the presence of some of the common genetic mutations with some of these lesions acting as an independent risk factor regardless of the IPSS /IPSS-R scoring system. This will open the door for the creation of a new risk stratification system that includes all these relevant clonal genomic abnormalities. The SNP/CGH microarray analysis is relatively more expensive and costs $750 NZD pert test compared to $560 NZD for conventional metaphase cytogenetics. While our data showed that microarray analysis has a higher detection rate of genomic abnormalities with relatively good correlation with metaphase cytogenetics, however in view of its inherent limitation to detect small clone size and balanced translocation, it is recommended to be used in combination with standard metaphase karyotyping. We conclude that SNP/CGH microarray is relevant option that can be easily performed in routine diagnostics in MDS in combination with standard G banding analysis. However given the significant cost implications associated with that, this option could be of particular relevance in certain cases such as: Diagnostically uncertain cases with normal standard metaphase cytogenetics. Transplant eligible patients where it is important to confirm the diagnosis and accurately determine the disease prognosis in order to make appropriate recommendations about the merits of a proceeding to stem cell transplant. Research situations. Further prospective studies with a larger sample size and adequate follow up period would be recommended to reliably assess both the diagnostic and prognostic utilities of SNP/CGH microarray analysis in MDS related disorders. Acknowledgement: Irene Zeng, Biostatistician at Middlemore hospital Daniel Ng, IGENZ laboratory. Dr Amanda Dixon-McIver, IGENZ laboratory Dr Ross Henderson, North Shore Hospital. Bibliography Afable, M.G., Wlodarski, M., Makishima, H., Shaik, M., Sekeres, M.A., Tiu, R.V., Kalaycio, M., OKeefe, C.L. and Maciejewski, J.P. (2011) SNP array-based karyotyping: Differences and similarities between aplastic anemia and hypocellular myelodysplastic syndromes, Blood, 117(25), pp. 68766884. doi: 10.1182/blood-2010-11-314393. Arenillas, L., Mallo, M., Ramos, F., Guinta, K., Barragn, E., Lumbreras, E., Larryoz, M.-J., De Paz, R., Tormo, M., Abigar, M., Pedro, C., Cervera, J., Such, E., Jos Calasanz, M., Dez-Campelo, M., Sanz, G.F., Hernndez, J.M., Luo, E., Saumell, S., Maciejewski, J., Florensa, L. and Sol, F. (2013) Single nucleotide polymorphism array karyotyping: A diagnostic and prognostic tool in myelodysplastic syndromes with unsuccessful conventional cytogenetic testing, Genes, Chromosomes and Cancer, 52(12), pp. 11671177. doi: 10.1002/gcc.22112. Bacher, U., Weissmann, S., Kohlmann, A., Schindela, S., Alpermann, T., Schnittger, S., Kern, W., Haferlach, T. and Haferlach, C. (2011) TET2 deletions are a recurrent but rare phenomenon in myeloid malignancies and are frequently accompanied by TET2 mutations on the remaining allele, British Journal of Haematology, 156(1), pp. 6775. doi: 10.1111/j.1365-2141.2011.08911.x. Bejar, R., Papaemmanuil, E., Haferlach, T., Garcia-Manero, G., Maciejewski, J.P., Sekeres, M.A., Walter, M.J., Graubert, T.A., Cazzola, M., Malcovati, L., Campbell, P.J., Ogawa, S., Boultwood, J., Bowen, D., Tauro, S., Groves, M.J., Fontenay, M., Shih, L.-Y., Tchler, H., Stevenson, K.E., Neuberg, D., Greenberg, P.L., Ebert, B.L., Center, U.M.C., Jolla, L., Institute, W.T.S., Hinxton, Kingdom, U., Laboratory, M.M.L., Clinic, C., Louis, S., Hospital, M.G., Medical, H., Unit, L.M.H., Hospital, J.R., Hospitals, L.T., Hospital, N., De Paris, A.P.-H., Hospital, C.G.M., Institute, L.-B., Research, L., Institute, D.F.C. and Hospital, W. (2014) TP53 mutation status divides MDS patients with complex Karyotypes into distinct Prognostic risk groups: Analysis of combined Datasets from the international working group for MDS-Molecular prognosis committee, Oral Abstracts, 124(21), p. 532. Bejar, R., Stevenson, K., Abdel-Wahab, O., Galili, N., Nilsson, B., Garcia-Manero, G., Kantarjian, H., Raza, A., Levine, R.L., Neuberg, D. and Ebert, B.L. (2011) Clinical effect of point mutations in Myelodysplastic Syndromes, New England Journal of Medicine, 364(26), pp. 24962506. doi: 10.1056/nejmoa1013343. Bejar, R., Stevenson, K.E., Caughey, B., Lindsley, R.C., Mar, B.G., Stojanov, P., Getz, G., Steensma, D.P., Ritz, J., Soiffer, R., Antin, J.H., Alyea, E., Armand, P., Ho, V., Koreth, J., Neuberg, D., Cutler, C.S. and Ebert, B.L. (2014) Somatic mutations predict poor outcome in patients with Myelodysplastic syndrome after Hematopoietic stem-cell transplantation, Journal of Clinical Oncology, 32(25), pp. 26912698. doi: 10.1200/jco.2013.52.3381. Bejjani, B.A. and Shaffer, L.G. (2006) Application of array-based comparative Genomic Hybridization to clinical diagnostics, The Journal of Molecular Diagnostics, 8(5), pp. 528533. doi: 10.2353/jmoldx.2006.060029. Cargo, C.A., Rowbotham, N., Evans, P.A., Barrans, S.L., Bowen, D.T., Crouch, S. and Jack, A.S. (2015) Targeted sequencing identifies patients with preclinical MDS at high risk of disease progression, Blood, 126(21), pp. 23622365. doi: 10.1182/blood-2015-08-663237. Chen, C.-Y., Lin, L.-I., Tang, J.-L., Ko, B.-S., Tsay, W., Chou, W.-C., Yao, M., Wu, S.-J., Tseng, M.-H. and Tien, H.-F. (2007) RUNX1 gene mutation in primary myelodysplastic syndrome - the mutation can be detected early at diagnosis or acquired during disease progression and is associated with poor outcome, British Journal of Haematology, 139(3), pp. 405414. doi: 10.1111/j.1365-2141.2007.06811.x. Delhommeau, F., Dupont, S., Valle, V.D., James, C., Trannoy, S., Mass, A., Kosmider, O., Le Couedic, J.-P., Robert, F., Alberdi, A., Lcluse, Y., Plo, I., Dreyfus, F.J., Marzac, C., Casadevall, N., Lacombe, C., Romana, S.P., Dessen, P., Soulier, J., Vigui, F., Fontenay, M., Vainchenker, W. and Bernard, O.A. (2009) Mutation in TET2 in myeloid cancers, New England Journal of Medicine, 360(22), pp. 22892301. doi: 10.1056/nejmoa0810069. Della Porta, M.G., Alessandrino, E.P., Bacigalupo, A., van Lint, M.T., Malcovati, L., Pascutto, C., Falda, M., Bernardi, M., Onida, F., Guidi, S., Iori, A.P., Cerretti, R., Marenco, P., Pioltelli, P., Angelucci, E., Oneto, R., Ripamonti, F., Bernasconi, P., Bosi, A., Cazzola, M. and Rambaldi, A. (2014) Predictive factors for the outcome of allogeneic transplantation in patients with MDS stratified according to the revised IPSS-R, Blood, 123(15), pp. 23332342. doi: 10.1182/blood-2013-12-542720. Gelsi-Boyer, V., Trouplin, V., Adlade, J., Bonansea, J., Cervera, N., Carbuccia, N., Lagarde, A., Prebet, T., Nezri, M., Sainty, D., Olschwang, S., Xerri, L., Chaffanet, M., Mozziconacci, M.-J., Vey, N. and Birnbaum, D. (2009) Mutations of polycomb-associated gene ASXL1 in myelodysplastic syndromes and chronic myelomonocytic leukaemia, British Journal of Haematology, 145(6), pp. 788800. doi: 10.1111/j.1365-2141.2009.07697.x. Georgiou, G., Karali, V., Zouvelou, C., Kyriakou, E., Dimou, M., Chrisochoou, S., Greka, P., Dufexis, D., Vervesou, E., Dimitriadou, E., Efthymiou, A., Petrikkos, L., Dima, K., Lilakos, K. and Panayiotidis, P. (2006) Serial determination of FLT3 mutations in myelodysplastic syndrome patients at diagnosis, follow up or acute myeloid leukaemia transformation: Incidence and their prognostic significance, British Journal of Haematology, 134(3), pp. 302306. doi: 10.1111/j.1365-2141.2006.06171.x. Haase, D., Germing, U., Schanz, J., Pfeilstocker, M., Nosslinger, T., Hildebrandt, B., Kundgen, A., Lubbert, M., Kunzmann, R., Giagounidis, A.A.N., Aul, C., Trumper, L., Krieger, O., Stauder, R., Muller, T.H., Wimazal, F., Valent, P., Fonatsch, C. and Steidl, C. (2007) New insights into the prognostic impact of the karyotype in MDS and correlation with subtypes: Evidence from a core dataset of 2124 patients, Blood, 110(13), pp. 43854395. doi: 10.1182/blood-2007-03-082404. Haferlach, T., Nagata, Y., Grossmann, V., Okuno, Y., Bacher, U., Nagae, G., Schnittger, S., Sanada, M., Kon, A., Alpermann, T., Yoshida, K., Roller, A., Nadarajah, N., Shiraishi, Y., Shiozawa, Y., Chiba, K., Tanaka, H., Koeffler, H.P., Klein, H.-U., Dugas, M., Aburatani, H., Kohlmann, A., Miyano, S., Haferlach, C., Kern, W. and Ogawa, S. (2013) Landscape of genetic lesions in 944 patients with myelodysplastic syndromes, Leukemia, 28(2), pp. 241247. doi: 10.1038/leu.2013.336. Heinrichs, S., Kulkarni, R.V., Bueso-Ramos, C.E., Levine, R.L., Loh, M.L., Li, C., Neuberg, D., Kornblau, S.M., Issa, J.-P., Gilliland, D.G., Garcia-Manero, G., Kantarjian, H.M., Estey, E.H. and Look, A.T. (2009) Accurate detection of uniparental disomy and microdeletions by SNP array analysis in myelodysplastic syndromes with normal cytogenetics, Leukemia, 23(9), pp. 16051613. doi: 10.1038/leu.2009.82. Horiike, S., Kita-Sasai, Y., Nakao, M. and Taniwaki, M. (2003) Configuration of the TP53 gene as an independent Prognostic parameter of Myelodysplastic syndrome, Leukemia Lymphoma, 44(6), pp. 915922. doi: 10.1080/1042819031000067620. Kolquist, K.A., Schultz, R.A., Furrow, A., Brown, T.C., Han, J.-Y., Campbell, L.J., Wall, M., Slovak, M.L., Shaffer, L.G. and Ballif, B.C. (2011) Microarray-based comparative genomic hybridization of cancer targets reveals novel, recurrent genetic aberrations in the myelodysplastic syndromes, Cancer Genetics, 204(11), pp. 603628. doi: 10.1016/j.cancergen.2011.10.004. Kosmider, O., Gelsi-Boyer, V., Cheok, M., Grabar, S., Della-Valle, V., Picard, F., Viguie, F., Quesnel, B., Beyne-Rauzy, O., Solary, E., Vey, N., Hunault-Berger, M., Fenaux, P., Mansat-De Mas, V., Delabesse, E., Guardiola, P., Lacombe, C., Vainchenker, W., Preudhomme, C., Dreyfus, F., Bernard, O.A., Birnbaum, D. and Fontenay, M. (2009) TET2 mutation is an independent favorable prognostic factor in myelodysplastic syndromes (MDSs), Blood, 114(15), pp. 32853291. doi: 10.1182/blood-2009-04-215814. Kwok, B., Hall, J.M., Witte, J.S., Xu, Y., Reddy, P., Lin, K., Flamholz, R., Dabbas, B., Yung, A., Al-Hafidh, J., Balmert, E., Vaupel, C., El Hader, C., McGinniss, M.J., Nahas, S.A., Kines, J. and Bejar, R. (2015) MDS-associated somatic mutations and clonal hematopoiesis are common in idiopathic cytopenias of undetermined significance, Blood, 126(21), pp. 23552361. doi: 10.1182/blood-2015-08-667063. Makishima, H., Visconte, V., Sakaguchi, H., Jankowska, A.M., Abu Kar, S., Jerez, A., Przychodzen, B., Bupathi, M., Guinta, K., Afable, M.G., Sekeres, M.A., Padgett, R.A., Tiu, R.V. and Maciejewski, J.P. (2012) Mutations in the spliceosome machinery, a novel and ubiquitous pathway in leukemogenesis, Blood, 119(14), pp. 32033210. doi: 10.1182/blood-2011-12-399774. Mohamedali, A., Gaken, J., Twine, N.A., Ingram, W., Westwood, N., Lea, N.C., Hayden, J., Donaldson, N., Aul, C., Gattermann, N., Giagounidis, A., Germing, U., List, A.F. and Mufti, G.J. (2007) Prevalence and prognostic significance of allelic imbalance by single-nucleotide polymorphism analysis in low-risk myelodysplastic syndromes, Blood, 110(9), pp. 33653373. doi: 10.1182/blood-2007-03-079673. Nakagawa, T., Saitoh, S., Imoto, S., Itoh, M., Tsutsumi, M., Hikiji, K., Nakamura, H., Matozaki, S., Ogawa, R., Nakao, Y. and Fujita, T. (2009) Multiple point mutation of N-ras and K-ras oncogenes in Myelodysplastic syndrome and acute myelogenous leukemia, Oncology, 49(2), pp. 114122. doi: 10.1159/000227023. Nybakken, G.E. and Bagg, A. (2014) The genetic basis and expanding role of molecular analysis in the diagnosis, prognosis, and therapeutic design for Myelodysplastic Syndromes, The Journal of Molecular Diagnostics, 16(2), pp. 145158. doi: 10.1016/j.jmoldx.2013.11.005. Oostlander, A., Meijer, G. and Ylstra, B. (2004) Microarray-based comparative genomic hybridization and its applications in human genetics, Clinical Genetics, 66(6), pp. 488495. doi: 10.1111/j.1399-0004.2004.00322.x. Papaemmanuil, E., Malcovati, L., Cazzola, M., Hellstrom-Lindberg, E., Bowen, D., Boultwood, J.B., Green, A.R., Futreal, P.A., Stratton, M.R. and Campbell, P.J. (2011) Identification of novel somatic mutations in SF3B1, a Gene Encoding a core component of RNA splicing machinery, in Myelodysplasia with ring Sideroblasts and other common cancers, European Journal of Cancer, 47, p. 7. doi: 10.1016/s0959-8049(11)70110-1. Patsouris, C., Michael, P.M. and Campbell, L.J. (2002) A new nonrandom unbalanced t(17;20) in myeloid malignancies, Cancer Genetics and Cytogenetics, 138(1), pp. 3237. doi: 10.1016/s0165-4608(02)00579-4. Pinkel, D. and Albertson, D.G. (2005) Array comparative genomic hybridization and its applications in cancer, Nature Genetics, 37(6s), pp. S11S17. doi: 10.1038/ng1569. Pozdnyakova, O., Miron, P.M., Tang, G., Walter, O., Raza, A., Woda, B. and Wang, S.A. (2008) Cytogenetic abnormalities in a series of 1029 patients with primary myelodysplastic syndromes, Cancer, 113(12), pp. 33313340. doi: 10.1002/cncr.23977. Ren, H., Francis, W., Boys, A., Chueh, A.C., Wong, N., La, P., Wong, L.H., Ryan, J., Slater, H.R. and Andy Choo, K.H. (2005) BAC-based PCR fragment microarray: High-resolution detection of chromosomal deletion and duplication breakpoints, Human Mutation, 25(5), pp. 476482. doi: 10.1002/humu.20164. Rodger, E.J. and Morison, I.M. (2012) Myelodysplastic syndrome in New Zealand and Australia, Internal Medicine Journal, 42(11), pp. 12351242. doi: 10.1111/j.1445-5994.2011.02619.x. Roller, A., Grossmann, V., Bacher, U., Poetzinger, F., Weissmann, S., Nadarajah, N., Boeck, L., Kern, W., Haferlach, C., Schnittger, S., Haferlach, T. and Kohlmann, A. (2013) Landmark analysis of DNMT3A mutations in hematological malignancies, Leukemia, 27(7), pp. 15731578. doi: 10.1038/leu.2013.65. Schanz, J., Tuchler, H., Sole, F., Mallo, M., Luno, E., Cervera, J., Granada, I., Hildebrandt, B., Slovak, M.L., Ohyashiki, K., Steidl, C., Fonatsch, C., Pfeilstocker, M., Nosslinger, T., Valent, P., Giagounidis, A., Aul, C., Lubbert, M., Stauder, R., Krieger, O., Garcia-Manero, G., Faderl, S., Pierce, S., Le Beau, M.M., Bennett, J.M., Greenberg, P., Germing, U. and Haase, D. (2012) New comprehensive Cytogenetic scoring system for primary Myelodysplastic Syndromes (MDS) and Oligoblastic acute myeloid leukemia after MDS derived from an international database merge, Journal of Clinical Oncology, 30(8), pp. 820829. doi: 10.1200/jco.2011.35.6394. Sequential molecular characterization based delineation of potential driver aberrations in ACUTE myeloid leukemia following Myelodysplastic syndrome (2015) Poster Abstracts, 126(23), p. 4123. SNP array (2016) in Wikipedia. Available at: https://en.wikipedia.org/wiki/SNP_array (Accessed: 20 June 2016). Starczynowski, D.T., Vercauteren, S., Telenius, A., Sung, S., Tohyama, K., Brooks-Wilson, A., Spinelli, J.J., Eaves, C.J., Eaves, A.C., Horsman, D.E., Lam, W.L. and Karsan, A. (2008) High-resolution whole genome tiling path array CGH analysis of CD34+ cells from patients with low-risk myelodysplastic syndromes reveals cryptic copy number alterations and predicts overall and leukemia-free survival, Blood, 112(8), pp. 34123424. doi: 10.1182/blood-2007-11-122028. Swerdlow, S.H., Who, S., H, S., International Agency for Research on Cancer and The International Agency for Research on Cancer (2008) WHO classification of tumours of Haematopoietic and Lymphoid tissues. Switzerland: World Health Organization. Thol, F., Kade, S., Schlarmann, C., Loffeld, P., Morgan, M., Krauter, J., Wlodarski, M.W., Kolking, B., Wichmann, M., Gorlich, K., Gohring, G., Bug, G., Ottmann, O., Niemeyer, C.M., Hofmann, W.., Schlegelberger, B., Ganser, A. and Heuser, M. (2012) Frequency and prognostic impact of mutations in SRSF2, U2AF1, and ZRSR2 in patients with myelodysplastic syndromes, Blood, 119(15), pp. 35783584. doi: 10.1182/blood-2011-12-399337. Tirado, C.A., Meloni-Ehrig, A.M., Wallenhorst, E., Burks, K., Scheerle, J., Morillon, M., Kelly, J.C., Heritage, D., Spira, A., Croft, C.D., Glasser, L., Butera, J.N. and Mowrey, P. (2006) Dicentric (17;20)(p11.2;q11.2): An uncommon cytogenetic abnormality in myeloid malignancies, Cancer Genetics and Cytogenetics, 170(1), pp. 6164. doi: 10.1016/j.cancergencyto.2006.04.013. Tiu, R.V., Gondek, L.P., Haddad, A., OKeefe, C.L., Sekeres, M.A., Sekeres, G., Ogawa, S. and Maciejewski, J.P. (2007) C021 SNP-array karyotyping complements routine metaphase cytogenetics in the detection of chromosomal aberrations including uniparental disomy in MDS, Leukemia Research, 31, p. S34. doi: 10.1016/s0145-2126(07)70059-0. Tiu, R.V., Gondek, L.P., Huh, J., OKeefe, C., Sekeres, M.A., Mufti, G.J., McDevitt, M.A., Advani, A.S. and Maciejewski, J. (2009) P035 improvement in cytogenetic diagnosis and clinical prognostication using SNP-A karyotyping in combination with metaphase cytogenetics in MDS, MDS/MPD and secondary AML, Leukemia Research, 33, pp. S78S79. doi: 10.1016/s0145-2126(09)70115-8. Tiu, R.V., Gondek, L.P., OKeefe, C.L., Elson, P., Huh, J., Mohamedali, A., Kulasekararaj, A., Advani, A.S., Paquette, R., List, A.F., Sekeres, M.A., McDevitt, M.A., Mufti, G.J. and Maciejewski, J.P. (2011) Prognostic impact of SNP array karyotyping in myelodysplastic syndromes and related myeloid malignancies, Blood, 117(17), pp. 45524560. doi: 10.1182/blood-2010-07-295857. Volkert, S., Schnittger, S., Holzwarth, J., Zenger, M., Kern, W., Staller, M., Nagata, Y., Yoshida, K., Ogawa, S., Haferlach, T. and Haferlach, C. (2015) Array CGH identifies copy number changes in 11% of 520 MDS patients with normal karyotype and uncovers prognostically relevant deletions, Leukemia, . doi: 10.1038/leu.2015.257. Walter, M.J., Shen, D., Ding, L., Shao, J., Koboldt, D.C., Chen, K., Larson, D.E., McLellan, M.D., Dooling, D., Abbott, R., Fulton, R., Magrini, V., Schmidt, H., Kalicki-Veizer, J., OLaughlin, M., Fan, X., Grillot, M., Witowski, S., Heath, S., Frater, J.L., Eades, W., Tomasson, M., Westervelt, P., DiPersio, J.F., Link, D.C., Mardis, E.R., Ley, T.J., Wilson, R.K. and Graubert, T.A. (2012) Clonal architecture of secondary acute myeloid leukemia, New England Journal of Medicine, 366(12), pp. 10901098. doi: 10.1056/nejmoa1106968. Weiss, M.M., Hermsen, M.A., Meijer, G.A., van Grieken, N.C., Baak, J.P., Kuipers, E.J. and van Diest, P.J. (1999) Comparative genomic hybridisation, Molecular Pathology, 52(5), pp. 243251. doi: 10.1136/mp.52.5.243. Wiktor, A., Rybicki, B.A., Piao, Z.S., Shurafa, M., Barthel, B., Maeda, K. and Van Dyke, D.L. (2000) Clinical significance of Y chromosome loss in hematologic disease, Genes, Chromosomes and Cancer, 27(1), pp. 1116. doi: 10.1002/(sici)1098-2264(200001)27:111::aid-gcc23.0.co;2-i. Woll, P.S., Kjllquist, U., Chowdhury, O., Doolittle, H., Wedge, D.C., Thongjuea, S., Erlandsson, R., Ngara, M., Anderson, K., Deng, Q., Mead, A.J., Stenson, L., Giustacchini, A., Duarte, S., Giannoulatou, E., Taylor, S., Karimi, M., Scharenberg, C., Mortera-Blanco, T., Macaulay, I.C., Clark, S.-A., Dybedal, I., Josefsen, D., Fenaux, P., Hokland, P., Holm, M.S., Cazzola, M., Malcovati, L., Tauro, S., Bowen, D., Boultwood, J., Pellagatti, A., Pimanda, J.E., Unnikrishnan, A., Vyas, P., Ghring, G., Schlegelberger, B., Tobiasson, M., Kvalheim, G., Constantinescu, S.N., Nerlov, C., Nilsson, L., Campbell, P.J., Sandberg, R., Papaemmanuil, E., Hellstrm-Lindberg, E., Linnarsson, S. and Jacobsen, S.E.W. (2014) Myelodysplastic Syndromes are propagated by rare and distinct human cancer stem cells in vivo, Cancer Cell, 25(6), pp. 794808. doi: 10.1016/j.ccr.2014.03.036.

Rehabilitation of Heroin Drug Addicts

Question: Discuss about the Rehabilitation of Heroin Drug Addicts. Answer: Introduction: Drug addiction is a relapsing brain disease that is chronic and is characterized by the need to look for and use drugs regardless of their harmful effects ("The Science of Drug Abuse and Addiction: The Basics", 2016). Substance abuse involves the introduction of drugs into the body. Therefore, the five primary methods of substance abuse include swallowing, smoking, snorting, suppositories, and injecting. The two main methods of addiction treatment are outpatient and inpatient treatment. These methods have various approaches that are used depending on the situation of the patients as well as the availability of the different resources that are necessary for the implementation of the programs. According to the Centers for Disease Control statics, more than a hundred people die to drugs in a day ("Drug Rehab Success Rates and Statistics", N.D). The methods of heroin addiction treatment and the various approaches towards the rehabilitation of drug addicts will be discussed in this essay to help in the understanding of the various issues surrounding drug addiction and recovery. The two primary methods for heroin abuse treatment are the behavioral and pharmacological treatment ("What are the treatments for heroin addiction?", 2014). The pharmacological treatment involves the substitution of tapering methadone. In addition, -2 Adrenergic agents can be used to substitute for antagonists when not available (Kleber, 2014). Although the withdrawals can be shortened by precipitating them with, the use if antagonists, studies show that it has safety issues and persisting symptoms (Kleber, 2014). The agonist maintenance therapies are essential since they lead to better results for heroin addicts especially when used with the residential therapeutic programs (Kleber, 2014; Patterson, N.D.) Therapy is the second treatment that can be used to help heroin addicts recover from their addiction. According to Utley et al. (2013), there are five types of therapies that can be used to help the heroin addicts recover efficiently. The first one is the cognitive behavioral therapy that helps a patient to recognize unhealthy thoughts and behaviors that contribute to the use of heroin. The second one is contingency management that focuses on the provision of positive reinforcements to the patient to motivate them to abstain from heroin use. The third type of therapy is motivational interviewing in which the therapist helps the patient in the identification and overcoming of hesitation. The fourth type of treatment is the matrix model that combines the various therapies to maximize the success rate of the program. The final type of therapy is the multidimensional family therapy that helps in the improvement of family functioning (Utley et al., 2013). Both the pharmacologic and treatment methods have individual programs that make them successful. An effective drug rehabilitation program must have several elements that will make the addiction treatment effective. Among the most important features that a drug rehabilitation program must have complete health evaluation, personalized treatment, counseling, and individual and group therapy ("Principles of Effective Treatment", 2012). It is essential to note that the various methods of addiction treatment are equally important to guarantee positive results. The reason for this is that the different approaches complement each other making the success rate of the rehabilitation program higher. On the other hand, the success rates of the treatment methods are lower whenever the individual approaches are used independently. The first minimum requirement of an effective treatment program is complete health evaluation. The assessment requires psychological interventions that are regarded as the central part of the individual psychotherapy in the rehabilitation counseling of the patients that are drug-dependent during the maintenance treatment of methadone in community programs (Popescu et al., 2014). Besides, it is essential that the need for psychological counseling is established since some patients require an extensive help to restore order to their lives. The requirement also involves behavior therapy, which is critical because it enhances interpersonal relationships as well the availability of individuals to work in both the family and community levels. The second minimum requirement of an effective treatment program is the personalized treatment that focuses on tailor-made care for people. It is essential since it helps the caregivers in the identification of key changes that can be made to ensure that reasonable progress is realized the epidemiological key figures. Studies show that it is easier to understand the effects of the intended treatment when the variables of a sub-group are given a more precise look (Stel, 2015). Besides, it helps to identify the specific needs of an individual thus avoiding chances of missing the point and choosing cheaper procedures that are ineffective. The third requirement for an effective treatment program is counseling. Counseling can be done using either of the three available options that include individual counseling, group counseling, and family counseling. The various types are critical and should be utilized during the treatment to ensure that patients recover fully and efficiently ("Drug Addiction Common Types of Drug Addiction Symptoms of Drug Abuse", N.D). The reason for this is that the individual counseling helps to identify the primary cause of the addiction and the development of life strategies that can contribute to improving sobriety. In addition, the group advice allows individuals to share stories and support with other recovering addicts (Marsh et al., 2007). On the other hand, the family counseling helps in the mending of the broken bonds within the family thus assist the patients to recover fast. The fourth primary requirement to an effective treatment program is individual and group therapy. The different therapeutic measures focus on individual members since they can influence and be influenced by the group they are born into. However, the group therapy is a powerful therapeutic tool since groups always have several rewarding benefits (1 Groups and Substance Abuse Treatment, 2005). For instance, the individuals within the groups can reduce chances of isolations and can witness the recovery of other members of the groups thus encouraging them to continue with the treatment program. Besides, groups are appropriate for treating issues that usually accompany drug abuse including isolation, depression, and shame (1 Groups and Substance Abuse Treatment, 2005). However, it is critical to note that the most efficient heroin addiction treatment program is one that utilizes both the pharmacologic and behavioral therapy options. In addition, the treatments success rate can be maximized by using the inpatient method. The reason for this is that the programs within the inpatient and residential treatment offer structure and safety (Utley et al., 2013). In addition, the patients are provided with comfort and security whenever health complications arise because they are monitored all the times in the inpatient rehabs and inpatient detox. Besides, the inpatient rehabs limit temptations from outside thus ensuring that the patients focus on getting healthy. Furthermore, the inpatient treatment facilities do not have to be concerned with relapse since the environment is drug-free for both the detox and treatment of the patients. There are no standardized ways to measure the success of addiction treatment programs. However, several people suggest that success rate indicators for the rehabilitation program include the completion of the program, rates of sobriety rates after treatment, interviews if the clients, and internal studies ("Drug Rehab Success Rates and Statistics", N.D). Although the various measures can be used to attempt to justify the success of the programs, the contention over the real measure of success will never end. As a result, it is not possible to set the duration that will mark a successful recovery method. For instance, some centers consider completion of the program as the measure of the success rate of the program ("Drug Rehab Success Rates and Statistics", N.D). Although it is not easy to settle on the best measure of addiction treatment success rate, it is possible to focus on certain actions that can promote the use of the programs. Besides, the high incidence of the utilization of the various treatment programs can be translated to increased success rates of the programs. Therefore, the success rate of the treatment options can be improved by acknowledging both the individual and program factors ("What helps people stay in treatment?", 2012). Among the different factors that should be considered include motivation, support from friends and family, and pressure from other institutions such as criminal justice and child protection services. Concerning the program, the clinicians have to build a positive therapeutic relationship with their patients to ensure they embrace the program fully. Drug addiction is the effect of substance abuse that makes an individual dependent on the drugs. The drugs can be abused through various methods including injection, snorting, smoking, swallowing, and suppositories. The two primary methods of addiction treatment are outpatient and inpatient. Both the methods have several approaches that are critical in helping to realize success in the fight against drug addictions. The various methods include complete health evaluation, personalized treatment, counseling, and individual and group therapy. Although the two primary methods may use the different approaches, the inpatient methods are the most efficient way of drug addiction treatment. There are no clear measures for success rates of addiction treatment program. However, some centers use distinct perspectives to measure their success rates. They include completion of the program, rates of sobriety rates after treatment, interviews if the clients, and internal studies. Center can also ack nowledge both the individual and program factors to increase the success rates of the various treatment programs. References Groups and Substance Abuse Treatment. (2005). National Center for Biotechnology Information. Retrieved 8 January 2017, from https://www.ncbi.nlm.nih.gov/books/NBK64223/ Drug Addiction Common Types of Drug Addiction Symptoms of Drug Abuse. (N.D). Drugabuse.net. Retrieved 8 January 2017, from https://www.drugabuse.net/drug-addiction/ Drug Rehab Success Rates and Statistics. (N.D). American Addiction Centers. Retrieved 8 January 2017, from https://americanaddictioncenters.org/rehab-guide/success-rates-and-statistics/ Marsh, A., Dale, A., Willis, L. (2007). A Counsellors Guide to Working with Alcohol and Drug Users (2nd ed.). Drug and Alcohol Office. Retrieved from https://www.dao.health.wa.gov.au/vsu/resources/www.dao.health.wa.gov.au/Counsellors%20guide%20to%20working%20with%20alcohol%20and%20drug%20users.pdf Patterson, E. (N.D). Inpatient Treatment. DrugAbuse.com. Retrieved 8 January 2017, from https://drugabuse.com/library/inpatient-treatment/ Popescu, G., Negrei, C., B?l?l?u, D., Ciobanu, A., Baconi, D. (N.D). The relevance of the psychological evaluation in drug dependence. PubMed Central (PMC). Retrieved 8 January 2017, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391414/ Principles of Effective Treatment. (2012). Drugabuse.gov. Retrieved 8 January 2017, from https://www.drugabuse.gov/publications/principles-drug-addiction-treatment-research-based-guide-third-edition/principles-effective-treatment Stel, J. (2015). Precision in Addiction Care: Does It Make a Difference?. PubMed Central (PMC). Retrieved 8 January 2017, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4654192/ The Science of Drug Abuse and Addiction: The Basics. (2016). Drugabuse.gov. Retrieved 8 January 2017, from https://www.drugabuse.gov/publications/media-guide/science-drug-abuse-addiction-basics Utley, T., Milios, R., Skelly, S., Hovitz, H. (2013). Choosing Inpatient Rehab vs. Outpatient Rehabilitation. Recovery.org. Retrieved 8 January 2017, from https://www.recovery.org/topics/choosing-inpatient-rehab-vs-outpatient-rehabilitation/ What are the treatments for heroin addiction?. (2014). Drugabuse.gov. Retrieved 9 January 2017, from https://www.drugabuse.gov/publications/research-reports/heroin/what-are-treatments-heroin-addiction What helps people stay in treatment?. (2012). Drugabuse.gov. Retrieved 8 January 2017, from https://www.drugabuse.gov/publications/principles-drug-addiction-treatment-research-based-guide-third-edition/frequently-asked-questions/what-helps-people-stay-in-treatment