Role of RNA Interference (RNAi) in the Moss Physcomitrella patens

RNA interference (RNAi) is a mechanism that regulates genes by either transcriptional (TGS) or posttranscriptional gene silencing (PTGS), required for genome maintenance and proper development of an organism. Small non-coding RNAs are the key players in RNAi and have been intensively studied in eukaryotes. In plants, several classes of small RNAs with specific sizes and dedicated functions have evolved. The major classes of small RNAs include microRNAs (miRNAs) and small interfering RNAs (siRNAs), which differ in their biogenesis. miRNAs are synthesized from a short hairpin structure while siRNAs are derived from long double-stranded RNAs (dsRNA). Both miRNA and siRNAs control the expression of cognate target RNAs by binding to reverse complementary sequences mediating cleavage or translational inhibition of the target RNA. They also act on the DNA and cause epigenetic changes such as DNA methylation and histone modifications. In the last years, the analysis of plant RNAi pathways was extended to the bryophyte Physcomitrella patens, a non-flowering, non-vascular ancient land plant that diverged from the lineage of seed plants approximately 450 million years ago. Based on a number of characteristic features and its phylogenetic key position in land plant evolution P. patens emerged as a plant model species to address basic as well as applied topics in plant biology. Here we summarize the current knowledge on the role of RNAi in P. patens that shows functional overlap with RNAi pathways from seed plants, and also unique features specific to this species

Factors Affecting Quality of Sleep in Intensive Care Unit

Background: The etiology of sleep disruption in intensive care unit is poorly known and often ignored complication. It is caused by the environmental factors especially pain, noise, diagnostic testing and human interventions that cause sleep disruption. Light, medications and activities related to patient care interfere with patient's ability to have good sleep. There are multi-factorial environmental etiologies for disruption of sleep in ICU. Objective: The objective of this study was to evaluate the factors disturbing the sleep quality in intensive care unit (ICU) admitted patients. Methodology: A cross sectional study was designed involving 150 patients admitted in intensive care unit and high dependency unit of Gulab Devi Chest Hospital. The duration of study was from September 2015 to March 2016. The questionnaire was made and filled with the help of patients. The data was analyzed using SPSS version 16.00. Results: Mean age of patients was 50.46+10.96 with maximum age of 65 and minimum age of 30 years. There was 53.33% male patients and 46.67% females participating in this study. The sleep quality was significantly poor in ICU than at home. After analysis, 54.67% patients were with poor quality of sleep due to pain and 48.67% were due to noise of environmental stimuli. The other factors were alarms, light and loud talking. Conclusion: Current study shows that reduced sleep quality is a common problem in ICU with multi-factorial etiologies. Patient reported the poor sleep quality in ICU due to environmental issues that are potentially modifiable. Conclusion: Current study shows that reduced sleep quality is a common problem in ICU with multi-factorial etiologies. Patient reported the poor sleep quality in ICU due to environmental issues that are potentially modifiable

The Effects of Vitamin D on the Renin-Angiotensin System

Implication for health policy/practice/research/medical education: The current literature indicates that maintaining adequate vitamin D levels may be an important consideration in the treatment of hypertension, especially in individuals with vitamin D insufficiency and deficiency

Assessment of Bholari River Sand for its Geotechnical Characterization as Fine Aggregate

Present study is aimed at assessment of Bholari river sand for its geotechnical characterization and suitability as fine aggregate which is being quarried in Jamshoro district, Sindh, Pakistan. For this purpose, sand samples (n=11) were collected from quarry sites and main river channel. Physical properties reveal that Bholari sand is mainly coarse to fine in size (0.2 mm-5 mm). Average values of fineness modulus, specific gravity, bulk density and void content of collected samples are 2.58, 2.56, 1659.90 kg/m3 and 35.12% respectively which varied within the corresponding permissible ranges of ACI (American Concrete Institute). Carbonate content of about 57.59% is also in agreement with corresponding range for fine aggregate. Petrographic examination revealed that Bholari River sand mainly comprises of quartz and rock fragments with subordinate limestone fragments. As per classification of Dott (1964), Bholari sand is lithic arenite where quartz (50%) occurs as main mineral followed by rock fragments (30%), feldspars (15%) and other opaque minerals (5%). Texturally, the sediments are angular (77%) to sub-round (33%). All these physical properties lie within the range set by National Highway Authority (NHA) and American Standard of Testing Material (ASTM). It is concluded that Bholari River sand is suitable for use in concrete mixed with cement and asphalt

Correlation filters for detection of cellular nuclei in histopathology images

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. Availability: A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist

CAFÉ-Map : context aware feature mapping for mining high dimensional biomedical data

Feature selection and ranking is of great importance in the analysis of biomedical data. In addition to reducing the number of features used in classification or other machine learning tasks, it allows us to extract meaningful biological and medical information from a machine learning model. Most existing approaches in this domain do not directly model the fact that the relative importance of features can be different in different regions of the feature space. In this work, we present a context aware feature ranking algorithm called CAFÉ-Map. CAFÉ-Map is a locally linear feature ranking framework that allows recognition of important features in any given region of the feature space or for any individual example. This allows for simultaneous classification and feature ranking in an interpretable manner. We have benchmarked CAFÉ-Map on a number of toy and real world biomedical data sets. Our comparative study with a number of published methods shows that CAFÉ-Map achieves better accuracies on these data sets. The top ranking features obtained through CAFÉ-Map in a gene profiling study correlate very well with the importance of different genes reported in the literature. Furthermore, CAFÉ-Map provides a more in-depth analysis of feature ranking at the level of individual examples

Studies on Chromene based 2, 6-disubstituted-Thiazolo [3,2-B] [1,2,4] Triazole derivatives: Synthesis and Biological Evaluation

In this study, a series of novel chromene based 2,6-disubstituted-thiazolo[3,2-b] [1,2,4] triazole derivatives (7a-g) were synthesized by condensing 5-substituted-1,2,4-traizole-thione (6a-g) using poly phosphoric acid through one pot reaction. The structure of new compounds was supported by 1H NMR, 13C NMR and MS data. The synthesized compounds were evaluated using writhing assays for analgesic and carrageenan-induced rat paw edema method for anti-inflammatory activities respectively. Some of the newly synthesized compounds 7c, 7f and 7g showed very good anti-inflammatory activity with 90.83%, 85.81% and 88.40% protection respectively along with low GI toxicity as compared to standard drug ibuprofen while compounds 7a, 7b, 7d and 7f showed highest analgesic activity with 52.54%, 54.02%, 56.76% and 52.45% protection among them compound 7d showed better protection than standard drug ibuprofen. Keywords: thiazolo-triazoles, Chromene, Anti-inflammatory, Analgesi