3790 research outputs found
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Developing an Intelligent Tool for Breast Cancer Prognosis Using Artificial Neural Network
No full textToday, there is ample scientific evidence that Breast Cancer (BC) is a global health challenge given its prevalence and invasive nature. Therefore, early detection of BC can help minimize the devastating effects of the disease. This study aimed to design a Clinical Decision Support System (CDSS) based on the best Artificial Neural Network (ANN) configuration to identify patients quickly. Using a single-center registry, we retrospectively reviewed the records of 3380 suspected BC cases. The independence test of Chi-Square at P<0.01 was utilized to select the most important criteria. Then the different ANN configuration was implemented in the Matlab R2013 environment and compared using some evaluation criteria. Finally, the best ANN configuration was obtained. After implementing feature selection, 20 variables were determined as the most relevant factors. The experimental results indicate that the best performance was obtained by the 20-25-1 configuration with PPV=90.9, NPV=99.7, Sensitivity=98.9, Specificity=97.9, Accuracy=98.1, and AUC=0.958. The proposed software can identify cases of BC from healthy individuals with optimal diagnostic accuracy. Additionally, it might be integrated as a practical and helpful tool in natural clinical settings for easy and effective disease screening. © 2022 Tehran University of Medical Sciences. All rights reserved
Evaluation of Triple Fragment Vaccine HSPX (Rv2031c) + PPE44 (Rv2770c) + Mouse IgG1 (Fcγ2a) with Auxiliary Adjuncts IL-22 in Comparison with BCG Vaccine
No full textBackground & Objective: Despite the vaccination with the BCG vaccine, tuberculosis (TB) remains one of the major health problems in the world. The aim of this study was to evaluate our newly designed vaccine using IL-22 as an adjuvant in comparison with the common BCG vaccine. Methods: The gene constructs were cloned into the expression vector of pET28a and then into the recombinant vector of PET28a – HSPX, and PPE44 was transformed into Escherichia coli BL21 (DE3). Finally, the immunogenicity of recombinant proteins with and without BCG and IL-22 in BALB/c mice was investigated. Results: The key cytokines INF-γ and TNF-α were elevated more greatly in BCG immunized group than in PHF immunized group. Immunization with PHF showed a significant increase in IL-4 levels versus the BCG group. Adding IL-22 to the vaccine formulations indicated a tiny increase in IL-4 levels compared to their related vaccine groups. Specific total IgG1 in the experimental groups showed an increase in comparison with control groups, but in the vaccinated groups, no significant differences were observed, and the presence of IL-22 in the vaccine formulations indicated a slight decrease compared with the related mere vaccine groups. Results of specific total IgG2a in the experimental groups revealed that only in the PHF group formulated with IL-22 a significant increase occurs compared with all other experimental groups. Conclusion: It seems that BCG, as the only licensed vaccine for TB infection, could be more potent than a recombinant vaccine in the induction of cellular and humoral immune responses. © 2022,Iranian Society of Pathology. All rights reserved
Effects of Dill Extract on Blood Lipid Levels (TC, TG, LDL and HDL): A Systematic Review and Meta-Analysis
No full textBackground & Objective: In recent years,there has been a growing trend towards the use of herbal medicine in the treatment and prevention of diseases. Blood lipid-lowering drugs have many side effects. On the other hand, various studies have reported the effect of dill (Anethum graveolens) on the reduction of blood lipids in different ways. This study aimed to evaluate the effect of dill on reducing the blood lipid levels. Materials & Methods: In this systematic review, 12 papers that evaluated the effect of dill on blood lipid levels up to the end of 2018 were studied using valid key words such as Lipid Profile, Dill (Anethum graveolens), and Hyperlipidemia in Pubmed, Medlib, Scopus, Sciencedirect, Embase, Google Scholar, Magiran, IranMedex, and SID. The results of the studies were combined using the random effects method of meta-analysis. The heterogeneity of studies was investigated using Q statistics and I2 Index. Results: In 12 studies, the weighted mean differences (WMDs) of cholesterol reduction (TC) before and after intervention were estimated to be WMD =-19.22 mg/dl (95 CI:-30.68,-7.77), triglyceride, WMD =-25.47 mg/dl (95 CI:-49.28,-1.66) and low density lipoprotein (LDL), WMD =-14.01 mg/dl (95 CI:-22.14,-5.89) which were statistically significant (p = 0.001). Meta-analysis after intervention in the case and placebo groups were (SMD=-2.71, 95 CI:-3.28,-1.06), for TC (SMD=-1.77, 95CI:-2.71,-0.82) for TG and (SMD=-2.64, 95CI:-3.88,-1.41)for LDL which indicated statistically significant reduction. Conclusion: Dill reduces cholesterol, triglyceride and low-density lipoprotein, but does not have a significant effect on high-density lipoprotein levels. © 2022, Zanjan University of Medical Sciences and Health Services. All rights reserved
GFAP and Neuron Specific Enolase (NSE) in the Serum of Suicide Attempters
No full textBackground: To determine whether neuronal damage and/or neuroinflammation exist in the brain of suicide attempters and to find a novel biological biomarker to help distinguishing high risk individuals with suicide behavior, we aimed to measure glial fibrillary acidic protein (GFAP), neuron specific enolase (NSE), and nerve growth factor (NGF) in suicide attempters. Methods: In the present case-control study, the serum level of NSE, GFAP, and NGF were measured quantitatively in 43 suicide attempters and 43 healthy control participants aged 18 to 35 years. Data were analyzed using the nonpaired t test followed by the Mann-Whitney posttest. Results: The mean serum level of NSE and GFAP were significantly higher in suicide attempters compared with healthy control individuals (p = 0.003, p = 0.001, respectively), while no significant difference was detected in NGF serum level between the 2 groups. Conclusion: Our findings of increased level of NSE along with the significant increase in GFAP would propose the presence of low grade neuroinflammation in the brain of these participants. NSE/GFAP might be good markers that is easily accessible and can be considered as prognostic markers in high-risk suicide attempters © Iran University of Medical Science
COVID-19 Mass Vaccination and Flu season: Concern for Decreased Public Health Measures and worsening the influenza situation
No full textReports show that other ordinary childhood infections like measles or Influenza are likely to reemerge. The re-emergence of infectious diseases may happen due to the direct impact of the pandemic on the community because of decreased access to health and medical services, interrupted transport systems, weaknesses in the supply chain, flight restrictions, closings of the border, and international trade problems. The most prevalent cause 60.9% for low vaccine uptake and coverage during the current pandemic was fear of exposure to the COVID-19 virus outside the home. The expectation and hope that the pattern of reduction in transmission and number of influenza cases will continue over the next flu season depend on continued adherence to nonpharmaceutical interventions and their long-term application. But there is always the fear and threat of increasing the spread of Influenza by reducing the movement restrictions and low adherence to protective health measures due to vaccination. So far, not much information has been published about the interaction between different infectious diseases in the background of the coronavirus pandemic and related interventions. The purpose of this article is to examine the general effects of the Covid-19 vaccination on the spread of Influenza in the coming seasons
Using decision tree algorithms for estimating ICU admission of COVID-19 patients
No full textIntroduction: Coronavirus disease 2019 (COVID-19) outbreak has overwhelmed many healthcare systems worldwide and put them at the edge of collapsing. As intensive care unit (ICU) capacities are limited, deciding on the proper allocation of required resources is crucial. This study aimed to develop and compare models for early predicting ICU admission in COVID-19 patients at the point of hospital admission. Materials and methods: Using a single-center registry, we studied the records of 512 COVID-19 patients. First, the most important variables were identified using Chi-square test (at p < 0.01) and logistic regression (with odds ratio at P < 0.05). Second, we trained seven decision tree (DT) algorithms (decision stump (DS), Hoeffding tree (HT), LMT, J-48, random forest (RF), random tree (RT) and REP-Tree) using the selected variables. Finally, the models' performance was evaluated. Furthermore, we used an external dataset to validate the prediction models. Results: Using the Chi-square test, 20 important variables were identified. Then, 12 variables were selected for model construction using logistic regression. Comparing the DT methods demonstrated that J-48 (F-score of 0.816 and AUC of 0.845) had the best performance. Also, the J-48 (F-score = 80.9 and AUC = 0.822) gained the best performance in generalizability using the external dataset. Conclusions: The study results demonstrated that DT algorithms can be used to predict ICU admission requirements in COVID-19 patients based on the first time of admission data. Implementing such models has the potential to inform clinicians and managers to adopt the best policy and get prepare during the COVID-19 time-sensitive and resource-constrained situation
Worldwide prevalence of fungal coinfections among COVID-19 patients: a comprehensive systematic review and meta-analysis
No full textMicrobial coinfections can increase the morbidity and mortality rates of viral respiratory diseases. Therefore, this study aimed to determine the pooled prevalence of fungal coinfections in coronavirus disease 2019 (COVID-19) patients. Web of Science, Medline, Scopus, and Embase were searched without language restrictions to identify the related research on COVID-19 patients with fungal coinfections from December 1, 2019, to December 30, 2020. A random-effects model was used for analysis. The sample size included 2,246 patients from 8 studies. The pooled prevalence of fungal coinfections was 12.60. The frequency of fungal subtype coinfections was 3.71 for Aspergillus, 2.39 for Candida, and 0.39 for other. The World Health Organization's Regional Office for Europe and Regional Office for Southeast Asia had the highest (23.28) and lowest (4.53) estimated prevalence of fungal coinfection, respectively. Our findings showed a high prevalence of fungal coinfections in COVID-19 cases, which is a likely contributor to mortality in COVID-19 patients. Early identification of fungal pathogens in the laboratory for COVID-19 patients can lead to timely treatment and prevention of further damage by this hidden infection
Novel Antimicrobial Target in Acinetobacter Baumannii
No full textBackground: Resistance to multiple drugs is one of the biggest challenges in managing infectious diseases. Acinetobacter baumannii is considered a nosocomial infection. According to the multiple roles of the toxin-antitoxin system, this system can be considered an antimicrobial target in the presence of bacteria. With the impact on bacterial toxin, it can be used as a new antibacterial target. The purpose of this study was to determine the mazEF genes as a potent antimicrobial target in A. baumannii clinical isolates. Methods: The functionality of mazEF genes was evaluated by qPCR in fifteen A. baumannii clinical isolates. Then, the mazE locus was targeted by peptide nucleic acid (PNA). Results: The results showed a significant difference in the mean number of copies of mazF gene in normal and stress conditions. Also, we found that at a concentration of 15 mu M of PNA the bacteria were killed and confirmed by culture on LB agar. Conclusions: This research is the first step in introducing mazEF TA loci as a sensitive target in A. baumannii. However, more studies are needed to test the effectiveness in vivo. In addition, the occurrence and potential for activation of the TA system, mazEF in other pathogenic bacteria should be further investigated
Comparing the Effectiveness of Curosurf and Beraksurf in the Treatment of Respiratory Distress in Premature Infants
No full textBackground: Research evidence has approved the effectiveness of surfactant prescription for respiratory distress syndrome (RDS). However, previous studies have not reported the priority of curosurf and Beraksurf. The present study aimed to compare the effectiveness of Iranian surfactant (beraksurf) and Italian surfactant (curosurf) in the treatment of pulmonary distress. Methods: This clinical trial was performed on 80 premature infants with respiratory distress in NICU of Taleghani Hospital in Ilam, all of whom were treated with surfactant. Results: There was no significant difference regarding the duration of needs for ventilation and/or oxygen, duration of hospitalization, pulmonary hemorrhage, bronchopulmonary dysplasia, intraventricular hemorrhage, patent ductus arteriosus (PDA) and pneumothorax between the groups (p>0.05). Conclusion: Beraksurf seems to be as effective as curosurf in premature neonates with RDS, but is less expensive than it
Simultaneous adsorption of heavy metals from aqueous matrices by nanocomposites: A first systematic review of the evidence
No full textBackground: Nanocomposites have received remarkable attention as effective adsorbents for removal of coexisting pollutants over the last decades. The presence of heavy metals (HMs) in wastewater has caused a global health concern. Therefore, the aim of this study was to review the most relevant publications reporting the use of nanostructures to simultaneous adsorption of HMs in mixed aqueous systems. Methods: In this systematic review, 9 studies were included through a systematic search in the three databases (ISI, Scopus, and PubMed) during 1990-2021. The optimal value of simultaneous adsorption parameters such as initial concentration, contact time, adsorbent dosage, and pH was discussed. Results: Findings indicate that the Langmuir and Freundlich models and the pseudo-second-order kinetic model have been widely used and the most popular models to describe the equilibrium of HMs by nanoadsorbents. This study confirmed that the simultaneous removal rate of HMs decreased with an increase in pH value. It was found that the major mechanisms of HMs adsorption onto nanostructures were electrostatic interactions and precipitation. Conclusion: Nanocomposites have remarkable adsorption performance for HMs with the highest adsorption capacity (qe(mg/g))