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Signaling between cells in the anterior (A) and posterior (P) compartments directs Drosophila wing disc development and is dependent on expression of the homeodomain transcription factor Engrailed (En) in P cells. Downstream of en, posteriorly expressed He

Introduction: Oligonucleotide (ON) therapy is a promising treatment for a wide range of complex genetic disorders, but inefficient intracellular ON delivery has hindered clinical translation. Hollow silica nanoparticles (HSN) hold potential as effective ON delivery vehicles since ON can be encapsulated in the hollow core in situ where they are protected from degradation by eg nucleases. However, HSN must be modified to allow degradation and subsequent (sub)cellular ON release. In this report, we investigated the use of ion and fluorescent dye co-doping in the HSN silica matrix to enable HSN degradability and in vitro visualization., Methods: HSN were core encapsulated with ON, doped with Ca 2+ , Cu 2+ , Zn 2+ , Se 2+ and Sr 2+ ions and co-condensed with rhodamine b isothiocyanate (RITC) by a modified reverse microemulsion method. HSN were physiochemically characterized and their biological activity such as uptake and toxicity were evaluated in mesenchymal stem cells (hMSCs)., Results: We successfully doped HSN with RITC and Ca 2+ , Cu 2+ , Zn 2+ and Sr 2+ ions. We observed that doping HSN with Ca 2+ and Sr 2+ enhanced RITC incorporation while ON encapsulation in HSN increased Cu 2+ and Zn 2+ doping efficiency. Moreover, our dual-doped HSN demonstrated controlled ON release in the presence of intracellular mimicking levels of glutathione (GSH) and limited release in the absence of GSH over 14 days. HSN were biocompatible in hMSCs up to 300 µg/mL except for Cu 2+ doped HSNs which were cytotoxic even at ~10 µg/mL. HSN uptake was influenced by the dopant ion, DNA encapsulation, and HSN concentration, where Zn-HSN showed the lowest and Sr-HSN and Se-HSN D, the highest uptake in hMSCs., Conclusion: We report a straightforward one-pot procedure to create ion and fluorescent dye co-doped HSN that can efficiently incorporate ON, as promising new gene vectors., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper., (© 2024 Trayford et al.)

Introduction: Psoriasis is a chronic inflammatory autoimmune skin disease. Several treatment options are available including topical and systemic options. Methotrexate was the main systemic medication in treating severe psoriasis, yet adverse events can limit its use. Leflunomide is an isoxazole derivative that inhibits the synthesis of pyrimidines, and subsequently inhibits RNA and DNA synthesis., Objectives: As available data directly comparing MTX to leflunomide in psoriasis are lacking, this double blinded study was designed to compare the efficacy of methotrexate versus leflunomide in the treatment of moderate to severe psoriasis., Methods: The study included 40 patients (25 males and 15 females) with chronic plaque psoriasis. s. Patients were randomly assigned to one of two equal groups, group A for subcutaneous methotrexate injections and group B for leflunomide (loading dose 100mg daily for the first 3 days, then 20 mg daily for 3 months. Disease severity was determined by psoriasis area and severity index (PASI) score before and at the end of treatment The treatment response was evaluated at the baseline and weeks 4, 8 and 12 PASI score., Results: Both groups were matching at the baseline in aspects of gender, age, disease duration and PASI scores Both medications yielded comparable results with no significant difference between both groups in PASI score neither in side effects., Conclusions: Leflunomide can be as effective as methotrexate in treatment of moderate to severe psoriasis.

Mouse models are a critical tool for studying human diseases, particularly developmental disorders 1 . However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse 2 . Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing 3 to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions 4,5 . We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be 'decomposable' through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution., (© 2023. The Author(s).)

The use of cardiovascular implants is commonplace in clinical practice. However, reproducing the key bioactive and adaptive properties of native cardiovascular tissues with an artificial replacement is highly challenging. Exciting new treatment strategies are under development to regenerate (parts of) cardiovascular tissues directly in situ using immunomodulatory biomaterials. Direct exposure to the bloodstream and hemodynamic loads is a particular challenge, given the risk of thrombosis and adverse remodeling that it brings. However, the blood is also a source of (immune) cells and proteins that dominantly contribute to functional tissue regeneration. This review explores the potential of the blood as a source for the complete or partial in situ regeneration of cardiovascular tissues, with a particular focus on the endothelium, being the natural blood-tissue barrier. We pinpoint the current scientific challenges to enable rational engineering and testing of blood-contacting implants to leverage the regenerative potential of the blood., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Atomic substitution or doping of a bioceramic material hydroxyapatite (HA) with specific ions is an appealing approach for improving its biocompatibility and activity, as well as imparting antibacterial properties. In this study, selenium- and/or copper-substituted hydroxyapatite powders were synthesized by an aqueous precipitation method and using the freeze-drying technique. The molar concentrations of constituents were calculated based on the proposed mechanism whereby selenium (Se 4+ ) ions partially substitute phosphorus (P 5+ ) sites, and copper (Cu 2+ ) ions partially substitute (Ca 2+ ) sites in the HA lattice. Dried precipitated samples were characterized using Inductively coupled plasma optical emission spectroscopy (ICP-OES), X-ray diffraction analysis (XRD), Fourier-transform infrared spectroscopy (FTIR) and Field-emission scanning electron microscopy with energy dispersive X-ray spectroscopy (FESEM-EDX). Accordingly, substitution of Se 4+ and/or Cu 2+ ions took place in the crystal lattice of HA without the formation of any impurities. The presence of sulphur (S 2- ) ions in the hydroxyapatite was detected by ICP-OES in all samples with copper substituted in the lattice. The cytotoxicity of the powders on osteoblastic (MC3T3-E1) cells was evaluated in vitro. Selenium substituted hydroxyapatite (SeHA), at the concentration (200 μg/mL), demonstrated higher populations of the live cells than that of control (cells without powders), suggesting that selenium may stimulate the proliferation of these cells. In addition, the copper substituted hydroxyapatite (CuHA) and the selenium and copper substituted hydroxyapatite (SeCuHA) at the concentrations (200 and 300 μg/mL) and (200 μg/mL), respectively demonstrated better results than the unsubstituted HA. Antimicrobial activity was assessed using a well-diffusion method against Streptococcus mutans and Candida albicans , and superior results has obtained with SeCuHA samples . Presented findings imply that selenium and/or copper substituted modified hydroxyapatite nanoparticles, may be an attractive antimicrobial and cytocompatible substrate to be considered for use in a range of translational applications.

Driver drowsiness is one of the main causes of traffic accidents today. In recent years, driver drowsiness detection has suffered from issues integrating deep learning (DL) with Internet-of-things (IoT) devices due to the limited resources of IoT devices, which pose a challenge to fulfilling DL models that demand large storage and computation. Thus, there are challenges to meeting the requirements of real-time driver drowsiness detection applications that need short latency and lightweight computation. To this end, we applied Tiny Machine Learning (TinyML) to a driver drowsiness detection case study. In this paper, we first present an overview of TinyML. After conducting some preliminary experiments, we proposed five lightweight DL models that can be deployed on a microcontroller. We applied three DL models: SqueezeNet, AlexNet, and CNN. In addition, we adopted two pretrained models (MobileNet-V2 and MobileNet-V3) to find the best model in terms of size and accuracy results. After that, we applied the optimization methods to DL models using quantization. Three quantization methods were applied: quantization-aware training (QAT), full-integer quantization (FIQ), and dynamic range quantization (DRQ). The obtained results in terms of the model size show that the CNN model achieved the smallest size of 0.05 MB using the DRQ method, followed by SqueezeNet, AlexNet MobileNet-V3, and MobileNet-V2, with 0.141 MB, 0.58 MB, 1.16 MB, and 1.55 MB, respectively. The result after applying the optimization method was 0.9964 accuracy using DRQ in the MobileNet-V2 model, which outperformed the other models, followed by the SqueezeNet and AlexNet models, with 0.9951 and 0.9924 accuracies, respectively, using DRQ.

Large structural variations (SV) are a class of mutations that have long been known to cause a wide range of genetic diseases, from rare congenital disease to cancer. Many of these SVs do not directly disrupt disease-related genes and determining causal genotype-phenotype relationships has been challenging to disentangle in the past. This has started to change with our increased understanding of the 3D genome folding. The pathophysiologies of the different types of genetic diseases influence the type of SVs observed and their genetic consequences, and how these are connected to 3D genome folding. We propose guiding principles for interpreting disease-associated SVs based on our current understanding of 3D chromatin architecture and the gene-regulatory and physiological mechanisms disrupted in disease., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Machine learning applications in the medical sector face a lack of medical data due to privacy issues. For instance, brain tumor image-based classification suffers from the lack of brain images. The lack of such images produces some classification problems, i.e. , class imbalance issues which can cause a bias toward one class over the others. This study aims to solve the imbalance problem of the "no tumor" class in the publicly available brain magnetic resonance imaging (MRI) dataset. Generative adversarial network (GAN)-based augmentation techniques were used to solve the imbalance classification problem. Specifically, deep convolutional GAN (DCGAN) and single GAN (SinGAN). Moreover, the traditional-based augmentation techniques were implemented using the rotation method. Thus, several VGG16 classification experiments were conducted, including (i) the original dataset, (ii) the DCGAN-based dataset, (iii) the SinGAN-based dataset, (iv) a combination of the DCGAN and SinGAN dataset, and (v) the rotation-based dataset. However, the results show that the original dataset achieved the highest accuracy, 73%. Additionally, SinGAN outperformed DCGAN by a significant margin of 4%. In contrast, experimenting with the non-augmented original dataset resulted in the highest classification loss value, which explains the effect of the imbalance issue. These results provide a general view of the effect of different image augmentation techniques on enlarging the healthy brain dataset., Competing Interests: The authors declare there are no competing interests., (©2023 Alrumiah et al.)

Limitations with the majority of bone therapeutic treatments include low availability, ethical constraints and low biological compatibility. Although a number of choice materials have been exploited successfully, there has always been scope for improvement as well as development of the next-generation of materials. Herein, scaffolds - developed from gelatin, chitosan and eggshell membranes - were crosslinked using tannic acid, and further infused with selenium and/or copper substituted hydroxyapatite nanoparticles to generate a novel nanocomposite substrate. FESEM images of the nanocomposite scaffolds revealed the presence of interconnected pores, mostly spread over the whole surface of the scaffold, alongside XRD and FTIR profiling that detailed the formation of hydroxyapatite as a sole phase. Moreover, physical characterisation of the nanocomposite confirmed that the hydroxyapatite particulates and the eggshell membrane fibres were uniformly distributed and contributed to the surface roughness of the scaffold. Biocompatibility and cytotoxicity of the novel constructs were assessed using the mouse-derived osteoblastic cell line, MC3T3-E1, and standard cell culture assays. Metabolic activity assessment (i.e. MTS assay), LDH-release profiles and Live/Dead staining demonstrated good cell adhesion, viability, and proliferation rates. Accordingly, this work summarises the successful development of a novel construct which may be exploited as a clinical/therapeutic treatment for bone repair as well as a possible translational application as a novel biomaterial for the drug development pipeline.

Background: Serum Prostate-specific antigen (PSA) has been used for screening and diagnosis of prostate cancer (PCa) but it is burdened by its low accuracy, creating a need for reliable diagnostic markers. Despite prostate-specific membrane antigen (PSMA) and prostate stem cell antigen (PSCA) being widely expressed in the tissue of PCa, no definite conclusion regarding their use as clinical biomarkers due to their lacking organ specificity. Therefore, this study aimed to evaluate the peripheral blood levels of PSMA and PSCA mRNAs and examine their diagnostic significance as non-invasive integrated markers., , Materials and Methods: 125 subjects were enrolled in this study. They were divided into 25 healthy controls, 25 BPH patients, and 75 PCa patients. The expression levels of PSMA and PSCA were determined using quantitative RT- PCR, in addition to measuring serum PSA., , Results: Levels of PSMA and PSCA were over-expressed in PCa patients compared to controls and BPH patients and were found to be associated with increased susceptibility to PCa. Moreover, the diagnostic values of PSMA and PSCA to distinguish PCa patients from BPH patients and controls were inferior to that of PSA. However, the combination of PSMA and PSCA with PSA enhanced the efficacy of the latter., , Conclusion: This study suggests that these genes were associated with malignant susceptibility. Concerning the duality of PSMA-PSA or PSCA-PSA, this implies the significance of their investigation together in peripheral blood of prostate patients.

Regulatory landscapes drive complex developmental gene expression, but it remains unclear how their integrity is maintained when incorporating novel genes and functions during evolution. Here, we investigated how a placental mammal-specific gene, Zfp42, emerged in an ancient vertebrate topologically associated domain (TAD) without adopting or disrupting the conserved expression of its gene, Fat1. In ESCs, physical TAD partitioning separates Zfp42 and Fat1 with distinct local enhancers that drive their independent expression. This separation is driven by chromatin activity and not CTCF/cohesin. In contrast, in embryonic limbs, inactive Zfp42 shares Fat1's intact TAD without responding to active Fat1 enhancers. However, neither Fat1 enhancer-incompatibility nor nuclear envelope-attachment account for Zfp42's unresponsiveness. Rather, Zfp42's promoter is rendered inert to enhancers by context-dependent DNA methylation. Thus, diverse mechanisms enabled the integration of independent Zfp42 regulation in the Fat1 locus. Critically, such regulatory complexity appears common in evolution as, genome wide, most TADs contain multiple independently expressed genes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Clinical pharmacists have a vital role during COVID-19 pandemic in mitigating medication errors, particularly prescribing errors in hospitals. That is owing to the fact that prescribing errors during the COVID-19 pandemic has increased., Aim: This study aimed to evaluate the impact of the clinical pharmacist on the rate of prescribing errors on COVID-19 patients in a governmental hospital., Methods: The study was a pre-post study conducted from March 2020 till September 2020. It included the pre-education phase P0; a retrospective phase where all the prescriptions for COVID-19 patients were revised by the clinical pharmacy team and prescription errors were extracted. Followed by a one-month period; the clinical pharmacy team prepared educational materials in the form of posters and flyers covering all prescribing errors detected to be delivered to physicians. Then, the post-education phase P1; all prescriptions were monitored by the clinical pharmacy team to assess the rate and types of prescribing errors and the data extracted was compared to that from pre-education phase., Results: The number of prescribing errors in P0 phase was 1054 while it was only 148 in P1 Phase. The clinical pharmacy team implemented education phase helped to significantly reduce the prescribing errors from 14.7/1000 patient-days in the P0 phase to 2.56/1000 patient-days in the P1 phase (p-value <0.001)., Conclusion: The clinical pharmacist significantly reduced the rate of prescribing errors in patients with COVID-19 which emphasizes the great role of clinical pharmacists' interventions in the optimization of prescribing in these stressful conditions., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

The SARS-CoV-2 virus has proliferated around the world and caused panic to all people as it claimed many lives. Since COVID-19 is highly contagious and spreads quickly, an early diagnosis is essential. Identifying the COVID-19 patients' mortality risk factors is essential for reducing this risk among infected individuals. For the timely examination of large datasets, new computing approaches must be created. Many machine learning (ML) techniques have been developed to predict the mortality risk factors and severity for COVID-19 patients. Contrary to expectations, deep learning approaches as well as ML algorithms have not been widely applied in predicting the mortality and severity from COVID-19. Furthermore, the accuracy achieved by ML algorithms is less than the anticipated values. In this work, three supervised deep learning predictive models are utilized to predict the mortality risk and severity for COVID-19 patients. The first one, which we refer to as CV-CNN, is built using a convolutional neural network (CNN); it is trained using a clinical dataset of 12,020 patients and is based on the 10-fold cross-validation (CV) approach for training and validation. The second predictive model, which we refer to as CV-LSTM + CNN, is developed by combining the long short-term memory (LSTM) approach with a CNN model. It is also trained using the clinical dataset based on the 10-fold CV approach for training and validation. The first two predictive models use the clinical dataset in its original CSV form. The last one, which we refer to as IMG-CNN, is a CNN model and is trained alternatively using the converted images of the clinical dataset, where each image corresponds to a data row from the original clinical dataset. The experimental results revealed that the IMG-CNN predictive model outperforms the other two with an average accuracy of 94.14%, a precision of 100%, a recall of 91.0%, a specificity of 100%, an F1-score of 95.3%, an AUC of 93.6%, and a loss of 0.22.

Deep learning models have been used in several domains, however, adjusting is still required to be applied in sensitive areas such as medical imaging. As the use of technology in the medical domain is needed because of the time limit, the level of accuracy assures trustworthiness. Because of privacy concerns, machine learning applications in the medical field are unable to use medical data. For example, the lack of brain MRI images makes it difficult to classify brain tumors using image-based classification. The solution to this challenge was achieved through the application of Generative Adversarial Network (GAN)-based augmentation techniques. Deep Convolutional GAN (DCGAN) and Vanilla GAN are two examples of GAN architectures used for image generation. In this paper, a framework, denoted as BrainGAN, for generating and classifying brain MRI images using GAN architectures and deep learning models was proposed. Consequently, this study proposed an automatic way to check that generated images are satisfactory. It uses three models: CNN, MobileNetV2, and ResNet152V2. Training the deep transfer models with images made by Vanilla GAN and DCGAN, and then evaluating their performance on a test set composed of real brain MRI images. From the results of the experiment, it was found that the ResNet152V2 model outperformed the other two models. The ResNet152V2 achieved 99.09% accuracy, 99.12% precision, 99.08% recall, 99.51% area under the curve (AUC), and 0.196 loss based on the brain MRI images generated by DCGAN architecture.

Recently, the Internet of Things (IoT) has gained a lot of attention, since IoT devices are placed in various fields. Many of these devices are based on machine learning (ML) models, which render them intelligent and able to make decisions. IoT devices typically have limited resources, which restricts the execution of complex ML models such as deep learning (DL) on them. In addition, connecting IoT devices to the cloud to transfer raw data and perform processing causes delayed system responses, exposes private data and increases communication costs. Therefore, to tackle these issues, there is a new technology called Tiny Machine Learning (TinyML), that has paved the way to meet the challenges of IoT devices. This technology allows processing of the data locally on the device without the need to send it to the cloud. In addition, TinyML permits the inference of ML models, concerning DL models on the device as a Microcontroller that has limited resources. The aim of this paper is to provide an overview of the revolution of TinyML and a review of tinyML studies, wherein the main contribution is to provide an analysis of the type of ML models used in tinyML studies; it also presents the details of datasets and the types and characteristics of the devices with an aim to clarify the state of the art and envision development requirements.

Introduction: Albumin is an expensive non-blood plasma substitutes with limited availability that has been reported to be inappropriately used in healthcare settings. Hence, interventions are recommended to control its misuse. Objective: To evaluate the impact of clinical pharmacist implemented dispensing protocol on optimization of albumin use in an intensive care unit (ICU). Design: A retrospective prospective 3-phase interventional study was conducted in an ICU in a tertiary Egyptian hospital over a period of 2 years. Methods: The study included three phases; a preparation phase where a local albumin dispensing protocol and a restriction dispensing form were prepared by clinical pharmacists and was approved by the local Drugs and Therapeutics Committee, a retrospective pre-implementation phase in which the medical records of all ICU patients receiving albumin were evaluated for appropriateness of albumin use according to the developed protocol, and a prospective implementation phase where the dispensing protocol and restriction dispensing form were applied. The pattern of albumin consumption and cost were recorded and compared between the retrospective and prospective phases. Results: In the retrospective phase, 190 ICU patients received albumin of whom 83.6% was considered inappropriate indications for albumin compared to only 44 patients in the prospective phase of whom 16% was considered inappropriate ( p -value <0.001). Clinical pharmacists' interventions significantly decreased the inappropriate albumin consumption from 4.7 vials/patient in the retrospective phase to 2.7 vials/patient in the prospective phase ( p -value <0.001) with a total cost savings of 313,900 Egyptian Pounds (19,930 US Dollars). Conclusion: The current study showed that clinical pharmacists' interventions led to a significant control on albumin use and consequently reduced the cost associated with its consumption., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ibrahim, Shawki, Solayman and Sabri.)

Prediction of building energy consumption is key to achieving energy efficiency and sustainability. Nowadays, the analysis or prediction of building energy consumption using building energy simulation tools facilitates the design and operation of energy-efficient buildings. The collection and generation of building data are essential components of machine learning models; however, there is still a lack of such data covering certain weather conditions. Such as those related to arid climate areas. This paper fills this identified gap with the creation of a new dataset for energy consumption of 3,840 records of typical residential buildings of the Saudi Arabia region of Qassim, and investigates the impact of residential buildings' eight input variables (Building Size, Floor Height, Glazing Area, Wall Area, window to wall ratio (WWR), Win Glazing U -value, Roof U -value, and External Wall U -value) on the heating load (HL) and cooling load (CL) output variables. A number of classical and non-parametric statistical tools are used to uncover the most strongly associated input variables with each one of the output variables. Then, the machine learning Multiple linear regression (MLR) and Multilayer perceptron (MLP) methods are used to estimate HL and CL, and their results compared using the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE), and coefficient of determination (R 2 ) performance measures. The use of the IES simulation software on the new dataset concludes that MLP accurately estimates both HL and CL with low MAE, RMSE, and R 2 , which evidences the feasibility and accuracy of applying machine learning methods to estimate building energy consumption., Competing Interests: The authors declare that they have no competing interests., (© 2022 Ibrahim et al.)

Aim: To assess impact of pharmacovigilance (PV) educational program on knowledge, attitude and practice (KAP) of healthcare professionals (HCPs)., Methods: a prospective study was conducted on HCPs at an Egyptian hospital. The study included: pre-education phase; where KAP questionnaire was administered by HCPs to obtain baseline data, intervention phase; where educational sessions were held by clinical pharmacists and Egyptian PV centre, and post-education phase; where the questionnaire was re-administered by participants 9 months post-receiving educational sessions. The questionnaire comprised five sections: participants' demographics, knowledge, attitude and practice sections and two multiple choice questions asking about the importance of establishment of ADRs monitoring centre, and factors hindering ADRs reporting. Pre-education and post-education data were compared., Results: From 221 HCPs invited to participate, only 153 filled the pre-education and post-education questionnaires. At baseline, the median (range) of the total KAP score were 1 (0-7), 1 (0-4) and 4 (0-14) for physicians, nurses and pharmacists, respectively. All KAP scores were low for all HCPs at baseline with the pharmacists having significantly higher knowledge and attitude scores compared with physicians, and nurses (P < .001). After education, all scores significantly increased and 13 ADRs were reported by HCPs compared with only 2 at baseline., Conclusion: It was concluded that educational program had a significant impact on enhancing KAP of HCPs towards PV and ADRs reporting., (© 2021 John Wiley & Sons Ltd.)

Background: Thyroid disorders may decrease the threshold for developing myopathy. Nonthyroidal illness syndrome (NTIS) is a common form of thyroid dysfunction in critically ill patients who are prone to the development of intensive care unit-acquired weakness (ICUAW). We therefore tested the hypothesis that patients with abnormalities in thyroid function are at a higher risk of developing ICUAW., Methods: We assessed blood samples from patients admitted to the ICU for ≥7 days for thyroid functions. Patients were classified into 4 categories (euthyroid, hyperthyroid, hypothyroid, and NTIS). Patients were then evaluated daily for ICUAW development. Patients with ICUAW were considered as cases, whereas patients who did not develop ICUAW served as controls. We compared demographic and clinical variables, such as APACHE II score; length of ICU stay; free T3 (FT3), free T4, and thyroid-stimulating hormone levels; incidence of the four categories of thyroid function; and other risk factors for ICUAW. Logistic regression was used to determine independent risk factors for ICUAW., Results: This case-control study included 114 patients: 57 cases (ICUAW) and 57 controls. FT3 levels were significantly lower in the cases (2.13 ± 0.96 mU/L) than in controls (2.69 ± 1.07 mU/L; P =0.004). There were no significant differences between cases and controls regarding the incidence of all categories of thyroid function. In univariate analysis, five independent variables had P < 0.25 (sepsis, vasopressors, mechanical ventilation duration, NTIS, and FT3 levels). Among these variables, multiple regression showed that only FT3 level (CI = 0.157-0.82, P =0.015) was an independent risk factor., Conclusion: The study revealed an inverse association between ICUAW incidence and FT3 levels., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Tarek Samir Shabana et al.)

Corona Virus Disease (COVID-19) has been announced as a pandemic and is spreading rapidly throughout the world. Early detection of COVID-19 may protect many infected people. Unfortunately, COVID-19 can be mistakenly diagnosed as pneumonia or lung cancer, which with fast spread in the chest cells, can lead to patient death. The most commonly used diagnosis methods for these three diseases are chest X-ray and computed tomography (CT) images. In this paper, a multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer from a combination of chest x-ray and CT images is proposed. This combination has been used because chest X-ray is less powerful in the early stages of the disease, while a CT scan of the chest is useful even before symptoms appear, and CT can precisely detect the abnormal features that are identified in images. In addition, using these two types of images will increase the dataset size, which will increase the classification accuracy. To the best of our knowledge, no other deep learning model choosing between these diseases is found in the literature. In the present work, the performance of four architectures are considered, namely: VGG19-CNN, ResNet152V2, ResNet152V2 + Gated Recurrent Unit (GRU), and ResNet152V2 + Bidirectional GRU (Bi-GRU). A comprehensive evaluation of different deep learning architectures is provided using public digital chest x-ray and CT datasets with four classes (i.e., Normal, COVID-19, Pneumonia, and Lung cancer). From the results of the experiments, it was found that the VGG19 +CNN model outperforms the three other proposed models. The VGG19+CNN model achieved 98.05% accuracy (ACC), 98.05% recall, 98.43% precision, 99.5% specificity (SPC), 99.3% negative predictive value (NPV), 98.24% F1 score, 97.7% Matthew's correlation coefficient (MCC), and 99.66% area under the curve (AUC) based on X-ray and CT images., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The development of bioinks based on shear-thinning and self-healing hydrogels has recently attracted significant attention for constructing complex three-dimensional physiological microenvironments. For extrusion-based bioprinting, it is challenging to provide high structural reliability and resolution of printed structures while protecting cells from shear forces during printing. Herein, we present shear-thinning and printable hydrogels based on silicate nanomaterials, laponite (LA), and glycosaminoglycan nanoparticles (GAGNPs) for bioprinting applications. Nanocomposite hydrogels (GLgels) were rapidly formed within seconds due to the interactions between the negatively charged groups of GAGNPs and the edges of LA. The shear-thinning behavior of the hydrogel protected encapsulated cells from aggressive shear stresses during bioprinting. The bioinks could be printed straightforwardly into shape-persistent and free-standing structures with high aspect ratios. Rheological studies demonstrated fast recovery of GLgels over multiple strain cycles. In vitro studies confirmed the ability of GLgels to support cell growth, proliferation, and spreading. In vitro osteogenic differentiation of pre-osteoblasts murine bone marrow stromal cells encapsulated inside the GLgels was also demonstrated through evaluation of ALP activity and calcium deposition. The subcutaneous implantation of the GLgel in rats confirmed its in vivo biocompatibility and biodegradability. The engineered shear-thinning hydrogel with osteoinductive characteristics can be used as a new bioink for 3D printing of constructs for bone tissue engineering applications., (Published by Elsevier Ltd.)

The management of corneal infections often requires complex therapeutic regimens involving the prolonged and high-frequency application of antibiotics that provide many challenges to patients and impact compliance with the therapeutic regimens. In the context of severe injuries that lead to tissue defects (e.g. corneal lacerations) topical drug regimens are inadequate and suturing is often indicated. There is thus an unmet need for interventions that can provide tissue closure while concurrently preventing or treating infection. In this study, we describe the development of an antibacterial bioadhesive hydrogel loaded with micelles containing ciprofloxacin (CPX) for the management of corneal injuries at risk of infection. The in vitro release profile showed that the hydrogel system can release CPX, a broad-spectrum antibacterial drug, for up to 24 h. Moreover, the developed CPX-loaded hydrogels exhibited excellent antibacterial properties against Staphylococcus aureus and Pseudomonas aeruginosa, two bacterial strains responsible for the most ocular infections. Physical characterization, as well as adhesion and cytocompatibility tests, were performed to assess the effect of CPX loading in the developed hydrogel. Results showed that CPX loading did not affect stiffness, adhesive properties, or cytocompatibility of hydrogels. The efficiency of the antibacterial hydrogel was assessed using an ex vivo model of infectious pig corneal injury. Corneal tissues treated with the antibacterial hydrogel showed a significant decrease in bacterial colony-forming units (CFU) and a higher corneal epithelial viability after 24 h as compared to non-treated corneas and corneas treated with hydrogel without CPX. These results suggest that the developed adhesive hydrogel system presents a promising suture-free solution to seal corneal wounds while preventing infection.

Pneumonia is a contagious disease that causes ulcers of the lungs, and is one of the main reasons for death among children and the elderly in the world. Several deep learning models for detecting pneumonia from chest X-ray images have been proposed. One of the extreme challenges has been to find an appropriate and efficient model that meets all performance metrics. Proposing efficient and powerful deep learning models for detecting and classifying pneumonia is the main purpose of this work. In this paper, four different models are developed by changing the used deep learning method; two pre-trained models, ResNet152V2 and MobileNetV2, a Convolutional Neural Network (CNN), and a Long Short-Term Memory (LSTM). The proposed models are implemented and evaluated using Python and compared with recent similar research. The results demonstrate that our proposed deep learning framework improves accuracy, precision, F1-score, recall, and Area Under the Curve (AUC) by 99.22%, 99.43%, 99.44%, 99.44%, and 99.77%, respectively. As clearly illustrated from the results, the ResNet152V2 model outperforms other recently proposed works. Moreover, the other proposed models-MobileNetV2, CNN, and LSTM-CNN-achieved results with more than 91% in accuracy, recall, F1-score, precision, and AUC, and exceed the recently introduced models in the literature.

Drawing stimulus from interpersonal acceptance-rejection theory, this multicultural study examined relations between men's versus women's remembrances of maternal and paternal acceptance-rejection in childhood and their current level of loneliness, as mediated by adults' self-reported psychological maladjustment. Adults (N = 899) from five nations (Iraq, Italy, the Netherlands, Pakistan, and the United States) responded to the Adult version of the Parental Acceptance-Rejection Questionnaire-short form for mothers and fathers, the Adult version of the Personality Assessment Questionnaire-short form, and the Interpersonal Acceptance-Rejection Loneliness Scale. Adults' remembrances of maternal and paternal rejection in childhood significantly and independently predicted feelings of loneliness but remembered paternal rejection was more strongly related to these feelings than were remembrances of maternal rejection. Psychological maladjustment fully mediated the effect of remembered maternal rejection but only partially mediated the effect of remembered paternal rejection on loneliness. There were no significant differences in these results across the five countries or genders. Overall, the results suggest that adults' remembrances of parental rejection in childhood-along with the theoretically expected development of psychological maladjustment-are likely to be associated panculturally with the experience of loneliness in adulthood., (© 2019 International Union of Psychological Science.)

Recent advances in understanding spatial genome organization inside the nucleus have shown that chromatin is compartmentalized into megabase-scale units known as topologically associating domains (TADs). In further studies, TADs were linked to differing transcriptional activity, suggesting that they might provide a scaffold for gene regulation by promoting enhancer-promoter interaction and by insulating regulatory activities. One strong argument for this hypothesis was provided by the effects of disease-causing structural variations in congenital disease and cancer. By rearranging TADs, these mutations result in a rewiring of enhancer-promoter contacts, consecutive gene misexpression, and ultimately disease. However, not all rearrangements are equally effective in creating these effects. Here, we review several recent studies aiming to understand the mechanisms by which disease-causing mutations achieve gene misregulation. We will discuss which regulatory effects are to be expected by different disease mutations and how this new knowledge can be used for diagnostics in the clinic., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Expansions of amino acid repeats occur in >20 inherited human disorders, and many occur in intrinsically disordered regions (IDRs) of transcription factors (TFs). Such diseases are associated with protein aggregation, but the contribution of aggregates to pathology has been controversial. Here, we report that alanine repeat expansions in the HOXD13 TF, which cause hereditary synpolydactyly in humans, alter its phase separation capacity and its capacity to co-condense with transcriptional co-activators. HOXD13 repeat expansions perturb the composition of HOXD13-containing condensates in vitro and in vivo and alter the transcriptional program in a cell-specific manner in a mouse model of synpolydactyly. Disease-associated repeat expansions in other TFs (HOXA13, RUNX2, and TBP) were similarly found to alter their phase separation. These results suggest that unblending of transcriptional condensates may underlie human pathologies. We present a molecular classification of TF IDRs, which provides a framework to dissect TF function in diseases associated with transcriptional dysregulation., Competing Interests: Declaration of Interests The Max Planck Society has filed a patent application based on this paper., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Bone injuries represent a major challenge in the medical field. The commonly used treatments for bone regeneration rely on the use of bone grafts that are usually associated with complications such as donor site morbidity, disease transmission, high cost, and lack of availability. Bone tissue engineering has become a golden solution for the repair of bone injuries by regenerating the damaged biological tissues using biocompatible scaffolds. However, most of the tissue engineered scaffolds do not possess the combined properties of high elasticity, appropriate stiffness, biocompatibility, osteoinductivity, and antimicrobial properties. In this study, we engineered bioactive and antimicrobial nanocomposites that can promote bone formation while simultaneously provide a barrier against bacterial infections commonly associated with bone implants. We used PEGylated polyglycerol sebacate as nanocomposites base, which was functionalized with Laponite nanosilicates, a synthetic nanoclay, and an antimicrobial peptide (AMP). The successful synthesis of the PEGylated polyglycerol sebacate and Laponite incorporation within the nanocomposites were confirmed through nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy (FTIR). The scaffolds had an elastic modulus and ultimate tensile strength within a range of 3.8-4.7 MPa and 1.5-3 MPa, respectively. Furthermore, the scaffolds loaded with antimicrobial peptide exhibited a significant antimicrobial activity against both Gram-negative ( Escherichia coli ) and Gram-positive ( Staphylococcus aureus ) bacteria. The in vitro cytocompatibility tests showed >90% viability of preosteoblast (W-20-17) cells. Moreover, in vitro differentiation assays demonstrated the scaffolds' ability to promote osteogenic differentiation of W-20-17. Collectively, the nanocomposites containing Laponite and antimicrobial peptide were proven to have osteoinductive and antimicrobial activity, making them desirable for bone tissue engineering applications.

The causal relationship between 3D chromatin domains and gene regulation has been of considerable debate in recent years. Initial Hi-C studies profiling the 3D chromatin structure of the genome described evolutionarily conserved Topologically Associating Domains (TADs) that correlated with gene expression. Subsequent evidence from mouse models and human disease directly linked TADs to gene regulation. However, a number of focused genetic and genome-wide studies questioned the relevance of 3D chromatin domains for orchestrating gene expression, ultimately yielding a more multi-layered view of 3D chromatin structure and gene regulation. We review the evidence for and against the importance of 3D chromatin structure for gene regulation and argue for a more comprehensive classification of regulatory chromatin domains that integrates 3D chromatin structure with genomic, functional, and evolutionary conservation., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

A new series of thiazolidinone (5a-g), thiazinone (9a-g) and dithiazepinone (9a-g) heterocycles bearing a benzenesulfonamide scaffold was synthesized. Cytotoxicity of these derivatives was assessed against MCF-7, HepG2, HCT-116 and A549 cancer cell lines and activity was compared to the known cytotoxic agents doxorubicin and 5-FU where the most active compounds displayed better to nearly similar IC 50 values to the reference compounds. For assessing selectivity, the most active derivatives against MCF-7, 5b, 5c and 5e, were also assessed against the normal breast cell line MCF-10 A where they demonstrated high selective cytotoxicity to cancerous cells over that to normal cells. Further, the effect of the most active compounds 5b-e on MCF-7 and HepG2 cell cycle phase distribution was assessed and the tested sulfonamide derivatives were found to induce accumulation of cells in the <2n phase. To further confirm apoptosis induction, caspase 8 and 9 levels in MCF-7 and HepG2 were evaluated before and after treatment with compounds 5b-e and were found to be significantly higher after exposure to the test agents. Since 5c was the most active, its effect on the cell cycle regulation was confirmed where it showed inhibition of the CDK2/cyclin E1. Finally, in vivo biodistribution study using radioiodinated-5c revealed a significant uptake and targeting ability into solid tumor in a xenograft mouse model., Competing Interests: Declaration of Competing Interest RKA wishes to acknowledge STDF for supporting part of this research project through the grant fund provided to her “STDF 25839”., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose : Limited and contradictory data on the circulating levels of glucagon-like peptide (GLP-1) and resistin in hepatitis C virus genotype-4 (HCV-4) cirrhotic patients are present. Thus, this study aimed to evaluate their concentrations and to investigate the association between total GLP-1, resistin, and insulin resistance in those patients. Materials and Methods : Non-diabetic HCV-4 cirrhotic patients (n = 80; 40 with Child-Pugh A, 20 with Child-Pugh B, and 20 with Child-Pugh C), and 25 healthy subjects were enrolled in this study. The basal circulating levels of total GLP-1 and resistin along with serum insulin, glucose, total cholesterol, and triglycerides were measured. Results : Plasma GLP-1 and serum resistin levels were significantly higher in cirrhotic patients than controls ( P < . 001). Moreover, circulating GLP-1 and resistin levels increased in a stepwise fashion in line with increasing grade of liver damage. According to Spearman's rank correlation, both GLP-1 and resisitin correlated positively with each other, insulin, homeostatic model assessment of insulin resistance, alanine aminotransferase (ALT), total bilirubin, and international normalized ratio while they correlated negatively with albumin ( P < .001). Multiple stepwise regression analysis showed that ALT, serum resistin and Child-Pugh score independently influenced the GLP-1 levels in cirrhotic patients. Conclusions : Circulating levels of GLP-1 and resistin were elevated in cirrhotic patients with HCV-4. Further, the severity of liver cirrhosis and serum resistin were the determinant factors explaining the variability of GLP-1 levels by about 84%. In addition, a positive relation was found between insulin resistance and both GLP-1 and resistin levels.

The genome is organized in three-dimensional units called topologically associating domains (TADs), through a process dependent on the cooperative action of cohesin and the DNA-binding factor CTCF. Genomic rearrangements of TADs have been shown to cause gene misexpression and disease, but genome-wide depletion of CTCF has no drastic effects on transcription. Here, we investigate TAD function in vivo in mouse limb buds at the Sox9-Kcnj2 locus. We show that the removal of all major CTCF sites at the boundary and within the TAD resulted in a fusion of neighboring TADs, without major effects on gene expression. Gene misexpression and disease phenotypes, however, were achieved by redirecting regulatory activity through inversions and/or the repositioning of boundaries. Thus, TAD structures provide robustness and precision but are not essential for developmental gene regulation. Aberrant disease-related gene activation is not induced by a mere loss of insulation but requires CTCF-dependent redirection of enhancer-promoter contacts.

Balanced chromosomal rearrangements such as inversions and translocations can cause congenital disease or cancer by inappropriately rewiring promoter-enhancer contacts 1,2 . To study the potentially pathogenic consequences of balanced chromosomal rearrangements, we generated a series of genomic inversions by placing an active limb enhancer cluster from the Epha4 regulatory domain at different positions within a neighbouring gene-dense region and investigated their effects on gene regulation in vivo in mice. Expression studies and high-throughput chromosome conformation capture from embryonic limb buds showed that the enhancer cluster activated several genes downstream that are located within asymmetric regions of contact, the so-called architectural stripes 3 . The ectopic activation of genes led to a limb phenotype that could be rescued by deleting the CCCTC-binding factor (CTCF) anchor of the stripe. Architectural stripes appear to be driven by enhancer activity, because they do not form in mouse embryonic stem cells. Furthermore, we show that architectural stripes are a frequent feature of developmental three-dimensional genome architecture often associated with active enhancers. Therefore, balanced chromosomal rearrangements can induce ectopic gene expression and the formation of asymmetric chromatin contact patterns that are dependent on CTCF anchors and enhancer activity.

Mammalian organogenesis is a remarkable process. Within a short timeframe, the cells of the three germ layers transform into an embryo that includes most of the major internal and external organs. Here we investigate the transcriptional dynamics of mouse organogenesis at single-cell resolution. Using single-cell combinatorial indexing, we profiled the transcriptomes of around 2 million cells derived from 61 embryos staged between 9.5 and 13.5 days of gestation, in a single experiment. The resulting 'mouse organogenesis cell atlas' (MOCA) provides a global view of developmental processes during this critical window. We use Monocle 3 to identify hundreds of cell types and 56 trajectories, many of which are detected only because of the depth of cellular coverage, and collectively define thousands of corresponding marker genes. We explore the dynamics of gene expression within cell types and trajectories over time, including focused analyses of the apical ectodermal ridge, limb mesenchyme and skeletal muscle.

The respiratory rhythm is generated by the preBötzinger complex in the medulla oblongata, and is modulated by neurons in the retrotrapezoid nucleus (RTN), which are essential for accelerating respiration in response to high CO 2 Here we identify a LBX1 frameshift ( LBX1 FS ) mutation in patients with congenital central hypoventilation. The mutation alters the C-terminal but not the DNA-binding domain of LBX1 Mice with the analogous mutation recapitulate the breathing deficits found in humans. Furthermore, the mutation only interferes with a small subset of Lbx1 functions, and in particular with development of RTN neurons that coexpress Lbx1 and Phox2b. Genome-wide analyses in a cell culture model show that Lbx1 FS and wild-type Lbx1 proteins are mostly bound to similar sites, but that Lbx1 FS is unable to cooperate with Phox2b. Thus, our analyses on Lbx1 FS (dys)function reveals an unusual pathomechanism; that is, a mutation that selectively interferes with the ability of Lbx1 to cooperate with Phox2b, and thus impairs the development of a small subpopulation of neurons essential for respiratory control., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Background: Cartonectin is a potent anti-inflammatory adipokine that might be implicated in metabolism and energy storage. Our objective was to evaluate the influence of weight reduction following laparoscopic sleeve gastrectomy (LSG) on serum cartonectin and vaspin levels., Subjects and Methods: Thirty-two individuals (29 female and 3 male) with morbid obesity underwent LSG. Anthropometric indices, lipid profile, fasting serum concentrations of glucose, insulin, vaspin, and cartonectin were measured prior and 3 months after LSG. Insulin sensitivity was determined using the homeostasis model assessment of insulin resistance (HOMA-IR)., Results: Following LSG, circulating cartonectin level increased significantly while serum vaspin was significantly decreased. The percentage change of serum cartonectin level correlated negatively with the percentage changes in body mass index, waist circumference, and waist-hip ratio and positively with percentage changes in LDL-C, triglycerides, and HOMA-IR after adjustment for age and sex. Moreover, the changes in vaspin concentration positively correlated with the changes in insulin level and HOMA-IR after adjustment for age and sex. In a multiple stepwise linear regression model, the changes in waist circumference explained 13% variability of changes in cartonectin level while the changes in HOMA-IR and LDL-C were responsible for 31% of the variability in changes of vaspin level., Conclusion: LSG-induced weight loss rapidly increases serum cartonectin level and decreases the serum vaspin level in morbidly obese subjects. The changes in cartonictin level seem to be influenced by the changes of waist circumference while the changes of HOMA-IR and LDL-C might be determinant factors of the changes in vaspin level.

Despite their clinical benefits in cancer treatment, the deleterious effects on heart following chemo/radiotherapy are of increasing importance. Zingerone, a natural polyphenol, possesses multiple biological activities, such as antioxidant and anti-inflammatory. Thus, the current study was designed to assess the potential cardioprotective effects of zingerone against cisplatin or γ-radiation. Zingerone was given by intragastric intubation (25 mg/kg) daily for three successive weeks prior to the induction of cardiotoxicity using a single dose of cisplatin (20 mg/kg, i.p.) or a whole body γ-irradiation at a single dose of 6 Gy. Zingerone pre-treatment significantly reduced the abnormalities in heart histology and the increase in the cardiotoxicity indices, serum lactate dehydrogenase, and creatine kinase-MB activities, as well as plasma cardiac troponin T and B-natriuretic peptide, induced by cisplatin or γ-radiation. Further, zingerone, except for superoxide dismutase, notably ameliorated the state of oxidative stress as evidenced by a significant decrease in malondialdehyde level accompanied with a significant increase in the reduced glutathione content and catalase activity. Additionally, zingerone mitigated the increase in the inflammatory markers including serum level of tumor necrosis factor-alpha, cardiac myeloperoxidase activity, and cyclooxygenase-2 protein expression. Moreover, zingerone alleviated the elevation of caspase-3 gene expression and the prominent nuclear DNA fragmentation and attenuated the decrease in mitochondrial complexes' activities. This study sheds the light on a probable protective role of zingerone as an antioxidant, anti-inflammatory, and antiapoptotic agent against cisplatin- or γ-radiation-induced cardiotoxicity and holds a potential in regard to therapeutic intervention for chemo/radiotherapy mediated cardiac damage.

Fibro-adipogenic progenitors (FAPs) are an interstitial cell population in adult skeletal muscle that support muscle regeneration. During development, interstitial muscle connective tissue (MCT) cells support proper muscle patterning, however the underlying molecular mechanisms are not well understood and it remains unclear whether adult FAPs and embryonic MCT cells share a common lineage. We show here that mouse embryonic limb MCT cells expressing the transcription factor Osr1, differentiate into fibrogenic and adipogenic cells in vivo and in vitro defining an embryonic FAP-like population. Genetic lineage tracing shows that developmental Osr1 + cells give rise to a subset of adult FAPs. Loss of Osr1 function leads to a reduction of myogenic progenitor proliferation and survival resulting in limb muscle patterning defects. Transcriptome and functional analyses reveal that Osr1 + cells provide a critical pro-myogenic niche via the production of MCT specific extracellular matrix components and secreted signaling factors.

Several novel thiazolidinone and fused thiazolidinone derivatives bearing benzenesulfonamide moiety were synthesized and confirmed via spectral and elemental analyses. The newly synthesized compounds were evaluated for their cytotoxic activity on colorectal cancer cell line (Caco-2). All the synthesized compounds showed better activity than the reference standards (Doxorubicin and 5-FU). Investigation of the apoptotic activity of the most active compounds revealed that compounds 3a, 5a, 5c and 6c activate both caspase-3 and Fas-ligand in Caco-2 cell line. Compound 3a was the most active compound with caspase-3 concentration of 0.43 nmol/mL and Fas-ligand concentration of 775.2 pg/mL in treated Caco-2 cells. Compound 3a was radiolabeled with 99m Tc and its biodistribution pattern was evaluated in vivo using normal Swiss Albino mice. 99m Tc-compound 3a complex didn't exhibit any accumulation in any body organs except for its accumulation in the colon; target organ; where it showed 8.97 ± 1.35 %ID/g at 15min p. i. that elevated till 16.02 ± 2.43 %ID/g at 120min p. i., (Copyright © 2017 Elsevier Masson SAS. All rights reserved.)

Doxorubicin (DOX) is a highly effective antineoplastic drug; however, the clinical use of DOX is limited by its dose dependent cardiotoxicity. This study was conducted to evaluate the cardioprotective effect of sea cucumber and valsartan against DOX-induced cardiotoxicity in rats. Also, the role of exposure to low dose γ radiation (LDR) on each of them was investigated, since LDR could suppress various reactive oxygen species-related diseases. Rats received DOX (2.5mg/kg, ip) in six equal injections over a period of 2weeks, sea cucumber (14.4mg/kg, p.o) and valsartan (30mg/kg, p.o) for 8 successive weeks. Exposure to LDR (0.5Gy) was performed one day prior to DOX. Results revealed that DOX administration elevated serum levels of aspartate aminotransferase (AST), lactate dehydrogenase (LDH), creatine kinase (CK-MB) and troponin-I as well as increased cardiac lipid peroxide content and myeloperoxidase (MPO) activity. Additionally, it increased cardiac expressions of iNOS and caspase-3, accompanied by reduction in cardiac total protein and glutathione (GSH) contents. Treatment with sea cucumber or valsartan improved the cardiotoxicity of DOX. Their adjuvant therapy with LDR offers an additional benefit to the cardioprotection of the therapeutic drugs. These results confirmed by histopathological examination. In conclusion, sea cucumber and valsartan alone or combined with LDR attenuated DOX-induced cardiotoxicity via their antioxidant and anti-apoptotic activities and thus might be useful in the treatment of human patients under doxorubicin chemotherapy., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Complex regulatory landscapes control the pleiotropic transcriptional activities of developmental genes. For most genes, the number, location, and dynamics of their associated regulatory elements are unknown. In this work, we characterized the three-dimensional chromatin microarchitecture and regulatory landscape of 446 limb-associated gene loci in mouse using Capture-C, ChIP-seq, and RNA-seq in forelimb, hindlimb at three developmental stages, and midbrain. The fine mapping of chromatin interactions revealed a strong preference for functional genomic regions such as repressed or active domains. By combining chromatin marks and interaction peaks, we annotated more than 1000 putative limb enhancers and their associated genes. Moreover, the analysis of chromatin interactions revealed two regimes of chromatin folding, one producing interactions stable across tissues and stages and another one associated with tissue and/or stage-specific interactions. Whereas stable interactions associate strongly with CTCF/RAD21 binding, the intensity of variable interactions correlates with changes in underlying chromatin modifications, specifically at the viewpoint and at the interaction site. In conclusion, this comprehensive data set provides a resource for the characterization of hundreds of limb-associated regulatory landscapes and a framework to interpret the chromatin folding dynamics observed during embryogenesis., (© 2017 Andrey et al.; Published by Cold Spring Harbor Laboratory Press.)

Homeotic genes code for key transcription factors (HOX-TFs) that pattern the animal body plan. During embryonic development, Hox genes are expressed in overlapping patterns and function in a partially redundant manner. In vitro biochemical screens probing the HOX-TF sequence specificity revealed largely overlapping sequence preferences, indicating that co-factors might modulate the biological function of HOX-TFs. However, due to their overlapping expression pattern, high protein homology, and insufficiently specific antibodies, little is known about their genome-wide binding preferences. In order to overcome this problem, we virally expressed tagged versions of limb-expressed posterior HOX genes (HOXA9-13, and HOXD9-13) in primary chicken mesenchymal limb progenitor cells (micromass). We determined the effect of each HOX-TF on cellular differentiation (chondrogenesis) and gene expression and found that groups of HOX-TFs induce distinct regulatory programs. We used ChIP-seq to determine their individual genome-wide binding profiles and identified between 12,721 and 28,572 binding sites for each of the nine HOX-TFs. Principal Component Analysis (PCA) of binding profiles revealed that the HOX-TFs are clustered in two subgroups (Group 1: HOXA/D9, HOXA/D10, HOXD12, and HOXA13 and Group 2: HOXA/D11 and HOXD13), which are characterized by differences in their sequence specificity and by the presence of cofactor motifs. Specifically, we identified CTCF binding sites in Group 1, indicating that this subgroup of HOX-proteins cooperates with CTCF. We confirmed this interaction by an independent biological assay (Proximity Ligation Assay) and demonstrated that CTCF is a novel HOX cofactor that specifically associates with Group 1 HOX-TFs, pointing towards a possible interplay between HOX-TFs and chromatin architecture., Competing Interests: The authors have declared that no competing interests exist.

Chromosome conformation capture methods have identified subchromosomal structures of higher-order chromatin interactions called topologically associated domains (TADs) that are separated from each other by boundary regions. By subdividing the genome into discrete regulatory units, TADs restrict the contacts that enhancers establish with their target genes. However, the mechanisms that underlie partitioning of the genome into TADs remain poorly understood. Here we show by chromosome conformation capture (capture Hi-C and 4C-seq methods) that genomic duplications in patient cells and genetically modified mice can result in the formation of new chromatin domains (neo-TADs) and that this process determines their molecular pathology. Duplications of non-coding DNA within the mouse Sox9 TAD (intra-TAD) that cause female to male sex reversal in humans, showed increased contact of the duplicated regions within the TAD, but no change in the overall TAD structure. In contrast, overlapping duplications that extended over the next boundary into the neighbouring TAD (inter-TAD), resulted in the formation of a new chromatin domain (neo-TAD) that was isolated from the rest of the genome. As a consequence of this insulation, inter-TAD duplications had no phenotypic effect. However, incorporation of the next flanking gene, Kcnj2, in the neo-TAD resulted in ectopic contacts of Kcnj2 with the duplicated part of the Sox9 regulatory region, consecutive misexpression of Kcnj2, and a limb malformation phenotype. Our findings provide evidence that TADs are genomic regulatory units with a high degree of internal stability that can be sculptured by structural genomic variations. This process is important for the interpretation of copy number variations, as these variations are routinely detected in diagnostic tests for genetic disease and cancer. This finding also has relevance in an evolutionary setting because copy-number differences are thought to have a crucial role in the evolution of genome complexity.