The influence of storage time on ponazuril concentrations in feline plasma

Background The pharmacokinetics of ponazuril have been determined in several species; however, there is very little information on the stability of the drug after storage for long periods of time. This study was undertaken to determine the stability of ponazuril in plasma samples stored at −80 °C, which is the temperature most commonly used in the author’s laboratory. Method Spiked plasma samples (0.3, 7.5, and 15 µg/mL) were stored at −80 °C for three months. Analysis occurred on the first day and then once a week for the following twelve weeks. The drug was extracted using a chloroform extraction and separated by high performance liquid chromatography using ultraviolet detection. Results There was no loss of drug for any concentration for the first four weeks of storage. There was an average loss of less than 5% from day 35 through day 70 and an average loss of 6% on day 77 and 84. The data suggest that ponazuril is stable for 4 weeks when stored at −80 °C and undergoes minimal loss in the remaining 8 weeks.

Application of Inverted Umbrella Technique in Offshore

The oil and gas industries are setting a new achievement every day by fulfilling the energy security of almost all the nations. With the continuous rise in the demand of a hydrocarbon, industries are facing many new challenges while fulfilling it. One of the major concerns is the safety of an environment and safety of working professionals that HSE Department is continuously focused in. The industry has been in continuous upgradation since its inception to counter all the challenges. Inverted Umbrella Technique (IUT) is the recent innovation in the industry and this could be further more conceptualized by adding its role into the energy industries. This could turn out as a major breakthrough in the oil and gas domain from HSE perspective. The paper here aimed for providing efficient solution by setting up the system that could help us to drawdown the rising concern in the safety of the environment. Inverted Umbrella Technique (IUT) could roll down the new horizons for the offshore productions system in oil and gas industries. The concept is focused on the minimal loss of methane during exploitation of gas hydrates as well as focused on the prevention of oil spill and reducing the damage that blowout of oil or gas well can make to the environment while making sure that industries do not suffer any kind of major capital loss and making it safe for industries to not face many health, safety, and environment (HSE) norms that are decided by the government and most important is, it will help us to create a safe environment for aquatic species living around the offshore platform and nearby.

Study of the Various Factors Involved in Monteggia Fractures Treated by Open Reduction and Internal Fixation in Government Medical College, Trichur

BACKGROUND The various factors involved in Monteggia fractures treated by open reduction and internal fixation (ORIF) were studied in patients presenting to Government Medical College, Trichur. Its distribution based on age, gender, and nature of trauma, were observed in the patients. METHODS This study was a prospective descriptive study, conducted in Department of Orthopaedics, Medical College, Thrissur from 1, January, 2016 to 1, July, 2017. Patients were assessed according to age, sex, side of injury, co-morbidities and final functional assessment was made according to Broberg and Morrey score. A total of 37 patients were observed. The patients were assessed, deemed fit for the study, and subjected to operation. Radial head reduction, fixation if needed, then ulna fracture was opened, reduced, and fixed with plate and screws. Postoperative plaster slab was applied, then converted to full above elbow cast, and retained for as long as needed. Post-operative mobilization was by home physiotherapy only. RESULTS Our study showed that open reduction and internal fixation of ulna outcome in Monteggia fractures leads to good elbow function and minimal loss of physical capacity. Immobilization of more than 2 months have very high chances of elbow stiffness. Early active mobilization after surgery is necessary for good functional outcome. Other than mild stiffness and loss of range of motion in some cases, very few other complications were found in our series. CONCLUSIONS Rigid internal fixation of ulna and early active mobilization is the key to achieve a good functional outcome and minimal loss of physical capacity in Monteggia fractures. Very few of the complications that were described in the literature were seen in the study. Even with restricted resources and minimal facilities, almost no permanent or debilitating morbidity or complications were seen in our series. Early active mobilization after surgery was the most important deciding factor for good functional outcome. Prolonged immobilization of more than one month consistently produces poor results. KEYWORDS Monteggia, Broberg and Morrey, Bado Classification, Internal Fixation, Ulna Fracture

The Possibility of Reuse of Nanofiber Mats by Machine Washing at Different Temperatures

The worldwide spread of coronavirus COVID-19 infections demonstrates the great need for personal protective equipment and, in particular, hygiene masks. These masks are essential for the primary protection of the respiratory tract against pathogens such as viruses and bacteria that are infectious and transmitted through the air as large droplets or via small airborne particles. The use of protective masks will continue to accompany humans for an indefinite period of time, and therefore there is an urgent need for a safe method to extend their usability by reusing them under perspective with minimal loss of protective properties. Nanofiber mats are widely used in masks and in this study the reusability of nanofiber mats is investigated by washing them at different temperatures. This paper shows the first measurements of the washability of nanofiber mats. Furthermore, the air permeability is measured, and the evaporation resistance is evaluated. According to the results of this study, the air permeability performance of nanofiber mats does not change significantly after washing, confirming the possibility of reuse.

Processing of EMG Signals with High Impact of Power Line and Cardiac Interferences

This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured EMG signal should be cleaned of different factors like power network interference and ECG heartbeat. Unfortunately, there are no completed studies showing full multistage signal processing of EMG recordings. In this article, the authors propose an original algorithm to perform muscle activity measurements based on raw measurements. The effectiveness of the proposed algorithm for EMG signal measurement was validated by a portable EMG system developed as a part of the EU research project and EMG raw measurement sets. Examples of removing the parasitic interferences are presented for each stage of signal processing. Finally, it is shown that the proposed processing of EMG signals enables cleaning of the EMG signal with minimal loss of the diagnostic content.

Why most Principal Component Analyses (PCA) in population genetic studies are wrong

Principal Component Analysis (PCA) is a multivariate analysis that allows reduction of the complexity of datasets while preserving data's covariance and visualizing the information on colorful scatterplots, ideally with only a minimal loss of information. PCA applications are extensively used as the foremost analyses in population genetics and related fields (e.g., animal and plant or medical genetics), implemented in well-cited packages like EIGENSOFT and PLINK. PCA outcomes are used to shape study design, identify and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, whereabouts, and relatedness. The replicability crisis in science has prompted us to evaluate whether PCA results are reliable, robust, and replicable. We employed an intuitive color-based model alongside human population data for eleven common test cases. We demonstrate that PCA results are artifacts of the data and that they can be easily manipulated to generate desired outcomes. PCA results may not be reliable, robust, or replicable as the field assumes. Our findings raise concerns on the validity of results reported in the literature of population genetics and related fields that place a disproportionate reliance upon PCA outcomes and the insights derived from them. We conclude that PCA may have a biasing role in genetic investigations. An alternative mixed-admixture population genetic model is discussed.

Reduced neutralization of SARS-CoV-2 variants by convalescent plasma and hyperimmune intravenous immunoglobulins for treatment of COVID-19

Hyperimmune immunoglobulin (hCoV-2IG) preparations generated from SARS-CoV-2 convalescent plasma (CP) are under evaluation in several clinical trials of hospitalized COVID-19 patients. Here we explored the antibody epitope repertoire, antibody binding and virus neutralizing capacity of six hCoV-2IG batches as well as nine convalescent plasma (CP) lots against SARS-CoV-2 and emerging variants of concern (VOC). The Gene-Fragment Phage display library spanning the SARS-CoV-2 spike demonstrated broad recognition of multiple antigenic sites spanning the entire spike including NTD, RBD, S1/S2 cleavage site, S2-fusion peptide and S2-heptad repeat regions. Antibody binding to the immunodominant epitopes was higher for hCoV-2IG than CP, with predominant binding to the fusion peptide. In the pseudovirus neutralization assay (PsVNA) and in the wild-type SARS-CoV-2 PRNT assay, hCoV-2IG lots showed higher titers against the WA-1 strain compared with CP. Neutralization of SARS-CoV-2 VOCs from around the globe were reduced to different levels by hCoV-2IG lots. The most significant loss of neutralizing activity was seen against the B.1.351 (9-fold) followed by P.1 (3.5-fold), with minimal loss of activity against the B.1.17 and B.1.429 (<2-fold). Again, the CP showed more pronounced loss of cross-neutralization against the VOCs compared with hCoV-2IG. Significant reduction of hCoV-2IG binding was observed to the RBD-E484K followed by RBD-N501Y and minimal loss of binding to RBD-K417N compared with unmutated RBD. This study suggests that post-exposure treatment with hCoV-2IG is preferable to CP. In countries with co-circulating SARS-CoV-2 variants, identifying the infecting virus strain could inform optimal treatments, but would likely require administration of higher volumes or repeated infusions of hCOV-2IG or CP, in patients infected with the emerging SARS-CoV-2 variants.

Unsupervised DNF Blocking for Efficient Linking of Knowledge Graphs and Tables

Entity Resolution (ER) is the problem of identifying co-referent entity pairs across datasets, including knowledge graphs (KGs). ER is an important prerequisite in many applied KG search and analytics pipelines, with a typical workflow comprising two steps. In the first ’blocking’ step, entities are mapped to blocks. Blocking is necessary for preempting comparing all possible pairs of entities, as (in the second ‘similarity’ step) only entities within blocks are paired and compared, allowing for significant computational savings with a minimal loss of performance. Unfortunately, learning a blocking scheme in an unsupervised fashion is a non-trivial problem, and it has not been properly explored for heterogeneous, semi-structured datasets, such as are prevalent in industrial and Web applications. This article presents an unsupervised algorithmic pipeline for learning Disjunctive Normal Form (DNF) blocking schemes on KGs, as well as structurally heterogeneous tables that may not share a common schema. We evaluate the approach on six real-world dataset pairs, and show that it is competitive with supervised and semi-supervised baselines.

EXPRESS: Exploration of Principal Component Analysis: Deriving PCA Visually Using Spectra

Spectroscopy rapidly captures a large amount of data that is not directly interpretable. Principal Components Analysis (PCA) is widely used to simplify complex spectral datasets into comprehensible information by identifying recurring patterns in the data with minimal loss of information. The linear algebra underpinning PCA is not well understood by many applied analytical scientists and spectroscopists who use PCA. The meaning of features identified through PCA are often unclear. This manuscript traces the journey of the spectra themselves through the operations behind PCA, with each step illustrated by simulated spectra. PCA relies solely on the information within the spectra, consequently the mathematical model is dependent on the nature of the data itself. The direct links between model and spectra allow concrete spectroscopic explanation of PCA, such the scores representing ‘concentration’ or ‘weights’. The principal components (loadings) are by definition hidden, repeated and uncorrelated spectral shapes that linearly combine to generate the observed spectra. They can be visualized as subtraction spectra between extreme differences within the dataset. Each PC is shown to be a successive refinement of the estimated spectra, improving the fit between PC reconstructed data and the original data. Understanding the data-led development of a PCA model shows how to interpret application specific chemical meaning of the PCA loadings and how to analyze scores. A critical benefit of PCA is its simplicity and the succinctness of its description of a dataset, making it powerful and flexible.