Pattern and Outcome of Chest Injuries at Bugando Medical Centre in Northwestern Tanzania.

Chest injuries constitute a continuing challenge to the trauma or general surgeon practicing in developing countries. This study was conducted to outline the etiological spectrum, injury patterns and short term outcome of these injuries in our setting. This was a prospective study involving chest injury patients admitted to Bugando Medical Centre over a six-month period from November 2009 to April 2010 inclusive. A total of 150 chest injury patients were studied. Males outnumbered females by a ratio of 3.8:1. Their ages ranged from 1 to 80 years (mean = 32.17 years). The majority of patients (72.7%) sustained blunt injuries. Road traffic crush was the most common cause of injuries affecting 50.7% of patients. Chest wall wounds, hemothorax and rib fractures were the most common type of injuries accounting for 30.0%, 21.3% and 20.7% respectively. Associated injuries were noted in 56.0% of patients and head/neck (33.3%) and musculoskeletal regions (26.7%) were commonly affected. The majority of patients (55.3%) were treated successfully with non-operative approach. Underwater seal drainage was performed in 39 patients (19.3%). One patient (0.7%) underwent thoracotomy due to hemopericardium. Thirty nine patients (26.0%) had complications of which wound sepsis (14.7%) and complications of long bone fractures (12.0%) were the most common complications. The mean LOS was 13.17 days and mortality rate was 3.3%. Using multivariate logistic regression analysis, associated injuries, the type of injury, trauma scores (ISS, RTS and PTS) were found to be significant predictors of the LOS (P < 0.001), whereas mortality was significantly associated with pre-morbid illness, associated injuries, trauma scores (ISS, RTS and PTS), the need for ICU admission and the presence of complications (P < 0.001). Chest injuries resulting from RTCs remain a major public health problem in this part of Tanzania. Urgent preventive measures targeting at reducing the occurrence of RTCs is necessary to reduce the incidence of chest injuries in this region

Understanding the adoption of business analytics and intelligence

Cruz-Jesus, F., Oliveira, T., & Naranjo, M. (2018). Understanding the adoption of business analytics and intelligence. In Á. Rocha, H. Adeli, L. P. Reis, & S. Costanzo (Eds.), Trends and Advances in Information Systems and Technologies, pp. 1094-1103. (Advances in Intelligent Systems and Computing; Vol. 745). Springer Verlag. DOI: 10.1007/978-3-319-77703-0_106Our work addresses the factors that influence the adoption of business analytics and intelligence (BAI) among firms. Grounded on some of the most prominent adoption models for technological innovations, we developed a conceptual model especially suited for BAI. Based on this we propose an instrument in which relevant hypotheses will be derived and tested by means of statistical analysis. We hope that the findings derived from our analysis may offer important insights for practitioners and researchers regarding the drivers that lead to BAI adoption in firms. Although other studies have already focused on the adoption of technological innovations by firms, research on BAI is scarce, hence the relevancy of our research.authorsversionpublishe

An allocation Malmquist index with an application in the China securities industry

This paper proposes an allocation Malmquist index which is inspired by the work on the non-parametric cost Malmquist index. We first show that how to decompose the cost Malmquist index into the input-oriented Malmquist index and the allocation Malmquist index. An application in corporate management of the China securities industry with the panel data set of 40 securities companies during the period 2005–2011 shows the practicality of the propose model

Improved measurement of the K+->pi+nu(nu)over-bar branching ratio

An additional event near the upper kinematic limit for K+-->pi(+)nu(nu) over bar has been observed by experiment E949 at Brookhaven National Laboratory. Combining previously reported and new data, the branching ratio is B(K+-->pi(+)nu(nu) over bar)=(1.47(-0.89)(+1.30))x10(-10) based on three events observed in the pion momentum region 211<P<229 MeV/c. At the measured central value of the branching ratio, the additional event had a signal-to-background ratio of 0.9

Context-sensitive autoassociative memories as expert systems in medical diagnosis

BACKGROUND: The complexity of our contemporary medical practice has impelled the development of different decision-support aids based on artificial intelligence and neural networks. Distributed associative memories are neural network models that fit perfectly well to the vision of cognition emerging from current neurosciences. METHODS: We present the context-dependent autoassociative memory model. The sets of diseases and symptoms are mapped onto a pair of basis of orthogonal vectors. A matrix memory stores the associations between the signs and symptoms, and their corresponding diseases. A minimal numerical example is presented to show how to instruct the memory and how the system works. In order to provide a quick appreciation of the validity of the model and its potential clinical relevance we implemented an application with real data. A memory was trained with published data of neonates with suspected late-onset sepsis in a neonatal intensive care unit (NICU). A set of personal clinical observations was used as a test set to evaluate the capacity of the model to discriminate between septic and non-septic neonates on the basis of clinical and laboratory findings. RESULTS: We show here that matrix memory models with associations modulated by context can perform automatic medical diagnosis. The sequential availability of new information over time makes the system progress in a narrowing process that reduces the range of diagnostic possibilities. At each step the system provides a probabilistic map of the different possible diagnoses to that moment. The system can incorporate the clinical experience, building in that way a representative database of historical data that captures geo-demographical differences between patient populations. The trained model succeeds in diagnosing late-onset sepsis within the test set of infants in the NICU: sensitivity 100%; specificity 80%; percentage of true positives 91%; percentage of true negatives 100%; accuracy (true positives plus true negatives over the totality of patients) 93,3%; and Cohen's kappa index 0,84. CONCLUSION: Context-dependent associative memories can operate as medical expert systems. The model is presented in a simple and tutorial way to encourage straightforward implementations by medical groups. An application with real data, presented as a primary evaluation of the validity and potentiality of the model in medical diagnosis, shows that the model is a highly promising alternative in the development of accuracy diagnostic tools

Comparing Respondent-Driven Sampling and Targeted Sampling Methods of Recruiting Injection Drug Users in San Francisco

The objective of this article is to compare demographic characteristics, risk behaviors, and service utilization among injection drug users (IDUs) recruited from two separate studies in San Francisco in 2005, one which used targeted sampling (TS) and the other which used respondent-driven sampling (RDS). IDUs were recruited using TS (n = 651) and RDS (n = 534) and participated in quantitative interviews that included demographic characteristics, risk behaviors, and service utilization. Prevalence estimates and 95% confidence intervals (CIs) were calculated to assess whether there were differences in these variables by sampling method. There was overlap in 95% CIs for all demographic variables except African American race (TS: 45%, 53%; RDS: 29%, 44%). Maps showed that the proportion of IDUs distributed across zip codes were similar for the TS and RDS sample, with the exception of a single zip code that was more represented in the TS sample. This zip code includes an isolated, predominantly African American neighborhood where only the TS study had a field site. Risk behavior estimates were similar for both TS and RDS samples, although self-reported hepatitis C infection was lower in the RDS sample. In terms of service utilization, more IDUs in the RDS sample reported no recent use of drug treatment and syringe exchange program services. Our study suggests that perhaps a hybrid sampling plan is best suited for recruiting IDUs in San Francisco, whereby the more intensive ethnographic and secondary analysis components of TS would aid in the planning of seed placement and field locations for RDS

Phase 1, placebo-controlled, dose escalation trial of chicory root extract in patients with osteoarthritis of the hip or knee

<p>Abstract</p> <p>Background</p> <p>Extracts of chicory root have anti-inflammatory properties <it>in vitro </it>and in animal models of arthritis. The primary objective of this investigator-initiated, Phase 1, placebo-controlled, double blind, dose-escalating trial was to determine the safety and tolerability of a proprietary bioactive extract of chicory root in patients with osteoarthritis (OA). Secondary objectives were to assess effects on the signs and symptoms of this disorder.</p> <p>Methods</p> <p>Individuals greater than 50 years of age with OA of the hip or knee were eligible for trial entry. A total of 40 patients were enrolled in 3 cohorts and were treated with escalating chicory doses of 600 mg/day, 1200 mg/day and 1800 mg/day for 1 month. The ratio of active treatment to placebo was 5:3 in cohorts 1 and 2 (8 patients) each and 16:8 in cohort 3 (24 patients). Safety evaluations included measurement of vital signs and routine lab tests at baseline and the end of the treatment period. Efficacy evaluations at baseline and final visits included self-assessment questionnaires and measurement of the 25-foot walking time.</p> <p>Results</p> <p>In the highest dose cohort, 18 patients who completed treatment per protocol were analyzed for efficacy. In this group, 13 patients showed at least 20% improvement in the defined response domains of pain, stiffness and global assessment: 9 of 10 (90%) patients randomized to active treatment with chicory and 4 of 8 (50%) patients randomized to placebo (P = 0.06). In general, the treatment was well-tolerated. Only one patient who was treated with the highest dose of chicory had to discontinue treatment due to an adverse event.</p> <p>Conclusions</p> <p>The results of this pilot study suggest that a proprietary bioactive extract of chicory root has a potential role in the management of OA and merits further investigation. Clinicaltrials.gov identifier: NCT 01010919.</p

Membrane TNF confers protection to acute mycobacterial infection

BACKGROUND: Tumour necrosis factor (TNF) is crucial for the control of mycobacterial infection as TNF deficient (KO) die rapidly of uncontrolled infection with necrotic pneumonia. Here we investigated the role of membrane TNF for host resistance in knock-in mice with a non-cleavable and regulated allele (mem-TNF). METHODS: C57BL/6, TNF KO and mem-TNF mice were infected with M. tuberculosis H37Rv (Mtb at 100 CFU by intranasal administration) and the survival, bacterial load, lung pathology and immunological parameters were investigated. Bone marrow and lymphocytes transfers were used to test the role of membrane TNF to confer resistance to TNF KO mice. RESULTS: While TNF-KO mice succumbed to infection within 4–5 weeks, mem-TNF mice recruited normally T cells and macrophages, developed mature granuloma in the lung and controlled acute Mtb infection. However, during the chronic phase of infection mem-TNF mice succumbed to disseminated infection with necrotic pneumonia at about 150 days. Reconstitution of irradiated TNF-KO mice with mem-TNF derived bone marrow cells, but not with lymphocytes, conferred host resistance to Mtb infection in TNF-KO mice. CONCLUSION: Membrane expressed TNF is sufficient to allow cell-cell signalling and control of acute Mtb infection. Bone marrow cells, but not lymphocytes from mem-TNF mice confer resistance to infection in TNF-KO mice. Long-term infection control with chronic inflammation likely disrupting TNF mediated cell-cell signalling, additionally requires soluble TNF

The Pathogenic Properties of a Novel and Conserved Gene Product, KerV, in Proteobacteria

Identification of novel virulence factors is essential for understanding bacterial pathogenesis and designing antibacterial strategies. In this study, we uncover such a factor, termed KerV, in Proteobacteria. Experiments carried out in a variety of eukaryotic host infection models revealed that the virulence of a Pseudomonas aeruginosa kerV null mutant was compromised when it interacted with amoebae, plants, flies, and mice. Bioinformatics analyses indicated that KerV is a hypothetical methyltransferase and is well-conserved across numerous Proteobacteria, including both well-known and emerging pathogens (e.g., virulent Burkholderia, Escherichia, Shigella, Vibrio, Salmonella, Yersinia and Brucella species). Furthermore, among the 197 kerV orthologs analyzed in this study, about 89% reside in a defined genomic neighborhood, which also possesses essential DNA replication and repair genes and detoxification gene. Finally, infection of Drosophila melanogaster with null mutants demonstrated that KerV orthologs are also crucial in Vibrio cholerae and Yersinia pseudotuberculosis pathogenesis. Our findings suggested that KerV has a novel and broad significance as a virulence factor in pathogenic Proteobacteria and it might serve as a new target for antibiotic drug design

Addressing the evolution of automated user behaviour patterns by runtime model interpretation

The final publication is available at Springer via http://dx.doi.org/10.1007/s10270-013-0371-3The use of high-level abstraction models can facilitate and improve not only system development but also runtime system evolution. This is the idea of this work, in which behavioural models created at design time are also used at runtime to evolve system behaviour. These behavioural models describe the routine tasks that users want to be automated by the system. However, users¿ needs may change after system deployment, and the routine tasks automated by the system must evolve to adapt to these changes. To facilitate this evolution, the automation of the specified routine tasks is achieved by directly interpreting the models at runtime. This turns models into the primary means to understand and interact with the system behaviour associated with the routine tasks as well as to execute and modify it. 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