TranStutter: A Convolution-Free Transformer-Based Deep Learning Method to Classify Stuttered Speech Using 2D Mel-Spectrogram Visualization and Attention-Based Feature Representation.

Stuttering, a prevalent neurodevelopmental disorder, profoundly affects fluent speech, causing involuntary interruptions and recurrent sound patterns. This study addresses the critical need for the accurate classification of stuttering types. The researchers introduce "TranStutter", a pioneering Convolution-free Transformer-based DL model, designed to excel in speech disfluency classification. Unlike conventional methods, TranStutter leverages Multi-Head Self-Attention and Positional Encoding to capture intricate temporal patterns, yielding superior accuracy. In this study, the researchers employed two benchmark datasets: the Stuttering Events in Podcasts Dataset (SEP-28k) and the FluencyBank Interview Subset. SEP-28k comprises 28,177 audio clips from podcasts, meticulously annotated into distinct dysfluent and non-dysfluent labels, including Block (BL), Prolongation (PR), Sound Repetition (SR), Word Repetition (WR), and Interjection (IJ). The FluencyBank subset encompasses 4144 audio clips from 32 People Who Stutter (PWS), providing a diverse set of speech samples. TranStutter's performance was assessed rigorously. On SEP-28k, the model achieved an impressive accuracy of 88.1%. Furthermore, on the FluencyBank dataset, TranStutter demonstrated its efficacy with an accuracy of 80.6%. These results highlight TranStutter's significant potential in revolutionizing the diagnosis and treatment of stuttering, thereby contributing to the evolving landscape of speech pathology and neurodevelopmental research. The innovative integration of Multi-Head Self-Attention and Positional Encoding distinguishes TranStutter, enabling it to discern nuanced disfluencies with unparalleled precision. This novel approach represents a substantial leap forward in the field of speech pathology, promising more accurate diagnostics and targeted interventions for individuals with stuttering disorders.

Histone deacetylase 9 represses cholesterol efflux and alternatively activated macrophages in atherosclerosis development.

OBJECTIVE: Recent genome-wide association studies revealed that a genetic variant in the loci corresponding to histone deacetylase 9 (HDAC9) is associated with large vessel stroke. HDAC9 expression was upregulated in human atherosclerotic plaques in different arteries. The molecular mechanisms how HDAC9 might increase atherosclerosis is not clear. APPROACH AND RESULTS: In this study, we show that systemic and bone marrow cell deletion of HDAC9 decreased atherosclerosis in LDLr(-/-) (low density lipoprotein receptor) mice with minimal effect on plasma lipid concentrations. HDAC9 deletion resulted upregulation of lipid homeostatic genes, downregulation of inflammatory genes, and polarization toward an M2 phenotype via increased accumulation of total acetylated H3 and H3K9 at the promoters of ABCA1 (ATP-binding cassette transporter), ABCG1, and PPAR-γ (peroxisome proliferator-activated receptor) in macrophages. CONCLUSIONS: We conclude that macrophage HDAC9 upregulation is atherogenic via suppression of cholesterol efflux and generation of alternatively activated macrophages in atherosclerosis.

Cognitive inference device for activity supervision in the elderly.

Human activity, life span, and quality of life are enhanced by innovations in science and technology. Aging individual needs to take advantage of these developments to lead a self-regulated life. However, maintaining a self-regulated life at old age involves a high degree of risk, and the elderly often fail at this goal. Thus, the objective of our study is to investigate the feasibility of implementing a cognitive inference device (CI-device) for effective activity supervision in the elderly. To frame the CI-device, we propose a device design framework along with an inference algorithm and implement the designs through an artificial neural model with different configurations, mapping the CI-device's functions to minimise the device's prediction error. An analysis and discussion are then provided to validate the feasibility of CI-device implementation for activity supervision in the elderly.

An approach to the dermatological classification of histopathological skin images using a hybridized CNN-DenseNet model.

This research addresses the challenge of automating skin disease diagnosis using dermatoscopic images. The primary issue lies in accurately classifying pigmented skin lesions, which traditionally rely on manual assessment by dermatologists and are prone to subjectivity and time consumption. By integrating a hybrid CNN-DenseNet model, this study aimed to overcome the complexities of differentiating various skin diseases and automating the diagnostic process effectively. Our methodology involved rigorous data preprocessing, exploratory data analysis, normalization, and label encoding. Techniques such as model hybridization, batch normalization and data fitting were employed to optimize the model architecture and data fitting. Initial iterations of our convolutional neural network (CNN) model achieved an accuracy of 76.22% on the test data and 75.69% on the validation data. Recognizing the need for improvement, the model was hybridized with DenseNet architecture and ResNet architecture was implemented for feature extraction and then further trained on the HAM10000 and PAD-UFES-20 datasets. Overall, our efforts resulted in a hybrid model that demonstrated an impressive accuracy of 95.7% on the HAM10000 dataset and 91.07% on the PAD-UFES-20 dataset. In comparison to recently published works, our model stands out because of its potential to effectively diagnose skin diseases such as melanocytic nevi, melanoma, benign keratosis-like lesions, basal cell carcinoma, actinic keratoses, vascular lesions, and dermatofibroma, all of which rival the diagnostic accuracy of real-world clinical specialists but also offer customization potential for more nuanced clinical uses.

Macrophage 12/15 lipoxygenase expression increases plasma and hepatic lipid levels and exacerbates atherosclerosis.

12/15 lipoxygenase (12/15LO) oxidizes polyunsaturated fatty acids (PUFAs) to form bioactive lipid mediators. The role of 12/15LO in atherosclerosis development remains controversial. We evaluated atherosclerosis development and lipid metabolism in 12/15LO-LDL receptor (LDLr) double knockout (DK) vs. LDLr knockout (SK) mice fed a PUFA-enriched diet to enhance production of 12/15LO products. Compared with SK controls, DK mice fed a PUFA-enriched diet had decreased plasma and liver lipid levels, hepatic lipogenic gene expression, VLDL secretion, and aortic atherosclerosis and increased VLDL turnover. Bone marrow transplantation and Kupffer cell ablation studies suggested both circulating leukocytes and Kupffer cells contributed to the lipid phenotype in 12/15LO-deficient mice. Conditioned medium from in vitro incubation of DK vs. SK macrophages reduced triglyceride secretion in McArdle 7777 hepatoma cells. Our results suggest that, in the context of dietary PUFA enrichment, macrophage 12/15LO expression adversely affects plasma and hepatic lipid metabolism, resulting in exacerbated atherosclerosis.

Histone deacetylase 9 deficiency protects against effector T cell-mediated systemic autoimmunity.

Co-repressor histone deacetylase 9 (HDAC9) plays a key role in the development and differentiation of many types of cells, including regulatory T cells. However, the biological function of HDAC9 in T effector cells is unknown. Systemic autoimmune diseases like lupus, diabetes, and rheumatoid arthritis have dysfunctional effector T cells. To determine the role of HDAC9 in systemic autoimmunity, we created MRL/lpr mice with HDAC9 deficiency that have aberrant effector T cell function. HDAC9 deficiency led to decreased lympho-proliferation, inflammation, autoantibody production, and increased survival in MRL/lpr mice. HDAC9-deficient mice manifested Th2 polarization, decreased T effector follicular cells positive for inducible co-stimulator, and activated T cells in vivo compared with HDAC9-intact MRL/lpr mice. HDAC9 deficiency also resulted in increased GATA3 and roquin and decreased BCL6 gene expression. HDAC9 deficiency was associated with increased site-specific lysine histone acetylation at H3 (H3K9, H3K14, and H3K18) globally that was localized to IL-4, roquin, and peroxisome proliferator-activated receptor-γ promoters with increased gene expression, respectively. In kidney and spleen, HDAC9 deficiency decreased inflammation and cytokine and chemokine production due to peroxisome proliferator-activated receptor γ overexpression. These findings suggest that HDAC9 acts as an epigenetic switch in effector T cell-mediated systemic autoimmunity.

Recurrent Neural Model to Analyze the Effect of Physical Training and Treatment in Relation to Sports Injuries.

Artificial intelligence has rapidly grown and has made the scenario that no field can function without it. Like every field, it also plays a vital role in the sports field nowadays. In certain sports, injuries happen very often due to heavy training and sudden speedy actions, especially in athletics and football. Here arises a need to analyze the effect of physical training in sportsperson by collecting data from their daily training. With the help of artificial intelligence, a recurrent neural model is developed to analyze the effect of physical training and treatment concerning sports injury. A Recurrent Neural Network (RNN) can be a subsection of Artificial Neural Networks (ANN) that uses the neural nodes connected in a temporal sequence. The temporal sequence is one of the essential terms in this research, which denotes a data sequence of events in a given timeframe. The recurrent neural model is an intelligent machine learning method that comprises a neural schema replicating humans. This neural schema studies the data it collects from the athletes/players and processes it by analyzing previous injuries. Sports injuries have to be analyzed because, in some cases, it becomes more dangerous to the sportsperson that they may even lose their career due to disability. Sometimes it may cause a massive loss to the club or company that hired the sportsperson for the sport. The prediction process can give the player rest until he recovers, thus becoming the safest approach in sports. Therefore, it is essential to analyze the sportsperson's track data to keep an eye on his health. In this research, RNN model is compared with the existing Support Vector Machine (SVM) in concerning to the effect of physical training and treatment for sports. The results show that the proposed model has achieved 99% accuracy, which is higher than the existing algorithm.

Lightweight Artificial Intelligence for Secure Data Communication in Energy-Constrained Healthcare Devices.

Logistics is the transfer of goods from one place to another, mostly from the production house to the customers. A logistics network is a set of operations that involve designing, production, and marketing the goods. Cold-chain logistics are those that needed to be transported in a cold refrigeration right from the production house to the customer. A secured networking model is essential to handle the logistics networks. In this article, we are going to see an intelligent secured networking model to identify the optimal path for cold-chain logistics to hospitals. The optimal pathfinder is used to find the path between point A to point B, which is short and best. It also considers the road traffic and cost of transport. The cold-chain logistics to the hospitals include medicines and vaccines, which are to be stored at a particular temperature. Thus, path optimization is more essential in cold-chain logistics to hospitals than other types of logistics. In this research, the bee-ant optimization algorithm (BAOA) is proposed to perform the intelligent transportation to the hospitals. The proposed algorithm is compared with the existing ant colony optimization (ACO), bee colony optimization (BCO), and neural network model. From the results, it can be observed that the proposed algorithm shows 98.83% for the accurate delivery of logistics to the hospitals.

Applications of Intelligent Model to Analyze the Green Finance for Environmental Development in the Context of Artificial Intelligence.

Green finance can be referred to as financial investments made on sustainable projects and policies that focus on a sustainable economy. The procedures include promoting renewable energy sources, energy efficiency, water sanitation, industrial pollution control, transportation pollution control, reduction of deforestation, and carbon emissions, etc. Mainly, these green finance initiatives are carried out by private and public agents like business organizations, banks, international organizations, government organizations, etc. Green finance provides a financial solution to create a positive impact on society and leads to environmental development. In the age of artificial intelligence, all industries adopt AI technologies. In this research, we see the applications of the intelligent model to examine the green finance for ecological advancement with regard to artificial intelligence. Feasible transportation and energy proficiency and power transmission are two significant fields to be advanced and focused on minimizing the carbon impression in these industries. Renewable sources like solar energies for power generation and electric vehicles are to be researched and developed. This R&D requires a considerable fund supply, thus comes the green finance. Globally, green finance plays a vital role in creating a sustainable environment. In this research, for performing the green finance analysis, financial maximally filtered graph (FMFG) algorithm is implemented in different domains. The proposed algorithm is compared with the neural model and observed that the proposed model has obtained 98.85% of accuracy which is higher than the neural model.

HDAC inhibition in lupus models.

Systemic lupus erythematosus (SLE) is a prototypic autoimmune inflammatory disease characterized by the production of autoantibodies directed against nuclear antigens such as nucleosomes, DNA and histone proteins found within the body's cells and plasma. Autoantibodies may induce disease by forming immune complexes that lodge in target organs or by crossreacting with targeted antigens and damaging tissue. In addition to autoantibody production, apoptotic defects and impaired removal of apoptotic cells contribute to an overload of autoantigens that initiate an autoimmune response. Besides the well-recognized genetic susceptibility to SLE, environmental and epigenetic factors play a crucial role in disease pathogenesis as evidenced by monozygotic twins typically being discordant for disease. Changes in DNA methylation and histone acetylation alter gene expression and are thought to contribute to the epigenetic deregulation in disease. In SLE, global and gene-specific DNA methylation changes have been demonstrated to occur. Additionally, aberrant histone acetylation is evident in individuals with SLE. Moreover, histone deacetylase inhibitors (HDACi) have been shown to reverse the skewed expression of multiple genes involved in SLE. In this review, we discuss the implications of epigenetic alterations in the development and progression of SLE, and how therapeutics designed to alter histone acetylation status may constitute a promising avenue to target disease.

Prolonged expression of CD154 on CD4 T cells from pediatric lupus patients correlates with increased CD154 transcription, increased nuclear factor of activated T cell activity, and glomerulonephritis.

OBJECTIVE: To assess CD154 expression in patients with pediatric systemic lupus erythematosus (SLE) and to explore a transcriptional mechanism that may explain dysregulated expression of CD154. METHODS: Cell surface CD154 expression (pre- and postactivation) in peripheral blood CD4 T cells from 29 children with lupus and 29 controls matched for age, sex, and ethnicity was examined by flow cytometry. CD154 expression was correlated with clinical features, laboratory parameters, and treatments received. Increased CD154 expression on CD4 T cells from the SLE patients was correlated with CD154 message and transcription rates by real-time reverse transcription-polymerase chain reaction (RT-PCR) and nuclear run-on assays, respectively. Nuclear factor of activated T cell (NF-AT) transcription activity and mRNA levels in CD4 T cells from SLE patients were explored by reporter gene analysis and real-time RT-PCR, respectively. RESULTS: CD154 surface protein levels were increased 1.44-fold in CD4 T cells from SLE patients as compared with controls in cells evaluated 1 day postactivation ex vivo. This increase correlated clinically with the presence of nephritis and an elevated erythrocyte sedimentation rate. Increased CD154 protein levels also correlated with increased CD154 mRNA levels and with CD154 transcription rates, particularly at later time points following T cell activation. Reporter gene analyses revealed a trend for increased NF-AT, but decreased activator protein 1 and similar NF-kappaB, activity in CD4 T cells from SLE patients as compared with controls. Moreover, NF-AT1 and, in particular, NF-AT2 mRNA levels were notably increased in CD4 T cells from SLE patients as compared with controls. CONCLUSION: Following activation, cell surface CD154 is increased on CD4 T cells from pediatric lupus patients as compared with controls, and this increase correlates with the presence of nephritis, increased CD154 transcription rates, and increased NF-AT activity. These results suggest that NF-AT/calcineurin inhibitors, such as tacrolimus and cyclosporine, may be beneficial in the treatment of lupus nephritis.

Curcumin modulates leukocyte and platelet adhesion in murine sepsis.

OBJECTIVE: Circulating cell-endothelial cell interaction in sepsis is a rate-determining factor in organ dysfunction, and interventions targeting this process have a potential therapeutic value. In this project, we examined whether curcumin, an active ingredient of turmeric and an anti-inflammatory agent, could disrupt interactions between circulating blood cells and endothelium and improve survival in a murine model of sepsis. METHODS: Mice were subjected to cecal ligation and puncture (CLP) to induce sepsis vs. sham surgery. We studied leukocyte and platelet adhesion in cerebral microcirculation using intravital fluorescent video microscopy technique, blood-brain barrier (BBB) dysfunction using Evans Blue (EB) leakage method, P-selectin expression using dual radiolabeling technique, and survival in mice subjected to Sham, CLP, and CLP with curcumin pre-treatment (CLP + curcumin). RESULTS: Curcumin significantly attenuated leukocyte and platelet adhesion in cerebral microcirculation, EB leakage in the brain tissue, and improved survival in mice with CLP. P-selectin expression in mice with CLP + curcumin was significantly attenuated compared with CLP in various microcirculatory beds, including brain. Reduction in platelet adhesion was predominantly via modulation of endothelium by curcumin. CONCLUSION: Curcumin pre-treatment modulates leukocyte and platelet adhesion and BBB dysfunction in mice with CLP via P-selectin expression and improves survival in mice with CLP.

Histone deacetylase inhibitors modulate renal disease in the MRL-lpr/lpr mouse.

Studies in human systemic lupus erythematosus (SLE) suggest a possible role for histone deacetylases (HDACs) in skewed gene expression and disease pathogenesis. We used the MRL-lpr/lpr murine model of lupus to demonstrate that HDACs play a key role in the heightened levels of both Th1 and Th2 cytokine expression that contribute to disease. The availability of specific HDAC inhibitors (HDIs) such as trichostatin A (TSA) and suberonylanilide hydroxamic acid (SAHA) permits the study of the role of HDACs in gene regulation. Our results indicate that HDIs downregulate IL-12, IFN-gamma, IL-6, and IL-10 mRNA and protein levels in MRL-lpr/lpr splenocytes. This effect on gene transcription is associated with an increased accumulation of acetylated histones H3 and H4 in total cellular chromatin. To elucidate the in vivo effects of TSA on lupuslike disease, we treated MRL-lpr/lpr mice with TSA (0.5 mg/kg/d) for 5 weeks. Compared with vehicle-treated control mice, TSA-treated mice exhibited a significant reduction in proteinuria, glomerulonephritis, and spleen weight. Taken together, these findings suggest that increased expression of HDACs leading to an altered state of histone acetylation may be of pathologic significance in MRL-lpr/lpr mice. In addition, TSA or other HDIs may have therapeutic benefit in the treatment of SLE.

mCAF: a multi-dimensional clustering algorithm for friends of social network services.

In recent years, social network services have grown rapidly. The number of friends of each user using social network services has also increased significantly and is so large that clustering and managing these friends has become difficult. In this paper, we propose an algorithm called mCAF that automatically clusters friends. Additionally, we propose methods that define the distance between different friends based on different sets of measurements. Our proposed mCAF algorithm attempts to reduce the effort and time required for users to manage their friends in social network services. The proposed algorithm could be more flexible and convenient by implementing different privacy settings for different groups of friends. According to our experimental results, we find that the improved ratios between mCAF and SCAN are 35.8 % in similarity and 84.9 % in F 1 score.

IoT Big-Data Centred Knowledge Granule Analytic and Cluster Framework for BI Applications: A Case Base Analysis.

The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering of knowledge granules represent highly thought-provoking application possibilities. The objective of the present work is to inspect the structural analysis and clustering of complex knowledge granules in an IoT big-data environment. In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application. Our work implements neuro-fuzzy analytic architecture rather than a standard fuzzified approach to discover the complex knowledge granules. Furthermore, we implement an enhanced knowledge granule clustering (e-KGC) mechanism that is more elastic than previous techniques when assembling the tactical and explicit complex knowledge granules from IoT big-data arrays. The analysis and discussion presented here show that the proposed framework and mechanism can be implemented to extract knowledge granules from an IoT big-data array in such a way as to present knowledge of strategic value to executives and enable knowledge users to perform further BI actions.

Proteomic and genomic approaches reveal critical functions of H3K9 methylation and heterochromatin protein-1γ in reprogramming to pluripotency.

Reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) involves a marked reorganization of chromatin. To identify post-translational histone modifications that change in global abundance during this process, we have applied a quantitative mass-spectrometry-based approach. We found that iPSCs, compared with both the starting fibroblasts and a late reprogramming intermediate (pre-iPSCs), are enriched for histone modifications associated with active chromatin, and depleted for marks of transcriptional elongation and a subset of repressive modifications including H3K9me2/me3. Dissecting the contribution of H3K9 methylation to reprogramming, we show that the H3K9 methyltransferases Ehmt1, Ehmt2 and Setdb1 regulate global H3K9me2/me3 levels and that their depletion increases iPSC formation from both fibroblasts and pre-iPSCs. Similarly, we find that inhibition of heterochromatin protein-1γ (Cbx3), a protein known to recognize H3K9 methylation, enhances reprogramming. Genome-wide location analysis revealed that Cbx3 predominantly binds active genes in both pre-iPSCs and pluripotent cells but with a strikingly different distribution: in pre-iPSCs, but not in embryonic stem cells, Cbx3 associates with active transcriptional start sites, suggesting a developmentally regulated role for Cbx3 in transcriptional activation. Despite largely non-overlapping functions and the predominant association of Cbx3 with active transcription, the H3K9 methyltransferases and Cbx3 both inhibit reprogramming by repressing the pluripotency factor Nanog. Together, our findings demonstrate that Cbx3 and H3K9 methylation restrict late reprogramming events, and suggest that a marked change in global chromatin character constitutes an epigenetic roadblock for reprogramming.

The podosome marker protein Tks5 regulates macrophage invasive behavior.

Tks5 is a Src substrate and adaptor protein previously recognized for its regulation of cancer cell invasion through modulation of specialized adhesion structures called podosomes/invadopodia. Here we show for the first time that Tks5 localizes to the podosomes of primary macrophages, and that Tks5 protein levels increase concurrently with podosome deposition during the differentiation of monocytes into macrophages. Similar results are reported for model THP-1 cells, which differentiate into macrophages and form proteolytically active podosomes in response to a PKC signaling agonist (PMA) and with sensitivity to a PKC inhibitor (bisindolylmaleimide). Genetic manipulation of Tks5 expression (silencing and overexpression) in stable THP-1 cell lines does not independently alter this macrophage differentiation process. Nor do these cells lose the ability to focalize F-actin and its accessory proteins into podosome-like structures following PMA treatment. However, Tks5 directly controls podosome-associated gelatin degradation and invasion through collective changes in adhesion, chemotaxis, and the expression/proteolytic activity of MMP9. The Src family kinase-dependent phosphorylation of Tks5 is also implicated in the regulation of THP-1 macrophage invasive behavior. These results therefore define a previously unappreciated function of Tks5 signaling specific to the functional attributes of the macrophage podosome in adhesion, motility, and extracellular matrix-remodeling.

The effect of epigenetic therapy on congenital neurogenic bladders--a pilot study.

OBJECTIVES: To demonstrate that human smooth muscle cells derived from neurogenic bladders produce more collagen in vitro than smooth muscle cells derived from normal bladders, and that epigenetic therapy may normalize this increased collagen production. METHODS: Human smooth muscle cells from normal (n = 3) and neurogenic bladders (n = 3) were cultured in normal culture media and at different concentrations of the histone deacetylase inhibitors trichostatin A, valproic acid, and the DNA methylation inhibitor 5-azacytidine (5-aza). Collagen type I and III gene expression was measured using real-time quantitative reverse transcription-polymerase chain reaction after varying doses of drug exposure. Cell viability was measured using trypan blue. RESULTS: The smooth muscle cells from neurogenic bladders released significantly more collagen than the normal bladder cells (mean 4.1 vs 1.8 microg/mL in control media) when grown in normal conditions. Treatment with trichostatin A at 50 ng/mL decreased the collagen level in cells from neurogenic bladders to almost normal levels (2.1 microg/mL). In addition, valproic acid treatment decreased collagen types I and III gene expression relative to controls, with maximal effect at 300 mg/mL. These treatments had little effect on cell viability. CONCLUSIONS: Histone deacetylase inhibitors decreased collagen production of smooth muscle cells from neurogenic bladders in vitro. These agents may be a means of effectively preventing bladder fibrosis in patients with this condition.

Inactivation of NuRD component Mta2 causes abnormal T cell activation and lupus-like autoimmune disease in mice.

Dynamic changes in chromatin structure through ATP-dependent remodeling and covalent modifications on histones play important roles in transcription regulation. Among the many chromatin modifiers identified, the NuRD (nucleosome remodeling histone deacetylase) complex is unique because it possesses both nucleosome remodeling and histone deacetylase activities. To understand the biological function of the NuRD complex, we generated a knock-out mouse model of the Mta2 (metastasis-associated protein 2) gene, which encodes a NuRD-specific component. Mta2 null mice exhibited partial embryonic lethality. The surviving mice developed lupus-like autoimmune symptoms including skin lesions, bodyweight loss, glomerulonephritis, liver inflammation, and production of autoantibodies. Transplantation of bone marrow cells from Mta2 null mice recapitulated some of the symptoms including skin lesion and bodyweight loss in the recipient mice. Mta2 null T lymphocytes showed normal development but hyperproliferation upon stimulation, which correlates with hyperinduction of interleukin (IL)-2, IL-4, and interferon (IFN)-gamma. T cell hyperproliferation, but not other autoimmune symptoms, was observed in T cell-specific Mta2 knock-out mice. Mta2 null T cells produced more IL-4 and IFN-gamma under Th2 activation conditions, but normal levels of IL-4 and IFN-gamma under Th1 activation conditions. Furthermore, we found that IL-4 is a direct target gene of Mta2. Our study suggests that Mta2/NuRD is involved in modulating IL-4 and IFN-gamma expression in T cell immune responses, and gene expression in non-T cells plays an important role in controlling autoimmunity.

Biologic activity and safety of belimumab, a neutralizing anti-B-lymphocyte stimulator (BLyS) monoclonal antibody: a phase I trial in patients with systemic lupus erythematosus.

INTRODUCTION: This trial evaluated the safety, biologic activity, and pharmacokinetics of belimumab, a fully human monoclonal antibody that inhibits the biologic activity of the soluble form of the essential B-cell survival factor B-lymphocyte stimulator (BLyS) in patients with systemic lupus erythematosus (SLE). METHODS: Seventy patients with mild-to-moderate SLE were enrolled in a phase I, double-blind, randomized study and treated with placebo (n = 13) or belimumab (n = 57) at four different doses (1.0, 4.0, 10, and 20 mg/kg) as a single infusion or two infusions 21 days apart. Patients were followed for 84 to 105 days to assess adverse events, pharmacokinetics, peripheral blood B-cell counts, serology, and SLE disease activity. Data from the study were summarized using descriptive statistics. chi2 type tests were used to analyze discrete variables. The Kruskal-Wallis test, the Wilcoxon test, and the analysis of covariance were used to analyze the continuous variables, as appropriate. The analysis was performed on all randomized patients who received study agent. RESULTS: The incidences of adverse events and laboratory abnormalities were similar among the belimumab and placebo groups. Belimumab pharmacokinetics were linear across the 1.0 to 20 mg/kg dose range. Long terminal elimination half-life (8.5 to 14.1 days), slow clearance (7 ml/day per kg), and small volume of distribution (69 to 112 ml/kg) were consistent with a fully human antibody. Significant reductions in median percentages of CD20+ B cells were observed in patients treated with a single dose of belimumab versus placebo (day 42: P = 0.0042; and day 84: P = 0.0036) and in patients treated with two doses of belimumab versus placebo (day 105: P = 0.0305). SLE disease activity did not change after one or two doses of belimumab. CONCLUSIONS: Belimumab was well tolerated and reduced peripheral B-cell levels in SLE patients. These data support further studies of belimumab in autoimmune disorders.