Volume 5 (2021): Issue 1 (January 2021)

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.

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 11^th, 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.

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 IL-17 immunostaining was performed to determine the expression levels among experimental groups. Bodyweights in the ADR group decreased significantly compared to the Control group and CLQ group. Furthermore, bodyweight in ADR+CLQ group was significantly higher compared to ADR group. The histopathological score was significantly higher in ADR group when compared to Control and CLQ group while CLQ administrations reduced the damage induced by ADR in the ADR+CLQ group. IL-17 immunoreactivity was considerably increased in the ADR group. On the other hand, IL-17 expressions of ADR+CLQ were substantially less compared to ADR group. We suggest that CLQ can be used as a therapeutic agent to reduce the detrimental effects of ADR, thanks to its anti-inflammatory properties.

A critical step during in vitro sexual propagation of terrestrial orchids is the treatment of the microscopic seeds with a disinfecting solution that kills bacteria and fungi attached to the seeds. This treatment is necessary to prevent infection of the culture vessels. At the same time, the treatment serves to scarify the seeds, a process that disrupts seed dormancy and initiates germination. The literature is inconclusive with respect to the proper combination of disinfecting solution strength and treatment duration. Both factors should be adapted to each species to guarantee minimal infection rate without damaging the embryo. This research aims to compare three disinfection/scarification methods for seeds of Anacamptis laxiflora (Lam.): (i) soaking in 0.5% NaClO, (ii) soaking in 0.5% NaClO, then centrifugation, and (iii) presoaking the seeds in sucrose solution, then soaking in 0.5% NaClO. The seeds were soaked in the disinfecting solution for 5 to 85 min. Following scarification, the seeds were sown in modified Malmgren nutrient medium. Infected and germinated vessels were counted at 41 and 189 d after sowing. We found that the longer the chemical treatment, the lower the infection rate, and the higher the germination rate. There was no significant difference in germination rate between the NaClO and the NaClO-plus-centrifugation method; in fact, the slight savings in disinfection time effected by centrifugation were more than offset by the added complexity of the method. Moreover, we found that centrifugation significantly delays germination. The sucrose presoak-plus-NaClO method was superior to plain NaClO, as the sucrose stimulates the germination of microbial spores on the surface of the seeds, making them easier to kill. Perhaps seeds with thicker testa as well as whole immature capsules could benefit even more from the pretreatment in sucrose solution.

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.

In the 21^st 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.