Plasma metabolites analysis of patients with papillary thyroid cancer: A preliminary untargeted 1H NMR-based metabolomics.

Metabolomics plays a crucial role in identifying molecular biomarkers that can differentiate pathological conditions. In the case of thyroid cancer, it is essential to accurately diagnose malignancy from benignity to avoid unnecessary surgeries. The objective of this research was to apply untargeted NMR-based metabolomics in order to identify metabolic biomarkers that can distinguish between plasma samples of patients with papillary thyroid cancer (PTC) and multinodular goiter (MNG), as well as PTC and healthy individuals. The study included a cohort of 55 patients who were divided into three groups: PTC (n=20), MNG (n=16), and healthy (n=19). Plasma samples were collected from all participants and subjected to 1H NMR spectroscopy. Differential metabolites were identified using chemometric pattern recognition algorithms. The obtained metabolic profile had the potential to differentiate PTC from healthy plasma, but not from MNG. In patients diagnosed with PTC, a total of 18 compounds were discovered, revealing elevated levels of leucine, lysine, and 4-acetamidobutyric acid, while acetate, proline, acetoacetate, 3-hydroxybutyrate, glutamate, pyruvate, cystine, glutathione, asparagine, ethanolamine, histidine, tyrosine, myo-inositol, and glycerol along with a lipid compound were found to be lower in comparison to those of healthy individuals. According to the area under the curve (AUC) of the receiver operating characteristic curve, this particular profile exhibited an impressive capability of 85% to discern PTC from healthy subjects (AUC=0.853, sensitivity=78.95, specificity=84.21). The utilization of the 1H NMR-based metabolomics approach revealed considerable promise in the identification of PTC from healthy plasma specimens. The modifications noticed in the plasma metabolites have the potential to act as practical biomarkers that are non-invasive and could suggest transformations in the metabolic profile of thyroid tumors.

SARS2Mutant: SARS-CoV-2 amino-acid mutation atlas database.

The coronavirus disease 19 (COVID-19) is a highly pathogenic viral infection of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in the global pandemic of 2020. A lack of therapeutic and preventive strategies has quickly posed significant threats to world health. A comprehensive understanding of SARS-CoV-2 evolution and natural selection, how it impacts host interaction, and phenotype symptoms is vital to develop effective strategies against the virus. The SARS2Mutant database (http://sars2mutant.com/) was developed to provide valuable insights based on millions of high-quality, high-coverage SARS-CoV-2 complete protein sequences. Users of this database have the ability to search for information on three amino acid substitution mutation strategies based on gene name, geographical zone, or comparative analysis. Each strategy is presented in five distinct formats which includes: (i) mutated sample frequencies, (ii) heat maps of mutated amino acid positions, (iii) mutation survivals, (iv) natural selections and (v) details of substituted amino acids, including their names, positions, and frequencies. GISAID is a primary database of genomics sequencies of influenza viruses updated daily. SARS2Mutant is a secondary database developed to discover mutation and conserved regions from the primary data to assist with design for targeted vaccine, primer, and drug discoveries.

Global landscape of SARS-CoV-2 mutations and conserved regions.

BACKGROUND: At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management. METHODS: 10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence. RESULTS: Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively. CONCLUSION: Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

SARS-CoV-2 Non-structural protein 1(NSP1) mutation virulence and natural selection: Evolutionary trends in the six continents.

OBJECTIVE: Rapid transmission and reproduction of RNA viruses prepare conducive conditions to have a high rate of mutations in their genetic sequence. The viral mutations make adapt the severe acute respiratory syndrome coronavirus 2 in the host environment and help the evolution of the virus then also caused a high mortality rate by the virus that threatens worldwide health. Mutations and adaptation help the virus to escape confrontations that are done against it. METHODS: In the present study, we analyzed 6,510,947 sequences of non-structural protein 1 as one of the conserved regions of the virus to find out frequent mutations and substitute amino acids in comparison with the wild type. NSP1 mutations rate divided into continents were different. RESULTS: Based on this continental categorization, E87D in global vision and also in Europe notably increased. The E87D mutation has signed up to January 2022 as the first frequent mutation observed. The remarkable mutations, H110Y and R24C have the second and third frequencies, respectively. CONCLUSION: According to the important role of non-structural protein 1 on the host mRNA translation, developing drug design against the protein could be so hopeful to find more effective ways the control and then treatment of the global pandemic coronavirus disease 2019.

In silico analysis of the substitution mutations and evolutionary trends of the SARS-CoV-2 structural proteins in Asia.

Objectives: To address a highly mutable pathogen, mutations must be evaluated. SARS-CoV-2 involves changing infectivity, mortality, and treatment and vaccination susceptibility resulting from mutations. Materials and Methods: We investigated the Asian and worldwide samples of amino-acid sequences (AASs) for envelope (E), membrane (M), nucleocapsid (N), and spike (S) proteins from the announcement of the new coronavirus 2019 (COVID-19) up to January 2022. Sequence alignment to the Wuhan-2019 virus permits tracking mutations in Asian and global samples. Furthermore, we explored the evolutionary tendencies of structural protein mutations and compared the results between Asia and the globe. Results: The mutation analyses indicated that 5.81%, 70.63%, 26.59%, and 3.36% of Asian S, E, M, and N samples did not display any mutation. Additionally, the most relative mutations among the S, E, M, and N AASs occurred in the regions of 508 to 635 AA, 7 to 14 AA, 66 to 88 AA, and 164 to 205 AA in both Asian and total samples. D614G, T9I, I82T, and R203M were inferred as the most frequent mutations in S, E, M, and N AASs. Timeline research showed that substitution mutation in the location of 614 among Asian and total S AASs was detected from January 2020. Conclusion: N protein was the most non-conserved protein, and the most prevalent mutations in S, E, M, and N AASs were D614G, T9I, I82T, and R203M. Screening structural protein mutations is a robust approach for developing drugs, vaccines, and more specific diagnostic tools.

Mutations in SARS-CoV-2 structural proteins: a global analysis.

BACKGROUND: Emergence of new variants mainly variants of concerns (VOC) is caused by mutations in main structural proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, we aimed to investigate the mutations among structural proteins of SARS-CoV-2 globally. METHODS: We analyzed samples of amino-acid sequences (AASs) for envelope (E), membrane (M), nucleocapsid (N), and spike (S) proteins from the declaration of the coronavirus 2019 (COVID-19) as pandemic to January 2022. The presence and location of mutations were then investigated by aligning the sequences to the reference sequence and categorizing them based on frequency and continent. Finally, the related human genes with the viral structural genes were discovered, and their interactions were reported. RESULTS: The results indicated that the most relative mutations among the E, M, N, and S AASs occurred in the regions of 7 to 14, 66 to 88, 164 to 205, and 508 to 635 AAs, respectively. The most frequent mutations in E, M, N, and S proteins were T9I, I82T, R203M/R203K, and D614G. D614G was the most frequent mutation in all six geographical areas. Following D614G, L18F, A222V, E484K, and N501Y, respectively, were ranked as the most frequent mutations in S protein globally. Besides, A-kinase Anchoring Protein 8 Like (AKAP8L) was shown as the linkage unit between M, E, and E cluster genes. CONCLUSION: Screening the structural protein mutations can help scientists introduce better drug and vaccine development strategies.

The potential key genes and pathways associated with Wilms tumor in quest of proper candidates for diagnostic and therapeutic purposes.

To designate the probable most important differentially expressed genes and genetic pathways in Wilms tumor and assess their expression and diagnostic potential by RT-PCR and statistical analysis. Systematic review of the literature and various bioinformatics analysis was carried out to gather and narrow down data. The expression of end-resulting genes was compared in Wilms tumor and normal tissue samples using RT-PCR. Statistical tests reported the diagnostic accuracy of genes and their correlation with clinicopathological features. Four genes including CDH1, NCAM1, EGF, and IGF2 were designated. The panel combining them has 100% sensitivity and specificity in differentiating tumors from normal tissue. Eight pathways, most involved in cell-cell and cell-basal matrix junction interactions, were found to be associated with disease pathogenesis. The suggested genes should undergo further evaluation to be validated as diagnostic biomarkers. Further research on the eight proposed pathways is recommended.

SARS-CoV-2 Non-Structural Protein 1(NSP1) Mutation Virulence and Natural Selection: Evolutionary Trends in the Six Continents.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an unsegmented positivesense single-stranded RNA virus that belongs to the ß-coronavirus . This virus was the cause of a novel severe acute respiratory syndrome in 2019 (COVID-19) that emerged in Wuhan, China at the early stage of the pandemic and rapidly spread around the world. Rapid transmission and reproduction of SARS-CoV-2 threaten worldwide health with a high mortality rate from the virus. According to the significant role of non-structural protein 1 (NSP1) in inhibiting host mRNA translation, this study focuses on the link between amino acid sequences of NSP1 and alterations of them spreading around the world. The SARS-CoV-2 NSP1 protein sequences were analyzed and FASTA files were processed by Python language programming libraries. Reference sequences compared with each NSP1 sample to identify every mutation and categorize them were based on continents and frequencies. NSP1 mutations rate divided into continents were different. Based on continental studies, E87D in global vision and also in Europe notably increased. The E87D mutation has significantly risen especially in the last months of the study as the first frequent mutation observed. The remarkable mutations, H110Y and R24C, have the second and third frequencies, respectively. Based on this mutational information, despite NSP1 being a conserved sequence occurrence, these mutations change the rate of flexibility and stability of the NSP1 protein, which can eventually affect inhibiting the host translation. IMPORTANCE: In this study, we analyzed 6,510,947 sequences of non-structural protein 1 as a conserved region of SARS-CoV-2. According to the obtained results, 93.4819% of samples had no mutant regions on their amino acid sequences. Heat map data of mutational samples demonstrated high percentages of mutations that occurred in the region of 72 to 126 amino acids indicating a hot spot region of the protein. Increased rates of E87D, H110Y, and R24C mutations in the timeline of our study were reported as significant compared to available mutant samples. Analyzing the details of replacing amino acids in the most frequent E87D mutation reveals the role of this alteration in increasing molecule flexibility and destabilizing the structure of the protein.

The First Geographic Identification by Country of Sustainable Mutations of SARS-COV2 Sequence Samples: Worldwide Natural Selection Trends.

The high mutation rates of RNA viruses, coupled with short generation times and large population sizes, allow viruses to evolve rapidly and adapt to the host environment. The rapidity of viral mutation also causes problems in developing successful vaccines and antiviral drugs. With the spread of SARS-CoV-2 worldwide, thousands of mutations have been identified, some of which have relatively high incidences, but their potential impacts on virus characteristics remain unknown. The present study analyzed mutation patterns, SARS-CoV-2 AASs retrieved from the GISAID database containing 10,500,000 samples. Python 3.8.0 programming language was utilized to pre-process FASTA data, align to the reference sequence, and analyze the sequences. Upon completion, all mutations discovered were categorized based on geographical regions and dates. The most stable mutations were found in nsp1(8% S135R), nsp12(99.3% P323L), nsp16 (1.2% R216C), envelope (30.6% T9I), spike (97.6% D614G), and Orf8 (3.5% S24L), and were identified in the United States on April 3, 2020, and England, Gibraltar, and, New Zealand, on January 1, 2020, respectively. The study of mutations is the key to improving understanding of the function of the SARS-CoV-2, and recent information on mutations helps provide strategic planning for the prevention and treatment of this disease. Viral mutation studies could improve the development of vaccines, antiviral drugs, and diagnostic assays designed with high accuracy, specifically useful during pandemics. This knowledge helps to be one step ahead of new emergence variants.

An improvement in acute wound healing in rats by the synergistic effect of photobiomodulation and arginine.

In this probe, at first we examined the best route and dosage of arginine administration on wound healing in an excisional wound model in rats. Next, we intend to assess the impact of photobiomodulation (PBM) and arginine, individually and together, on the wound healing. In the pilot study, an excisional wound was made in each of 24 rats. There were 4 groups. Group 1 was the control group. In groups 2 and 3, wounds were topically treated with arginine ointments (ARG.) 2% and 5%, respectively. In group 4, arginine was injected (ARG. INJ.,i.p.). In the main phase, in 24 new rats, an excisional wound was made. There were 4 groups: group 5 served as the control. Wounds in group 6 were topically treated with ARG 2%. Wounds in group 7 were subjected to PBM. Wounds in group 8 were treated with PBM+ARG. 2%. On day 15, wound area measurement, wound strength, and stereological examination were performed. In the pilot study, we found that the ARG 2% ointment significantly decreased wound area than ARG. 5%, ARG. INJ. and control groups, and significantly increased wound strength compared to the control and ARG.5% groups. In the main phase, a significant decrease of wound area in all treatment regimens was induced. PBM + ARG. 2% and PBM treatment regimens significantly improved wound strength and almost all stereological parameters, compared to the control and ARG. 2% groups. PBM + ARG. 2% induced anti-inflammatory and angiogenic activities, and hastened the wound healing process in an excisional wound model in rats.