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

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

Boron, zinc and microtone effects on growth, chlorophyll contents and yield attributes in rice (Oryza sativa L.) cultivar

The micronutrient required in minute quantity and their deficiency leads to diminished growth and yield of crops. The effect of soil application of Zinc (Zn), Boron (B) and Microtone (MT) on growth, chlorophyll contents, mineral profile and yield components were investigated in rice at Chakkanwali Reclamation Research Station District, Gujranwala, Pakistan in the year 2011. Seven treatments which includes Zn 33% at 3 kg/acre, Zn 33% at 6 kg/acre, B 11.3% at 1.5 kg/acre, B 11.3% at 3 kg/acre, Zn + B at 3 + 1.5 kg/acre, Zn + B at 6 + 3 kg/acre and MT + Zn 6% + B + Fe + Mn + Cu 1% each at 500 ml/acre, and F0 considered as the control were used. The results reveal that foliar application of Zn and B (Zn + B at 6 + 3 kg/acre) were proved as the best balanced fertilizer dose for higher growth and yield response. The plant height, tiller/plant, panicle length, kernels/plant, filled kernel/plant, productive kernel, straw, paddy and biological yield increased up to 29.75, 38.40, 28.19, 25.81, 36.52, 38.52, 32.47, 38.27 and 31.79%, respectively. The chlorophyll contents, B and Zn contents in rice plant also increased significantly as compared to the control. However, the B, Zn and MT application reduced the amylase and protein contents of rice plant at all treatment levels.Keywords: Micronutrients, rice crop, growth, chlorophyll contents, Oryza sativa L., yield attribute

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

Analysis of morphological traits in different host plants associated with resistance to Phenacoccus solenopsis- an invasive pest in Pakistan

Phenacoccus solenopsis Tinsley (Pseudococcidae: Hemiptera) is a sucking insect pest and is polyphagous in nature. Twenty five (25) different host plants were screened against P. solenopsis and their  physicomorphic traits were determined to correlate their role against pest population. Among the tested plant species, most favorable host plants of mealy bug on the basis of population were Gossypium hirsutum (69.74±10.5), Solamum melongena (62.41±10.0), Helianthus annuus (61.83±10.0), Hibiscus rosa-sinensis (61.1±10.0) and Lantana camara (55.83±9.75), but the least preferred plants were tandla Digera arvensis (1.57±1.00) and Conyza bonariensis (3.83±1.75). Significant variations were observed in all the morphological plant characters recorded from different plant species. The maximum leaf thickness per plant was 2.04±0.23 ìm in plant species S. melongena while minimum thickness of leaf was recorded from lehli (0.25±0.02 ìm). Maximum trichome density per plant was 444±72.4 in sunflower followed by 411.6±19.6, 399±52, 391.6±22.0, in C. bonariensis, Abelmoschus esculentus and Withania somnifera respectively but minimum were 2.33±1.45 in Chinopodium morale, followed by 2.66±1.4, and 3±2.08 in Portulaca oleracea and Trianthema portulacastrum respectively. The maximum hair length per plant (2.62±0.07 mm) was of sunflower followed by 2.55±0.03 mm in okra, 2.53±0.06 mm in both S. melongena and G. hirsutum. It was concluded that plant characters including trichome density and hair length favor mealy bug population showing r-values of 0.357* and 0.190 respectively but leaf size and leaf width (leaf area and leaf thickness) exerted negative effect on pest population showing r-values of -0.172 and -0.285 respectively.Key words: Phenacoccus solenopsis, invasive species, physicomorphic traits, resistance

Analysis of Human Gait Cycle with Body Equilibrium based on leg Orientation

Gait analysis identifies the posture during movement in order to provide the correct actions for a normal gait. A person\u27s gait may differ from others and can be recognized by specific patterns. Healthy individuals exhibit normal gait patterns, while lower limb amputees exhibit abnormal gait patterns. To better understand the pitfalls of gait, it is imperative to develop systems capable of capturing the gait patterns of healthy individuals. The main objective of this research was to introduce a new concept in gait analysis by computing the static and dynamic equilibrium in a real-world environment. A relationship was also presented among the parameters stated as static \& dynamic equilibrium, speed, and body states. A sensing unit was installed on the designed metal-based leg mounting assembly on the lateral side of the leg. An algorithm was proposed based on two variables: the position of the leg in space and the angle of the knee joint measured by an IMU sensor and a rotary encoder. It was acceptable to satisfy the static conditions when the body was in a fixed position and orientation, whether lying down or standing. While walking and running, the orientation is determined by the position and knee angle variables, which fulfill the dynamic condition. High speed reveals a rapid change in orientation, while slow speed reveals a slow change in orientation. The proposed encoder-based feedback system successfully determined the flexion at 47$^\circ$, extension at 153$^\circ$, and all seven gait cycle phases were recognized within this range of motion. Body equilibrium facilitates individuals when they are at risk of falling or slipping

Evaluation of seed priming on germination of Gladiolus alatus

Seed priming improves seed performance under environmental conditions. The study was designed to evaluate the effect of different priming treatments on germination behavior of Gladiolus alatus. The experiment was conducted under complete randomized design (CRD) with four replications. Seed priming was done with different concentration of potassium nitrate (KNO3) and hydropriming. All the treatments had significant effect on germination percentage, germination test in growth room, time for 50% germination and mean germination time. Results show that maximum invigoration was observed in seeds osmoprimed at lower concentrations of KNO3 and with hydropriming while minimum invigoration was observed at higher concentration of KNO3-. It was concluded that germination percentage can be increased by using lower concentrations of KNO3 and with hydropriming.Key words: Priming, hydropriming, gladiolus, germination

Experimental validation of bulk-graphene as a thermoelectric generator

Quest for alternate energy sources is the core of most of the research activities these days. No matter how small or large amount of energy can be produced by utilizing the non-conventional techniques and sources, every bit of innovation can reshape the future of energy. In this work, experimental analysis of the thermoelectric (TE) properties of bulk-graphene in the temperature range of (303 to 363) K is presented. Graphene powder was pressed to form a pellet which was used to fabricate the TE device. The effects of temperature on the Seebeck coefficient, electrical and thermal conductivities, and the dimensionless figure of merit (FOM) were measured. The increasing value of the Seebeck coefficient (thermopower) with temperature is indicant of the metallic behavior. Additionally, the observed thermopower (TEP) is positive, which shows that the majority charge carriers are holes and peaked to a value of 56 μV K-1 at 363 K. The thermopower of the pellet is four times larger than the previously reported values for single layer graphene (SLG) and few layer graphene (FLG). In addition to this, low values of the thermal conductivity were observed for the pellet which is one of the requirements of a good TE material. Besides this, an upward trend is observed with increasing temperature for FOM, which attains a peak value of 0.0016 at 363 K, which is almost ten times that of the previously reported values

A distance vector hop-based secure and robust localization algorithm for wireless sensor networks

Location information of sensor nodes in a wireless sensor network is important. The sensor nodes are usually required to ascertain their positions so that the data collected by these nodes can be labeled with this information. On the other hand, certain attacks on wireless sensor networks lead to the incorrect estimation of sensor node positions. In such situations, when the location information is not correct, the data may be labeled with wrong location information that may subvert the desired operation of the wireless sensor network. In this work, we formulate and propose a distance vector hop-based algorithm to provide secure and robust localization in the presence of malicious sensor nodes that result in incorrect position estimation and jeopardize the wireless sensor network operation. The algorithm uses cryptography to ensure secure and robust operation in the presence of adversaries in the sensor network. As a result of the countermeasures, the attacks are neutralized and the sensor nodes are able to estimate their positions as desired. Our secure localization algorithm provides a defense against various types of security attacks, such as selective forwarding, wormhole, Sybil, tampering, and traffic replay, compared with other algorithms which provide security against only one or two types. Simulation experiments are performed to evaluate the performance of the proposed method, and the results indicate that our secure localization algorithm achieves the design objectives successfully. Performance of the proposed method is also compared with the performance of basic distance vector hop algorithm and two secure algorithms based on distance vector hop localization. The results reveal that our proposed secure localization algorithm outperforms the compared algorithms in the presence of multiple attacks by malicious nodes