Effect of prenatal exposure to bisphenol a on the vagina of albino rats: immunohistochemical and ultrastructural study

Background: Bisphenol-A (BPA) is an industrial chemical, used to manufacture polycarbonate and numerous plastic articles. It has been found to cause biological effects, mimic that of oestrogen. It belongs to a group of chemicals termed “endocrine disruptors” able to disrupt the chemical messenger system in the body. Aim of the study was to demonstrate the biological effects of BPA on the vagina of female rats, with the prediction of the neoplastic changes in relation to its potential impact. Materials and methods: Sprague-Dawley gravid dams were divided into three groups (10 per group): G1 — control group had an equivalent volume of sesame oil to that taken in the treated groups, G2 — group was administered by gavage 0.1 mg BPA/kg body weight (low-dose group) per day, and G3 — group was administered 50 mg BPA/kg body weight (high-dose group) per day, dissolved in sesame oil. Treatment was carried out on gestation days 10 through 20. The female offsprings of each group were weaned at day 21 and the vagina was dissected when became 3 months old for histological, immunohistochemical analysis (for detection of oestrogen receptors a [ERa], and the proliferation marker Ki-67), and ultrastructural study. Results: The low dose group showed degeneration of the epithelial lining with focal patches of decreased epithelial layers. The high dose group revealed cytoplasmic hydropic degeneration, and the pyknotic nuclei of epithelial cells. Oestrogen receptors demonstrated a significant decrease of positive cells in low dose treated group and this decrease markedly accentuated in the high dose one. Positive nuclei for Ki-67 were markedly increased with increasing doses of BPA. Electron microscopic study revealed cytoplasmic degeneration, vacuolation and mitochondrial degeneration in both treated groups. Conclusions: BPA showed an obvious mix of degenerative and proliferative histological changes and clear damage of the cellular organelles. This stressful condition may predispose to neoplastic changes of the vagina.

Decentralized Federated Learning Over Slotted ALOHA Wireless Mesh Networking

Federated Learning (FL) presents a mechanism to allow decentralized training for machine learning (ML) models inherently enabling privacy preservation. The classical FL is implemented as a client-server system, which is known as Centralised Federated Learning (CFL). There are challenges inherent in CFL since all participants need to interact with a central server resulting in a potential communication bottleneck and a single point of failure. In addition, it is difficult to have a central server in some scenarios due to the implementation cost and complexity. This study aims to use Decentralized Federated learning (DFL) without a central server through one-hop neighbours. Such collaboration depends on the dynamics of communication networks, e.g., the topology of the network, the MAC protocol, and both large-scale and small-scale fading on links. In this paper, we employ stochastic geometry to model these dynamics explicitly, allowing us to quantify the performance of the DFL. The core objective is to achieve better classification without sacrificing privacy while accommodating for networking dynamics. In this paper, we are interested in how such topologies impact the performance of ML when deployed in practice. The proposed system is trained on a well-known MINST dataset for benchmarking, which contains labelled data samples of 60K images each with a size $28\times 28$ pixels, and 1000 random samples of this MNIST dataset are assigned for each participant’ device. The participants’ devices implement a CNN model as a classifier model. To evaluate the performance of the model, a number of participants are randomly selected from the network. Due to randomness in the communication process, these participants interact with the random number of nodes in the neighbourhood to exchange model parameters which are subsequently used to update the participants’ individual models. These participants connected successfully with a varying number of neighbours to exchange parameters and update their global models. The results show that the classification prediction system was able to achieve higher than 95% accuracy using the three different model optimizers in the training settings (i.e., SGD, ADAM, and RMSprop optimizers). Consequently, the DFL over mesh networking shows more flexibility in IoT systems, which reduces the communication cost and increases the convergence speed which can outperform CFL

Synthesis and characterization of cellulose acetate-hydroxyapatite micro and nano composites membranes for water purification and biomedical applications

In this work, we report facile synthesis and characterization of new cellulose acetate-hydroxyapatite membranes for water purification and biomedical applications. The membranes were synthesized from a polymer solution in N, N’-dimethylformamide (12% wt.) where different concentrations of hydroxyapatite (1, 2, 4% wt. based on the amount of polymer) were dispersed using sonication. The synthesis of membranes was carried out by precipitation employing phase inversion using deionized water. The morphological and structural characterization of the synthesized membranes was carried out using SEM, EDS and FT-IR. Thermal characterization (TGA & DTG) and water flows analysis of the synthesized membranes was also carried out. The SEM analysis confirmed the presence of hydroxyapatite micro/nanostructured particles in the membrane as well as significant changes in the morphology of the membranes surface. The presence of inorganic compounds was also found to influence the thermal or hydrodynamic properties of the composite membranes, leading to a more stable hydrodynamic behavior, flow variation in time being much lower compared to the control membrane of cellulose acetate

Pegylated interferon alfa-2a for polycythemia vera or essential thrombocythemia resistant or intolerant to hydroxyurea

Prior studies have reported high response rates with recombinant interferon-a (rIFN-a) therapy in patients with essential thrombocythemia (ET) and polycythemia vera (PV). To further define the role of rIFN-a,we investigated the outcomes of pegylated-rIFN-a2a (PEG) therapy in ET and PV patients previously treated with hydroxyurea (HU). The Myeloproliferative Disorders Research Consortium (MPD-RC)-111 study was an investigator-initiated, international, multicenter, phase 2 trial evaluating the ability of PEG therapy to induce complete (CR) and partial (PR) hematologic responses in patients with high-risk ET or PVwho were either refractory or intolerant to HU. The study included 65 patients with ET and 50 patients with PV. The overall response rates (ORRs; CR/PR) at 12 monthswere 69.2%(43.1% and 26.2%) in ET patients and 60% (22% and 38%) in PV patients. CR rates were higher in CALR-mutated ET patients (56.5% vs 28.0%; P 5 .01), compared with those in subjects lacking a CALR mutation. The median absolute reduction in JAK2V617F variant allele fraction was 26% (range, 284%to 47%) in patients achieving a CR vs 14%(range, 218% to 56%) in patients with PR or nonresponse (NR). Therapy was associated with a significant rate of adverse events (AEs); most were manageable, and PEG discontinuation related to AEs occurred in only 13.9% of subjects. We conclude that PEG is an effective therapy for patients with ET or PV who were previously refractory and/or intolerant of HU

Particle swarm optimization for the Steiner tree in graph and delay-constrained multicast routing problems

This paper presents the first investigation on applying a particle swarm optimization (PSO) algorithm to both the Steiner tree problem and the delay constrained multicast routing problem. Steiner tree problems, being the underlining models of many applications, have received significant research attention within the meta-heuristics community. The literature on the application of meta-heuristics to multicast routing problems is less extensive but includes several promising approaches. Many interesting research issues still remain to be investigated, for example, the inclusion of different constraints, such as delay bounds, when finding multicast trees with minimum cost. In this paper, we develop a novel PSO algorithm based on the jumping PSO (JPSO) algorithm recently developed by Moreno-Perez et al. (Proc. of the 7th Metaheuristics International Conference, 2007), and also propose two novel local search heuristics within our JPSO framework. A path replacement operator has been used in particle moves to improve the positions of the particle with regard to the structure of the tree. We test the performance of our JPSO algorithm, and the effect of the integrated local search heuristics by an extensive set of experiments on multicast routing benchmark problems and Steiner tree problems from the OR library. The experimental results show the superior performance of the proposed JPSO algorithm over a number of other state-of-the-art approaches

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Measurement of the mass difference between top quark and antiquark in pp collisions at root s=8 TeV

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