Small bowel obstruction secondary to paravesical hernia

Background: Bowel obstruction in the setting of the unscarred abdomen can be due to a wide variety of causes. Internal hernias are a rare cause of bowel obstruction with paravesical hernia being exceedingly rare. Paravesical hernia should form part of the differential diagnosis in the patient presenting with bowel obstruction. Prompt management and reduction of the incarcerated bowel are essential. This will prevent further complications especially related to bowel ischemia. Case summary: The patient presented with a classical history of small bowel obstruction. Abdominal X-ray revealed distended loops of small bowel and absence of air in the rectum. An exploratory laparotomy revealed a paravesical internal hernia. A loop of terminal ileum had incarcerated and was the cause of the bowel obstruction. The defect was repaired after reducing the bowel and the patient made an uneventful recovery. Conclusion: Internal paravesical hernia although extremely rare should form part of the differential diagnosis in the patient presenting with small bowel obstruction especially in the previously unscarred abdomen. If the obstruction is complete then prompt exploration via laparotomy or laparoscopy is required. Delays in definitive management may result in marginally viable bowel becoming ischemic and requiring bowel resection

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories

This paper presents “optimal identification,” a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate

Sugar palm (Arenga pinnata) fibers: new emerging natural fibre and its relevant properties, treatments and potential applications

The key factors influencing the widespread acceptance of natural fibres as green materials are due to the quick depletion of petroleum resources and the growing awareness of environmental issues associated to the usage of conventional plastics. Due to their eco-friendly and sustainable, natural fibres have garnered the interest of scientists. Sugar palm (Arenga pinnata) tree is cultivated in tropical regions and is thought to hold promise as a source of natural fibres. The potential use of fibres derived from the sugar palm in a number of applications has been studied especially as composites materials. Investigations into these fibres on it potential uses have been conducted. Treatments of fibres is one of the important elements to increase the useability of this fibre. However, there is a problem regarding the inconsistent data reported by previous authors on experimental methods and the values of mechanical and physical properties. Therefore, it is now vital to organise data that would be helpful in the design of this fibre so that researchers may make wise choices regarding future study and application. Present review focuses on recent works related to properties of sugar palm fibers, fibers modification and their fabrication as green composites. The review also unveils the potential of sugar palm fibers and polymer for advanced industrial applications such as automotive, defense, packaging, and others. Many manufacturing sectors are focusing on using natural resources, particularly fiber-rich plants, for the production of polymer composites as a result of environmental protection, the use of renewable resources, and product biodegradability. This tendency has led to the substitution of plant fibers for synthetic fibers as reinforcement in polymer mixtures. Natural fibers are now prioritized in the composite industry due to economics and their superior properties, which have persuaded many industrial sectors to use synthetic fibers to reinforce plastics

Automated classification and characterization of the mitotic spindle following knockdown of a mitosis-related protein

Cell division (mitosis) results in the equal segregation of chromosomes between two daughter cells. The mitotic spindle plays a pivotal role in chromosome alignment and segregation during metaphase and anaphase. Structural or functional errors of this spindle can cause aneuploidy, a hallmark of many cancers. To investigate if a given protein associates with the mitotic spindle and regulates its assembly, stability, or function, fluorescence microscopy can be performed to determine if disruption of that protein induces phenotypes indicative of spindle dysfunction. Importantly, functional disruption of proteins with specific roles during mitosis can lead to cancer cell death by inducing mitotic insult. However, there is a lack of automated computational tools to detect and quantify the effects of such disruption on spindle integrity.We developed the image analysis software tool MatQuantify, which detects both large-scale and subtle structural changes in the spindle or DNA and can be used to statistically compare the effects of different treatments. MatQuantify can quantify various physical properties extracted from fluorescence microscopy images, such as area, lengths of various components, perimeter, eccentricity, fractal dimension, satellite objects and orientation. It can also measure textual properties including entropy, intensities and the standard deviation of intensities. Using MatQuantify, we studied the effect of knocking down the protein clathrin heavy chain (CHC) on the mitotic spindle. We analysed 217 microscopy images of untreated metaphase cells, 172 images of metaphase cells transfected with small interfering RNAs targeting the luciferase gene (as a negative control), and 230 images of metaphase cells depleted of CHC. Using the quantified data, we trained 23 supervised machine learning classification algorithms. The Support Vector Machine learning algorithm was the most accurate method (accuracy: 85.1%; area under the curve: 0.92) for classifying a spindle image. The Kruskal-Wallis and Tukey-Kramer tests demonstrated that solidity, compactness, eccentricity, extent, mean intensity and number of satellite objects (multipolar spindles) significantly differed between CHC-depleted cells and untreated/luciferase-knockdown cells.MatQuantify enables automated quantitative analysis of images of mitotic spindles. Using this tool, researchers can unambiguously test if disruption of a protein-of-interest changes metaphase spindle maintenance and thereby affects mitosis

Assessment of Appropriateness of Antimicrobial Therapy in Resource-Constrained Settings: Development and Piloting of a Novel Tool—AmRAT

Inappropriate antimicrobial prescribing is considered to be the leading cause of high burden of antimicrobial resistance (AMR) in resource-constrained lower- and middle-income countries. Under its global action plan, the World Health Organization has envisaged tackling the AMR threat through promotion of rational antibiotic use among prescribers. Given the lack of consensus definitions and other associated challenges, we sought to devise and validate an Antimicrobial Rationality Assessment Tool—AmRAT—for standardizing the assessment of appropriateness of antimicrobial prescribing. A consensus algorithm was developed by a multidisciplinary team consisting of intensivists, internal medicine practitioners, clinical pharmacologists, and infectious disease experts. The tool was piloted by 10 raters belonging to three groups of antimicrobial stewardship (AMS) personnel: Master of Pharmacology (M.Sc.) (n = 3, group A), Doctor of Medicine (MD) residents (n = 3, group B), and DM residents in clinical pharmacology (n = 4, group C) using retrospective patient data from 30 audit and feedback forms collected as part of an existing AMS program. Percentage agreement and the kappa (κ) coefficients were used to measure inter-rater agreements amongst themselves and with expert opinion. Sensitivity and specificity estimates were analyzed comparing their assessments against the gold standard. For the overall assessment of rationality, the mean percent agreement with experts was 76.7% for group A, 68.9% for group B, and 77.5% for group C. The kappa values indicated moderate agreement for all raters in group A (κ 0.47–0.57), and fair to moderate in group B (κ 0.22–0.46) as well as group C (κ 0.37–0.60). Sensitivity and specificity for the same were 80% and 68.6%, respectively. Though evaluated by raters with diverse educational background and variable AMS experience in this pilot study, our tool demonstrated high percent agreement and good sensitivity and specificity, assuring confidence in its utility for assessing appropriateness of antimicrobial prescriptions in resource-constrained healthcare environments