Compositional Nutrient Diagnosis Norms (CND) for Guava (Psidium guajava L.)

Multivariate nutrient diagnostic norms were developed for guava using compositional nutrient diagnosis (CND) through leaf nutrient concentration vs. yield data bank. CND norms for N (VN), P (VP) and K (VK) were 2.48, 0.23 and 2.13, respectively. Norms for N and K were much higher compared to P, indicating higher requirement of these two nutrients. CND norms are multivariate norms that consider all elements, including unmeasured factors and, therefore, has higher diagnostic sensitivity. Among micronutrients, Fe requirement was much higher than all other nutrients. Interaction among different nutrients was explained by principal component analysis conducted on log-transformed data which produced four significant PCs, explaining about 73.66% of the variance. The four Eigen values added up to 8.1 denoting the four significant PCs. The first PC was positively correlated with P, Zn and R (residue, which is a reflection of dry matter accumulation in the plant) and negatively correlated with Ca, Mg, S and Fe, indicating that P and Zn behaved in one direction and the other elements in opposite direction. In the second PC, antagonistic effect of N, Fe with P and Cu was evident. In PC3, P and Mg were negatively correlated with Mn and Cu. In PC4, N and S showed their behaviour in the same direction. Diagnostic norms developed were used for identification of yield-limiting nutrients in low-yielding orchards. Thus, diagnostic norms and nutrient interactions help evolve nutrient management strategies for guava to realize higher yields and better quality

Synergistic interactions within a multispecies biofilm enhance individual species protection against grazing by a pelagic protozoan

Biofilm formation has been shown to confer protection against grazing, but little information is available on the effect of grazing on biofilm formation and protection in multispecies consortia. With most biofilms in nature being composed of multiple bacterial species, the interactions and dynamics of a multispecies bacterial biofilm subject to grazing by a pelagic protozoan predator were investigated. To this end, a mono and multispecies biofilms of four bacterial soil isolates, namely Xanthomonas retroflexus, Stenotrophomonas rhizophila, Microbacterium oxydans and Paenibacillus amylolyticus, were constructed and subjected to grazing by the ciliate Tetrahymena pyriformis. In monocultures, grazing strongly reduced planktonic cell numbers in P. amylolyticus and S. rhizophila and also X. retroflexus. At the same time, cell numbers in the underlying biofilms increased in S. rhizophila and X. retroflexus, but not in P. amylolyticus. This may be due to the fact that while grazing enhanced biofilm formation in the former two species, no biofilm was formed by P. amylolyticus in monoculture, either with or without grazing. In four- species biofilms, biofilm formation was higher than in the best monoculture, a strong biodiversity effect that was even more pronounced in the presence of grazing. While cell numbers of X. retroflexus, S. rhizophila, and P. amylolyticus in the planktonic fraction were greatly reduced in the presence of grazers, cell numbers of all three species strongly increased in the biofilm. Our results show that synergistic interactions between the four-species were important to induce biofilm formation, and suggest that bacterial members that produce more biofilm when exposed to the grazer not only protect themselves but also supported other members which are sensitive to grazing, thereby providing a "shared grazing protection" within the four- species biofilm model. Hence, complex interactions shape the dynamics of the biofilm and enhance overall community fitness under stressful conditions such as grazing. These emerging inter-and intra-species interactions could play a vital role in biofilm dynamics in natural environments like soil or aquatic systems

Synergistic interactions in microbial biofilms facilitate the establishment of opportunistic pathogenic fungi in household dishwashers

Biofilms formed on rubber seals in dishwashers harbor diverse microbiota. In this study, we focussed on the microbial composition of bacteria and fungi, isolated from a defined area of one square centimeter of rubber from four domestic dishwashers and assessed their abilities to in vitro multispecies biofilm formation. A total of 80 isolates (64 bacterial and 16 fungal) were analyzed. Multiple combinations of bacterial isolates from each dishwasher were screened for synergistic interactions. 32 out of 140 tested (23%) four-species bacterial combinations displayed consistent synergism leading to an overall increase in biomass, in all experimental trails. Bacterial isolates from two of the four dishwashers generated a high number of synergistically interacting four-species consortia. Network based correlation analyses also showed higher co-occurrence patterns observed between bacterial members in the same two dishwasher samples, indicating cooperative effects. Furthermore, two synergistic fourspecies bacterial consortia were tested for their abilities to incorporate an opportunistic fungal pathogen, Exophiala dermatitidis and their establishment as biofilms on sterile ethylene propylene diene monomer M-class (EPDM) rubber and polypropylene (PP) surfaces. When the bacterial consortia included E. dermatitidis, the overall cell numbers of both bacteria and fungi increased and a substantial increase in biofilm biomass was observed. These results indicate a novel phenomenon of cross kingdom synergy in biofilm formation and these observations could have potential implications for human health

Gluteal rhabdomyosarcoma in a newborn – A case report

Rhabdomyosarcoma is the most common soft tissue malignancy of childhood; however, can be seen very rarelyin the neonatal period also. It may arise anywhere in the body; head and neck, and genitourinary regions beingthe most frequent sites. Truncal and gluteal rhabdomyosarcoma is relatively rare occurrence. We report aneonate with embryonal rhabdomyosarcoma arising from the gluteal muscles at birth. Ultrasonography andMagnetic resonance imaging raised the possibility of hemangioma lymhangioma. Total excision was done andchemotherapy given. The child had a recurrence after 6 months where the nodule along with the scar wasexcised. A chemoport was introduced and the child underwent further 4 cycles of chemotherapy afterrecurrence. He is well on 2 years follow up without any disability

To find the efficacy of crude extract from plants on germination of seeds

Germination is the growth of an embryonic plant contained within a seed; it results in the formation of the seedling. The seed of a higher plant is a small package produced in a fruit or cone after the union of male and female sex cells. All fully developed seeds contain an embryo and, in most plant species some store of food reserves, wrapped in a seed coat. Some plants produce varying numbers of seeds that lack embryos, these are called empty seeds, and never germinate. Most seeds go through a period of quiescence where there is no active growth; during this time the seed can be safely transported to a new location and/or survive adverse climate conditions until circumstances are favorable for growth. Quiescent seeds are ripe seeds that do not germinate because they are subject to external environmental conditions that prevent the initiation of metabolic processes and cell growth. Under favorable conditions, the seed begins to germinate and the embryonic tissues resume growth. In the present study, research was done to find the effect of crude extract of plants on germination of seeds. The plants which we have chosen may show the positive or negative effect on the germination of seeds. This has some importance in the rain fed areas. Even the specific plant extract soaked and sow in land may helpful to tolerate the drought conditions. Also study is helpful to agriculture or agricultural industry. It helps to find out the anti sprouting property of the plants. However, further work is needed to improve this method

Challenges in managing real-time data in health information system (HIS)

© Springer International Publishing Switzerland 2016. In this paper, we have discussed the challenges in handling real-time medical big data collection and storage in health information system (HIS). Based on challenges, we have proposed a model for realtime analysis of medical big data. We exemplify the approach through Spark Streaming and Apache Kafka using the processing of health big data Stream. Apache Kafka works very well in transporting data among different systems such as relational databases, Apache Hadoop and nonrelational databases. However, Apache Kafka lacks analyzing the stream, Spark Streaming framework has the capability to perform some operations on the stream. We have identified the challenges in current realtime systems and proposed our solution to cope with the medical big data streams

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Data-Driven Understanding of Smart Service Systems Through Text Mining

Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define ???smart service system??? based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems

Microarray analysis of expression of cell death-associated genes in rat spinal cord cells exposed to cyclic tensile stresses in vitro

<p>Abstract</p> <p>Background</p> <p>The application of mechanical insults to the spinal cord results in profound cellular and molecular changes, including the induction of neuronal cell death and altered gene expression profiles. Previous studies have described alterations in gene expression following spinal cord injury, but the specificity of this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile stresses on cultured spinal cord cells from E15 Sprague-Dawley rats, using the FX3000^®Flexercell Strain Unit. We examined cell morphology and viability over a 72 hour time course. Microarray analysis of gene expression was performed using the Affymetrix GeneChip System^®, where categorization of identified genes was performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) systems. Changes in expression of 12 genes were validated with quantitative real-time reverse transcription polymerase chain reaction (RT-PCR).</p> <p>Results</p> <p>The application of cyclic tensile stress reduced the viability of cultured spinal cord cells significantly in a dose- and time-dependent manner. Increasing either the strain or the strain rate independently was associated with significant decreases in spinal cord cell survival. There was no clear evidence of additive effects of strain level with strain rate. GO analysis identified 44 candidate genes which were significantly related to "apoptosis" and 17 genes related to "response to stimulus". KEGG analysis identified changes in the expression levels of 12 genes of the mitogen-activated protein kinase (MAPK) signaling pathway, which were confirmed to be upregulated by RT-PCR analysis.</p> <p>Conclusions</p> <p>We have demonstrated that spinal cord cells undergo cell death in response to cyclic tensile stresses, which were dose- and time-dependent. In addition, we have identified the up regulation of various genes, in particular of the MAPK pathway, which may be involved in this cellular response. These data may prove useful, as the accurate knowledge of neuronal gene expression in response to cyclic tensile stress will help in the development of molecular-based therapies for spinal cord injury.</p

From mechatronics to the Cloud

At its conception mechatronics was viewed purely in terms of the ability to integrate the technologies of mechanical and electrical engineering with computer science to transfer functionality, and hence complexity, from the mechanical domain to the software domain. However, as technologies, and in particular computing technologies, have evolved so the nature of mechatronics has changed from being purely associated with essentially stand-alone systems such as robots to providing the smart objects and systems which are the building blocks for Cyber-Physical Systems, and hence for Internet of Things and Cloud-based systems. With the possible advent of a 4th Industrial Revolution structured around these systems level concepts, mechatronics must again adapt its world view, if not its underlying technologies, to meet this new challenge