Physical disruption of intervertebral disc promotes cell clustering and a degenerative phenotype

© 2019, The Author(s). To test the hypothesis that physical disruption of an intervertebral disc disturbs cell-matrix binding, leading to cell clustering and increased expression of matrix degrading enzymes that contribute towards degenerative disc cell phenotype. Lumbar disc tissue was removed at surgery from 21 patients with disc herniation, 11 with disc degeneration, and 8 with adolescent scoliosis. 5 μm sections were examined with histology, and 30-µm sections by confocal microscopy. Antibodies were used against integrin α5beta1, matrix metalloproteinases (MMP) 1, MMP-3, caspase 3, and denatured collagen types I and II. Spatial associations were sought between cell clustering and various degenerative features. An additional, 11 non-herniated human discs were used to examine causality: half of each specimen was cultured in a manner that allowed free ‘unconstrained’ swelling (similar to a herniated disc in vivo), while the other half was cultured within a perspex ring that allowed ‘constrained’ swelling. Changes were monitored over 36 h using live-cell imaging. 1,9-Di-methyl methylene blue (DMMB) assay for glycosaminoglycan loss was carried out from tissue medium. Partially constrained specimens showed little swelling or cell movement in vitro. In contrast, unconstrained swelling significantly increased matrix distortion, glycosaminoglycan loss, exposure of integrin binding sites, expression of MMPs 1 and 3, and collagen denaturation. In the association studies, herniated disc specimens showed changes that resembled unconstrained swelling in vitro. In addition, they exhibited increased cell clustering, apoptosis, MMP expression, and collagen denaturation compared to ‘control’ discs. Results support our hypothesis. Further confirmation will require longitudinal animal experiments

Methods of isolation and identification of pathogenic and potential pathogenic bacteria from skins and tannery effluents

Currently there is no standard protocol available within the leather industry to isolate and identify pathogenic bacteria from hides, skins or tannery effluent. This study was therefore carried out to identify simple but effective methods for isolation and identification of bacterial pathogens from the effluent and skins during leather processing. Identification methods based on both phenotypic and genotypic characteristics were investigated. Bacillus cereus and Pseudomonas aeruginosa were used as indicator bacteria to evaluate the isolation and identification methods. Decontaminated calfskins were inoculated with a pure culture of the above mentioned bacterial species followed by a pre-tanning and chromium tanning processes. Effluent samples were collected and skins were swabbed at the end of each processing stage. Bacterial identification was carried out based on the phenotypic characteristics; such as colony appearance on selective solid media, cell morphology following a standard Gram-staining and spore staining techniques, and biochemical reactions, e.g., the ability of a bacterial species to ferment particular sugars and ability to produce certain enzymes. Additionally, an identification system based on bacterial phenotypic characteristics, known as Biolog® system was applied. A pulsed-filed gel electrophoresis (PFGE) method for bacterial DNA fingerprinting was also evaluated and used for the identification of the inoculated bacteria. The methods described in the study were found to be effective for the identification of pathogenic bacteria from skins and effluent

Akvo FLOW in Nepal: real time monitoring of WASH services

Service delivery in sanitation has been accelerated with the formulation of National Sanitation and Hygiene Master Plan, 2011 by Government of Nepal that aims to achieve universal coverage by 2017. Functionality and sustainability are prime issues that emerge with a question mark in the sanitation promotion and also sprout issues of behaviour change of communities that have already been declared as Open Defecation Free (ODF) areas. The conventional paper based monitoring is sure to fail in coming up with real time data collection, hence leaving flaws for actual analysis and plans for ways forward. In such situation, mobile based data collection has come up as better option, which gives real time monitoring with Global Positioning System (GPS) reference, provides visualisation of collected data (see Photograph 1 on page 4). This helps in making real time decisions through intelligent analysis of data, which can be also viewed in the maps plotted through use of internet

Metals loads into the Mediterranean Sea: estimate of Sarno River inputs and ecological risk

The metals pollution in the Sarno River and its environmental impact on the Gulf of Naples (Tyrrhenian Sea, Central Mediterranean Sea) were estimated. Eight selected metals (As, Hg, Cd, Cr, Cu, Ni, Pb and Zn) were determined in the water dissolved phase (DP), suspended particulate matter (SPM) and sediment samples. Selected metals concentrations ranged from 0.32 to 1,680.39 μg l(-1) in water DP, from 103.6 to 7,734.6 μg l(-1) in SPM and from 90.7 to 2,470.3 mg kg(-1) in sediment samples. Contaminant discharges of selected metals into the sea were calculated in about 13,977.6 kg year(-1) showing that this river should account as one of the main contribution sources of metals to the Tyrrhenian Sea

Regional Cooperation and Conflict Resolution

[Traditional constructions of security, based on pure geo-political conception of threat, have dominated the South Asia region. The nature of conflicts and threats, however, is transforming and voices for peace and cooperation have emerged, primarily from non-state organizations. It is time to develop new, and strengthen already present, stake-holdings such as business and trade, preventive diplomacy and interactions among civil societies for long-term and sustainable peace in the region.] </p

An American Epidemic: Burnout Syndrome in Hospital Nurses

The number of Registered Nurses (RNs) in the United States (U.S.) is roughly three times that of physicians and surgeons, making RNs a critically important component of the U.S. healthcare system. RN Burnout – defined as the feeling of exhaustion from working long hours without rest – is a real concern, having been reported in many hospitals. The purpose of this research is to examine the causes and consequences of Burnout Syndrome among RNs in U.S. hospitals, in order to identify solutions to this problem. The methodology involves a review of the literature and semi-structured interviews. Seven primary databases, two websites, and 35 articles were consulted in this project. Findings indicate that Burnout Syndrome in RNs can be analyzed in terms of four clusters of characteristics: individual, management, organizational, and work. The consequences of Burnout Syndrome are increased RN turnover rates, poor job performance, and threats to patient safety. Burnout Syndrome is more prevalent in hospitals with a higher number of patients per nurse, and among younger RNs. RN Burnout in hospitals negatively impacts the quality of care, patient safety, and the functioning of staff workers in the healthcare industry

The rise of self-judging essential security interest clauses in international investment agreements

Self-judging “essential security interest” clauses permit a state to act as “it considers necessary” for the protection of such interests. This Perspective examines trends in their diffusion and scope, and outlines suggestions for treaty drafters to consider when balancing the desire for regulatory sovereignty with the need for legal stability

PCR Based Genotyping of Lulu Cattle of Nepal for A1, A2 Type Beta-caseins

Lulu is an indigenous breed of cattle (Bos taurus) found in high altitude regions of western Nepal. Population of Lulu cattle has been declining due to introgression with other exotic breeds to increase milk productivity. Here we aimed at finding potential approach for conserving Lulu cattle and its assets by studying the milk contents and investigating which variant of beta-casein protein is present in this breed. Beta caseins are an abundant protein in cow milk with A1 and A2 being the most common genetic variants of this protein. Consumption of A1 type of milk has numerous health-related complications whereas A2 type of milk has numerous human health promoting factors. We used restriction fragment length polymorphism (RFLP) for determining the A1 and A2 variant of beta casein in Lulu cattle. For performing DNA extraction, we collected (n = 18) blood samples of Lulu from Mustang and (n=17) Nepal Agriculture research council farm. The amplified fragments in 3% agarose at 251bp and 213bp respectively confirmed the presence of both A1 and A2 gene in Lulu; however, A2 was of greater abundance. Our study indicated that Lulu has A2 variant of beta-casein predominantly. The gene frequency of A1A1 is 0, A1A2 is 0.06 and A2A2 is 0.94. We further found that the allele frequency of A1 and A2 is 0.03 and 0.97 respectively. We designed special primer for sequencing CSN2 genes since A2 type beta casein gene was predominantly seen on Lulu. The sequencing result further supports our RFLP result as most of our samples have “C” nucleotide SNP in amplified CSN2 gene sequence. The Chi-square value of the current study is 0.04 which supports Hardy-Weinberg equilibrium inferring that Lulu cattle are still in the pure state, where there is no genetic introgression with the exotic breed for the sake of improvement of productivity

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types