Attitude of Kerman medical sciences students on mental diseases

Introduction: Nowadays، in spite of the scientific advances in diagnosis and treatment of mental diseases، provision of psychological and psychiatric services to public often are encountering to some difficulties because negative and stereotypic approaches. Hence، determination of attitude on mental disorders is very important and modifying the attitudes is one of the main aims in this domain. Objective: This study was performed to determination of the attitude of Kerman medical sciences students about mental diseases in 2009. Method: In this cross–sectional descriptive study، 3400 students in Kerman university of medical sciences were participated through census route. For data collecting، questionnaire of evaluating the attitude toward mental diseases was used. This questionnaire consists of two parts: demographic variables and questions about attitude on mental diseases. For evaluating the reliability of questions، alpha -Chronbach was calculated and high coefficient was obtained (0/691). Data analysis was done by using the factor analysis method of questions in which all questions in one factor (by considering the indexes of kmo. bartlett) were added. The Data were analyzed by ANOVA and T-tests. Results: The results showed that most students had a positive and realistic attitude toward the mental patients. there was a significant difference between the attitude with the demographic variables such as age، sex، marital status and academic discipline. On the other hand، medicine and nursing groups had the more positive attitude other than majors (p<0/001). Also، there was negative relationship between age and attitude (p<0/29). Conclusion: Based on the findings of this study and by considering the attitude score of all medical sciences students، especially medicine and nursing groups who are often dealing with mental patients. Hence، medical students are playing an important role in mental health centers and their attitude toward these people will affect the attitude of people in the society، therefore learning the clinical courses in all majors relevant to the medical sciences not only plays an important role in the students but also in the society. Keywords: Attitude, Mental Diseases, Medical Sciences Student

Species delimitation and relationship in Crocus L. (Iridaceae)

The genus Crocus L. (Iridaceae) is monophyletic and contains about 100 species throughout the world. Crocus species have horticultural, medicinal and pharmacological importance. Saffron is the dried styles of C. sativus and is one of the world’s most expensive spices by weight. Controversy exits about the taxonomy of the genus and the species relationship. Exploring genetic diversity and inter-specific cross-ability are important tasks for conservation of wild taxa and for breeding of cultivated C. sativus. The present study was performed to study genetic variability and population structure in five Crocus L. species including Crocus almehensis Brickell & Mathew, C. caspius Fischer & Meyer, C. speciosus Marschall von Biberstein, C. haussknechtii Boissier, and C. sativus L. by inter simple sequence repeat (ISSR) molecular markers. We also used published internal transcribed spacer (ITS) sequences to study species relationship and compare the results with ISSR data. The results revealed a high degree of genetic variability both within and among the studied species. Neighbor joining (NJ) tree and network analysis revealed that ISSR markers are useful in Crocus species delimitation. Population fragmentation occurred in C. caspius and C. sativus. Both ISSR and sequenced based analyses separated C. sativus from the other studied species. Close genetic affinity of C. sativus and C. pallisii and inter-specific gene flow was supported by both data sets

Decision fusion in healthcare and medicine : a narrative review

Objective: To provide an overview of the decision fusion (DF) technique and describe the applications of the technique in healthcare and medicine at prevention, diagnosis, treatment and administrative levels. Background: The rapid development of technology over the past 20 years has led to an explosion in data growth in various industries, like healthcare. Big data analysis within the healthcare systems is essential for arriving to a value-based decision over a period of time. Diversity and uncertainty in big data analytics have made it impossible to analyze data by using conventional data mining techniques and thus alternative solutions are required. DF is a form of data fusion techniques that could increase the accuracy of diagnosis and facilitate interpretation, summarization and sharing of information. Methods: We conducted a review of articles published between January 1980 and December 2020 from various databases such as Google Scholar, IEEE, PubMed, Science Direct, Scopus and web of science using the keywords decision fusion (DF), information fusion, healthcare, medicine and big data. A total of 141 articles were included in this narrative review. Conclusions: Given the importance of big data analysis in reducing costs and improving the quality of healthcare; along with the potential role of DF in big data analysis, it is recommended to know the full potential of this technique including the advantages, challenges and applications of the technique before its use. Future studies should focus on describing the methodology and types of data used for its applications within the healthcare sector

Nanocarriers call the last shot in the treatment of brain cancers

Our brain is protected by physio-biological barriers. The blood–brain barrier (BBB) main mechanism of protection relates to the abundance of tight junctions (TJs) and efflux pumps. Although BBB is crucial for healthy brain protection against toxins, it also leads to failure in a devastating disease like brain cancer. Recently, nanocarriers have been shown to pass through the BBB and improve patients’ survival rates, thus becoming promising treatment strategies. Among nanocarriers, inorganic nanocarriers, solid lipid nanoparticles, liposomes, polymers, micelles, and dendrimers have reached clinical trials after delivering promising results in preclinical investigations. The size of these nanocarriers is between 10 and 1000 nm and is modified by surface attachment of proteins, peptides, antibodies, or surfactants. Multiple research groups have reported transcellular entrance as the main mechanism allowing for these nanocarriers to cross BBB. Transport proteins and transcellular lipophilic pathways exist in BBB for small and lipophilic molecules. Nanocarriers cannot enter via the paracellular route, which is limited to water-soluble agents due to the TJs and their small pore size. There are currently several nanocarriers in clinical trials for the treatment of brain cancer. This article reviews challenges as well as fitting attributes of nanocarriers for brain tumor treatment in preclinical and clinical studies

Preparation, characterization, and biodistribution of glutathione PEGylated nanoliposomal doxorubicin for brain drug delivery with a post-insertion approach

Objective(s): Brain cancer treatments have mainly failed due to their inability to cross the blood-brain barrier. Several studies have confirmed the presence of glutathione (GSH) receptors on BBB’s surface, as a result, products like 2B3-101, which contain over 5% pre-inserted GSH PEGylated liposomal Doxorubicin, are being tested in clinical trials. Here we conducted the PEGylated nanoliposomal Doxorubicin particles that are covalently attached to the glutathione using the post-insertion technique. Compared with the pre-insertion approach, the post-insertion method is notably simpler, faster, and more cost-effective, making it ideal for large-scale pharmaceutical manufacturing. Materials and Methods: The ligands of the DSPE PEG(2000) Maleimide-GSH were introduced in the amounts of 25, 50, 100, 200, and 400 on the available Caelyx. Following physicochemical evaluations, animal experiments such as biodistribution, fluorescence microscopy, and pharmacokinetics were done. Results: In comparison with Caelyx, the 200L and 400L treatment arms were the most promising formulations. We showed that nanocarriers containing 40 times fewer GSH micelles than 2B3-101 significantly increased blood-brain barrier penetrance. Due to the expressed GSH receptors on tissues as an endogenous antioxidant, Doxorubicin will likely concentrate in the liver, spleen, heart, and lung in comparison with Caelyx, according to other tissue analyses. Conclusion: The post-insertion technique was found a successful approach with more pharmaceutical aspects for large-scale production. Moreover, further investigations are highly recommended to determine the efficacy of 5% post-inserted GSH targeted nanoliposomes versus 2B3-101 as a similar formulation with a different preparation method

Burnout and its Influencing Factors among Primary Health Care Providers in the North East of Iran

<div><p>Introduction</p><p>Burnout is a popular research topics in service providing jobs, including the health care field. This study aimed at assessing the level of job burnout and to consider the important antecedents which might be related to job burnout among primary health care providers in Iran.</p><p>Methods</p><p>The participants in this applied cross-sectional study which was conducted in 2013 were 548 primary health care providers who were randomly selected from among those working in Shahroud, Sabzevar, Neishabour, Bojnord (provinces located in the north east of Iran). Maslach Burnout Inventory (MBI) was administered to the participants and the collected data were analyzed using SPSS through chi-square test and ordinal logistic regression model.</p><p>Results</p><p>The burnout mean score among the participants was 54.1 ± 27.2 and the mean scores of burnout components i.e., emotional exhaustion, depersonalization and personal accomplishment were 15.5 ± 13.6, 3.7 ± 5.4 and 35.5 ± 13.5 respectively. In terms of levels of burnout, 64.2% of the participants showed low levels (n = 352), 18.4% average levels (n = 101) and 17.3% high levels (n = 95). A significant relationship was observed between burnout, job resources and interest in job (p ≤ 0.05). However, no significant relationship was observed between burnout and the place (university) of working, age, satisfaction with income, experience, gender, level of education, marital status, housing status, having a second job and place of residence (p ≥0.05).</p><p>Conclusion</p><p>Lack of personal accomplishment was highly prevalent among the participating primary health care providers. Lack of career advancement and job transfer opportunities may play a role in the burnout of primary health care providers. Therefore, paying attention to this aspect may help to reduce burnout and even increase job engagement.</p></div

Breast cancer prediction using different machine learning methods applying multi factors

Objective: Breast cancer (BC) is a multifactorial disease and is one of the most common cancers globally. This study aimed to compare different machine learning (ML) techniques to develop a comprehensive breast cancer risk prediction model based on features of various factors. Methods: The population sample contained 810 records (115 cancer patients and 695 healthy individuals). 45 attributes out of 85 were selected based on the opinion of experts. These selected attributes are in genetic, biochemical, biomarker, gender, demographic and pathological factors. 13 Machine learning models were trained with proposed attributes and coefficient of attributes and internal relationships were calculated. Result: Compared to other methods random forest (RF) has higher performance (accuracy 99.26%, precision 99%, and area under the curve (AUC) 99%). The results of assessing the impact and correlation of variables using the RF method based on PCA indicated that pathology, biomarker, biochemistry, gene, and demographic factors with a coefficient of 0.35, 0.23, 0.15, 0.14, and 0.13 respectively, affected the risk of BC (r 2 = 0.54). Conclusion: Breast cancer has several risk factors. Medical experts use these risk factors for early diagnosis. Therefore, identifying related risk factors and their effect can increase the accuracy of diagnosis. Considering the broad features for predicting breast cancer leads to the development of a comprehensive prediction model. In this study, using RF technique a breast cancer prediction model with 99.3% accuracy was developed based on multifactorial features.</p

The relationship between burnout and physical facilities and interest in the job among primary health care providers (n = 548) studied in 2013 by multivariate analysis using ordinal logistic regression model.

<p>The relationship between burnout and physical facilities and interest in the job among primary health care providers (n = 548) studied in 2013 by multivariate analysis using ordinal logistic regression model.</p