Activation of Persulfate for Improved Naproxen Degradation Using FeCo2O4@g-C3N4 Heterojunction Photocatalysts

An effective heterojunction with robust charge separation and enormous degradation efficiency is the major task for photocatalyst preparation. In this study, we have prepared the FeCo2O4-loaded g-C3N4 nanosheet by the sol-gel-assisted calcination method for photo-Fenton-like degradation under visible-light irradiation by activating persulfate. The nanocomposite exhibits a higher charge separation efficiency than pure g-C3N4 and FeCo2O4 for the degradation reaction against naproxen drugs. An effective interaction between the nanoparticles increases the degradation efficiency up to 91% with a synergistic index of 73.62%. Moreover, the nanocomposite exhibits a 78% mineralization efficiency against the naproxen pollutant under visible-light irradiation. For practical implementation, the degradation reaction was tested with various pH values, different water sources (DI, lake, and tap water), and light sources (LED (visible)/direct sunlight (UV-visible)). Moreover, the possible degradation mechanism predicted by the elemental trapping experiment and the recycling experiment clearly revealed that the heterojunction composite has a high enough degradation stability.

Genome-wide identification and prediction of SARS-CoV-2 mutations show an abundance of variants: Integrated study of bioinformatics and deep neural learning

Genomic data analysis is a fundamental system for monitoring pathogen evolution and the outbreak of infectious diseases. Based on bioinformatics and deep learning, this study was designed to identify the genomic variability of SARS-CoV-2 worldwide and predict the impending mutation rate. Analysis of 259044 SARS-CoV-2 isolates identified 3334545 mutations with an average of 14.01 mutations per isolate. Globally, single nucleotide polymorphism (SNP) is the most prevalent mutational event. The prevalence of C > T (52.67%) was noticed as a major alteration across the world followed by the G > T (14.59%) and A > G (11.13%). Strains from India showed the highest number of mutations (48) followed by Scotland, USA, Netherlands, Norway, and France having up to 36 mutations. D416G, F106F, P314L, UTR:C241T, L93L, A222V, A199A, V30L, and A220V mutations were found as the most frequent mutations. D1118H, S194L, R262H, M809L, P314L, A8D, S220G, A890D, G1433C, T1456I, R233C, F263S, L111K, A54T, A74V, L183A, A316T, V212F, L46C, V48G, Q57H, W131R, G172V, Q185H, and Y206S missense mutations were found to largely decrease the structural stability of the corresponding proteins. Conversely, D3L, L5F, and S97I were found to largely increase the structural stability of the corresponding proteins. Multi-nucleotide mutations GGG > AAC, CC > TT, TG > CA, and AT > TA have come up in our analysis which are in the top 20 mutational cohort. Future mutation rate analysis predicts a 17%, 7%, and 3% increment of C > T, A > G, and A > T, respectively in the future. Conversely, 7%, 7%, and 6% decrement is estimated for T > C, G > A, and G > T mutations, respectively. T > G\A, C > G\A, and A > T\C are not anticipated in the future. Since SARS-CoV-2 is mutating continuously, our findings will facilitate the tracking of mutations and help to map the progression of the COVID-19 intensity worldwide.

Prediction of the Effects of Variants and Differential Expression of Key Host Genes ACE2, TMPRSS2, and FURIN in SARS-CoV-2 Pathogenesis: An In Silico Approach

A new strain of the beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is solely responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Although several studies suggest that the spike protein of this virus interacts with the cell surface receptor, angiotensin-converting enzyme 2 (ACE2), and is subsequently cleaved by TMPRSS2 and FURIN to enter into the host cell, conclusive insight about the interaction pattern of the variants of these proteins is still lacking. Thus, in this study, we analyzed the functional conjugation among the spike protein, ACE2, TMPRSS2, and FURIN in viral pathogenesis as well as the effects of the mutations of the proteins through the implementation of several bioinformatics approaches. Analysis of the intermolecular interactions revealed that T27A (ACE2), G476S (receptor-binding domain [RBD] of the spike protein), C297T (TMPRSS2), and P812S (cleavage site for TMPRSS2) coding variants may render resistance in viral infection, whereas Q493L (RBD), S477I (RBD), P681R (cleavage site for FURIN), and P683W (cleavage site for FURIN) may lead to increase viral infection. Genotype-specific expression analysis predicted several genetic variants of ACE2 (rs2158082, rs2106806, rs4830971, and rs4830972), TMPRSS2 (rs458213, rs468444, rs4290734, and rs6517666), and FURIN (rs78164913 and rs79742014) that significantly alter their normal expression which might affect the viral spread. Furthermore, we also found that ACE2, TMPRSS2, and FURIN proteins are functionally co-related with each other, and several genes are highly co-expressed with them, which might be involved in viral pathogenesis. This study will thus help in future genomics and proteomics studies of SARS-CoV-2 and will provide an opportunity to understand the underlying molecular mechanism during SARS-CoV-2 pathogenesis.

Increased lipid peroxidation, depleted non-enzymatic antioxidant, and variability in trace elements concentration in serum are correlated with Bangladeshi end-stage renal disease population

INTRODUCTION

End-stage renal disease (ESRD) is an abnormality where the kidneys are not usually working. This case-control study was planned to determine the extent of serum lipid peroxidation, non-enzymatic antioxidant (vitamin c), and trace elements in 50 patients with ESRD as cases and 50 normal healthy individuals as controls.

METHODS

Determination of lipid peroxidation was carried out by ascertaining concentration of malondialdehyde (MDA) and vitamin C in serum using UV spectrophotometry whereas atomic absorption spectroscopy was used for trace elements estimation. The statistical analysis was conducted via the independent t-test samples and Pearson correlation test.

RESULTS

The blood serum study has shown substantially higher MDA values than the control level and lowers vitamin C levels in the patient population (P < .001). A negative correlation was found between the vitamin C in serum with BMI and MDA for both patients (r = -0.017 and r = -0.132, respectively) and the control group (r = -0.014 and r = -0.229, respectively) after Pearson's correlation analysis. Regarding trace elements, significantly (P < .001) lower concentrations of zinc, copper, and manganese were found in the patient group than control subjects. Inter-element-relationship established a strong positive harmonization between these studied elements in both the cases of patients and control subjects.

CONCLUSION

Our results indicate strong associations of the pathogenesis of ESRD with depleted non-enzymatic antioxidant, increased lipid peroxidation, and inconsistency in trace elements concentration in serum, which may provide a prognostic tool for the treatment of this concerning the disease.

Stomatal development and genetic expression in Arabidopsis thaliana L

Stomata are turgor-driven microscopic epidermal valves of land plants. The controlled opening and closing of the valves are essential for regulating the gas exchange and minimizing the water loss and eventually regulating the internal temperatures. Stomata are also a major site of pathogen/microbe entry and plant defense system. Maintaining proper stomatal density, distribution, and development are pivotal for plant survival. Arabidopsis is a model plant to study molecular basis including signaling pathways, transcription factors, and key components for the growth and development of specific organs as well as the whole plant. It has intensively been studied and found out the driver for the development and patterning of stomata. In this review, we have explained how the MAPK signaling cascade is controlled by TOO MANY MOUTHS (TMM) receptor-like protein and the Erecta (ER) receptor-like kinase family. We have also summarized how this MAPK cascade affects primary transcriptional regulators to finally activate the main three basic Helix-Loop-Helix (bHLH) principal transcription factors, which are required for the development and patterning of stomata. Moreover, regulatory activity and cellular connections of polar proteins and environmentally mediated ligand-receptor interactions in the stomatal developmental pathways have extensively been discussed in this review.

Temporal landscape of mutational frequencies in SARS-CoV-2 genomes of Bangladesh: possible implications from the ongoing outbreak in Bangladesh

Along with intrinsic evolution, adaptation to selective pressure in new environments might have resulted in the circulatory SARS-CoV-2 strains in response to the geoenvironmental conditions of a country and the demographic profile of its population. With this target, the current study traced the evolutionary route and mutational frequency of 198 Bangladesh-originated SARS-CoV-2 genomic sequences available in the GISAID platform over a period of 13 weeks as of 14 July 2020. The analyses were performed using MEGA X, Swiss Model Repository, Virus Pathogen Resource and Jalview visualization. Our analysis identified that majority of the circulating strains strikingly differ from both the reference genome and the first sequenced genome from Bangladesh. Mutations in nonspecific proteins (NSP2-3, NSP-12(RdRp), NSP-13(Helicase)), S-Spike, ORF3a, and N-Nucleocapsid protein were common in the circulating strains with varying degrees and the most unique mutations (UM) were found in NSP3 (UM-18). But no or limited changes were observed in NSP9, NSP11, Envelope protein (E) and accessory factors (NSP7a, ORF 6, ORF7b) suggesting the possible conserved functions of those proteins in SARS-CoV-2 propagation. However, along with D614G mutation, more than 20 different mutations in the Spike protein were detected basically in the S2 domain. Besides, mutations in SR-rich region of N protein and P323L in RDRP were also present. However, the mutation accumulation showed a significant association (p = 0.003) with sex and age of the COVID-19-positive cases. So, identification of these mutational accumulation patterns may greatly facilitate vaccine development deciphering the age and the sex-dependent differential susceptibility to COVID-19.

First detection of SARS-CoV-2 genetic material in the vicinity of COVID-19 isolation Centre in Bangladesh: Variation along the sewer network

We made the first and successful attempt to detect SARS-CoV-2 genetic material in the vicinity wastewaters of an isolation centre i.e. Shaheed Bhulu Stadium, situated at Noakhali, Southeastern Bangladesh. Owing to the fact that isolation centre, in general, always contained a constant number of 200 COVID-19 patients, the prime objective of the study was to check if several drains carrying RNA of coronavirus are actually getting diluted or accumulated along with the sewage network. Our finding suggested that while the temporal variation of the genetic load decreased in small drains over the span of 50 days, the main sewer exhibited accumulation of SARS-CoV-2 RNA. Other interesting finding displays that probably distance of sampling location in meters is not likely to have a significant impact on the detected gene concentration, although the quantity of the RNA extracted in the downstream of the drain was higher. These findings are of immense value from the perspective of wastewater surveillance of COVID-19, as they largely imply that we do not need to monitor every wastewater system, and probably major drains monitoring may illustrate the city health. Perhaps, we are reporting the accumulation of SARS-CoV-2 genetic material along with the sewer network i.e. from primary to tertiary drains. The study sought further data collection in this line to simulate conditions prevailed in most of the developing countries and to shed further light on decay/accumulation processes of the genetic load of the SARS-COV-2.

First detection of SARS-CoV-2 genetic material in the vicinity of COVID-19 isolation Centre in Bangladesh: Variation along the sewer network

We made the first and successful attempt to detect SARS-CoV-2 genetic material in the vicinity wastewaters of an isolation centre i.e. Shaheed Bhulu Stadium, situated at Noakhali, Southeastern Bangladesh. Owing to the fact that isolation centre, in general, always contained a constant number of 200 COVID-19 patients, the prime objective of the study was to check if several drains carrying RNA of coronavirus are actually getting diluted or accumulated along with the sewage network. Our finding suggested that while the temporal variation of the genetic load decreased in small drains over the span of 50 days, the main sewer exhibited accumulation of SARS-CoV-2 RNA. Other interesting finding displays that probably distance of sampling location in meters is not likely to have a significant impact on the detected gene concentration, although the quantity of the RNA extracted in the downstream of the drain was higher. These findings are of immense value from the perspective of wastewater surveillance of COVID-19, as they largely imply that we do not need to monitor every wastewater system, and probably major drains monitoring may illustrate the city health. Perhaps, we are reporting the accumulation of SARS-CoV-2 genetic material along with the sewer network i.e. from primary to tertiary drains. The study sought further data collection in this line to simulate conditions prevailed in most of the developing countries and to shed further light on decay/accumulation processes of the genetic load of the SARS-COV-2.

Biogas production from anaerobic co-digestion using kitchen waste and poultry manure as substrate-part 1: substrate ratio and effect of temperature

The rapidly declining fossil fuels are no longer able to meet the ever-increasing energy demand. Moreover, they are considered responsible for greenhouse gas (GHG) emission, contributing to the global warming. On the other hand, organic wastes, such as kitchen waste (KW) and poultry manure (PM), represent considerable pollution threat to the environment, if not properly managed. Therefore, anaerobic co-digestion of KW and PM could be a sustainable way of producing clean and renewable energy in the form of biogas while minimizing environmental impact. In this study, the anaerobic co-digestion of KW with PM was studied to assess the rate of cumulative biogas (CBG) production and methane percentage in four digester setups (D1, D2, D3, and D4) operated in batch mode. Each digester setup consisted of five parallelly connected laboratory-scale digesters having a capacity of 1 L each. The digester setups were fed with KW and PM at ratios of 1:0 (D1), 1:1 (D2), 2:1 (D3), and 3:1 (D4) at a constant loading rate of 300 mg/L with 50 gm cow manure (CM) as inoculum and were studied at both room temperature (28 °C) and mesophilic temperature (37 °C) over 24 days. The co-digestion of KW with PM demonstrated a synergistic effect which was evidenced by a 16% and 74% increase in CBG production and methane content, respectively, in D2 over D1. The D3 with 66.7% KW and 33.3% PM produced the highest CBG and methane percentage (396 ± 8 mL and 36%) at room temperature. At mesophilic condition, all the digesters showed better performance, and the highest CBG (920 ± 11 mL) and methane content (48%) were observed in D3. The study suggests that co-digestion of KW and PM at mesophilic condition might be a promising way to increase the production of biogas with better methane composition by ensuring nutrient balance, buffering capacity, and stability of the digester.

MicroRNAs expression analysis shows key affirmation of Synaptopodin-2 as a novel prognostic and therapeutic biomarker for colorectal and cervical cancers

MicroRNAs play a crucial role in tumorigenesis, tumor progression, and metastasis, and thus they contribute in development of different malignancies including cervical cancer (CC) and colorectal cancer (CRC). Through integrated strategies of computational biology, this study aims to identify prognostic biomarkers responsible for CRC and CC prognosis, and potential therapeutic agents to halt the progression of these cancers. Expression analysis of miRNA datasets of CRC and CC identified 17 differentially expressed miRNAs (DEMs). SYNPO2, NEGR1, FGF7, LIFR, RUNX1T1, CFL2, BNC2, EPHB2, PMAIP1, and CDC25A differentially expressed genes (DEGs) regulated by these DEMs were classified as candidate genes responsible for CRC and CC. Down-regulation of Synaptopodin-2 (SYNPO2) is involved in emergence and progression of these cancers by activating ER, PI3K/AKT, and EMT pathways as well as by suppressing DNA damage response, and cell cycle pathways. Higher methylation rate in promoter region of SYNPO2 could be a possible reason for lowering the expression of SYNPO2 in tumor stages. Hence, the lower expression of SYNPO2 is associated with poor prognosis of CRC and CC and could function as prognostic biomarker and therapeutic target. Fourteen transcription factors were recognized which can activate/inhibit the transcription of SYNPO2 and may be a potential target to regulate expression of SYNPO2 in CRC and CC. Retinoic acid and Estradiol were identified as putative therapeutic drugs for CRC and CC patients. This study will thus help in understanding the underlying molecular events in CRC and CC that may improve the detection of malignant lesions in primary screening and will broaden the clinical applications.

COVID-19 and Travel: How Our Out-of-home Travel Activity, In-home Activity, and Long-Distance Travel Have Changed

COVID-19 has made unprecedented impacts on our daily life. This paper investigates individuals' immediate response to COVID-19, exploring out-of-home activities, in-home activities, and long-distance travel. Data for the Kelowna region of Canada comes from a web-based COVID-19 Survey for assessing Travel impact (COST). In addition to analyzing the survey, this research models adjustments in travel decisions by developing ordered logit models for in-home and out-of-home activities, and a binomial logit model for long-distance travel. Data analysis suggests a reduction of about 50% out-of-home activities/day/person during COVID-19 compared to the pre-pandemic period, with the only exception being picking up online orders which significantly increased in frequency. Individuals were engaged in longer duration of in-home activities; the average duration of teleworking, online shopping for groceries and other goods at-home was around 5.5 h/day/person, 32 min/day/person, and 26 min/day/person respectively. The out-of-home activity model results suggest that higher income, younger and middle aged individuals, and full-time workers are more likely to decrease their out-of-home activity; whereas, males, lower income groups, health care professionals, and picking up online orders are more likely to increase. The in-home activity model suggests that older and younger adults, higher and lower income, full-time workers, and highly educated individuals are most likely to increase their in-home activity frequency; in contrast, health care professionals are likely to decrease. Long-distance travel model results reveal that seniors, students, and airline travelers are more likely to reschedule; whereas, trips to visit friends and family are more likely to be cancelled.

Protective role of tebuconazole and trifloxystrobin in wheat (Triticum aestivum L.) under cadmium stress via enhancement of antioxidant defense and glyoxalase systems

Cadmium (Cd) is a toxic metal and an environmental pollutant that significantly reduces plant growth and productivity. Proper management can ameliorate dysfunction and improve the plant growth and productivity exposed to Cd. Therefore, the present study was conducted to explore the protective role of the fungicides tebuconazole (TEB) and trifloxystrobin (TRI) in helping wheat (Triticum aestivum L. cv. Norin 61) seedlings to tolerate Cd. Five-day-old hydroponically grown seedlings were allowed to mild (0.25 mM CdCl₂) and severe (0.5 mM CdCl₂) Cd stress separately and with the fungicides (2.75 µM TEB + 1.0 µM TRI) for the next four days. Compared to control, the level of H₂O₂ in the seedlings exposed to mild and severe Cd stress alone increased by 81 and 112%, respectively. The accumulation of Cd also increased in the wheat seedlings along with declining mineral nutrients under Cd stress. The protective effect of TEB and TRI was observed with the enhancement of the antioxidant defense and methylglyoxalase systems and reduction in oxidative damage. Applying TEB and TRI reduced MDA (by 9 and 18%), EL (by 21 and 17%), MG (by 12 and 17%), and LOX activity (by 37 and 27%), respectively, relative to Cd stress alone. Cadmium uptake also decreased in the shoots (by 48 and 50%, respectively) and roots (by 23 and 25%, respectively) of the fungicide-treated wheat seedlings under mild and severe Cd stress, relative to stress alone. These results indicate the exogenous application of TEB and TRI is a promising approach to improve Cd tolerance in wheat plants. Further investigation is needed under field conditions and for other crop species to determine the Cd-tolerance induced by TEB and TRI application.

Data on growth, productivity, pigments and proximate composition of indigenous marine microalgae isolated from Cox's Bazar Coast

Data on growth, productivity, pigments and proximate composition of the four different indigenous marine microalgae (isolated from Cox's Bazar Coast) were collected to compare the growth performance, pigments and nutritional composition. Chlorella sp., Nannochloropsis sp., Tetraselmis sp. and Chaetoceros sp. are the four different marine microalgae. Growth curve was determined as the prerequisite to identify the stationary phase for each of the isolated microalgae. Data on growth curves were collected in terms of cell density and optical density to observe the growth rates and division per day. Isolated species were mass cultured in commercial culture medium. When the culture reached at stationary phase, microalgae were extracted to determine productivity, pigments, and proximate composition. The data of productivity (volumetric, areal and lipid productivity), pigments (Chlorophyll a, b, c, carotenoids, and phycobiliproteins), and proximate composition (protein, lipid, and carbohydrate) were significantly (p < 0.05) different among the four different microalgae. Therefore, this data will contribute to the selection of potential microalgae species through proper characterization for vast industrializations.

Investigation on wind energy for grid connection in Bangladesh: Case study

The increasing demand for energy in Bangladesh as well as all over the world is continuously growing unabated because of the increase of the world population and the countries’ fast-developing industrialization programs. In this critical stage of energy crisis, renewable energy is a highly welcome reliable energy source wherein wind energy is the cheapest replenishable and available energy source of the time. Regarding this particular energy source, a feasibility study of the wind energy in Chittagong has been done by analyzing the wind speed data. It is estimated that the maximum practical power output generated can be 124.53 MW at Parky beach. The number of wind turbines, operation and maintenance cost and pay-back period of those sites are also calculated.

A Novel Bayesian Optimization-Based Machine Learning Framework for COVID-19 Detection From Inpatient Facility Data

The whole world faces a pandemic situation due to the deadly virus, namely COVID-19. It takes considerable time to get the virus well-matured to be traced, and during this time, it may be transmitted among other people. To get rid of this unexpected situation, quick identification of COVID-19 patients is required. We have designed and optimized a machine learning-based framework using inpatient's facility data that will give a user-friendly, cost-effective, and time-efficient solution to this pandemic. The proposed framework uses Bayesian optimization to optimize the hyperparameters of the classifier and ADAptive SYNthetic (ADASYN) algorithm to balance the COVID and non-COVID classes of the dataset. Although the proposed technique has been applied to nine state-of-the-art classifiers to show the efficacy, it can be used to many classifiers and classification problems. It is evident from this study that eXtreme Gradient Boosting (XGB) provides the highest Kappa index of 97.00%. Compared to without ADASYN, our proposed approach yields an improvement in the kappa index of 96.94%. Besides, Bayesian optimization has been compared to grid search, random search to show efficiency. Furthermore, the most dominating features have been identified using SHapely Adaptive exPlanations (SHAP) analysis. A comparison has also been made among other related works. The proposed method is capable enough of tracing COVID patients spending less time than that of the conventional techniques. Finally, two potential applications, namely, clinically operable decision tree and decision support system, have been demonstrated to support clinical staff and build a recommender system.

Observation of spontaneous ferromagnetism in a two-dimensional electron system

What are the ground states of an interacting, low-density electron system? In the absence of disorder, it has long been expected that as the electron density is lowered, the exchange energy gained by aligning the electron spins should exceed the enhancement in the kinetic (Fermi) energy, leading to a (Bloch) ferromagnetic transition. At even lower densities, another transition to a (Wigner) solid, an ordered array of electrons, should occur. Experimental access to these regimes, however, has been limited because of the absence of a material platform that supports an electron system with very high quality (low disorder) and low density simultaneously. Here we explore the ground states of interacting electrons in an exceptionally clean, two-dimensional electron system confined to a modulation-doped AlAs quantum well. The large electron effective mass in this system allows us to reach very large values of the interaction parameter [Formula: see text], defined as the ratio of the Coulomb to Fermi energies. As we lower the electron density via gate bias, we find a sequence of phases, qualitatively consistent with the above scenario: a paramagnetic phase at large densities, a spontaneous transition to a ferromagnetic state when [Formula: see text] surpasses 35, and then a phase with strongly nonlinear current-voltage characteristics, suggestive of a pinned Wigner solid, when [Formula: see text] exceeds [Formula: see text] However, our sample makes a transition to an insulating state at [Formula: see text], preceding the onset of the spontaneous ferromagnetism, implying that besides interaction, the role of disorder must also be taken into account in understanding the different phases of a realistic dilute electron system.

Application of machine intelligence technology in the detection of vaccines and medicines for SARS-CoV-2

Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug structures that can be used to treat COVID-19. Despite the effectively demonstrated repurposed drugs, more repurposed drugs should be recognized. Furthermore, technological advancements have been helpful in the battle against COVID-19. Machine intelligence technology can support this procedure by rapidly determining adequate and effective drugs against COVID-19 and by overcoming any barrier between a large number of repurposed drugs, laboratory/clinical testing, and final drug authorization. This paper reviews the proposed vaccines and medicines for SARS-CoV-2 and the current application of AI in drug repurposing for COVID-19 treatment.

Drug Repurposing for Prevention and Treatment of COVID-19: A Clinical Landscape

SARS-CoV-2, the novel coronavirus strain responsible for the current pandemic of COVID-19, has rendered the entire humanity suffering. Several months have passed since the pandemic has struck. However, the world is still looking for an effective treatment plan to battle the viral infection. The first vaccine just received emergency approval in December 2020 for use in USA and UK. These are excellent news, however, the worldwide distribution of such vaccine, the possibility of virus mutation and the lack of data regarding the long-term effects of such vaccines are a significant concern. In addition, although remdesivir was recently approved by the FDA to be used as a clinical drug against COVID-19, it hasn't stood out yet as a proven form of therapeutics. Such inability to produce a novel therapy has caused enough inconveniences for the affected people worldwide. Repurposing the already available drugs to fight against the virus seems to be a reasonable option amidst such uncertainty. Given the vast collection of potential treatment candidates to be explored against COVID-19, there is a decent chance that a success in this regard will serve the intermediary purpose of clinically treating the infection until a COVID-19 vaccine is widely distributed worldwide and will be able to treat COVID-19 patients that do not adequately respond to vaccines. Such treatments may prove very useful in future coronavirus outbreaks too. Proper research into these repurposing treatments may yield a certain insight into the field of novel treatment production as well. This review study accumulates a relevant set of information about drugs and vaccines against COVID-19, in terms of their repurposing properties and the specific phases of clinical trials they are undergoing across the world.  A potential timeline is also suggested to estimate when an effective result can be expected from the ongoing clinical trials for a better anticipation of the drug landscape. This study will hopefully help accelerate investment of resources into development and discovery of drugs and vaccines against the infection.

Genomic exploration light on multiple origin with potential parsimony-informative sites of the severe acute respiratory syndrome coronavirus 2 in Bangladesh

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of beta coronavirus that has spread worldwide within a short period of time and has been responsible for the current COVID-19 pandemic. This novel virus shows high transmission and adaptability frequency into the host with rapid changes in genomic sequences. In this study, we analyzed the complete genome of 41 strains isolated in Bangladesh to understand the evolutionary route and genetic variations of this rapidly evolving virus. The phylogenetics, parsimony informative sites and mutation analyses were performed using MEGA X, Multiple sequence alignment program (MAFFT), and Virus Pathogen Resource. The phylogenetic analysis of the studied genomes along with the reference genome suggested that the viral strains found in Bangladesh might be coming from multiple countries such as France, Germany, India, the USA, and Brazil. After entering into the country, intra-cluster and inter-cluster began to circulate in the 8 individual divisions of Bangladesh. We also identified 26 parsimony-informative sites along with the 9 most important sites for virus evolution. Genome-wide annotations revealed 256 mutations, of which 10 were novel (NSP3, RdRp, Spike) in Bangladeshi strains where I120F(NSP2), P323L(RdRp), D614G (Spike), R203K, G204R(N) are the most prominent. Most importantly, numerous mutations were flourishing in the N protein gene (67) followed by S (45), RdRp (38), NSP2 (34), NSP3 (20), and ORF8 (6) gene. Moreover, nucleotide deletion analysis found nine deletions throughout the genomes including in ORF7a (8), ORF8 (1) with one insertion (G) at 265 positions in only one genome. The underlying mechanism of disease severity, molecular evolution, and epidemiology lie in genomic sequences that are not fully understood yet. Identification of the evolutionary history, parsimony-informative sites and others genetic variations of this deadly virus will facilitate the development of new strategies to control the local transmission and provide deep insight in the identification of potential therapeutic targets for controlling COVID-19.

Status of Plasma Vitamin-D Level in Predicting Adverse In-Hospital Outcome in Patients with First Attack of Acute Myocardial Infarction

Acute myocardial infarction has many risk factors and etiologies. Different factors are responsible for adverse in-hospital outcome after acute MI. Status of plasma vitamin D level has been found to be a good predictor of future adverse cardiovascular outcomes in patients with acute MI. Plasma vitamin D level has been considered as a potential marker for identifying individuals under risk of CAD and associated events. This study was done to investigate the role of plasma vitamin D level in predicting in-hospital adverse cardiac events in patients with acute MI. This cross sectional descriptive type of study was conducted in the cardiology department of Mymensingh Medical College Hospital, Mymensingh, Bangladesh from October 2017 to March 2019. Total 257 patients of first attack of acute MI were included considering inclusion and exclusion criteria. Fasting blood samples were analyzed for plasma vitamin D level. Sample population were grouped at first into two, normal and low vitamin D level, taking 30ng/ml as cut-off value, low vitamin D level is further subdivided into insufficiency (21-29ng/ml), deficiency (10-20ng/ml) and severe deficiency (<10ng/ml). Adverse in-hospital cardiac outcomes were observed. In-hospital adverse outcomes occurred in 42.9% patients having normal vitamin D level (>30ng/ml), 66.2% of patients having vitamin D insufficiency (21-29ng/ml), 78.2% of patients having vitamin D deficiency (10-20ng/ml) and 94.4% patients having severe vitamin D deficiency (<10ng/ml), which was statistically significant (p<0.05). Heart failure (30.3%, 47.7%, 63.6% and 77.8%, p<0.05), cardiogenic shock (12.6%, 27.7%, 34.5% and 33.3%, p<0.05), Arrhythmias (14.3%, 21.5%, 23.6% and 22.2%, p>0.05), death (2.5%, 0%, 3.6% and 11.1%, p>0.05) occurred more in low vitamin D groups. Mean vitamin D level was significantly different between Group I and Group II (42.59±10.08 vs. 18.64±6.54, p<0.0001). Multivariate regression analysis showed vitamin D is an independent predictor of in-hospital adverse cardiac events (p=0.001). Age (p=0.001) and obesity (p=0.048) were also other predictors of in-hospital adverse cardiac events. Low plasma vitamin D level is an important predictor for in-hospital adverse cardiac events in patients hospitalized with first attack of acute MI.

Relationship of Plasma Vitamin-D Level with Left Ventricular Ejection Fraction in Patients with First Attack of Acute Myocardial Infarction

It has been widely reported that vitamin D deficiency is associated with Coronary heart disease (CHD), especially acute Myocardial infarction (MI). Many factors are responsible for reduced Left ventricular ejection fraction (LVEF) and acute Left ventricular fraction (LVF) after acute MI. This cross sectional descriptive type of study was conducted in the Cardiology department of Mymensingh Medical College Hospital from October 2017 to March 2019 to investigate the relationship of plasma vitamin D with LVEF in patients with first attack of acute MI. Total 185 patients of first attack of acute MI were included considering inclusion and exclusion criteria. Fasting blood samples were analyzed for plasma vitamin D level. Sample population were grouped at first into two, normal and low vitamin D level, taking 30ng/ml as cut-off value, low vitamin D level is further subdivided into insufficiency (21-29ng/ml), deficiency (10-20ng/ml) and severe deficiency (<10ng/ml). LVEF among the patients was observed. LVEF was found 49.88±8.58% patients having normal vitamin D level (>30ng/ml), 47.60±8.24% of patients having vitamin D insufficiency (21-29ng/ml), 44.38±8.12% of patients having vitamin D deficiency (10-20ng/ml) and 40.61±8.64% patients having severe vitamin D deficiency (<10ng/ml), which was statistically significant (p<0.05). So, low plasma vitamin D level is associated with reduced LVEF in patients hospitalized with first attack of acute MI.