The canonical Brucella species-host dependency is changing, however, the antibiotic susceptibility profiles remain unchanged.

Brucellosis is a chronic disease caused by Brucella species with a wide range of hosts, from marine mammals to terrestrial species, but with strict host preferences. With the zoonotic character, the prevalence of human brucellosis cases is a reflection of animal infections. This study aimed to identify 192 Brucella isolates obtained from various sources by Bruce-ladder PCR and to determine their antibiotic susceptibilities by gradient diffusion method (E-test). As a result of the PCR, all human isolates (n = 57) were identified as B. melitensis. While 58 (82.9%) of the cattle isolates were identified as B. abortus, 59 (90.8%) of the sheep isolates were identified as B. melitensis. In addition, 12 (17.1%) of the cattle isolates and 6 (9.2%) of the sheep isolates were determined as B. melitensis and B. abortus, respectively. The primary host change behavior of B. melitensis was 1.9 times higher than that of B. abortus. While gentamicin and ciprofloxacin susceptibilities of Brucella isolates were 100%, tetracycline, doxycycline, streptomycin, trimethoprim/sulfamethoxazole and rifampicin susceptibilities were 99%, 99%, 97.4%, 91.7% and 83.9%, respectively. The lowest sensitivity of the isolates was determined against to cefoperazone as 26%. A triple-drug resistance was detected in 1 B. abortus isolate that included simultaneous resistance to cefoperazone, rifampicin, and trimethoprim/sulfamethoxazole. The high susceptibility profiles we found against to antibiotics such as tetracycline, doxycycline gentamicin and ciprofloxacin, used widely in treatment, are encouraging. However, the change in the canonical Brucella species-primary host preference suggests the need to reconsider eradication program, including updating vaccine formulations.

Cues Disseminated by Professional Associations That Represent 5 Health Care Professions Across 5 Nations: Lexical Analysis of Tweets.

BACKGROUND: Collaboration across health care professions is critical in efficiently and effectively managing complex and chronic health conditions, yet interprofessional care does not happen automatically. Professional associations have a key role in setting a profession's agenda, maintaining professional identity, and establishing priorities. The associations' external communication is commonly undertaken through social media platforms, such as Twitter. Despite the valuable insights potentially available into professional associations through such communication, to date, their messaging has not been examined. OBJECTIVE: This study aimed to identify the cues disseminated by professional associations that represent 5 health care professions spanning 5 nations. METHODS: Using a back-iterative application programming interface methodology, public tweets were sourced from professional associations that represent 5 health care professions that have key roles in community-based health care: general practice, nursing, pharmacy, physiotherapy, and social work. Furthermore, the professional associations spanned Australia, Canada, New Zealand, the United Kingdom, and the United States. A lexical analysis was conducted of the tweets using Leximancer (Leximancer Pty Ltd) to clarify relationships within the discourse. RESULTS: After completing a lexical analysis of 50,638 tweets, 7 key findings were identified. First, the discourse was largely devoid of references to interprofessional care. Second, there was no explicit discourse pertaining to physiotherapists. Third, although all the professions represented in this study support patients, discourse pertaining to general practitioners was most likely to be connected with that pertaining to patients. Fourth, tweets pertaining to pharmacists were most likely to be connected with discourse pertaining to latest and research. Fifth, tweets about social workers were unlikely to be connected with discourse pertaining to health or care. Sixth, notwithstanding a few exceptions, the findings across the different nations were generally similar, suggesting their generality. Seventh and last, tweets pertaining to physiotherapists were most likely to refer to discourse pertaining to profession. CONCLUSIONS: The findings indicate that health care professional associations do not use Twitter to disseminate cues that reinforce the importance of interprofessional care. Instead, they largely use this platform to emphasize what they individually deem to be important and advance the interests of their respective professions. Therefore, there is considerable opportunity for professional associations to assert how the profession they represent complements other health care professions and how the professionals they represent can enact interprofessional care for the benefit of patients and carers.

Node similarity-based graph convolution for link prediction in biological networks.

BACKGROUND: Link prediction is an important and well-studied problem in network biology. Recently, graph representation learning methods, including Graph Convolutional Network (GCN)-based node embedding have drawn increasing attention in link prediction. MOTIVATION: An important component of GCN-based network embedding is the convolution matrix, which is used to propagate features across the network. Existing algorithms use the degree-normalized adjacency matrix for this purpose, as this matrix is closely related to the graph Laplacian, capturing the spectral properties of the network. In parallel, it has been shown that GCNs with a single layer can generate more robust embeddings by reducing the number of parameters. Laplacian-based convolution is not well suited to single-layered GCNs, as it limits the propagation of information to immediate neighbors of a node. RESULTS: Capitalizing on the rich literature on unsupervised link prediction, we propose using node similarity-based convolution matrices in GCNs to compute node embeddings for link prediction. We consider eight representative node-similarity measures (Common Neighbors, Jaccard Index, Adamic-Adar, Resource Allocation, Hub- Depressed Index, Hub-Promoted Index, Sorenson Index and Salton Index) for this purpose. We systematically compare the performance of the resulting algorithms against GCNs that use the degree-normalized adjacency matrix for convolution, as well as other link prediction algorithms. In our experiments, we use three-link prediction tasks involving biomedical networks: drug-disease association prediction, drug-drug interaction prediction and protein-protein interaction prediction. Our results show that node similarity-based convolution matrices significantly improve the link prediction performance of GCN-based embeddings. CONCLUSION: As sophisticated machine-learning frameworks are increasingly employed in biological applications, historically well-established methods can be useful in making a head-start. AVAILABILITY AND IMPLEMENTATION: Our method, SiGraC, is implemented as a Python library and is freely available at https://github.com/mustafaCoskunAgu/SiGraC.

Comparison of naltrexone implant and oral buprenorphine-naloxone in the treatment of opiate use disorder.

OBJECTIVE: We aimed to compare the effectiveness of extended-release naltrexone (XR-NTX) implant and sublingual buprenorphine-naloxone (BUP-NX) in relapse prevention in opiate use disorder (OUD). METHODS: Medical records of 400 patients who were treated for OUD between 2016 and 2020 were retrospectively evaluated concerning sociodemographic and clinical characteristics and abstinence duration with either BUP-NX (192 patients) or XR-NTX (208 patients) as maintenance treatments. RESULTS: The median age of patients using BUP-NX was 25.00, and the median age of patients using XR-NTX was 25.50 (p = .785). The ratio of female patients in the BUP-NX group and the XR-NTX group was 7.3% (n = 14) and 6.7% (n = 14), respectively. A significantly higher abstinence time was observed in the BUP-NX group (median = 4 months) than in the XR-NTX group (median = 3 months) (p = .015). Liver function tests were within the normal ranges at the three time points, which were just before the beginning and in the first and third months of treatment. CONCLUSIONS: These findings suggest that BUP-NX might be more effective than XR-NTX in preventing relapse in OUD and both drugs are safe for the liver. Prospective randomized studies are needed to replicate our results.

Copper and zinc impact on stress biomarkers and growth parameters in a model organism, Galleria mellonella larvae.

The objective of the present study was to investigate the impact of zinc and copper on some biomarkers in a model organism Galleria mellonella L. We investigated the effects of Cu and Zn (10, 50, and 100 mg/100 g diets) on different biomarkers such as oxidative stress parameters (SOD and CAT activities and MDA levels), energy resources (protein, lipid and glycogen levels), electrolyte contents (Ca, Na, and K levels), total hemocyte count (THC), and growth and development of G. mellonella. Additionally, the accumulation levels of the used metals were also studied. Cu caused a significant decrease in protein, lipid and glycogen levels. SOD and CAT activities significantly increased at all concentrations of Cu, while they significantly increased at only high concentrations of Zn (50 and 100 mg). Lipid peroxidation levels (MDA) significantly elevated at high concentrations of both metals. It was determined that the Cu and Zn accumulation increased depending on the increase of the concentration. Zn caused an alteration in Ca level at the concentrations of 50 and 100 mg, and K and Na levels at all concentrations. While, THC significantly reduced at all Cu concentrations, this reduction was observed only at higher Zn concentrations (50 and 100 mg). Larval and pupal development time significantly extended at the highest concentration (100 mg) of Cu, and females' lifespan significantly shortened at all concentrations of Cu. Zinc caused an extension in larval development time at the highest concentration (100 mg), and caused a shortening in females and males' lifetime at all concentrations. The observed changes in biomarkers can be used as the illustration of potential toxic effects of high levels of Cu and Zn in organisms.

[Helicobacter pylori Positivity and Risk Analysis in Patients with Abdominal Pain Complaints]. / Abdominal Agri Yakinmali Hastalarda Helicobacter pylori Pozitifligi ve Risk Analizi.

Helicobacters have wide host diversity due to the their particular virulence and environmental factors and may cause infections in humans. As they live in and around the stomach the group is called as gastric helicobacters which particularly consists of Helicobacter pylori and Helicobacter heilmanni, Helicobacter felis, Helicobacter salomonis and many other species, as well. In this study, it was aimed to evaluate 195 patients (119 urban and 76 rural residents, 121 female and 74 male individuals between 18 and 93 years of age) in terms of gastric Helicobacter (H.pylori, H.felis and H.heilmanii) who have admitted to the Health Research and Application Center of Kafkas University Endoscopy Unit of the General Surgery Department with the complaints of abdominal pain. For this purpose, biopsy specimens obtained from various parts of the stomach (corpus and antrum) by endoscopy were analyzed with histopathological examination and PCR. Histopathological analysis sections were stained with May-Grunwald-Giemsa and spiral-shaped helicobacters attached to the surface of the epithelium were investigated. For the direct analysis of Helicobacter in biopsy samples, 16S rRNA gene based genus-specific and urease B gene based species-specific PCR methods were used. Out of the 195 cases that were histopathologically evaluated 163 (83.58%) were found to be positive for gastric Helicobacter, while five were suspected and 27 were negative. Helicobacter spp. DNA were detected in 107 (54.87%) samples, of these samples 91 were histopathologically positive, 13 were negative and three were suspicious samples. Eighty seven (44.61%) of the samples were identified as H.pylori by species-specific PCR. H.felis and H.heilmannii could not be detected in any of the samples; meanwhile genus-specific PCR positive 20 samples were not identified. In this study, 42.85% of the individuals living in urban area and 47.36% of those living in rural area were identified as H.pylori positive. 46.28% of women and 41.89% of men were positive for H.pylori. The age range of H.pylori positive individuals were as follows: 60% of the individuals were between 15-24 years, 60.27% of the individuals were between 25-44 years, 34.66% of the individuals were between 45-64 years and 29.72% of the individuals were 65 and over. 42.64% of the cat or dog owners were found as H.pylori positive whereas H.pylori was positive in 45.66% of the individuals who do not own animals. No significant relationship was found between these determinants and the prevalence of the disease (p> 0.05). However, the positivity of H.pylori was higher in the 25-44 active working age group due to the increased agent exposure (p<0.05). This study is the first study on the prevalence of H.pylori in humans and analysis of possible risk factors in the region and hoped to provide useful information for the researchers working in this field.

Determining the appropriate amount of anesthetic gas using DWT and EMD combined with neural network.

The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models have used the full spectrum of EEG signals together with the systolic-diastolic pressure and pulse values. As it is generally agreed today that the brain is in stable state and the delta-theta bands of the EEG spectrum remain active during anesthesia. Considering this background, two questions that motivates this paper. First, determining the amount of gas to be administered is whether feasable from the spectrum of EEG during the maintenance stage of surgical operations. Second, more specifically, the delta-theta bands of the EEG spectrum are whether sufficient alone for this aim. This research aims to answer these two questions together. Discrete wavelet transformation (DWT) and empirical mode decomposition (EMD) were applied to the EEG signals to extract delta-theta bands. The power density spectrum (PSD) values of target bands were presented as inputs to multi-layer perceptron (MLP) neural network (NN), which predicted the gas level. The present study has practical implications in terms of using less data, in an effective way and also saves time as well.

The impact of ankle kinesio taping on pain management in patients with acute ankle sprain.

BACKGROUND: The objective of this study was to assess the efficacy of Kinesio Tape (KT) application as a complementary treatment for patients with acute ankle sprain (AAS) in an Emergency Department (ED) setting. METHODS: A prospective, quasi-randomized controlled trial was conducted in a tertiary care ED. Adult patients diagnosed with isolated, stable Grade 1 and Grade 2 AAS were included. Patients were divided into two groups: the KT group, where KT was applied in addition to conventional treatment, and the control group, receiving only conventional treatment. Pain intensity, analgesic usage, and patient satisfaction were assessed. RESULTS: While pain levels were similar between both groups at baseline and the 30th minute, the control group reported significantly lower pain levels at the 60th minute (p=0.575, p=0.437, and p=0.042, respectively). The KT group exhibited reduced analgesic drug consumption and higher patient satisfaction levels (p<0.001 and p=0.003, respectively). Logistic regression analysis revealed that the difference in pain intensity at the 60th minute lost significance, while analgesic usage and patient satisfaction remained significant (p=0.631, p=0.003, and p=0.026, respectively). CONCLUSION: KT application, as a complementary treatment, may reduce the need for analgesics and enhance patient satisfaction in patients with AAS in the ED. Further research is needed to refine its application and confirm its effectiveness in standard AAS treatment protocols.

Intelligent PID control of an industrial electro-hydraulic system.

In this study, an intelligent PID (i-PID) controller is designed for position control of a nonlinear electro-hydraulic system with uncertain valve characteristics and supply pressure variations. The proposed controller uses estimation of ultra-local model of the system. To exhibit the capability of the proposed method, the controller parameters are optimized via the particle swarm optimization method through a nominal nonlinear model of the system. Then, the performance of the i-PID controller, parameters of which are optimized by using the nominal model, is examined under uncertainties caused by valve characteristics and supply pressure variations. Moreover, the friction between the piston and the hydraulic cylinder is also considered in experiments. A PID controller whose parameters are also optimized based on the same performance criteria, is used for comparison purposes with i-PID control both in simulations and experiments. Performance metrics of the controllers are examined and presented by employing two separate reference signals: Sine wave and ramp. The results show that the i-PID controller shows significantly better results than the classical PID controller in tracking the test signals under various supply pressures and valve modes.

Topological feature generation for link prediction in biological networks.

Graph or network embedding is a powerful method for extracting missing or potential information from interactions between nodes in biological networks. Graph embedding methods learn representations of nodes and interactions in a graph with low-dimensional vectors, which facilitates research to predict potential interactions in networks. However, most graph embedding methods suffer from high computational costs in the form of high computational complexity of the embedding methods and learning times of the classifier, as well as the high dimensionality of complex biological networks. To address these challenges, in this study, we use the Chopper algorithm as an alternative approach to graph embedding, which accelerates the iterative processes and thus reduces the running time of the iterative algorithms for three different (nervous system, blood, heart) undirected protein-protein interaction (PPI) networks. Due to the high dimensionality of the matrix obtained after the embedding process, the data are transformed into a smaller representation by applying feature regularization techniques. We evaluated the performance of the proposed method by comparing it with state-of-the-art methods. Extensive experiments demonstrate that the proposed approach reduces the learning time of the classifier and performs better in link prediction. We have also shown that the proposed embedding method is faster than state-of-the-art methods on three different PPI datasets.

Evaluation of Code Blue Notifications and Their Results: A University Hospital Example.

OBJECTIVE: Code blue is one of the important practices for preventing mortality and morbidity and increasing the quality of care in hospitals. The aim of this study was to evaluate the blue code notifications and their results, emphasise their importance, and determine the effectiveness and deficiencies of the application. METHODS: In this study, all code blue notification forms recorded between January 1 and December 31, 2019, were examined retrospectively. RESULTS: It was determined that code blue calls were made for 108 cases, including 61 females and 47 males, and the mean age of the patients was 56.47 ± 20.73. The accuracy rate of the code blue calls was determined as 42.6%, and 57.4% of them were made during non-working hours. Also, 15.2% of the correct code blue calls were made from dialysis and radiology units. The mean time for the teams to reach the scene was 2.83 ± 1.30 minutes, and the mean time to respond to correctly made code blue calls was 33.97 ± 17.95 minutes. It was found that 15.7% of the patients in correctly made code blue calls were exitus after the intervention. CONCLUSION: Early diagnosis of cardiac or respiratory arrest cases and quick and correct intervention are very important in achieving patient and employee safety. For this reason, it is necessary to continuously evaluate code blue practices, educate the staff, and organise improvement activities constantly.

Biomechanics Characterization of Autonomic and Somatic Nerves by High Dynamic Closed-Loop MEMS force sensing.

The biomechanics of peripheral nerves are determined by the blood-nerve barrier (BNB), together with the epineural barrier, extracellular matrix, and axonal composition, which maintain structural and functional stability. These elements are often ignored in the fabrication of penetrating devices, and the implant process is traumatic due to the mechanical distress, compromising the function of neuroprosthesis for sensory-motor restoration in amputees. Miniaturization of penetrating interfaces offers the unique opportunity of decoding individual nerve fibers associated to specific functions, however, a main issue for their implant is the lack of high-precision standardization of insertion forces. Current automatized electromechanical force sensors are available; however, their sensitivity and range amplitude are limited (i.e. mN), and have been tested only in-vitro. We previously developed a high-precision bi-directional micro-electromechanical force sensor, with a closed-loop mechanism (MEMS-CLFS), that while measuring with high-precision (-211.7µN to 211.5µN with a resolution of 4.74nN), can be used in alive animal. Our technology has an on-chip electrothermal displacement sensor with a shuttle beam displacement amplification mechanism, for large range and high-frequency resolution (dynamic range of 92.9 dB), which eliminates the adverse effect of flexural nonlinearity measurements, observed with other systems, and reduces the mechanical impact on delicate biological tissue. In this work, we use the MEMS-CLFS for in-vivo bidirectional measurement of biomechanics in somatic and autonomic nerves. Furthermore we define the mechanical implications of irrigation and collagen VI in the BNB, which is different for both autonomic and somatic nerves (~ 8.5-8.6 fold density of collagen VI and vasculature CD31+ in the VN vs ScN). This study allowed us to create a mathematical approach to predict insertion forces. Our data highlights the necessity of nerve-customization forces to prevent injury when implanting interfaces, and describes a high precision MEMS technology and mathematical model for their measurements.

Developing a label propagation approach for cancer subtype classification problem.

Cancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, treatment methods need to be customized. The identification of distinct cancer subtypes is an important problem in bioinformatics, since it can guide future precision medicine applications. In order to design targeted treatments, bioinformatics methods attempt to discover common molecular pathology of different cancer subtypes. Along this line, several computational methods have been proposed to discover cancer subtypes or to stratify cancer into informative subtypes. However, existing works do not consider the sparseness of data (genes having low degrees) and result in an ill-conditioned solution. To address this shortcoming, in this paper, we propose an alternative unsupervised method to stratify cancer patients into subtypes using applied numerical algebra techniques. More specifically, we applied a label propagation-based approach to stratify somatic mutation profiles of colon, head and neck, uterine, bladder, and breast tumors. We evaluated the performance of our method by comparing it to the baseline methods. Extensive experiments demonstrate that our approach highly renders tumor classification tasks by largely outperforming the state-of-the-art unsupervised and supervised approaches.

Emergency nurse triage in the hospital information management system: A quality improvement study.

BACKGROUND: Assessment of nurse triage decision accuracy and triage times is currently carried out through paper-based methods. This quality improvement study aims to develop a method that can assess the accuracy and duration of nurse triage decisions based on a computerized system and to share an example of the application of this method. METHODS: This is a descriptive quality improvement study. The study was carried out in two stages between March and May 2019. The functionality of the developed method was examined using 3835 patients' triage data, which were obtained between June 1 and 14, 2019. RESULTS: With this study, the determination of the accuracy and duration of nurse triage decisions was accomplished with a computerized process based on real patient outputs, and the accuracy and duration of these decisions were continuously measured, monitored, and assessed, which is different from paper-based methods. The functionality of the method was evaluated with data from 3835 real patients. The triage decision accuracy rate was 64.4%, and the average duration of triage was 81.3s. Positive feedback on the method was received from all triage nurses. CONCLUSION: The study result outputs can be integrated into quality processes and can be used internationally as performance assessment criteria and quality indicators for triage nursing.

Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter.

COVID-19 has ruptured routines and caused breakdowns in what had been conventional practice and custom: everything from going to work and school and shopping in the supermarket to socializing with friends and taking holidays. Nonetheless, COVID-19 does provide an opportunity to study how people make sense of radically changing circumstances over time. In this paper we demonstrate how Twitter affords this opportunity by providing data in real time, and over time. In the present research, we collect a large pool of COVID-19 related tweets posted by New Zealanders-citizens of a country successful in containing the coronavirus-from the moment COVID-19 became evident to the world in the last days of 2019 until 19 August 2020. We undertake topic modeling on the tweets to foster understanding and sensemaking of the COVID-19 tweet landscape in New Zealand and its temporal development and evolution over time. This information can be valuable for those interested in how people react to emergent events, including researchers, governments, and policy makers.

Integrated querying and version control of context-specific biological networks.

MOTIVATION: Biomolecular data stored in public databases is increasingly specialized to organisms, context/pathology and tissue type, potentially resulting in significant overhead for analyses. These networks are often specializations of generic interaction sets, presenting opportunities for reducing storage and computational cost. Therefore, it is desirable to develop effective compression and storage techniques, along with efficient algorithms and a flexible query interface capable of operating on compressed data structures. Current graph databases offer varying levels of support for network integration. However, these solutions do not provide efficient methods for the storage and querying of versioned networks. RESULTS: We present VerTIoN, a framework consisting of novel data structures and associated query mechanisms for integrated querying of versioned context-specific biological networks. As a use case for our framework, we study network proximity queries in which the user can select and compose a combination of tissue-specific and generic networks. Using our compressed version tree data structure, in conjunction with state-of-the-art numerical techniques, we demonstrate real-time querying of large network databases. CONCLUSION: Our results show that it is possible to support flexible queries defined on heterogeneous networks composed at query time while drastically reducing response time for multiple simultaneous queries. The flexibility offered by VerTIoN in composing integrated network versions opens significant new avenues for the utilization of ever increasing volume of context-specific network data in a broad range of biomedical applications. AVAILABILITY AND IMPLEMENTATION: VerTIoN is implemented as a C++ library and is available at http://compbio.case.edu/omics/software/vertion and https://github.com/tjcowman/vertion. CONTACT: tyler.cowman@case.edu.

Effects of Selenium and Vitamin E on Enzymatic, Biochemical, and Immunological Biomarkers in Galleria mellonella L.

To understand the effects of micronutrients have particular biological functions that are involved mainly in the antioxidant system, which has essential implications for the development of diseases, this study investigated how vitamin E, selenium, and their combination affect lipid, protein, carbohydrate, and malondialdehyde (MDA) content; antioxidant enzyme (catalase [CAT], superoxide dismutase [SOD], glutathione-S-transferase [GST]) activity; and the total hemocyte count (THC) in larvae of Galleria mellonella L. fed different diets. Diet 1 (100 µg of selenium) significantly decreased carbohydrate and lipid content. Diets 2 (100 µg of vitamin E), 3 (100 µg of selenium and vitamin E each), and 5 (Tween 80) did not significantly affect protein and carbohydrate content. Diet 2 significantly increased the lipid content compared to diet 4 (control). Diet 1 increased CAT, SOD, and GST activity and MDA content (highest at 27.64 nmol/mg protein). Diet 2 significantly decreased SOD activity and MDA content compared to other diets. Diet 1 significantly decreased the THC compared to other diets. These results suggested that selenium changes oxidative stress parameters, energy reserves, and THC in G. mellonella. These changes could be a physiological adaptation against selenium-induced oxidative stress. Vitamin E could play a protective role in selenium toxicity.

Factors affecting the accuracy of nurse triage in tertiary care emergency departments.

OBJECTIVES: The accuracy and duration of triage is vital in emergency departments. However, patient density, diversity of cases, and time pressure make triage difficult. Triage performed properly and at the right time prevents patients from experiencing any untoward incidents that may occur because of waiting. Therefore, the study aimed to share the data obtained from the Hospital Information Management System (HIMS) regarding the accuracy and duration of nurse triage in an adult emergency department. METHODS: This descriptive and cross-sectional study evaluated the accuracy and duration of triage decisions made by nurses for patients admitted to an adult emergency department between June 15 and July 15, 2019. Statistical analysis was performed using Statistical analysis was performed using SPSS software version 23.00. RESULTS: The study included the data of 7705 adult patients. The accuracy rate of nurse triage was 59.3% (n = 4566), and the average duration of triage was 1.52 ± 2.10 min. It was observed that the average duration of accurate triage decisions was longer in patients with triage category 3. A statistically significant relationship was determined between the accuracy of nurse triage and the duration of triage, years of seniority of the nurse, and shifts (P < 0.05). CONCLUSIONS: The accuracy and duration of nurse triage in the hospital where the study was conducted can be evaluated via the HIMS. In order to increase the accuracy of nurse triage in the emergency department, it is necessary to employ experienced and trained nurses, develop computer-based support systems, and increase the number of nurses working in shifts providing care to a large number of patients.

Impact of organophosphorus insecticide, malathion on the progeny sex ratio of Pimpla turionellae L.

The effects of 0.001, 0.01, 0.1 and 0.5 ppm concentrations of malathion, an organophosphorus insecticide, viewed over the course of the experiment, on adult emergence and sex ratios of emerging adults of the parasitic wasp, Pimpla turionellae L. (Hymenoptera: Ichneumonidae) were investigated. Diets which contain 0.001 and 0.01 ppm malathion significantly increased the total adult emergence on day 13, 28 and 31 when compared to control diet. Although 0.01 and 0.1 ppm malathion increased the female emergence, higher concentration of malathion (0.5 ppm) significantly decreased the female emergence. Adult female emergence significantly decreased on day 10, 16 and 25 in the group which was fed with the meridic diet containing 0.5 ppm malathion. This study indicated that orally administrated high concentration of malathion (0.5 ppm) significantly decreased female emergence of P. turionellae.