An evaluation of fungal contamination and its relationship with PM levels in public transportation systems.

Transmission of fungi in the air and its impact on health are regarded as important public health issues. Bioaerosols play an important role in causing or exacerbating infectious diseases, acute toxic effects, allergies, and cardiopulmonary symptoms. As many people use the public transportation system daily, it is necessary to determine the type and manner of dispersal and abundance of airborne fungi in public transport places. Three public transportation systems including a bus station, a train station, and an airport in Ahvaz city (Iran) were examined. At each of these stations, the air samples were taken from inside and outside the hall stations, and in-vehicle. A bio-stage Anderson sampler was used by suctioning air and passing it over a Petri dish containing culture medium Sabouraud Dextrose Agar (SDA). Relative humidity (RH, %), temperature (T, ◦C), and mass concentration of particulate matter (PM1, PM2.5, and PM10, µg/m3) at the sampling points were measured. The highest concentration of airborne fungi was observed in the airport. The concentration of fungi in the ambient air was higher than that in the indoor air of halls and in-vehicle. In all sampling points, the ambient predominant airborne fungi were Cladosporium and Alternaria, while the indoor predominant airborne fungi were Cladosporium, Aspergillus, and Penicillium. The indoor to outdoor ratio showed that the fungi were of an external origin. Due to the influence of the ambient air on indoor air, it is recommended to use proper ventilation and enhance the hygiene level of vehicles in public transportation systems to reduce exposure to environmentally pathogenic bioaerosols.

Synthesis, in silico studies, and in vitro biological evaluation of newly-designed 5-amino-1H-tetrazole-linked 5-fluorouracil analog as a potential antigastric-cancer agent.

5-Fluorouracil (5FU) is a chemotherapy drug used to treat various cancers, such as colorectal, prostate, skin, pancreas, and stomach, as an ointment or solution. However, its consumption has several side effects. Therefore, a new derivative of fluorouracil containing 5-Amino-1H-tetrazole was designed and synthesized through multi-step synthesis to reduce urea excretion and toxicity. The effectiveness of the synthesized drug on the Adenocarcinoma gastric cell line (AGS) gastric cancer cell line was evaluated using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test, which showed that the new 5-fluorouracil (5FU) analog, with an IC50 of 15.67 µg/mL, is more effective in inhibiting the proliferation of AGS cells after 24 h compared to both synthesized and reported 5FU. In addition, In-silico studies showed that the new 5FU derivative based on amino tetrazole, with a binding energy of -7.2 kcal/mol, exhibits greater anti-cancer activity against the BCL2 enzyme than 5FU, with a binding energy of - 4.8 kcal/mol. It is predicted that the new 5FU derivative will be effective in treating gastric and colorectal cancers. The new derivative of the 5-fluorouracil drug was characterized and identified using FTIR and NMR spectroscopy.Communicated by Ramaswamy H. Sarma.

Anti-quorum sensing effects of SidA protein on Escherichia coli receptors: in silico analysis.

Quorum sensing enables cell-cell communication in bacteria and regulates biofilm formation. Biofilm production promotes pathogenicity of Escherichia coli and causes infections. However, antibiotic resistance limits conventional treatment efficacy against biofilm infections. Quorum quenching offers an alternative by disrupting quorum sensing signals. Allicin, extracted from garlic, possesses antimicrobial and anti-quorum sensing properties. This study employed molecular docking and dynamics simulations to investigate allicin's interaction with the E. coli quorum sensing system, specifically targeting the cytoplasmic SidA receptor protein. SidA binds to N-acyl-homoserine lactone ligands and regulates quorum sensing in E. coli. The crystal structure of SidA was obtained from the PDB. Molecular docking revealed that allicin competitively binds to the ligand-binding pocket of SidA. Simulations analyzed the effects of allicin binding on SidA stability and affinity for N-acyl-homoserine lactones over 200 ns. Parameters like RMSD, RMSF, and hydrogen bonding indicated SidA was more stable when bound to allicin compared to unbound. Binding free energies suggested allicin reduced SidA's affinity for native ligands. Therefore, allicin binding to SidA alters its conformation and inhibits interaction with N-acyl-homoserine lactones, disrupting quorum sensing signaling and biofilm production in E. coli.Communicated by Ramaswamy H. Sarma.

Detection and quantification of single chain rFVII impurity in final drug products by SE-UPLC and CE-SDS as an alternative to SDS-PAGE.

Recombinant factor VII, produced in recombinant BHK cell line, is secreted as a single chain zymogen form (rFVII, non-activated) in cell culture supernatant and subsequently converts to its active form during anion exchange chromatography step in the downstream purification process, with the aid of calcium ion. Single chain rFVII impurity (non-activated form) in final drug products should not exceed more than 3.0 % of total rFVIIa content. Therefore, one of the most essential quality control tests in pharmaceutical companies is to precisely quantify and report this impurity. SDS-PAGE, as a traditional method in quality control laboratories to quantify single chain rFVII, is a laborious, time-consuming, low output, and semi-quantitative method for quantification of non-activated form impurity which utilizes a densitometer to scan the gel and calculate the non-activated form band density. In this work, we developed two novel instrumental-based techniques (SE-UPLC and CE-SDS) with superior precision, accuracy, sensitivity, and efficiency that overcome SDS-PAGE shortcomings. The results of both methods were comparable to SDS-PAGE and showed an even higher correlation with expected values. Finally, we concluded that these two methods could be used as a high throughput routine method in quality control laboratories as an alternative choice to manual SDS-PAGE.

Structure-based virtual screening and molecular dynamics approaches to identify new inhibitors of Staphylococcus aureus sortase A.

Staphylococcus aureus is a prevalent Gram-positive bacteria leading cause of a wide range of human pathologies. Moreover, antibiotic résistance of pathogenesis bacteria is one of the worldwide health problems. In Gram-positive bacteria, the enzyme of SrtA, is responsible for the anchoring of surface-exposed proteins to the cell wall peptidoglycan. Because of its critical role in Gram-positive bacterial pathogenesis, SrtA is an attractive target for anti-virulence during drug development. To date, some SrtA inhibitors have been discovered most of them being derived from flavonoid compounds, like Myricetin. In order to provide potential hit molecules against SrtA for clinical use, we obtained a total of 293 compounds by performing in silico shape-based screening of compound libraries against Myristin as a reference structure. Employing molecular docking and scoring functions, the top 3 compounds Apigenin, Efloxate, and Compound 8261032 were screened by comparing their docking scores with Myricetin. Furthermore, MD simulations and MM-PBSA binding energy calculation studies revealed that only Compound 8261032 strongly binds to the catalytic core of the SrtA enzyme than Myricetin, and stable behavior was consistently observed in the docking complex. Compound 8261032 showed a good number of hydrogen bonds with SrtA and higher MM-PBSA binding energy when compared to all three molecules. Also, it makes strength interactions with Arg139 and His62, which are critical for SrtA biological activity. This study showed that the development of this inhibitor could be a fundamental strategy against resistant bacteria, but further studies in vitro are needed to confirm this claim.Communicated by Ramaswamy H. Sarma.

Association of the corona virus (Covid-19) epidemic with environmental risk factors.

The current outbreak of the novel coronavirus SARS-CoV-2 (coronavirus disease 2019; previously 2019-nCoV), epicenter in Hubei Province (Wuhan), People's Republic of China, has spread too many other countries. The transmission of the corona virus occurs when people are in the incubation stage and do not have any symptoms. Therefore, the role of environmental factors such as temperature and wind speed becomes very important. The study of Acute Respiratory Syndrome (SARS) indicates that there is a significant relationship between temperature and virus transmission and three important factors, namely temperature, humidity and wind speed, cause SARS transmission. Daily data on the incidence and mortality of Covid-19 disease were collected from World Health Organization (WHO) website and World Meter website (WMW) for several major cities in Iran and the world. Data were collected from February 2020 to September 2021. Meteorological data including temperature, air pressure, wind speed, dew point and air quality index (AQI) index are extracted from the website of the World Meteorological Organization (WMO), The National Aeronautics and Space Administration (NASA) and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Statistical analysis carried out for significance relationships. The correlation coefficient between the number of infected people in one day and the environmental variables in the countries was different from each other. The relationship between AQI and number of infected was significant in all cities. In Canberra, Madrid and Paris, a significant inverse relationship was observed between the number of infected people in one day and wind speed. There is a significant positive relationship between the number of infected people in a day and the dew point in the cities of Canberra, Wellington and Washington. The relationship between the number of infected people in one day and Pressure was significantly reversed in Madrid and Washington, but positive in Canberra, Brasilia, Paris and Wuhan. There was significant relationship between Dew point and prevalence. Wind speed showed a significant relationship in USA, Madrid and Paris. AQI was strongly associated with the prevalence of covid19. The purpose of this study is to investigate some environmental factors in the transmission of the corona virus.

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies.

The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored. Therefore, the aim of this study is to present a computational screening method to identify potential inhibitor candidates with a high probability of blocking the binding of RBD to the ACE2 receptor. Pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations, and binding free-energy analyses were performed to identify potential inhibitor candidates against ACE2/SARS-CoV-2. In conclusion, we propose the compound PubChem-84280085 as a potential inhibitor of protein-protein interactions to disrupt the binding of the SARS-CoV-2-RBD to the ACE2 receptor.

Unveiling diagnostic and therapeutic strategies for cervical cancer: biomarker discovery through proteomics approaches and exploring the role of cervical cancer stem cells.

Cervical cancer (CC) is a major global health problem and leading cause of cancer deaths among women worldwide. Early detection through screening programs has reduced mortality; however, screening compliance remains low. Identifying non-invasive biomarkers through proteomics for diagnosis and monitoring response to treatment could improve patient outcomes. Here we review recent proteomics studies which have uncovered biomarkers and potential drug targets for CC. Additionally, we explore into the role of cervical cancer stem cells and their potential implications in driving CC progression and therapy resistance. Although challenges remain, proteomics has the potential to revolutionize the field of cervical cancer research and improve patient outcomes.

Inhibitory Effects of Dutasteride on TLR4: An In vitro Pain Study.

Dutasteride was potentially proposed to control chronic pain by Toll-Like Receptor 4 (TLR4) inhibition through its effect on TLR4 expression, Myeloid differentiation primary response 88 (MyD88), Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), secretory Interleukin-1ß (IL-1ß), and nitric oxide (NO) in the Lipopolysaccharides (LPS)-stimulated U-87 MG cell line. Human astrocytoma U-87 MG cell line was cultured and incubated with 10 µg/mL of LPS for 24 hours to create a neuro-inflammation model, using two different treatment approaches. The first approach included LPS treatment for 24 hours, followed by dutasteride (20 µg/mL) incubation for the next 72 hours. In the second treatment approach, the cells were co-incubated with LPS and dutasteride for 72 hours. Expression of TLR4, MyD88, NF-κBp65, and secretory IL-1 was evaluated by Western blotting while expression of NO was assessed by NO assay. TLR4, MyD88, NF-κBp65, and secretory IL-1ß levels increased in LPS-treated cells after 24 hours. Dutasteride significantly decreased the secretion of NO and also, the levels of TLR4, MyD88, and NF-κBp65 in both treatment approaches. No difference in IL-1ß level was seen with the second treatment approach. Dutasteride has anti-inflammatory properties and probably analgesic effects, by mechanisms different from conventional analgesics.

Prediction of airborne pollen concentrations by artificial neural network and their relationship with meteorological parameters and air pollutants.

After the early rainfall in the autumn of 2013, respiratory syndromes spread in the Khuzestan province of Iran with the most severity in Ahvaz. There have been recurring outbreaks in recent years. Considering that pollen-derived airborne allergens are regarded as key aeroallergens and the main cause of allergic rhinitis and asthma, this work aimed to forecast total pollen concentration in Ahvaz through an artificial neural network (ANN), followed by evaluating the pollen spatial distribution across the city and the association between pollen concentrations and environmental parameters. The utilized ANN in this work included an input layer with 13 parameters, a hidden layer of five neurons, and an output layer. Data were classified into training, validation, and testing sets. The ANN was implemented with 70% and 80% of data for training. The value of the correlation coefficient for the data validation of these two networks was 0.89 and 0.92, respectively. The results also indicated that despite the difference in the mean concentration of the pollens in various areas of Ahvaz, this difference was not statistically significant (P > 0.05). Furthermore, there was a negative correlation between the concentration of total pollen and relative humidity, precipitation, and air pressure. However, it had a positive correlation with temperature. Consequently, considering the logistical challenges of monitoring bioaerosols in the air, the ANN approach could predict total pollen concentrations. Therefore, in addition to measurements, the ANN technique can be a good tool to enable authorities to mitigate the impact of airborne pollen on people.

Temporal profiles of ambient air pollutants and associated health outcomes in two polluted cities of the Middle East.

Dust storms and particulate matters had been increased due to climate change in the Middle East. On the other hand, urbanization and industrialization raised levels of gaseous air pollutants in all big cities. In the current study, air pollution information collected from Environmental Protection Agency of Khuzestan and Tehran containing hourly O3, NO2, CO, SO2, PM10 and PM2.5 concentrations between 2014 and 2015. This study evaluated the air quality of these two cities by Air Quality Index (AQI). As a result, mean concentrations of O3, NO2, PM10 and PM2.5 were higher in Ahvaz than Tehran while Tehran was more pollutant in terms of CO and SO2. Diurnal variations of O3 in weekend were the only trend located above weekday variations along the daytimes. Hourly variations of all pollutants changed with a wider range of concentrations in Ahvaz. Diurnal peaks of all pollutants showed their highest level on Monday as the busiest day in mega city, Tehran with the exception of SO2. PM2.5 was the worst and limiting pollutant for both cities. Accordingly, winter was the most polluted season by 77 and 33 µg m-3 in Ahvaz and Tehran, respectively. Number of clean days was significantly lower in Ahvaz (no-day) than mega city, Tehran (<17 days). The number of unhealthy days was also presented significantly higher in Ahvaz (>186 days). Although, annual PM2.5 concentrations were more in Ahvaz, the higher at-risk population in Tehran caused more health endpoints in the capital of Iran. Consequently, both cities should have their own especial pattern to control air pollution and attributed health damages.

Mesenchymal Stem Cells in the Treatment of New Coronavirus Pandemic: A Novel Promising Therapeutic Approach.

After severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, coronavirus disease 2019 (COVID-19) is the third coronavirus epidemic that soon turned into a pandemic. This virus causes acute respiratory syndrome in infected people. The mortality rate of SARS-CoV-2 infection will probably rise unless efficient treatments or vaccines are developed. The global funding and medical communities have started performing more than five hundred clinical examinations on a broad spectrum of repurposed drugs to acquire effective treatments. Besides, other novel treatment approaches have also recently emerged, including cellular host-directed therapies. They counteract the unwanted responses of the host immune system that led to the severe pathogenesis of SARS-CoV-2. This brief review focuses on mesenchymal stem cell (MSC) principles in treating the COVID-19. The US clinical trials database and the world health organization database for clinical trials have reported 82 clinical trials (altogether) exploring the effects of MSCs in COVID-19 treatment. MSCs also had better be tried for treating other pathogens worldwide. MSC treatment may have the potential to end the high mortality rate of COVID-19. Besides, it also limits the long-term inability of survivors.

Clinical Applications and Anticancer Effects of Antimicrobial Peptides: From Bench to Bedside.

Cancer is a multifaceted global health issue and one of the leading causes of death worldwide. In recent years, medical science has achieved great advances in the diagnosis and treatment of cancer. Despite the numerous advantages of conventional cancer therapies, there are major drawbacks including severe side effects, toxicities, and drug resistance. Therefore, the urgency of developing new drugs with low cytotoxicity and treatment resistance is increasing. Antimicrobial peptides (AMPs) have attracted attention as a novel therapeutic strategy for the treatment of various cancers, targeting tumor cells with less toxicity to normal tissues. In this review, we present the structure, biological function, and underlying mechanisms of AMPs. The recent experimental studies and clinical trials on anticancer peptides in different cancer types as well as the challenges of their clinical application have also been discussed.

Contrasting Iran's air quality improvement during COVID-19 with other global cities.

BACKGROUND AND PURPOSE: In late 2019, a novel infectious disease (COVID-19) was identified in Wuhan China, which turned into a global pandemic. Countries all over the world have implemented some sort of lockdown to slow down its infection and mitigate it. This study investigated the impact of the COVID-19 pandemic on air quality during 1st January to 30th April 2020 compared to the same period in 2016-2019 in ten Iranian cities and four major cities in the world. METHODS: In this study, the required data were collected from reliable sites. Then, using SPSS and Excel software, the data were analyzed in two intervals before and after the corona pandemic outbreak. The results are provided within tables and charts. RESULTS: The current study showed the COVID-19 lockdown positively affected Iran's air quality. During the COVID-19 pandemic, the four-month mean air quality index (AQI) values in Tehran, Wuhan, Paris, and Rome were 76, 125, 55, and 60, respectively, which are 8 %, 22 %, 21 %, and 2 % lower than those during the corresponding period (83, 160, 70, and 61) from 2016 to 2019. CONCLUSIONS: Although the outbreak of coronavirus has imposed devastating impacts on economy and health, it can have positive effects on air quality, according to the results.

Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach.

The RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) from SARS-CoV-2 play crucial roles in the viral life cycle and are considered the most promising targets for drug discovery against SARS-CoV-2. In this study, FDA-approved drugs were screened to identify the probable anti-RdRp and 3CLpro inhibitors by molecular docking approach. The number of ligands selected from the PubChem database of NCBI for screening was 1760. Ligands were energy minimized using Open Babel. The RdRp and 3CLpro protein sequences were retrieved from the NCBI database. For Homology Modeling predictions, we used the Swiss model server. Their structure was then energetically minimized using SPDB viewer software and visualized in the CHIMERA UCSF software. Molecular dockings were performed using AutoDock Vina, and candidate drugs were selected based on binding affinity (∆G). Hydrogen bonding and hydrophobic interactions between ligands and proteins were visualized using Ligplot and the Discovery Studio Visualizer v3.0 software. Our results showed 58 drugs against RdRp, which had binding energy of - 8.5 or less, and 69 drugs to inhibit the 3CLpro enzyme with a binding energy of - 8.1 or less. Six drugs based on binding energy and number of hydrogen bonds were chosen for the next step of molecular dynamics (MD) simulations to investigate drug-protein interactions (including Nilotinib, Imatinib and dihydroergotamine for 3clpro and Lapatinib, Dexasone and Relategravir for RdRp). Except for Lapatinib, other drugs-complexes were stable during MD simulation. Raltegravir, an anti-HIV drug, was observed to be the best compound against RdRp based on docking binding energy (-9.5 kcal/mole) and MD results. According to the MD results and binding energy, dihydroergotamine is a suitable candidate for 3clpro inhibition (-9.6 kcal/mol). These drugs were classified into several categories, including antiviral, antibacterial, anti-inflammatory, anti-allergic, cardiovascular, anticoagulant, BPH and impotence, antipsychotic, antimigraine, anticancer, and so on. The common prescription-indications for some of these medication categories appeared somewhat in line with manifestations of COVID-19. We hope that they can be beneficial for patients with certain specific symptoms of SARS-CoV-2 infection, but they can also probably inhibit viral enzymes. We recommend further experimental evaluations in vitro and in vivo on these FDA-approved drugs to assess their potential antiviral effect on SARS-CoV-2.

Forecasting PM2.5 concentration using artificial neural network and its health effects in Ahvaz, Iran.

The main objective of the present study was to predict the associated health endpoint of PM2.5 using an artificial neural network (ANN). The neural network used in this work contains a hidden layer with 27 neurons, an input layer with 8 parameters, and an output layer. First, the artificial neural network was implemented with 80% of data for training then with 90% of data for training. The value of R for the data validation of these two networks was 0.80 and 0.83 respectively. The World Health Organization AirQ + software was utilized for assessing Health effects of PM2.5 levels. The mean PM2.5 over the 9-year study period was 63.27(µg/m3), about six times higher than the WHO guideline. However, the PM2.5 concentration in the last year decreased by about 25% compared to the first year, which is statistically significant (P-value = 0.0048). This reduced pollutant concentration led to a decrease in the number of deaths from 1785 in 2008 to 1059 in 2016. Moreover, a positive correlation was found between PM2.5 concentration and temperature and wind speed. Considering the importance of predicting PM2.5 concentration for accurate and timely decisions as well as the accuracy of the artificial neural network used in this study, the artificial neural network can be utilized as an effective instrument to reduce health and economic effects.

Spatial modeling of environmental vulnerability in the biggest river in Iran using geographical information systems.

BACKGROUND AND PURPOSE: The Karoon River, located in southwest Iran, has always been considered as an important water source for people in the southward areas. Khuzestan Province is one of the strategic provinces of Iran thus the development of this province is significantly affected by the water pollution of the Karoon River system. Therefore, the current study aims to assess the environmental vulnerability of the Karoon River as well as preparing a classified map of its vulnerabilities using the fuzzy logic method via the geographical information systems (GIS). METHODS: In this study, the required data were gathered from the Water and Electricity Organization of Khuzestan Province. Afterward, the primary maps were created by converting the map of the study origin into a raster format. Then, fuzzy membership was performed by placing the digits in the range of zero and one using the fuzzy membership function. The primary maps were mixed, and finally, the risk map was prepared by applying the fuzzy overly function. RESULTS: According to the results, a clear trend of water quality deterioration exists since water moves from upstream to downstream areas. The ecological vulnerability of the Karoon basin is mostly located at a low-level (78.05 %) rank. The vulnerable areas were ranked extremely high, high, medium, and low as 2.09, 8.09, 12.08, and 78.05, respectively. CONCLUSIONS: Considering that 22 % of the Karoon River drainage basin in Khuzestan province is considered to have a medium to extremely high risk range, it is mandatory for the authorities to take precautions to prevent the entry of polluting sources into this precious river.

Effect of long-term exposure to PM2.5 on years of life lost in a populated Middle Eastern city.

From a public health point of view, years of life lost (YLL) is a more important index than the number of deaths to evaluate the effect of risk factors. The objective of the present study was to estimate the burden of disease including years of life lost (YLL) and expected life remaining (ELR) attributed to long-term exposure to PM2.5 in Ahvaz, one of the most polluted cities of the world, during March 2014 through March 2017. AirQ + software was used for the estimation of YLL and ELR due to all natural causes of death. Hourly concentrations of PM2.5 were acquired from the Department of Environment (DoE) of Ahvaz. Several steps were performed to validate the raw air quality data. Only the monitors were included that had minimum data completeness of 75%. Two age groups were selected for this study, including 0-64 and 65 < years. The life table approach was used to estimate YLL and ELR. Annual averages of PM2.5 were 5.2-8 times higher than the air quality guideline (10 µg/m3) set by WHO for long-term exposure to PM2.5. In total, PM2.5 has caused 234,041 years of life lost due to mortality. About 84% of YLLs were attributed to people older than 65 years old. The YLLs of men were higher than those for women. The YLLs in the third year were greater than the first two years. PM2.5 has caused the average age of total population, people aged 0-64 years old, and people > 65 years old decreased by 2.5, 3, and 1.6 years, respectively. These studies indicated that people in a city that the air quality is highly affected by dust storms, industrial emissions, and urban air pollution are significantly at risk. Air pollution control strategies and actions should be designed and executed to improve the quality of ambient air.

Improving SDS-PAGE method for monoclonal antibodies: The advantages of Tris-Acetate over Tris-Glycine SDS-PAGE system and comparison with CE-SDS method.

Present study compares two different buffer systems for the electrophoretic separation of the IgG1 and IgG2 Monoclonal Antibodies using SDS-PAGE method. A modified Tris-acetate system was shown to be superior for separation of these proteins in a 6-20% gradient gel as compared with the traditionally used Tris-glycine method. This modified Tris-acetate buffer system showed sharper bands, more accurate determination of molecular weight, higher resolution, and better estimation of sub-fragments with closer results to those obtained by Capillary Gel Electrophoresis. Also in a parallel experiment, effect of IgG deglycosylation by PNGase-F enzyme was investigated and revealed no significant improvement on the SDS-PAGE results.

Cancer Care Management During the COVID-19 Pandemic.

New cases of the novel coronavirus, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are increasing around the world. Currently, health care services are mainly focused on responding to and controlling the unique challenges of the coronavirus disease 2019 (COVID-19) pandemic. These changes, along with the higher susceptibility of patients with cancer to infections, have profound effects on other critical aspects of care and pose a serious challenge for the treatment of such patients. During the COVID-19 pandemic, it is important to provide strategies for managing the treatment of patients with cancer to limit COVID-19-associated risks at this difficult time. The present study set out to summarize the latest research on epidemiology, pathogenesis, and clinical features of COVID-19. We also address some of the current challenges associated with the management of patients with cancer during the COVID-19 pandemic and provide practical guidance to clinically deal with these challenges.