Intelligent Model of Nursing Shift in Tehran University of Medical Sciences, Tehran, Iran.

Background: Nurses play a key role in increasing the efficiency of healthcare systems. Given the 24-hour performance of hospitals and the small number of nurses in the field of treatment, it is quintessential to re-shift them in the hospital. This study set out to achieve coherence in nursing shift planning and justice in the order of shifts in hospital. Methods: This applied and a developmental study was performed from 2019 to 2020. We used genetic algorithm to provide operational solutions and define flexible shifts and plan nurses' working hours in Yas Hospital, Tehran University of Medical Sciences Hospital, Tehran, Iran. Results: Based on the selection of each nurse and determining the approved shifts of each ward, the possibility of appropriate planning was provided to determine the required shifts per month and to estimate the needs of each department. Conclusion: Using genetic algorithm and nursing shift in office automation console provides useful tools for managers at all organizational levels, according to which a good balance between the hospital's need for nurse and nurses' demands in different time periods.

A Combination of MALDI-TOF MS Proteomics and Species-Unique Biomarkers' Discovery for Rapid Screening of Brucellosis.

Brucellosis is considered to be a zoonotic infection with a predominant incidence in most parts of Iran that may even simply involve diagnostic laboratory personnel. In the present study, we apply matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for rapid and reliable discrimination of Brucella abortus and Brucella melitensis, based on proteomic mass patterns from chemically treated whole-cell analyses. Biomarkers of the low molecular weight proteome in the MALDI-TOF MS spectra were assigned to conserved ribosomal and structural protein families that were found in genome assemblies of B. abortus and B. melitensis in the NCBI database. Significant protein mass signals successfully mapped to ribosomal proteins and structural proteins, such as integration host factor subunit alpha, cold-shock proteins, HU family DNA-binding protein, ATP synthase subunit C, and GNAT family N-acetyltransferase, with specific biomarker peaks that have been identified for each virulent and vaccine strain. Web-accessible bioinformatics algorithms, with a robust data analysis workflow, followed by ribosomal and structural protein mapping, significantly enhanced the reliable assignment of key proteins and accurate identification of Brucella species. Furthermore, clinical samples were analyzed to confirm the most dominant protein biomarker candidates and their relevance for the identifications of B. melitensis and B. abortus. With proper optimization, we envision that the presented MALDI-TOF MS proteomics analyses, coupled with special usage of bioinformatics, could be used as a cost-efficient strategy for the diagnostics of brucellosis and introduce a reliable identification protocol for species of dangerous bacteria.

Rapid and sensitive determination of neomycin and kanamycin in measles, mumps, and rubella vaccine via high-performance liquid chromatography-tandem mass spectrometry using modified super-paramagnetic Fe3O4 nanospheres.

A simple magnetic dispersive solid-phase extraction (MDSPE) methodology based on mesoporous Fe3O4@ succinic acid nanospheres and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) has been developed to determine kanamycin (KNM) and neomycin (NEO) contents in Measles, Mumps, and Rubella (MMR) vaccine products. The monodispersed mesoporous Fe3O4 nanospheres with self-assembled carboxyl terminated shell have been prepared via a simple solvothermal method. These as-synthesized mesoporous Fe3O4 nanospheres showed a high magnetic saturation value (Ms = 46 emu g-1) and large specific surface area (111.12 m2 g-1) which made them potential candidates as sorbents in magnetic solid-phase extraction. The adsorption experimental data fitted well with the Freundlich-Langmuir isotherm and followed a pseudo-second-order kinetic model. Moreover influential parameters on extraction efficiency were investigated and optimized. Under optimal conditions, the limits of detection for KNM and NEO were 1.0 and 0.1 ng mL-1, respectively. Recovery assessments using real samples exhibited recoveries in the range of 96.0 ± 4.3 to 101.5 ± 7.1 %, with relative standard deviations of <10.7% (for intra- day) and <14.6% (for inter- day). The proposed method was successfully applied for different spiked and un-spiked MMR vaccine samples. The presented extraction method provides a fast, selective, robust and practical platform for the detection of KNM and NEO in MMR vaccine samples.