Anti-pPKCθ (T538) Delivery via Cell Penetrating Peptide Mimics as a Novel Treatment of Aplastic Anemia

The objective of this study is to deliver anti-pPKCθ (T538) into T cells (hPBMCs) by using cell penetrating peptide mimics (CPPMs) to neutralize PKCθ activity both in vitro and in vivo, with the eventual goal of treating aplastic anemia (AA). AA is an immune-mediated bone marrow failure disease caused by T helper type 1 (Th1) autoimmune responses, which destroy blood cell progenitors. It was previously reported that protein kinase C theta (PKCθ), expressed specifically in T cells, plays an important role in T cell signaling by mediating Th1 differentiation. Mice treated with Rottlerin, a pharmacological inhibitor of PKCθ, are rescued from the disease when PKCθ phosphorylation was inhibited. Furthermore, humanized antibodies are increasingly gaining attention as therapies. The delivery of antibodies could be achieved via cell penetrating peptides (CPPs), which are able to internalize cargo into cells. Here, we designed, synthesized and characterized CPPMs to increase delivery efficiency of an antibody against phosphorylated PKCθ (T538), which subsequently interfered with the function of the kinase. We designed an in vitro delivery method for the CPPM/Anti-pPKCθ complex then assessed T cell activation and AA disease marker expression. Also, we generated an in vivo humanized mouse model of AA and tested the complex for delivery and effect on survival of these mice. Altogether the results reveal that PKCθ may be an optimal target for bone marrow failure treatment and intracellular antibody delivery may represent a novel approach for AA treatment

Inositols: From established knowledge to novel approaches

Myo-inositol (myo-Ins) and D-chiro-inositol (D-chiro-Ins) are natural compounds involved in many biological pathways. Since the discovery of their involvement in endocrine signal transduction, myo-Ins and D-chiro-Ins supplementation has contributed to clinical approaches in ameliorating many gynecological and endocrinological diseases. Currently both myo-Ins and D-chiro-Ins are well-tolerated, effective alternative candidates to the classical insulin sensitizers, and are useful treatments in preventing and treating metabolic and reproductive disorders such as polycystic ovary syndrome (PCOS), gestational diabetes mellitus (GDM), and male fertility disturbances, like sperm abnormalities. Moreover, besides metabolic activity, myo-Ins and D-chiro-Ins deeply influence steroidogenesis, regulating the pools of androgens and estrogens, likely in opposite ways. Given the complexity of inositol-related mechanisms of action, many of their beneficial effects are still under scrutiny. Therefore, continuing research aims to discover new emerging roles and mechanisms that can allow clinicians to tailor inositol therapy and to use it in other medical areas, hitherto unexplored. The present paper outlines the established evidence on inositols and updates on recent research, namely concerning D-chiro-Ins involvement into steroidogenesis. In particular, D-chiro-Ins mediates insulin-induced testosterone biosynthesis from ovarian thecal cells and directly affects synthesis of estrogens by modulating the expression of the aromatase enzyme. Ovaries, as well as other organs and tissues, are characterized by a specific ratio of myo-Ins to D-chiro-Ins, which ensures their healthy state and proper functionality. Altered inositol ratios may account for pathological conditions, causing an imbalance in sex hormones. Such situations usually occur in association with medical conditions, such as PCOS, or as a consequence of some pharmacological treatments. Based on the physiological role of inositols and the pathological implications of altered myo-Ins to D-chiro-Ins ratios, inositol therapy may be designed with two different aims: (1) restoring the inositol physiological ratio; (2) altering the ratio in a controlled way to achieve specific effects

The genetic architecture of membranous nephropathy and its potential to improve non-invasive diagnosis

Membranous Nephropathy (MN) is a rare autoimmune cause of kidney failure. Here we report a genome-wide association study (GWAS) for primary MN in 3,782 cases and 9,038 controls of East Asian and European ancestries. We discover two previously unreported loci, NFKB1 (rs230540, OR = 1.25, P = 3.4 × 10-12) and IRF4 (rs9405192, OR = 1.29, P = 1.4 × 10-14), fine-map the PLA2R1 locus (rs17831251, OR = 2.25, P = 4.7 × 10-103) and report ancestry-specific effects of three classical HLA alleles: DRB1*1501 in East Asians (OR = 3.81, P = 2.0 × 10-49), DQA1*0501 in Europeans (OR = 2.88, P = 5.7 × 10-93), and DRB1*0301 in both ethnicities (OR = 3.50, P = 9.2 × 10-23 and OR = 3.39, P = 5.2 × 10-82, respectively). GWAS loci explain 32% of disease risk in East Asians and 25% in Europeans, and correctly re-classify 20-37% of the cases in validation cohorts that are antibody-negative by the serum anti-PLA2R ELISA diagnostic test. Our findings highlight an unusual genetic architecture of MN, with four loci and their interactions accounting for nearly one-third of the disease risk

Investigation of subsynchronous resonance risk in the 380 kv Turkish electric network

Subsynchronous resonance (SSR) occurs when a resonant frequency of a series compensated transmission system interacts with a natural frequency of the turbine prime mover. This form of SSR is referred to as torsional interaction which, under certain conditions, may become self-excited and cause serious damage to electrical equipment and turbine shafts. The presence of a thermal power plant (Kangal) in the close vicinity of a group of series capacitors in Eastern Turkey necessitated a careful investigation of SSR phenomena in the 380-kV network. Extensive computer simulations, utilizing both a frequency-scanning approach and time-domain analysis, revealed that under normal operating conditions the risk is minimal. However, due to inaccuracies in both the machine data and system data, and to the assumptions utilized, the results are non conclusive

ACCURATE DETERMINATION OF NEUTRAL CONDUCTOR CURRENT DISTRIBUTION ALONG LOW-VOLTAGE FEEDERS

Accurate determination of the neutral conductor current distribution along a low voltage distribution feeder is vitally important from two perspectives. The first is to investigate the voltage profile along the feeder. The second is directly related to the economical feasibility of the system (i.e. total losses occurring on the feeder). Due to numerous reasons, actual measurements are case specific. Hence, a typical low voltage feeder is modeled in detail and simulated with randomly assigned actual residential load data obtained from energy consumption measurements. Results indicate better voltage regulation and economic advantages of neutral conductors selected in the same cross-section as phase conductors

A PROPOSED APPLICATION OF AN INDUSTRIAL DOS COMPUTER FOR DISTRIBUTION SUBSTATION MONITORING AND CONTROL

This paper presents the design and implementation of an intelligent controller intended for use in distribution substations to perform monitoring and control duties within the framework of distribution automation needs. The hardware of the developed controller is a DOS based industrial computer running on ECB-BUS. The application software handles all input/output tasks, data collection, manipulation and control decisions with its flexible structure. This embedded controller measures bus voltage, transformer and feeder currents and calculates the real and reactive power, power factor, frequency, and total harmonic distortion of voltage and current. In addition to its local and remote data acquisition and monitoring functions by means of console and SCADA outputs, the system, through its relay outputs, is capable of performing automation tasks such as integrated Volt/Var control, overload and underfrequency detection and load shedding at the substation level. This reliable, high capacity and low cost system is completely programmable so that it can handle new requirements with new configurations easily

Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning

Two established approaches to engineer adaptive systems are architecture-based adaptation that uses a Monitor-Analysis-Planning-Executing (MAPE) loop that reasons over architectural models (aka Knowledge) to make adaptation decisions, and control-based adaptation that relies on principles of control theory (CT) to realize adaptation. Recently, we also observe a rapidly growing interest in applying machine learning (ML) to support different adaptation mechanisms. While MAPE and CT have particular characteristics and strengths to be applied independently, in this paper, we are concerned with the question of how these approaches are related with one another and whether combining them and supporting them with ML can produce better adaptive systems. We motivate the combined use of different adaptation approaches using a scenario of a cloud-based enterprise system and illustrate the analysis when combining the different approaches. To conclude, we offer a set of open questions for further research in this interesting area