RNA promotes the formation of spatial compartments in the nucleus.

RNA, DNA, and protein molecules are highly organized within three-dimensional (3D) structures in the nucleus. Although RNA has been proposed to play a role in nuclear organization, exploring this has been challenging because existing methods cannot measure higher-order RNA and DNA contacts within 3D structures. To address this, we developed RNA & DNA SPRITE (RD-SPRITE) to comprehensively map the spatial organization of RNA and DNA. These maps reveal higher-order RNA-chromatin structures associated with three major classes of nuclear function: RNA processing, heterochromatin assembly, and gene regulation. These data demonstrate that hundreds of ncRNAs form high-concentration territories throughout the nucleus, that specific RNAs are required to recruit various regulators into these territories, and that these RNAs can shape long-range DNA contacts, heterochromatin assembly, and gene expression. These results demonstrate a mechanism where RNAs form high-concentration territories, bind to diffusible regulators, and guide them into compartments to regulate essential nuclear functions.

Xist nucleates local protein gradients to propagate silencing across the X chromosome.

The lncRNA Xist forms ∼50 diffraction-limited foci to transcriptionally silence one X chromosome. How this small number of RNA foci and interacting proteins regulate a much larger number of X-linked genes is unknown. We show that Xist foci are locally confined, contain ∼2 RNA molecules, and nucleate supramolecular complexes (SMACs) that include many copies of the critical silencing protein SPEN. Aggregation and exchange of SMAC proteins generate local protein gradients that regulate broad, proximal chromatin regions. Partitioning of numerous SPEN molecules into SMACs is mediated by their intrinsically disordered regions and essential for transcriptional repression. Polycomb deposition via SMACs induces chromatin compaction and the increase in SMACs density around genes, which propagates silencing across the X chromosome. Our findings introduce a mechanism for functional nuclear compartmentalization whereby crowding of transcriptional and architectural regulators enables the silencing of many target genes by few RNA molecules.

SARS-CoV-2 Disrupts Splicing, Translation, and Protein Trafficking to Suppress Host Defenses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently identified coronavirus that causes the respiratory disease known as coronavirus disease 2019 (COVID-19). Despite the urgent need, we still do not fully understand the molecular basis of SARS-CoV-2 pathogenesis. Here, we comprehensively define the interactions between SARS-CoV-2 proteins and human RNAs. NSP16 binds to the mRNA recognition domains of the U1 and U2 splicing RNAs and acts to suppress global mRNA splicing upon SARS-CoV-2 infection. NSP1 binds to 18S ribosomal RNA in the mRNA entry channel of the ribosome and leads to global inhibition of mRNA translation upon infection. Finally, NSP8 and NSP9 bind to the 7SL RNA in the signal recognition particle and interfere with protein trafficking to the cell membrane upon infection. Disruption of each of these essential cellular functions acts to suppress the interferon response to viral infection. Our results uncover a multipronged strategy utilized by SARS-CoV-2 to antagonize essential cellular processes to suppress host defenses.

Denaturing purifications demonstrate that PRC2 and other widely reported chromatin proteins do not appear to bind directly to RNA in vivo.

Polycomb repressive complex 2 (PRC2) is reported to bind to many RNAs and has become a central player in reports of how long non-coding RNAs (lncRNAs) regulate gene expression. Yet, there is a growing discrepancy between the biochemical evidence supporting specific lncRNA-PRC2 interactions and functional evidence demonstrating that PRC2 is often dispensable for lncRNA function. Here, we revisit the evidence supporting RNA binding by PRC2 and show that many reported interactions may not occur in vivo. Using denaturing purification of in vivo crosslinked RNA-protein complexes in human and mouse cell lines, we observe a loss of detectable RNA binding to PRC2 and chromatin-associated proteins previously reported to bind RNA (CTCF, YY1, and others), despite accurately mapping bona fide RNA-binding sites across others (SPEN, TET2, and others). Taken together, these results argue for a critical re-evaluation of the broad role of RNA binding to orchestrate various chromatin regulatory mechanisms.

Covalent Organic Framework Catalyzed Amide Synthesis Directly from Alcohol Under Red Light Excitation.

The dehydrogenative coupling of alcohols and amines to form amide bonds is typically catalysed by homogeneous transition metal catalysts at high temperatures ranging from 130-140 °C. In our pursuit of an efficient and recyclable photocatalyst capable of conducting this transformation at room temperature, we report herein a COF-mediated dehydrogenative synthesis. The TTT-DHTD COF was strategically designed to incorporate a high density of functional units, specifically dithiophenedione, to trap photogenerated electrons and effectively facilitate hydrogen atom abstraction reactions. The photoactive TTT-DHTD COF, synthesized using solvothermal methods showed high crystallinity and moderate surface area, providing an ideal platform for heterogeneous amide synthesis.  Light absorption by the COF across the entire visible range, narrow band gap, and valence band position make it well-suited for the efficient generation of excitons necessary for targeted dehydrogenation. Utilizing red light irradiation and employing extremely low loading of the COF, we have successfully prepared a wide range of amides, including challenging secondary amides, in good to excellent yields. The substrate's functional group tolerance, very mild reaction conditions, and the catalyst's significant recyclability represent substantial advancements over prior methodologies.

Interfaces and Interphases in All-Solid-State Batteries with Inorganic Solid Electrolytes.

All-solid-state batteries (ASSBs) have attracted enormous attention as one of the critical future technologies for safe and high energy batteries. With the emergence of several highly conductive solid electrolytes in recent years, the bottleneck is no longer Li-ion diffusion within the electrolyte. Instead, many ASSBs are limited by their low Coulombic efficiency, poor power performance, and short cycling life due to the high resistance at the interfaces within ASSBs. Because of the diverse chemical/physical/mechanical properties of various solid components in ASSBs as well as the nature of solid-solid contact, many types of interfaces are present in ASSBs. These include loose physical contact, grain boundaries, and chemical and electrochemical reactions to name a few. All of these contribute to increasing resistance at the interface. Here, we present the distinctive features of the typical interfaces and interphases in ASSBs and summarize the recent work on identifying, probing, understanding, and engineering them. We highlight the complicated, but important, characteristics of interphases, namely the composition, distribution, and electronic and ionic properties of the cathode-electrolyte and electrolyte-anode interfaces; understanding these properties is the key to designing a stable interface. In addition, conformal coatings to prevent side reactions and their selection criteria are reviewed. We emphasize the significant role of the mechanical behavior of the interfaces as well as the mechanical properties of all ASSB components, especially when the soft Li metal anode is used under constant stack pressure. Finally, we provide full-scale (energy, spatial, and temporal) characterization methods to explore, diagnose, and understand the dynamic and buried interfaces and interphases. Thorough and in-depth understanding on the complex interfaces and interphases is essential to make a practical high-energy ASSB.

Glassy Li metal anode for high-performance rechargeable Li batteries.

Lithium metal has been considered an ideal anode for high-energy rechargeable Li batteries, although its nucleation and growth process remains mysterious, especially at the nanoscale. Here, cryogenic transmission electron microscopy was used to reveal the evolving nanostructure of Li metal deposits at various transient states in the nucleation and growth process, in which a disorder-order phase transition was observed as a function of current density and deposition time. The atomic interaction over wide spatial and temporal scales was depicted by reactive molecular dynamics simulations to assist in understanding the kinetics. Compared to crystalline Li, glassy Li outperforms in electrochemical reversibility, and it has a desired structure for high-energy rechargeable Li batteries. Our findings correlate the crystallinity of the nuclei with the subsequent growth of the nanostructure and morphology, and provide strategies to control and shape the mesostructure of Li metal to achieve high performance in rechargeable Li batteries.

Digital Twins Supporting Efficient Digital Industrial Transformation.

Industry 4.0 applications help digital industrial transformation to be achieved through smart, data-driven solutions that improve production efficiency, product consistency, preventive maintenance, and the logistics of industrial applications and related supply chains. To enable and accelerate digital industrial transformation, it is vital to support cost-efficient Industry 4.0 application development. However, the development of such Industry 4.0 applications is currently expensive due to the limitations of existing IoT platforms in representing complex industrial machines, the support of only production line-based application testing, and the lack of cost models for application cost/benefit analysis. In this paper, we propose the use of Cyber Twins (CTs), an extension of Digital Twins, to support cost-efficient Industry 4.0 application development. CTs provide semantic descriptions of the machines they represent and incorporate machine simulators that enable application testing without any production line risk and cost. This paper focuses on CT-based Industry 4.0 application development and the related cost models. Via a case study of a CT-based Industry 4.0 application from the dairy industry, the paper shows that CT-based Industry 4.0 applications can be developed with approximately 60% of the cost of IoT platform-based application development.

Na3 SbS4 : A Solution Processable Sodium Superionic Conductor for All-Solid-State Sodium-Ion Batteries.

All-solid-state sodium-ion batteries that operate at room temperature are attractive candidates for use in large-scale energy storage systems. However, materials innovation in solid electrolytes is imperative to fulfill multiple requirements, including high conductivity, functional synthesis protocols for achieving intimate ionic contact with active materials, and air stability. A new, highly conductive (1.1 mS cm(-1) at 25 °C, Ea =0.20 eV) and dry air stable sodium superionic conductor, tetragonal Na3 SbS4 , is described. Importantly, Na3 SbS4 can be prepared by scalable solution processes using methanol or water, and it exhibits high conductivities of 0.1-0.3 mS cm(-1) . The solution-processed, highly conductive solidified Na3 SbS4 electrolyte coated on an active material (NaCrO2 ) demonstrates dramatically improved electrochemical performance in all-solid-state batteries.

De novo variants in immune regulatory genes in Down syndrome regression disorder.

BACKGROUND: Down Syndrome Regression Disorder (DSRD) is a rare and poorly understood disorder of the central nervous system, characterized by acute or subacute neuropsychiatric symptoms in previously healthy individuals with Down syndrome (DS). Many patients exhibit immunotherapy-responsiveness, indicative of immune dysregulation as a potential underlying etiology. While hypotheses are emerging regarding the role of interferon signaling in DSRD and other autoimmune conditions associated with DS, it is unclear why a small subset of individuals with DS develop DSRD. The aim of this study was to investigate genes of immune regulation in persons with DSRD. METHODS: This study included individuals with DSRD aged 10-30 years with trio exome sequencing performed during the diagnostic work up. Descriptive statistics and univariate analysis (Chi-square and Fisher's exact test) were used to describe and compare the characteristics of individuals with and without variants. RESULTS: Forty-one individuals with DSRD had trio exome sequencing results. Eight (20%) had heterozygous de novo variants of immune regulatory genes, with four variants being pathogenic or likely pathogenic (UNC13D, XIAP, RNASEH2A, and DNASE1L3). All genes harboring pathogenic variants were associated with interferon type-1 inflammatory response. Individuals harboring variants were more likely to have a preceding trigger (p = 0.03, 95% CI 1.21-97.06), rapid clinical decline in less than 1 month (p = 0.01, 95% CI 1.67-52.06), and MRI abnormalities (p < 0.001, 95% CI 4.89-527.71). DISCUSSION: A distinct subset of individuals with DSRD exhibited pathogenic variants in immune regulation genes associated with interferon-mediated inflammatory response, coinciding with previously established links between these genes and interferonopathies such as Aicardi-Goutieres syndrome. Our observations suggest that these variants might potentially contribute to the development of DSRD in individuals with DS.

Citrate milling of oxides: from poly-dispersed micron scale to nearly mono-dispersed nanoscale.

Complex (multivalent/mixed valent) oxides involving two or more cations (e.g. ABO3, AB2O4 and A2B2O7) exhibit the most fascinating range of physical and chemical properties amongst the family of materials systems. There is growing interest in nanoscale forms of such oxides which emanates from the novel changes in their properties with size. To obtain nanomaterials with a high degree of crystallinity it is desirable to first make crystalline oxide powders by high temperature processing and then mill them down to nanometer size. In this paper we show that simple citric acid treatment of BiFeO3 and Bi2O3 powders leads to the desired micron-scale to nanoscale transformation, yielding nearly monodispersed nanoparticles. Importantly, these are highly dispersible and stable in water. By performing similar experiments on Fe3O4 and Fe2O3 we have elucidated the possible mechanism, which hinges on valence-controlled dissolution and ripening phenomena.

Mitigating Dendrite Formation on a Zn Electrode in Aqueous Zinc Chloride by the Competitive Surface Chemistry of an Imidazole Additive.

Electrochemical energy storage systems are critical in several ways for a smooth transition from nonrenewable to renewable energy sources. Zn-based batteries are one of the promising alternatives to the existing state-of-the-art Li-ion battery technology, since Li-ion batteries pose significant drawbacks in terms of safety and cost-effectiveness. Zn (with a reduction potential of -0.76 V vs SHE) has a significantly higher theoretical volumetric capacity (5851 mAh/cm3) than Li (2061 mAh/cm3), and it is certainly far less expensive, safer, and more earth-abundant. The formation of dendrites, hydrogen evolution, and the formation of a ZnO passivation layer on the Zn anode are the primary challenges in the development and deployment of rechargeable zinc batteries. In this work, we examine the role of imidazole as an electrolyte additive in 2 M ZnCl2 to prevent dendrite formation during zinc electrodeposition via experimental (kinetics and imaging) and theoretical density functional theory (DFT) studies. To characterize the efficacy and to identify the appropriate concentration of imidazole, linear sweep voltammetry (LSV) and chronoamperometry (CA) are performed with in situ monitoring of the electrodeposited zinc. The addition of 0.025 wt % imidazole to 2 M ZnCl2 increases the cycle life of Zn-symmetric cells cycled at 1 mA/cm2 for 60 min of plating and stripping dramatically from 90 to 240 h. A higher value of the nucleation overpotential is noted in the presence of imidazole, which suggests that imidazole is adsorbed at a competitively faster rate on the surface of zinc, thereby suppressing the zinc electrodeposition kinetics and the formation. X-ray tomography reveals that a short circuit caused by dendrite formation is the main plausible failure mechanism of Zn symmetric cells. It is observed that the electrodeposition of zinc is more homogeneous in the presence of imidazole, and its presence in the electrolyte also inhibits the production of a passivating coating (ZnO) on the Zn surface, thereby preventing corrosion. DFT calculations conform well with the stated experimental observations.

Immunotherapy Responsiveness and Risk of Relapse in Down Syndrome Regression Disorder.

Down syndrome regression disorder (DSRD) is a clinical symptom cluster consisting of neuropsychiatric regression without an identifiable cause. This study evaluated the clinical effectiveness of IVIg and evaluated clinical characteristics associated with relapse after therapy discontinuation. A prospective, multi-center, non-randomized, observational study was performed. Patients met criteria for DSRD and were treated with IVIg. All patients underwent a standardized wean off therapy after 9-12 months of treatment. Baseline, on therapy, and relapse scores of the Neuropsychiatric Inventory Total Score (NPITS), Clinical Global Impression-Severity (CGI-S), and the Bush-Francis Catatonia Rating Scale (BFCRS) were used to track clinical symptoms. Eighty-two individuals were enrolled in this study. Patients had lower BFCRS (MD: -6.68; 95% CI: -8.23, -5.14), CGI-S (MD: -1.27; 95% CI: -1.73, -0.81), and NPITS scores (MD: -6.50; 95% CI: -7.53, -5.47) while they were on therapy compared to baseline. Approximately 46% of the patients (n = 38) experienced neurologic relapse with wean of IVIg. Patients with neurologic relapse were more likely to have any abnormal neurodiagnostic study (χ2 = 11.82, p = 0.001), abnormal MRI (χ2 = 7.78, p = 0.005), and abnormal LP (χ2 = 5.45, p = 0.02), and a personal history of autoimmunity (OR: 6.11, p < 0.001) compared to patients without relapse. IVIg was highly effective in the treatment of DSRD. Individuals with a history of personal autoimmunity or neurodiagnostic abnormalities were more likely to relapse following weaning of immunotherapy, indicating the potential for, a chronic autoimmune etiology in some cases of DSRD.

Immunotherapy responsiveness and risk of relapse in Down syndrome regression disorder.

Down syndrome regression disorder (DSRD) is a clinical symptom cluster consisting of neuropsychiatric regression without an identifiable cause. This study evaluated the clinical effectiveness of IVIg and evaluated clinical characteristics associated with relapse after therapy discontinuation. A prospective, multi-center, non-randomized, observational study was performed. Patients met criteria for DSRD and were treated with IVIg. All patients underwent a standardized wean-off therapy after 9-12 months of treatment. Baseline, on-therapy, and relapse scores of the Neuropsychiatric Inventory Total Score (NPITS), Clinical Global Impression-Severity (CGI-S), and the Bush-Francis Catatonia Rating Scale (BFCRS) were used to track clinical symptoms. Eighty-two individuals were enrolled in this study. Patients had lower BFCRS (MD: -6.68; 95% CI: -8.23, -5.14), CGI-S (MD: -1.27; 95% CI: -1.73, -0.81), and NPITS scores (MD: -6.50; 95% CI: -7.53, -5.47) while they were on therapy compared to baseline. Approximately 46% of the patients (n = 38) experienced neurologic relapse with wean of IVIg. Patients with neurologic relapse were more likely to have any abnormal neurodiagnostic study (χ2 = 11.82, P = 0.001), abnormal MRI (χ2 = 7.78, P = 0.005), and abnormal LP (χ2 = 5.45, P = 0.02), and a personal history of autoimmunity (OR: 6.11, P < 0.001) compared to patients without relapse. IVIg was highly effective in the treatment of DSRD. Individuals with a history of personal autoimmunity or neurodiagnostic abnormalities were more likely to relapse following weaning of immunotherapy, indicating the potential for, a chronic autoimmune etiology in some cases of DSRD.

Search for New Anode Materials for High Performance Li-Ion Batteries.

Owing to an unmatched combination of power and energy density along with cyclic stability, the Li-ion battery has qualified itself to be the highest performing rechargeable battery. Taking both transportable and stationary energy storage requirements into consideration, Li-ion batteries indeed stand tall in comparison to any other existing rechargeable battery technologies. However, graphite, which is still one of the best performing Li-ion anodes, has specific drawbacks in fulfilling the ever-increasing energy and power density requirements of the modern world. Therefore, further research on alternative anode materials is absolutely essential. Equally important is the search for and enhanced use of right earth abundant materials for battery electrodes so as to bring down the costs of the battery systems. In this spotlight article, we discuss the current research progress in the area of alternative anode materials for Li-ion battery, putting our own research work over the past several years into perspective. Starting from conversion anode systems like oxides and sulfides, to insertion cum alloying systems like transition metal carbides, to molecularly engineered open framework systems like metal organic frameworks (MOFs), covalent organic frameworks (COFs), and organic-inorganic hybrid perovskites (OIHPs), this spotlight provides a complete essence of the recent developments in the area of alternative anodes. The possible and potential impact of these new anode materials is detailed and discussed here.

Xist spatially amplifies SHARP/SPEN recruitment to balance chromosome-wide silencing and specificity to the X chromosome.

Although thousands of long non-coding RNAs (lncRNAs) are encoded in mammalian genomes, their mechanisms of action are poorly understood, in part because they are often expressed at lower levels than their proposed targets. One such lncRNA is Xist, which mediates chromosome-wide gene silencing on one of the two X chromosomes (X) to achieve gene expression balance between males and females. How a limited number of Xist molecules can mediate robust silencing of a much larger number of target genes while maintaining specificity exclusively to genes on the X within each cell is not well understood. Here, we show that Xist drives non-stoichiometric recruitment of the essential silencing protein SHARP (also known as SPEN) to amplify its abundance across the inactive X, including at regions not directly occupied by Xist. This amplification is achieved through concentration-dependent homotypic assemblies of SHARP on the X and is required for chromosome-wide silencing. Expression of Xist at higher levels leads to increased localization at autosomal regions, demonstrating that low levels of Xist are critical for ensuring its specificity to the X. We show that Xist (through SHARP) acts to suppress production of its own RNA which may act to constrain overall RNA levels and restrict its ability to spread beyond the X. Together, our results demonstrate a spatial amplification mechanism that allows Xist to achieve two essential but countervailing regulatory objectives: chromosome-wide gene silencing and specificity to the X. This suggests a more general mechanism by which other low-abundance lncRNAs could balance specificity to, and robust control of, their regulatory targets.

Assessment of clinical continuity strategies offered by dual-degree training programs in the USA.

Background: Integration of clinical skills during graduate training in dual-degree programs remains a challenge. The present study investigated the availability and self-perceived efficacy of clinical continuity strategies for dual-degree trainees preparing for clinical training. Methods: Survey participants were MD/DO-PhD students enrolled in dual-degree-granting institutions in the USA. The response rate was 95% of 73 unique institutions surveyed, representing 56% of the 124 MD-PhD and 7 DO-PhD recognized training programs. Respondents were asked to indicate the availability and self-perceived efficacy of each strategy. Results: Reported available clinical continuity strategies included clinical volunteering (95.6%), medical grand rounds (86.9%), mentored clinical experiences (84.2%), standardized patients/ practice Objective Structured Clinical Examinations (OSCEs) (70.3%), clinical case reviews (45.9%), clinical journal clubs (38.3%), and preclinical courses/review sessions (37.2%). Trainees rated standardized patients (µ = 6.98 ± 0.356), mentored clinical experiences (µ = 6.94 ± 0.301), clinical skills review sessions (µ = 6.89 ± 0.384), preclinical courses/review sessions (µ = 6.74 ± 0.482), and clinical volunteering (µ = 6.60 ± 0.369), significantly (p < 0.050) higher than clinical case review (µ = 5.34 ± 0.412), clinical journal club (µ = 4.75 ± 0.498), and medicine grand rounds (µ = 4.45 ± 0.377). Further, 84.4% of respondents stated they would be willing to devote at least 0.5-1 hour per week to clinical continuity opportunities during graduate training. Conclusion: Less than half of the institutions surveyed offered strategies perceived as the most efficacious in preparing trainees for clinical reentry, such as clinical skills review sessions. Broader implementation of these strategies could help better prepare dual-degree students for their return to clinical training.

Association of rare variants in genes of immune regulation with pediatric autoimmune CNS diseases.

BACKGROUND: There is a gap in the literature regarding genetic underpinnings of pediatric autoimmune CNS diseases. This study explored rare gene variants implicated in immune dysregulation within these disorders. METHODS: This was a single-center observational study of children with inflammatory CNS disorder who had genetic testing through next generation focused exome sequencing targeting 155 genes associated with innate or adaptive immunity. For in silico prediction of functional effects of single-nucleotide variants, Polymorphism Phenotyping v2, and Sorting Intolerant from Tolerant were used, and Combined Annotation Dependent Depletion (CADD) scores were calculated. Identified genes were analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. RESULTS: Of 54 patients, 42 (77.8%) carried variant(s), among which 12 (22.2%) had 3-8 variants. Eighty-eight unique single-nucleotide variants of 55 genes were identified. The most variants were detected in UNC13D, LRBA, LYST, NOD2, DOCK8, RNASEH2A, STAT5B, and AIRE. The majority of variants (62, 70.4%) had CADD > 10. KEGG pathway analysis revealed seven genes associated with primary immunodeficiency (Benjamini 1.40E - 06), six genes with NOD-like receptor signaling (Benjamini 4.10E - 04), five genes with Inflammatory Bowel Disease (Benjamini 9.80E - 03), and five genes with NF-kappa B signaling pathway (Benjamini 1.90E - 02). DISCUSSION: We observed a high rate of identification of rare and low-frequency variants in immune regulatory genes in pediatric neuroinflammatory CNS disorders. We identified 88 unique single-nucleotide variants of 55 genes with pathway analysis revealing an enrichment of NOD2-receptor signaling, consistent with involvement of the pathway within other autoinflammatory conditions and warranting further investigation.

An ensemble machine learning model based on multiple filtering and supervised attribute clustering algorithm for classifying cancer samples.

BACKGROUND: Machine learning is one kind of machine intelligence technique that learns from data and detects inherent patterns from large, complex datasets. Due to this capability, machine learning techniques are widely used in medical applications, especially where large-scale genomic and proteomic data are used. Cancer classification based on bio-molecular profiling data is a very important topic for medical applications since it improves the diagnostic accuracy of cancer and enables a successful culmination of cancer treatments. Hence, machine learning techniques are widely used in cancer detection and prognosis. METHODS: In this article, a new ensemble machine learning classification model named Multiple Filtering and Supervised Attribute Clustering algorithm based Ensemble Classification model (MFSAC-EC) is proposed which can handle class imbalance problem and high dimensionality of microarray datasets. This model first generates a number of bootstrapped datasets from the original training data where the oversampling procedure is applied to handle the class imbalance problem. The proposed MFSAC method is then applied to each of these bootstrapped datasets to generate sub-datasets, each of which contains a subset of the most relevant/informative attributes of the original dataset. The MFSAC method is a feature selection technique combining multiple filters with a new supervised attribute clustering algorithm. Then for every sub-dataset, a base classifier is constructed separately, and finally, the predictive accuracy of these base classifiers is combined using the majority voting technique forming the MFSAC-based ensemble classifier. Also, a number of most informative attributes are selected as important features based on their frequency of occurrence in these sub-datasets. RESULTS: To assess the performance of the proposed MFSAC-EC model, it is applied on different high-dimensional microarray gene expression datasets for cancer sample classification. The proposed model is compared with well-known existing models to establish its effectiveness with respect to other models. From the experimental results, it has been found that the generalization performance/testing accuracy of the proposed classifier is significantly better compared to other well-known existing models. Apart from that, it has been also found that the proposed model can identify many important attributes/biomarker genes.