Genetic Classification System Research Articles

Genetic risk stratification and outcomes among treatment-naive patients with AML treated with venetoclax and azacitidine

AbstractThe European LeukemiaNet (ELN) acute myeloid leukemia (AML) genetic risk classification systems are based on response to intensive chemotherapy; their ability to discriminate outcomes in older patients treated with venetoclax-azacitidine may be suboptimal. This pooled analysis of the phase 3 VIALE-A trial (NCT02993523) and phase 1b study (NCT02203773) examined prognostic stratification according to the 2017 and 2022 ELN risk classifications and derived new molecular signatures differentiating venetoclax-azacitidine–treated patients based on overall survival (OS). Overall, 279 patients treated with venetoclax-azacitidine and 113 patients treated with placebo-azacitidine were analyzed. The ELN 2017 or 2022 prognostic criteria classified most patients as adverse-risk AML (60.2% and 72.8% for venetoclax-azacitidine and 65.5% and 75.2% for placebo-azacitidine, respectively). Although outcomes with venetoclax-azacitidine improved across all ELN risk groups compared with placebo-azacitidine, ELN classification systems poorly discriminated venetoclax-azacitidine outcomes. By applying a bioinformatic algorithm, new molecular signatures were derived differentiating OS outcomes with venetoclax-azacitidine. The mutational status of TP53, FLT3 internal tandem duplication (FLT3-ITD), NRAS, and KRAS categorized patients into higher-, intermediate-, and lower-benefit groups (52%, 25%, and 23% of patients, respectively), each associated with a distinct median OS (26.5 months [95% confidence interval (CI), 20.2-32.7]; 12.1 months [95% CI, 7.3-15.2]; and 5.5 months [95% CI, 2.8-7.6], respectively). ELN prognostic classifiers did not provide clinically meaningful risk stratification of OS outcomes in patients treated with venetoclax-azacitidine. TP53, FLT3-ITD, NRAS, and KRAS mutation status allows the classification of these patients into 3 risk groups with distinct differences in median OS. These trials were registered at www.clinicaltrials.gov as #NCT02993523 and #NCT02203773.

Refining PRRSV-2 genetic classification based on global ORF5 sequences and investigation of their geographic distributions and temporal changes.

Porcine reproductive and respiratory syndrome virus (PRRSV) is an important swine pathogen affecting the global swine industry. The first open reading frame 5 (ORF5)-based genetic lineage classification system describing global PRRSV-2 genetic diversity was introduced over a decade ago. Although refinements have been proposed for the predominant lineage in the USA (lineage 1), PRRSV-2 phylogenetic classification system at international levels has not been thoroughly evaluated and updated since 2010. In this study, based on analysis of 82,237 global ORF5 sequences reported during 1989-2021, we classified PRRSV-2 into 11 genetic lineages (L1‒L11) and 21 sublineages (L1A‒L1F, L1H‒L1J, L5A‒L5B, L8A‒L8E, and L9A‒L9E). The proposed classification system is flexible for growth if additional lineages, sublineages, or more granular classifications are needed. For example, for more fine-scale epidemiological investigation, L1C was further divided into five groups (L1C.1‒L1C.5), with L1C.5 corresponding to the recently emerged L1C variant. Comparison between restriction fragment length polymorphism (RFLP) typing and phylogenetic classification revealed the inaccuracy of using RFLP to determine PRRSV-2 genetic relatedness in most scenarios. Genetic homology of six commercial PRRSV-2 vaccines to each lineage/sublineage and detection frequency of vaccine-like viruses were determined. Global geographic distribution of each lineage/sublineage was presented. Temporal dynamic changes of PRRSV-2 in the USA during 1989-2021 were investigated by analyzing 73,092 ORF5 sequences. In summary, this study refined PRRSV-2 ORF5-based phylogenetic classification and investigated the geographic distribution and temporal changes of PRRSV-2 at the lineage/sublineage levels. The refined classification system and molecular epidemiology data in this study will be invaluable for future characterization of PRRSV-2.IMPORTANCEIn this study, comprehensive analysis of 82,237 global porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2) open reading frame 5 sequences spanning from 1989 to 2021 refined PRRSV-2 genetic classification system, which defines 11 lineages and 21 sublineages and provides flexibility for growth if additional lineages, sublineages, or more granular classifications are needed in the future. Geographic distribution and temporal changes of PRRSV-2 were investigated in detail. This is a thorough study describing the molecular epidemiology of global PRRSV-2. In addition, the reference sequences based on the refined genetic classification system are made available to the public for future epidemiological and diagnostic applications worldwide. The data from this study will facilitate global standardization and application of PRRSV-2 genetic classification.

Towards a Unified Genetic Classification System for Diffuse Large B-Cell Lymphoma (DLBCL)

Introduction: Diffuse large B-cell lymphoma (DLBCL) is an aggressive B-cell neoplasm and the most common lymphoid malignancy worldwide. DLBCL, NOS is a genetically and biologically complex entity that remains uniformly treated at diagnosis despite the growing appreciation for subgroups with molecular distinctions. There are various approaches for assigning DLBCL into one or more molecular subgroups using either gene expression and/or mutation patterns. Several genetic classification systems have been proposed, each sharing commonalities. Distinctions between the definitions of individual classes and the ability to reproducibly assign individual patient samples to subgroups using each system remains a significant barrier to their implementation, further emphasized by up to 50% of patients that remain unclassified. The disparities among the genetic features considered by each classification scheme further limits the ability to consolidate, let alone adopt, these for research and clinical studies. We aimed to develop a classification system that unifies and extends the robustness of existing classification algorithms. Methods: We assembled whole genome sequencing (WGS) data from 900 tumors from DLBCL, Burkitt (BL), follicular (FL) and other mature B-cell neoplasms to comprehensively determine the set of significantly mutated genes (SMG) and common targets of aberrant somatic hypermutation (aSHM). These were intersected with the features used by the current DLBCL classification systems and a curated set of lymphoma genes to tabulate the mutation matrix. Common structural rearrangements involving oncogenes were determined from WGS data and the copy number state of focal high-level recurrent alterations was united with simple somatic mutations. For genes containing mutation hot-spots each was considered separately. Results: Clustering all cases using non-negative matrix factorization (NMF) analysis resulted in a solution with 7 distinct genetic subgroups (Figure 1). Many of these directly resemble clusters in the existing systems with either expanded coverage or refinement of a subgroup into two. First, the BNZ cluster was highly enriched for any aberration in BCL6, 3'UTR mutations in NFKBIZ, and truncating mutations in NOTCH2. Unlike the similar BN2/C1/NOTCH2 groups defined previously, the NFKBIZ mutations were weighted more highly than those of NOTCH2 in defining the BNZ subgroup. The cluster we named MCaP resembled the MCD/C5/MYD88 group. Tumors classified in this subgroup had evidence of aSHM with frequent non-coding mutations in PIM1,CD44, GRHPR, PIM2, and BCL11A among others. Another cluster, MP3, was enriched for coding mutations or aSHM in the MYC TSS (MYC_aSHM), which were generally correspondent with IG::MYC rearrangements. MP3 tumors were characterized by TP53 mutations, including hotspots, and significantly depleted for aberrations in BCL2, BCL6 and lower mutation rates at aSHM targets SGK1, PAX5, CIITA, RHOH and others. Notably, tumors in this subgroup were enriched for IRF4 translocations, suggesting potential overlap with large B-cell lymphoma with IRF4 rearrangement. Our approach further refined both the the ST2/C4 and EZB/C3/BCL2 classes into two smaller subgroups, aSEL/aSCI and EGB/ETB, respectively. The EGB tumors were enriched for GNAI2 mutations, and MYC translocations involving the BCL6 enhancer, and were more often associated with MEF2B hotspot mutations. Notably, ETB was significantly enriched for mutations in the lysine acetyltransferase (KAT) domain in CREBBP, while EGB was significantly enriched for non-KAT domain mutations. ETB tumors were further characterized by mutations in STAT6 and FOXO1 hotspot regions, MYC rearrangements with other non-IG partners, and TNFRSF14 mutations, largely resembling the mutational profile of follicular lymphomas. Conclusions: We present here a refined classification of DLBCL genetic subgroups that combines previously described classification algorithms and extends it to allow classification of more tumors into additional subgroups that preserve the major divisions of existing systems. This represents an important advancement that will facilitate further understanding of genomic complexity in this disease. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Research on Modeling and Simulation System of Economic Factors Based on Swarm Platform

Based on the VAR model, this paper uses the stepwise regression analysis method to analyze the main influencing factors of the economy, and empirically analyzes the impact of Nanning's fixed asset investment on urban and rural economic development in the past ten years. Use eviews statistical analysis software to perform regression analysis on the data to obtain a regression model, and build a VAR model according to investment and income, and finally find out the correlation of variables. On the basis of the existing theory (genetic algorithm, cellular automata and classification system), according to the agent-based modeling and simulation method Swarm, according to the steps of agent-based distributed simulation of complex system, modeling and simulation are carried out. The abstraction level of simulation is established on the big data computing level, and the final simulation results are briefly explained and explained.

Characterising the late Quaternary facies stratigraphy of floodplains in South Africa

AbstractSouth African river floodplains and their alluvial deposits reflect a diversity of geological and geographical drivers. We use a genetic geomorphic classification system originally developed for dryland wetlands to characterise geomorphic processes and potential successions of sedimentary fill for South African floodplains. Using case studies from the literature, we consider differences between alluvial rivers and mixed bedrock-alluvial rivers in the context of macro-scale geomorphic setting, and evaluate the impact of the setting on floodplain persistence and potential as a palaeo-environmental archive. Sedimentary facies associations represented in South African floodplains, including lateral and oblique accretion, channel, channel infill, levee vertical accretion, floodplain vertical accretion and debris flow deposits, are also evaluated.Floodplains of South Africa’s interior are typically mixed bedrock-alluvial as channel beds are set upon or close to bedrock and sediment thickness is limited. By contrast some floodplains in tectonic basin settings have sediment deposits exceeding 30 m in thickness. The resulting rivers are alluvial, and thus able to adjust their width, depth and slope to accommodate changes in discharge and sediment supply. Similarly, coastal floodplain rivers are alluvial due to downcutting during the last glacial maximum and subsequent sedimentary infilling as sea levels rose.When considering the potential of floodplains as palaeoarchives of environmental change, two considerations emerge. First, floodplain stratigraphy is not a response to a single variable due to complex process-form feedbacks. Rather, floodplain stratigraphy is an outcome of both autogenic and allogenic processes. Second, most South African floodplains are zones of sediment recycling, and as such, preservation potential is typically low. Thus, although floodplain settings of the interior may be a few million years old, the sediment within them may be only thousands to tens of thousands of years old. Our review indicates that research has historically focused on meandering river and mixed bedrock-alluvial anabranching river floodplains, while understanding of other floodplain sub-types remains limited.

Diffuse large B-cell lymphoma genetics - simplifying the subtyping.

Diffuse large B-cell lymphoma genetics - simplifying the subtyping.

ALX-Related Frontonasal Dysplasias: Clinical Characteristics and Surgical Management.

The term frontonasal dysplasia (FND) represents a spectrum of anomalies and its genetics have not been well defined. Recently, the critical role of the aristaless-like homeobox (ALX) gene family on the craniofacial development has been discovered. In the present study, we aimed to propose a systematic surgical treatment plan for the ALX-related FNDs according to the genotypic classification as well as demonstrating their clinical characteristics to help surgeons diagnose the underlying pathology accurately. Single-institution retrospective. Tertiary health care. Eighty-nine FND cases were evaluated. Eight of them had ALX1-related FND3, 3 had ALX3-related FND1, and 2 had ALX4-related FND2. Phenotype characteristics of ALX-related FNDs were evaluated, and relevant surgical interventions were assessed. The ALX1-related FND3 phenotype is striking due to the involvement of the eyes in addition to the presence of hypertelorism, facial clefts, and nasal deformities. A widened philtrum and prominent philtral columns are remarkable features of the ALX3-related FND1, whereas the ALX4-related FND2 has more severe deformities: severe hypertelorism, brachycephaly, large parietal bone defects, broad nasal dorsum, and alopecia. Facial bipartition, box osteotomies, eyelid coloboma repair, cleft lip and palate repair, nasal reconstruction, and fronto-orbital advancement can be performed in ALX-related FNDs based on the characteristics of each subtype. This genetic classification system will help surgeon diagnose patients with FND with unique features and draw a roadmap for their treatment with a better surgical perspective.

Genomic Analysis of Diffuse Large B Cell Lymphoma in a Japanese Cohort Using Targeted DNA Sequencing

Introduction: Recent studies based on next-generation sequencing revealed the genetic landscape of diffuse large B cell lymphoma (DLBCL). A new genetic classification system was proposed, including four groups; the BCL2 and SGK1 groups that were both associated with germinal center B-cell like (GCB) DLBCL, an MYD88 group that was associated with non-GCB DLBCL, and a NOTCH2 group that was not associated with a specific cell-of-origin (COO). Unfortunately, this classification method is somewhat complex and thus not fully accepted in clinical practice. Furthermore, part of all cases remained unclassified; as such, it is clear that the diversity of the genetic landscape of DLBCL is not yet fully understood. In this study, we performed a retrospective analysis of genetic abnormalities and their correlations with clinical characteristics in a Japanese cohort of patients diagnosed with DLBCL. Materials and Methods: We collected clinical data from 224 of a total of 234 patients who were diagnosed with DLBCL between 2013 and 2018 at Chiba University Hospital. We also collected formalin-fixed paraffin-embedded (FFPE) specimens obtained from 204 patients via standard diagnostic procedures. The COO for each sample was assessed using the Hans algorithm with immunohistochemical staining; rearrangements of BCL2, BCL6, and MYC were evaluated by fluorescence in situ hybridization. Targeted DNA sequencing was performed using a 144-gene custom panel. Results: Of the 224 DLBCL patients evaluated in our study, the median age at diagnosis was 69 years (range, 18 - 92 years). The median follow-up time was 34 months; three-year progression-free survival (PFS) was 63.2%, and three-year overall survival was 78.0%. COO was determined in 218 cases; 93 of these cases (41.5%) were classified as GCB type and 125 cases (55.8%) as non-GCB type. We successfully performed targeted DNA sequencing in 167 of the 204 FFPE samples. Compared to previous reports, our cohort included relatively higher frequencies of mutations in PIM1 (44.3%), KMT2D (40.7%), MYD88L265P (37.7%), and CD79B (24.5%); by contrast, we detected comparatively lower mutation frequencies in B2M (6.6%), ETV6 (5.4%), CDKN2A (4.7%), and TNFAIP3 (4.1%). Multivariate adjustment of genes extracted by univariate analysis and factors identified by International Prognostic Index score revealed that genetic mutations of MYD88L265P (Hazard ratio [HR] = 2.045), IL16 (HR = 4.848), and BCOR (HR = 6.295) were significant prognostic factors. Mutations in IL16 and BCOR are novel factors that will be used to predict poor prognosis. In the 167 sequenced cases, 110 were classified into the aforementioned four subtypes based on mutations detected in 23 genes together with rearrangements of BCL2 and BCL6; specifically, 47 cases were classified as members of the MYD88 group, 28 in the BCL2 group, 19 in the NOTCH2 group, and 16 in the SGK1 group. We identified a trend toward differential PFSs among the four groups (p = 0.18); three-year PFS was 51.2% among patients with MYD88 group, 59.6% in the BCL2 group, 63.2% in the NOTCH2 group, and 75.0% for the SGK1 group. When compared outcomes of patients in the BCL6 group, patients in the MYD88 group had significantly inferior PFS (p = 0.043) among the non-GCB DLBCL patients; those in the BCL2 group revealed a trend toward inferior PFS compared with those in the SGK1 group (p = 0.34) among the GCB DLBCL patients. We next focused on 28 cases of CD5-positive DLBCL; this is a distinct DLBCL subtype with poor prognosis that is identified more frequently among Asians. We observed significantly higher frequencies of frameshift or nonsense mutations in CD58 and missense mutations in MYD88L265P. Furthermore, evaluation of gene expression data for CD5-positive DLBCL reported in a published database (Miyazaki K et al. Int J Hematol. 2015) revealed diminished expression of CD58 (p = 0.01) and augmented expression of MYD88L265P (p < 0.001). These results suggest that there may be a specific correlation between genetic mutations and gene expression. Intriguingly, these specific genes are key regulators of the immune response, suggesting that inflammation contribute to the unfavorable outcome of CD5-positive DLBCL. Conclusion: Our study provides support for the genetic classification of DLBCL using targeted DNA sequencing to evaluate outcomes in our Japanese cohort. We also identified mutations in novel candidate genes that may be used to predict clinical outcomes. Disclosures Nakaseko: Novartis Pharma KK: Speakers Bureau; Pfizer Japan Inc.: Speakers Bureau. Kaneda:SRL Inc.: Research Funding; SCRUM Inc.: Research Funding; Tsubakimoto Chain Co.: Research Funding; Takeda Foundation: Research Funding; Princess Takamatsu Cancer Research Fund.: Research Funding; Wedge Co Ltd: Research Funding.

A Genetic Geomorphic Classification System for Southern African Palustrine Wetlands: Global Implications for the Management of Wetlands in Drylands

Due to climatic constraints in dryland regions, wetlands usually occur at confluences of flow paths, whether from surface flow, inter-flow or at locations of groundwater discharge. Long-term landscape processes that shape valleys and focus the movement of water and sediment are accountable for providing a suitable template with which hydrology interacts to allow wetland formation. Current hydrogeomorphic classification systems do not address system-scale linkages of sediment and water transport across the landscape, and are therefore unable to contextualise long-term process dynamics. Misunderstanding long-term earth system processes can result in the application of inappropriate restoration strategies that isolate wetlands from longitudinal drivers of their formation. We propose a genetic classification system that focuses on the mode of wetland formation, and is based on the understanding that genetic processes impact on the outcome hydrology, sedimentology, geomorphology, ecosystem service provision and long-term dynamics of wetlands in drylands. The classification aims to impart understanding of dynamic processes of sediment transport through wetlands, such that restoration plans can be sensitive to long-term landscape processes. The classification system, derived from a combination of international literature and published South African case studies, has four wetland macrotypes based on sediment source (colluvial, alluvial, aeolian and geochemical). These are subdivided into 8 wetland types; hillslope seep, floodplain, valley-bottom, plain, blocked-valley, alluvial fan, aeolian depression and geochemical depression. The classification is based on landscape location, shape and the occurrence of geomorphic characteristics indicative of process.

Review: The international consensus classification of Focal Cortical Dysplasia – a critical update 2018

The Diagnostic Methods commission of the International League against Epilepsy (ILAE) released a first international consensus classification of Focal Cortical Dysplasia (FCD) in 2011. Since that time, this FCD classification has been widely used in clinical diagnosis and research (more than 740 papers cited in Pubmed between 1/1/2012 and 7/1/2017). Herein, we review the new data that will inform and revise the FCD classification. Many recent papers described molecular-genetic characteristics in FCD type II including multiple mutations in the mTOR pathway. In addition, the electro-clinico-imaging phenotype and surgical outcomes of FCD type II (in particular type IIb) were further defined and validated. These results pave the way for the design of an integrated clinico-pathological and genetic classification system, as recently recommended by the WHO for the classification of malignant brain tumours. On the other hand, little new information was acquired on FCD types I and III. Focal cortical dysplasia type I subtypes are still lacking a comprehensive description of clinical phenotypes, reproducible imaging characteristics, and specific molecular/genetic biomarkers. Associated FCD III subtypes also became rare in published literature. Despite temporal lobe epilepsy being the most common focal epilepsy in adults, we have not identified neurophysiological, imaging, histopathological and/or genetic biomarkers to reliably classify FCD III with or without hippocampal sclerosis. In respect of pathogenesis, FCD adjacent to a non-developmental, postnatally acquired lesion is difficult to explain and perhaps does not exist. This update may help foster shared efforts towards a better understanding of FCD, potential future updates of classification and novel targeted treatments.

Extent to which pH and topographic factors control soil organic carbon level in dry farming cropland soils of the mountainous region of Southwest China

Soil organic carbon (SOC) in agricultural land is influenced greatly by indeterminate human activity, making it difficult to understand the spatial pattern of SOC. Soil pH and topographic conditions are key indices in the Chinese Soil Genetic Classification System (CSGCS) and manage some critical factors that control the dynamics of SOC either directly or indirectly. To identify the extent to which pH and topographic factors control SOC levels in dry farming cropland soils of the mountainous region of Southwest China, we compared the differences along topographic gradients, and analysed the contribution of different factors in determining SOC status using analysis of variance (ANOVA) and linear regression. Our results indicated the SOC levels ranged from 10.46g•kg−1 to 37.60g•kg−1 and were significantly correlated with soil pH, landscape position, slope and elevation (p<0.05). On a large scale, the combined effects of landscape position and elevation contributed to fluctuating SOC levels along the elevation gradient. SOC levels slightly, but significantly, decreased from base to summit. The difference of SOC levels along a 200m elevation gradient exhibited statistical significance (p<0.05). A slope range, from 0 to 42°, was categorized into three groups, namely, 5° to 15°, 15° to 30° and others. The slope range 15° to 30° had significantly greater SOC values than the other groups. These variables could all together explain approximately 40% of total variation in SOC, of which approximately 70% was attributable to soil pH, suggesting soil pH plays a key role in forming the spatial pattern of SOC levels in dry farming cropland soils of the mountainous region of Southwest China. The combined effect of landscape position and elevation could further explain 7.3% of SOC variation, which is more apparent than the effect of elevation alone.

Osteogenesis imperfecta.

Skeletal deformity and bone fragility are the hallmarks of the brittle bone dysplasia osteogenesis imperfecta. The diagnosis of osteogenesis imperfecta usually depends on family history and clinical presentation characterized by a fracture (or fractures) during the prenatal period, at birth or in early childhood; genetic tests can confirm diagnosis. Osteogenesis imperfecta is caused by dominant autosomal mutations in the type I collagen coding genes (COL1A1 and COL1A2) in about 85% of individuals, affecting collagen quantity or structure. In the past decade, (mostly) recessive, dominant and X-linked defects in a wide variety of genes encoding proteins involved in type I collagen synthesis, processing, secretion and post-translational modification, as well as in proteins that regulate the differentiation and activity of bone-forming cells have been shown to cause osteogenesis imperfecta. The large number of causative genes has complicated the classic classification of the disease, and although a new genetic classification system is widely used, it is still debated. Phenotypic manifestations in many organs, in addition to bone, are reported, such as abnormalities in the cardiovascular and pulmonary systems, skin fragility, muscle weakness, hearing loss and dentinogenesis imperfecta. Management involves surgical and medical treatment of skeletal abnormalities, and treatment of other complications. More innovative approaches based on gene and cell therapy, and signalling pathway alterations, are under investigation.

Advances and challenges in barcoding pathogenic and environmental Leptospira.

Leptospirosis is a zoonotic bacterial disease of global importance. A large spectrum of asymptomatic animal hosts can carry the infection and contribute to the burden of human disease. Environmental sources of human contamination also point to the importance of a hydrotelluric reservoir. Leptospirosis can be caused by as many as 15 different pathogenic or intermediate Leptospira species. However, classification of these bacteria remains complicated through the use of both serological and genetic classification systems that show poor correlation. With the advent of molecular techniques, DNA-based barcoding offers a conceptual framework that can be used for leptospirosis surveillance as well as source tracking. In this review, we summarize some of the current techniques, highlight significant successes and weaknesses and point to the future opportunities and challenges to successfully establish a widely applicable barcoding scheme for Leptospira.

Low-grade epilepsy-associated neuroepithelial tumours - the 2016 WHO classification.

Rapid developments in molecular genetic technology and research have swiftly advanced our understanding of neuro-oncology. As a consequence, the WHO invited their expert panels to revise the current classification system of brain tumours and to introduce, for the first time, a molecular genetic approach for selected tumour entities, thus setting a new gold standard in histopathology. The revised 5th edition of the 'blue book' was released in May 2016 and will have a major impact in stratifying diagnosis and treatment. However, low-grade neuroepithelial tumours that present with early-onset focal epilepsy and are mostly seen in children and young adults (previously designated as long-term epilepsy-associated neuroepithelial tumours, LEAT) lack such innovative clinicopathological and molecular genetic tools. The Neuropathology Task Force of the International League against Epilepsy will critically discuss this issue, and will offer perspectives on how to decipher and validate clinically meaningful LEAT entities using the current WHO approach that integrates clinicopathological and genetic classification systems.

Neonatal skeletal dysplasias

Skeletal dysplasias are a large diverse group of disorders characterized by abnormal bone and cartilage growth. Approximately one-quarter of them are considered lethal in the perinatal period. This paper will review the components of the skeletal survey, the primary imaging tool for diagnosing dysplasias postnatally, emphasizing the use of an organized approach and appropriate descriptive terminology. Several illustrative cases of lethal and nonlethal dysplasias will be shown, with additional discussion of commonly associated genetic mutations and classification systems.

Adaptive Genetic Algorithm Based Data Classification Rules Learning System

It’s a worthy research topic to use genetic algorithm for classification rules in data mining. In this paper, it was studied and researched in-depth. Firstly, we combined genetic algorithm and machine learning together, and then analyzed architecture of the genetic algorithm-based classification system, and also its development concrete structure was given. Secondly, we proposed a data classification rules learning system based on adaptive genetic algorithm, which can learn the classification rules accurately from the dataset. Finally the standard Play Tennis dataset was used for a closed test and after learning the system got three classification rules all with 100% accuracy rate, which fully demonstrated the feasibility of this algorithm.

Insight and Advancement in Hereditary Retinal Degenerations

Hereditary retinal degenerations comprise a diverse group of inherited genetic defects in one or more retinal or retinal pigment epithelial cellular proteins. Traditionally, anatomic classification based on clinical and histopathologic phenotype has been used to organize these disorders. In the modern era of advanced molecular biological techniques and genetic screening the current classification system may soon become obsolete, due to the fact that significant overlap between different retinal degenerations has been observed, resulting from variation in gene expression, common genetic pathways, and variable inheritance patterns. In this article, we review the various clinical disease entities, emphasize a genetic classification system, and give special attention to recent advances in molecular biology and gene therapy.

Insight and Advancement in Hereditary Retinal Degenerations

Hereditary retinal degenerations comprise a diverse group of inherited genetic defects in one or more retinal or retinal pigment epithelial cellular proteins. Traditionally, anatomic classification based on clinical and histopathological phenotype has been used to organise these disorders. In the modern era of advanced molecular biological techniques and genetic screening the current classification system may soon become obsolete, due to the fact that significant overlap between different retinal degenerations has been observed, resulting from variation in gene expression, common genetic pathways and variable inheritance patterns. In this article, we review the various clinical disease entities, emphasise a genetic classification system and give special attention to recent advances in molecular biology and gene therapy.

Classification of Plasma Signals by Genetic Algorithms

In the analysis and classification of signals from massive databases, it is highly desirable to use automatic mechanisms. The synergy of artificial intelligence and advanced signal processing techniques is becoming very efficient in developing this kind of task. In this work we employ a signal processing strategy based on the wavelet transform and then genetic algorithms for classification purposes. An in-depth analysis of the waveforms has been carried out, and an analytical preprocessing has been applied to prepare the signals for their classification. Each individual of the simulated population represents a classifying rule, composed of an antecedent and a consequent. The codification of the knowledge is one of the main contributions of this paper. This genetic classification system has been applied to six different classes of plasma signals of the TJ-II stellarator database at CIEMAT in Spain with satisfactory results.

A Bead-Based Activity Screen for Small-Molecule Inhibitors of Signal Transduction in Chronic Myelogenous Leukemia Cells

Chronic myelogenous leukemia is characterized by the presence of the chimeric BCR-ABL gene, which is expressed as the constitutively active Bcr-Abl kinase. Although kinase activity is directly responsible for the clinical phenotype, current diagnostic and prognostic methods focus on a genetic classification system in which molecularly distinct subcategories are used to predict patient responses to small-molecule inhibitors of the Bcr-Abl kinase. Point mutations in the kinase domain are a central factor regulating inhibitor resistance; however, compensatory signaling caused by the activation of unrelated kinases can influence inhibitor efficacy. Kinase activity profiling can be used as a complementary approach to genetic screening and allows direct screening of small-molecule inhibitors. We developed a quantitative assay to monitor tyrosine kinase activities and inhibitor sensitivities in a model of chronic myelogenous leukemia using peptide reporters covalently immobilized on Luminex beads. Kinase activity is quantified by nonlinear regression from well-specific internal standard curves. Using optimized synthetic substrates and peptides derived from native substrates as probes, we measured kinase inhibition in cell lysates by the signal transduction inhibitors imatinib and dasatinib. Taking advantage of a convenient 96-well plate format, this assay also allows a straightforward and quantitative analysis of the differential effects of ATP and inhibitors on kinase activity. This method for analyzing a focused signaling network benefits from rigorous statistical analysis and short processing times, thereby offering a powerful tool for drug discovery and clinical testing.