- Journal Details
- First Published
- 30 Jan 2017
- Publication timeframe
- 4 times per year
- Open Access
Page range: 1 - 3
The pandemic COVID-19 is caused by a highly transmissible severe acute respiratory coronavirus 2 (SARS-CoV-2) which showed the highest morbidity and mortality rates among the other coronavirus infections such as SARS-CoV and MERS-CoV. However, the numbers of infected cases as well as mortality rates are varying from population to population. Therefore, scientist has urged the SARS-CoV-2 genome and host genetic factors investigations. Recently, new SARS-CoV-2 variants has been detected and though to affect the diseases transmission from human to human. In this mini-review, we aimed to explained detected SARS-CoV-2 variants that thought to influence the COVID-19 severity and transmission using the literature.
- Open Access
Page range: 4 - 7
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first reported in the city Wuhan, China in December 2019. The high rates of infection led to quick spread of the virus around the world and on March 11th, 2020, the World Health Organization (WHO) announced the pandemic of the Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2. The pharmaceutical companies and institutions have been working towards developing a safe and effective vaccine in order to control the pandemic. The biology of SARS-CoV-2 is briefly discussed describing the transcription of the virus and the receptor recognition. The spike protein of SARS-CoV-2 is important in the attachment of the host cell and RNA-dependent RNA polymerase (RdRp) is involved in the replication of the virus making them good candidates for drug and vaccine targets. To date many different strategies have been employed in the development of vaccines and a number of them are in the phase III of clinical trials with promising results. In this mini-review, we assessed the literature throughly and described the latest developments in SARS-CoV-2 vaccines for humans. The main benefits and drawbacks of each platform is evaluated and the possible changes in the vaccine effectivity due to naturally occuring SARS-CoV-2 mutations have been described.
- Open Access
Page range: 8 - 14
The aim of this study is to investigate the therapeutic effects of Chloroquine (CLQ) against Adriamycin (ADR) induced hepatotoxicity. ADR is a chemotherapeutic agent used in the treatment of many cancer types, but it causes hepatotoxicity. CLQ is used as an anti-inflammatory drug in the treatment of malaria, rheumatoid arthritis, and pneumonia caused by Covid-19. Rats were divided into four groups: Control group, ADR group (2 mg/kg Adriamycin, one in three days for 30 days, i.p.), CLQ group (50 mg/kg Chloroquine, per day for 30 days, i.p.), ADR+CLQ (2 mg/kg Adriamycin, one in three days for 30 days, i.p. and 50 mg/ kg Chloroquine, per day for 30 days, i.p.). Animals were sacrificed, and liver tissues were extracted for further examinations. Histopathological changes in liver tissues were scored and
- liver damage
- Open Access
Influence of scarification method on seed germination of the terrestrial orchid
Anacamptis laxiflora (Lam.)
Page range: 15 - 23
A critical step during
- Open Access
Page range: 24 - 33
Eating Disorders (EDs) refer to a group of psychiatric conditions in which disorderly food intake results in impaired psychological functioning or physical health. Nowadays, these disorders represent an increasing problem in modern society. There are no universally validated clinical parameters to confirm, disprove or simply help to identify EDs except for diagnostic criteria on psychiatric basis. The aim of this study was the assessment of Vitamin D3 level in patients with EDs to understand if it might be a valid clinical biochemistry parameter useful as prognostic marker.
The sample consists of 28 female patients, who suffer from EDs. Blood samples were examined in terms of blood count, glucose, cholesterol and Vitamin D3 levels. The other clinical biochemistry parameters were analysed to understand if the Vitamin D3 was the only altered parameter.
The parameters that appear altered are glycemia, cholesterol and, in particular, Vitamin D3. Significant results were obtained comparing controls with restrictive-type anorexia nervosa (p value= 0,003) and with purging-type anorexia nervosa (p value= 0,007).
There are currently no universally validated and diagnostic reliable clinical biochemistry parameters for EDs but, in the light of the findings, but our research indicates the potential use of Vitamin D3 as a biomarker for anorexia nervosa.
Level III: Evidence obtained from a single-center cohort study.
- Eating Disorders
- Anorexia Nervosa
- Bulimia Nervosa
- Other Specified Feeding or Eating Disorder
- Vitamin D3
- Open Access
Comparison of deep learning and conventional machine learning methods for classification of colon polyp types
Page range: 34 - 42
Determination of polyp types requires tissue biopsy during colonoscopy and then histopathological examination of the microscopic images which tremendously time-consuming and costly. The first aim of this study was to design a computer-aided diagnosis system to classify polyp types using colonoscopy images (optical biopsy) without the need for tissue biopsy. For this purpose, two different approaches were designed based on conventional machine learning (ML) and deep learning. Firstly, classification was performed using random forest approach by means of the features obtained from the histogram of gradients descriptor. Secondly, simple convolutional neural networks (CNN) based architecture was built to train with the colonoscopy images containing colon polyps. The performances of these approaches on two (adenoma & serrated vs. hyperplastic) or three (adenoma vs. hyperplastic vs. serrated) category classifications were investigated. Furthermore, the effect of imaging modality on the classification was also examined using white-light and narrow band imaging systems. The performance of these approaches was compared with the results obtained by 3 novice and 4 expert doctors. Two-category classification results showed that conventional ML approach achieved significantly better than the simple CNN based approach did in both narrow band and white-light imaging modalities. The accuracy reached almost 95% for white-light imaging. This performance surpassed the correct classification rate of all 7 doctors. Additionally, the second task (three-category) results indicated that the simple CNN architecture outperformed both conventional ML based approaches and the doctors. This study shows the feasibility of using conventional machine learning or deep learning based approaches in automatic classification of colon types on colonoscopy images.
- Open Access
Irrational use of antibiotics with representation of antimicrobial resistance patterns in Sudan: a narrative review
Page range: 43 - 47
Increasing bacterial resistance to antibiotics is a growing menace, mainly caused by the rapid genetic modification of bacterial strains and new alternations in behavior favoring their survival. There is no doubt that the irrational use of antibiotics is one of the factors contributing to the rise of this problem, whether that be in hospitals or at a community level. Although the extent of this influence is yet to be learned, it is definite that this is of great impact on the endemic disease patterns in developing areas specifically and on an expanding global issue generally.
This paper will provide a narrative review of relevant previous publications of antibiotic misuse to portray a clearer picture of its causes and consequences in Sudan.
The PICO method was used by which evidence-based research websites were scanned for key words. Results were assessed for relevance and then critically appraised. All papers included were summarized and presented in a narrative review format.
From a total of 9 research papers from Pub Med, Scopus, Cochrane and Google Scholar search engines, 7 were selected, presented, and discussed.
Given the facts of high bacterial resistance that has emerged worldwide catastrophically, the implementation of a meticulous surveillance system designed to restrict the irrational use of antibiotics by the public and health sectors alike with adjunct educational and training programs relevant to the regional epidemiology and economy will massively contribute to a lower resistance rate due to antibiotic misuse.
- Open Access
Page range: 48 - 55
In the 21st century, additive manufacturing technologies have gained in popularity mainly due to benefits such as rapid prototyping, faster small production runs, flexibility and space for innovations, non-complexity of the process and broad affordability. In order to meet diverse requirements that 3D models have to meet, it is necessary to develop new 3D printing technologies as well as processed materials. This review is focused on 3D printing technologies applicable for polyhydroxyalkanoates (PHAs). PHAs are thermoplastics regarded as a green alternative to petrochemical polymers. The 3D printing technologies presented as available for PHAs are selective laser sintering and fused deposition modeling. Stereolithography can also be applied provided that the molecular weight and functional end groups of the PHA are adjusted for photopolymerization. The chemical and physical properties primarily influence the processing of PHAs by 3D printing technologies. The intensive research for the fabrication of 3D objects based on PHA has been applied to fulfil criteria of rapid and customized prototyping mainly in the medical area.
- 3D printing
- fused deposition modeling
- selective laser sintering