Inhibition of dengue virus 3 in mammalian cell culture by synthetic small interfering RNAs targeting highly conserved sequences

Purpose: To evaluate the inhibition of Dengue virus 3 by synthetic siRNAs targeting the untranslated regions UTR and structural regions of DENV3 genome in Vero-81 cell line.Methods: Vero-81 cells transfected with synthetic siRNAs were challenged by DENV3. The effectiveness of siRNAs was confirmed by four established virus quantification procedures. Starting with focus assay, DENV3 was quantified using anti-E antibody (Envelope), in which DENV3 was quantified by counting the number of foci per well. Initial results were then confirmed by immuno-florescence assay (IFA) as the number of Vero-81 cells displaying DENV3 (Envelope) E antigen had a higher florescent intensity in comparison to cells lacking DENV3 replication . DENV3 RNA copy numbers were quantified by real-time quantative polymerase chain reaction RT-qPCR and in the final step supernatant of Vero-81 cells challenged with DENV3 was collected and protein analysis was performed to determine the presence of DENV3 E protein via western blot analysisResults: A marked decrease in virus titer of DENV3 in Vero cells was observed with DV3UTR3'siRNA2 targeting the 3'UTR. Focus assay data revealed more than 70 % reduction in DENV3 in Vero-81 cells treated with DV3UTR3'siRNA2. Images showing IFA of infected Vero-81 cells exhibited a major drop in DENV3 titer in the presence of DV3UTR3'siRNA2 and DV3UTR5'siRNA1. DENV3 RNA, quantified by qPCR, DV3UTR3'siRNA2 showed 80 % reduction in DENV3 RNA level in comparsion with positive control cells having higher titers of DENV3. Finally, a negligible level of DENV3 E protein was detected in the supernatant of Vero-81 cells containing DV3UTR3'siRNA2. These findings suggest that DV3UTR3'siRNA2 and DV3UTR5'siRNA1 can significantly inhibit DENV3 in mammalian cell line.Conclusion: Overall, the results demonstrate that DV3UTR3'siRNA2 and  V3UTR5'siRNA1 can become a potential vital component of a therapeutic formulation for major anti-dengue therapy against DENV3.Keywords: Dengue virus, siRNA, anti-E antibody, Conserve regions, Vero-81 cell

تربية الأطفال في نظرية المعرفة في القرآن الكريم

This study aims to explore the instructions of the Qur\u27an on epistimologi education of children. Based on the idea that childhood is a phase of life that is very important and influential on subsequent periods. Educational success in childhood will have a positive impact on the personality and life of the child in the future. As well as failure. This study is the library research with a qualitative approach. The primary data sources are the Qur\u27an and Tafsir. While the secondary data sources are books related to the theme of research. The research results showed that the Qur\u27an very concerned about the education of children and encourage parents and teachers to carry out such a comprehensive education. According to the Qur\u27an children can be jewelry of the world (zînat al-hayât al-dunyâ), a gem that boast (qurrata a\u27yun), trial for parents (fitnah), and enemies (\u27aduww). Several things related and affect a child\u27s education is the goal, materials, methods and educator. Everything has to be integrated in an integrated manner for all the requirements are met properly

Concurrent homozygous sickle‐cell disease and severe haemophilia A: Thromboelastography profiles

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148348/1/hae13692_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148348/2/hae13692.pd

A Multi-modal Approach for Crop Health Mapping using low altitude Remote Sensing, Internet of Things (IoT) and Machine Learning

The agriculture sector holds paramount importance in Pakistan due to the intrinsic agrarian nature of the economy. Pakistan has its GDP based on agriculture, however it relies on manual monitoring of crops, which is a labour intensive and ineffective method. In contrast to this, several cutting edge technology-based solutions are being employed in the developed countries to enhance the crop yield with the optimal use of resources. To this end, we have proposed an integrated approach for monitoring crop health using IoT, machine learning and drone technology. The integration of these sensing modalities generate heterogeneous data which not only varies in nature (i.e. observed parameter) but also has different temporal fidelity. The spatial resolution of these methods is also different, hence, the optimal integration of these sensing modalities and their implementation in practice are addressed in the proposed system. In our proposed solution, the IoT sensors provide the real-time status of environmental parameters impacting the crop, and the drone platform provide the multispectral data used for generating Vegetation Indices (VIs) such as Normalized Difference vegetation Index (NDVI) for analyzing the crop health. The NDVI provides information about the crop based on the chlorophyll content, which offers limited information regarding the crop health. In order to obtain a rich and detailed knowledge about crop health, the variable length time series data of IoT sensors and multispectral images were converted to a fixed-sized representation to generate crop health maps. A number of machine and deep learning algorithms were applied on the collected data wherein deep neural network with two hidden layers was found to be the most optimal model among all the selected models, providing an accuracy of (98.4%). Further, the health maps were validated through ground surveys and by agriculture experts due to the absence of reference data. The proposed research is basically an indigenous, technology based agriculture solution capable of providing important insights into the crop health by extracting complementary features from multi-modal data set, and minimizing the crop ground survey effort, particularly useful when the agriculture land is large in size

Internet of Things (IoT) Based Indoor Air Quality Sensing and Predictive Analytic—A COVID-19 Perspective

Indoor air quality typically encompasses the ambient conditions inside buildings and public facilities that may affect both the mental and respiratory health of an individual. Until the COVID-19 outbreak, indoor air quality monitoring was not a focus area for public facilities such as shopping complexes, hospitals, banks, restaurants, educational institutes, and so forth. However, the rapid spread of this virus and its consequent detrimental impacts have brought indoor air quality into the spotlight. In contrast to outdoor air, indoor air is recycled constantly causing it to trap and build up pollutants, which may facilitate the transmission of virus. There are several monitoring solutions which are available commercially, a typical system monitors the air quality using gas and particle sensors. These sensor readings are compared against well known thresholds, subsequently generating alarms when thresholds are violated. However, these systems do not predict the quality of air for future instances, which holds paramount importance for taking timely preemptive actions, especially for COVID-19 actual and potential patients as well as people suffering from acute pulmonary disorders and other health problems. In this regard, we have proposed an indoor air quality monitoring and prediction solution based on the latest Internet of Things (IoT) sensors and machine learning capabilities, providing a platform to measure numerous indoor contaminants. For this purpose, an IoT node consisting of several sensors for 8 pollutants including NH3, CO, NO2, CH4, CO2, PM 2.5 along with the ambient temperature & air humidity is developed. For proof of concept and research purposes, the IoT node is deployed inside a research lab to acquire indoor air data. The proposed system has the capability of reporting the air conditions in real-time to a web portal and mobile app through GSM/WiFi technology and generates alerts after detecting anomalies in the air quality. In order to classify the indoor air quality, several machine learning algorithms have been applied to the recorded data, where the Neural Network (NN) model outperformed all others with an accuracy of 99.1%. For predicting the concentration of each air pollutant and thereafter predicting the overall quality of an indoor environment, Long and Short Term Memory (LSTM) model is applied. This model has shown promising results for predicting the air pollutants’ concentration as well as the overall air quality with an accuracy of 99.37%, precision of 99%, recall of 98%, and F1-score of 99%. The proposed solution offers several advantages including remote monitoring, ease of scalability, real-time status of ambient conditions, and portable hardware, and so forth

Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma

Several methods have been proposed for the segmentation of ¹⁸F-FDG uptake in PET. In this study, we assessed the performance of four categories of ¹⁸F-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the benchmark

Parents just don't understand: Parent-offspring conflict over mate choice

Previous research reveals that children and parents are not in complete agreement over which traits are most important for the mate of the child. Children tend to prefer traits that suggest genetic quality, whereas parents prefer characteristics that suggest high parental investment and cooperation with the ingroup. Using a sample of parents, mothers (n = 234) and fathers (n =240) the hypothesis was supported; parents perceived characteristics indicating a lack of genetic quality as being more unacceptable to the child, while characteristics indicating a lack of parental investment and cooperation with the ingroup were more unacceptable to themselves. Sex differences between mothers and fathers and sons and daughters were explored

The clock genes Period 2 and Cryptochrome 2 differentially balance bone formation

Background: Clock genes and their protein products regulate circadian rhythms in mammals but have also been implicated in various physiological processes, including bone formation. Osteoblasts build new mineralized bone whereas osteoclasts degrade it thereby balancing bone formation. To evaluate the contribution of clock components in this process, we investigated mice mutant in clock genes for a bone volume phenotype. Methodology/Principal Findings: We found that Per2Brdm1 mutant mice as well as mice lacking Cry2-/- displayed significantly increased bone volume at 12 weeks of age, when bone turnover is high. Per2Brdm1 mutant mice showed alterations in parameters specific for osteoblasts whereas mice lacking Cry2-/- displayed changes in osteoclast specific parameters. Interestingly, inactivation of both Per2 and Cry2 genes leads to normal bone volume as observed in wild type animals. Importantly, osteoclast parameters affected due to the lack of Cry2, remained at the level seen in the Cry2-/- mutants despite the simultaneous inactivation of Per2. Conclusions/Significance: This indicates that Cry2 and Per2 affect distinct pathways in the regulation of bone volume with Cry2 influencing mostly the osteoclastic cellular component of bone and Per2 acting on osteoblast parameters

An orally bioavailable Chkl inhibitor, CCT244747, sensitizes bladder and head and neck cancer cell lines to radiation

Purpose Chk1 inhibition increases cell sensitivity to both chemotherapy and radiotherapy in several tumour types and is, therefore, a promising anti-cancer approach. Although several Chk1 inhibitors have been developed, their clinical progress has been hampered by low bioavailability and off-target toxicities.Materials and methods We characterized the radiosensitizing activity of CCT244747, the first orally bioavailable Chk1 inhibitor. We used a panel of bladder and head and neck cancer cell lines and monitored the effect of combining CCT244747 with radiation both in in vitro and in vivo models.Results CCT244747 sensitized cancer cell lines to radiation in vitro and resulted in a growth delay in cancer xenograft models associated with a survival benefit. Radiosensitization was elicited by abrogation of the radiation-induced G2 arrest and premature entry into mitosis.Conclusions CCT244747 is a potent and specific Chk1 inhibitor that can be administered orally. It radiosensitizes tumour cell lines and represents a new therapy for clinical application in combination with radiotherapy

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors