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Monomeric serum immunoglobulin A (IgA) can contribute to the development of various autoimmune diseases, but the regulation of serum IgA effector functions is not well defined. Here, we show that the two IgA subclasses (IgA1 and IgA2) differ in their effect on immune cells due to distinct binding and signaling properties. Whereas IgA2 acts pro-inflammatory on neutrophils and macrophages, IgA1 does not have pronounced effects. Moreover, IgA1 and IgA2 have different glycosylation profiles, with IgA1 possessing more sialic acid than IgA2. Removal of sialic acid increases the pro-inflammatory capacity of IgA1, making it comparable to IgA2. Of note, disease-specific autoantibodies in patients with rheumatoid arthritis display a shift toward the pro-inflammatory IgA2 subclass, which is associated with higher disease activity. Taken together, these data demonstrate that IgA effector functions depend on subclass and glycosylation, and that disturbances in subclass balance are associated with autoimmune disease. Immunoglobulin A (IgA) has two subclasses, IgA1 and IgA2, but differential effects on inflammation are unclear. Here the authors show that IgA2, when compared with IgA1, has stronger pro-inflammatory functions associated with changed glycosylation and higher disease scores in patients with rheumatoid arthritis.

Alterations of cell death pathways, including apoptosis and the neutrophil specific kind of death called NETosis, can represent a potential source of autoantigens. Defects in the clearance of apoptotic cells may be responsible for the initiation of systemic autoimmunity in several chronic inflammatory diseases, including systemic lupus erythematosus (SLE). Autoantigens are released mainly from secondary necrotic cells because of a defective clearance of apoptotic cells or an inefficient degradation of DNA-containing neutrophil extracellular traps (NETs). These modified autoantigens are presented by follicular dendritic cells to autoreactive B cells in germinal centers of secondary lymphoid organs. This results in the loss of self-tolerance and production of autoantibodies, a unifying feature of SLE. Immune complexes (IC) are formed from autoantibodies bound to uncleared cellular debris in blood or tissues. Clearance of IC by blood phagocytes, macrophages, and dendritic cells leads to proinflammatory cytokine secretion. In particular, plasmacytoid dendritic cells produce high amounts of interferon-α upon IC uptake, thereby contributing to the interferon signature of patients with SLE. The clearance of antinuclear IC via Fc-gamma receptors is considered a central event in amplifying inflammatory immune responses in SLE. Along with this, the accumulation of cell remnants represents an initiating event of the etiology, while the subsequent generation of autoantibodies against nuclear antigens (including NETs) results in the perpetuation of inflammation and tissue damage in patients with SLE. Here, we discuss the implications of defective clearance of apoptotic cells and NETs in the development of clinical manifestations in SLE.

Objective Diabetic retinopathy (DR) is a common problem of diabetes, and it is the cause of blindness worldwide. Detection of diabetic radiology disease in the early detection stage is crucial for preventing vision loss. In this work, a deep learning-based binary classification of DR images has been proposed to classify DR images into healthy and unhealthy. Transfer learning-based 20 pre-trained networks have been fine-tuned using a robust dataset of diabetic radiology images. The combined dataset has been collected from three robust databases of diabetic patients annotated by experienced ophthalmologists indicating healthy or non-healthy diabetic retina images. Method This work has improved robust models by pre-processing the DR images by applying a denoising algorithm, normalization, and data augmentation. In this work, three rubout datasets of diabetic retinopathy images have been selected, named DRD- EyePACS, IDRiD, and APTOS-2019, for the extensive experiments, and a combined diabetic retinopathy image dataset has been generated for the exhaustive experiments. The datasets have been divided into training, testing, and validation sets, and the models use classification accuracy, sensitivity, specificity, precision, F1-score, and ROC-AUC to assess the model's efficiency for evaluating network performance. The present work has selected 20 different pre-trained networks based on three categories: Series, DAG, and lightweight. Results This study uses pre-processed data augmentation and normalization of data to solve overfitting problems. From the exhaustive experiments, the three best pre-trained have been selected based on the best classification accuracy from each category. It is concluded that the trained model ResNet101 based on the DAG category effectively identifies diabetic retinopathy disease accurately from radiological images from all cases. It is noted that 97.33% accuracy has been achieved using ResNet101 in the category of DAG network. Conclusion Based on the experiment results, the proposed model ResNet101 helps healthcare professionals detect retina diseases early and provides practical solutions to diabetes patients. It also gives patients and experts a second opinion for early detection of diabetic retinopathy.

In recent times, Vehicular Ad hoc Network (VANET) has been the focal point of the research community to devise efficient smart transportation systems. VANET provides the key advantage of providing cautionary measures and safety to passengers and drivers. With the evolution of fifth-generation (5G) network technology and rapid growth in vehicles, it becomes challenging for conventional VANET to manage large-scale dynamic heterogeneous networks due to their limited flexibility and scalability features. Moreover, the dynamic nature of VANET makes it vulnerable to malicious attacks. Software Defined Networking (SDN) is a technology that provides an integrated improvement over the conventional VANETs. SDN architecture is flexible, programmable, scalable, and provides globally the knowledge of the network. However, its centralized nature makes SDN based VANETs a prime target of attackers, which may adversely impact the VANETs causing life-threatening consequences. To address these issues, this paper presents two novel schemes. Firstly, this paper presents a trusted routing scheme named Jellyfish Chimp Optimization Algorithm (JChOA) for SDN based VANETs. JChOA is designed by amalgamation of the Jellyfish Search Optimization algorithm (JS) and Chimp Optimization algorithm (ChOA). Secondly, this paper presents an attack detection and mitigation scheme named JChOA_RideNN for SDN based VANETs. This attack detection scheme utilizes the Rider Optimization Algorithm based neural network (RideNN) architecture at the SDN controller, where the weighting parameters of RideNN tunned through the use of JChOA. The effectiveness of JChOA routing is evaluated based on the metrics energy and trust value where the performance of JChOA_RideNN is assessed using precision and recall. Moreover, the JChOA routing algorithm attained greater performance with a maximum of 0.947 J energy and 0.462 trust value and JChOA_RideNN attained with a maximum of 93.9% precision, and 93.1% recall than other traditional approaches. The results of the experiments clearly show the effectiveness of the proposed defensive schemes for SDN based VANETs.

In this study, we identified and characterized the potential of a high ratio of bicarbonate to CO2 and a moderately alkaline pH to render neutrophils prone to undergo neutrophil extracellular trap (NET) formation. Both experimental settings increased the rate of spontaneous NET release and potentiated the NET-inducing capacity of phorbol esters (phorbol-2-myristate-13-acetate), ionomycin, monosodium urate, and LPS. In contrast, an acidic environment impaired NET formation both spontaneous and induced. Our findings indicate that intracellular alkalinization of neutrophils in response to an alkaline environment leads to an increase of intracellular calcium and neutrophil activation. We further found that the anion channel blocker DIDS strongly reduced NET formation induced by bicarbonate. This finding suggests that the effects observed are due to a molecular program that renders neutrophils susceptible to NET formation. Inflammatory foci may be characterized by an acidic environment. Our data indicate that NET formation is favored by the higher pH at the border regions of inflamed areas. Moreover, our findings highlight the necessity for strict pH control during assays of NET formation.

The small signal model of MOSFET is a must for implementation of analog/digital circuits. The non-quasi-static (NQS) model is well known and provides accurate parameters for MOSFET. In the present work, extrinsic and intrinsic NQS model parameters were extracted for 20 nm Gate Stacked Junction-less Accumulation Mode (GSJAM) MOSFET using two-port admittance parameters. Further, for analog/RF applications, the first order active high pass filter (HPF), low pass filter (LPF) and second order active HPF, LPF are implemented using 20 nm GSJAM MOSFET. The first order and second order active filters are implemented for 10 GHz circuit applications. For amplifying the processed filtered input signal, a CMOS single stage common source voltage amplifier is used in the output circuit. Filter circuits use GSJAM N-type MOSFET as an active load in conjunction with a passive capacitor. With cut-off frequency, further bode-plot analysis of the low pass filter and high pass filter circuits is conducted. For numerical simulation, the well-known silvaco CAD tool is used.

For low-power circuit applications, the performance of the circuit is significantly influenced by the MOSFET's analog/RF and non-linearity properties. Gate-all-around junction-less accumulation mode MOSFETs (JAM) are now the perfect choice for low-power circuit applications. In the present work, the gate-stack engineering method is used for gate-all-around junction-less accumulation mode MOSFET (GSJAM) to improve the analog/RF characteristics. The analog/RF and linearity parameter analyses are numerically performed for a 20 nm channel length gate-all-around gate-stacked junction-less MOSFET using an ATLAS 3D device simulator. The comparative analysis of these analog/RF and linearity parameters is also done. The gate stack engineering shows significant improvements in analog/RF parameters, i.e., trans-conductance (g m ), output resistance (R out ), early voltage (V ea ), intrinsic gain (A V ), trans-conductance frequency product (TFP), gain frequency product (GFP), trans-conductance generation factor (TGF), gain bandwidth product (GBWP), gain trans-conductance frequency product (GTFP), and cut-off frequency (f T ). The results of the simulation investigation show that when GSJM is compared to JAM MOSFET, the values of gm, R out , V ea , and TGF are all 26.37%, 2.24 times, 22.38%, and 20.78% higher, respectively. Also, the gate-stack junction-less MOSFET improves the linearity parameters, i.e., 2nd -order trans-conductance (g m2 ) , 3rd -order trans-conductance (g m3 ), VIP 2 , VIP 3 , IIP 3 , IMD 3 , and 1-dBCP. When comparing GSJAM to JAM MOSFET, the values of VIP2 are 81.63% higher, VIP3 is 1.77 times higher, IIP3 is 6.72 times higher, and 1-dBCP is twice as high. Further, for analog/RF applications, a 20 nm CMOS common-source voltage amplifier circuit using gate-stake junction-less MOSFET has also been designed for a 20 mV and 1 GHz sinusoidal input signal.

Neutrophils respond to various stimuli by decondensing and releasing nuclear chromatin characterized by citrullinated histones as neutrophil extracellular traps (NETs). This achieves pathogen immobilization or initiation of thrombosis, yet the molecular mechanisms of NET formation remain elusive. Peptidyl arginine deiminase-4 (PAD4) achieves protein citrullination and has been intricately linked to NET formation. Here we show that citrullination represents a major regulator of proteolysis in the course of NET formation. Elevated cytosolic calcium levels trigger both peptidylarginine deiminase-4 (PAD4) and calpain activity in neutrophils resulting in nuclear decondensation typical of NETs. Interestingly, PAD4 relies on proteolysis by calpain to achieve efficient nuclear lamina breakdown and chromatin decondensation. Pharmacological or genetic inhibition of PAD4 and calpain strongly inhibit chromatin decondensation of human and murine neutrophils in response to calcium ionophores as well as the proteolysis of nuclear proteins like lamin B1 and high mobility group box protein 1 (HMGB1). Taken together, the concerted action of PAD4 and calpain induces nuclear decondensation in the course of calcium-mediated NET formation.

The enlightenment of the formation of neutrophil extracellular traps (NETs) as a part of the innate immune system shed new insights into the pathologies of various diseases. The initial idea that NETs are a pivotal defense structure was gradually amended due to several deleterious effects in consecutive investigations. NETs formation is now considered a double-edged sword. The harmful effects are not limited to the induction of inflammation by NETs remnants but also include occlusions caused by aggregated NETs (aggNETs). The latter carries the risk of occluding tubular structures like vessels or ducts and appear to be associated with the pathologies of various diseases. In addition to life-threatening vascular clogging, other occlusions include painful stone formation in the biliary system, the kidneys, the prostate, and the appendix. AggNETs are also prone to occlude the ductal system of exocrine glands, as seen in ocular glands, salivary glands, and others. Last, but not least, they also clog the pancreatic ducts in a murine model of neutrophilia. In this regard, elucidating the mechanism of NETs-dependent occlusions is of crucial importance for the development of new therapeutic approaches. Therefore, the purpose of this review is to address the putative mechanisms of NETs-associated occlusions in the pathogenesis of disease, as well as prospective treatment modalities.

IntroductionTypical Western diet, rich in salt, contributes to autoimmune disease development. However, conflicting reports exist about the effect of salt on neutrophil effector functions, also in the context of arthritis.MethodsWe investigated the effect of sodium chloride (NaCl) on neutrophil viability and functions in vitro , and in vivo employing the murine K/BxN-serum transfer arthritis (STA) model.Results and discussionThe effects of NaCl and external reactive oxygen species (H2O2) were further examined on osteoclasts in vitro. Hypertonic sodium-rich media caused primary/secondary cell necrosis, altered the nuclear morphology, inhibited phagocytosis, degranulation, myeloperoxidase (MPO) peroxidation activity and neutrophil extracellular trap (NET) formation, while increasing total ROS production, mitochondrial ROS production, and neutrophil elastase (NE) activity. High salt diet (HSD) aggravated arthritis by increasing inflammation, bone erosion, and osteoclast differentiation, accompanied by increased NE expression and activity. Osteoclast differentiation was decreased with 25 mM NaCl or 100 nM H2O2 addition to isotonic media. In contrast to NaCl, external H2O2 had pro-resorptive effects in vitro . We postulate that in arthritis under HSD, increased bone erosion can be attributed to an enhanced oxidative milieu maintained by infiltrating neutrophils, rather than a direct effect of NaCl.