Neurological complications after COVID-19: A narrative review.

COVID-19 is primarily classified as a respiratory disorder; however, various neurological symptoms have been reported in COVID-19 patients. Neurological manifestations may be the initial signs of COVID-19 and can develop in patients of different age groups and with or without underlying disease. COVID-19 causes a broad range of complications in the central nervous system. These include headaches, altered mental status, dizziness, seizures, cerebrovascular events, encephalitis, and other encephalopathies. Moreover, a broad spectrum of peripheral nervous system symptoms such as olfactory and gustatory dysfunctions, neuropathy, visual impairments, neuralgia, cranial nerves palsy, and muscle involvement could manifest as symptoms. Despite various efforts, the exact pathogenesis of the COVID-19 neurological complications has not been clarified yet. Moreover, the reason for the development of neurological manifestation in only some COVID-19 patients has not been determined. This review focuses on the different neurological symptoms associated with COVID-19 and the possible pathological mechanisms hoping to provide new insights for diagnosis, therapies, or other forms of intervention.

Potential miRNA-gene interactions determining progression of various ATLL cancer subtypes after infection by HTLV-1 oncovirus.

BACKGROUND: Adult T-cell Leukemia/Lymphoma (ATLL) is a rapidly progressing type of T-cell non-Hodgkin lymphoma that is developed after the infection by human T-cell leukemia virus type 1 (HTLV-1). It could be categorized into four major subtypes, acute, lymphoma, chronic, and smoldering. These different subtypes have some shared clinical manifestations, and there are no trustworthy biomarkers for diagnosis of them. METHODS: We applied weighted-gene co-expression network analysis to find the potential gene and miRNA biomarkers for various ATLL subtypes. Afterward, we found reliable miRNA-gene interactions by identifying the experimentally validated-target genes of miRNAs. RESULTS: The outcomes disclosed the interactions of miR-29b-2-5p and miR-342-3p with LSAMP in ATLL_acute, miR-575 with UBN2, miR-342-3p with ZNF280B, and miR-342-5p with FOXRED2 in ATLL_chronic, miR-940 and miR-423-3p with C6orf141, miR-940 and miR-1225-3p with CDCP1, and miR-324-3p with COL14A1 in ATLL_smoldering. These miRNA-gene interactions determine the molecular factors involved in the pathogenesis of each ATLL subtype and the unique ones could be considered biomarkers. CONCLUSION: The above-mentioned miRNAs-genes interactions are suggested as diagnostic biomarkers for different ATLL subtypes.

Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review.

Diabetes as a metabolic illness can be characterized by increased amounts of blood glucose. This abnormal increase can lead to critical detriment to the other organs such as the kidneys, eyes, heart, nerves, and blood vessels. Therefore, its prediction, prognosis, and management are essential to prevent harmful effects and also recommend more useful treatments. For these goals, machine learning algorithms have found considerable attention and have been developed successfully. This review surveys the recently proposed machine learning (ML) and deep learning (DL) models for the objectives mentioned earlier. The reported results disclose that the ML and DL algorithms are promising approaches for controlling blood glucose and diabetes. However, they should be improved and employed in large datasets to affirm their applicability.

MIL-88B(Fe)-reduced graphene oxide as an artificial enzyme for gold nanorod etching and its application to develop the prostate-specific antigen immunosensor.

An immunosensor based on gold nanorods (AuNRs) etchant activity of a metal-organic framework (MOF): MIL-88B(Fe)-reduced graphene oxide (rGMOF) was developed for the determination of prostate-specific antigen (PSA). Several techniques, including FTIR, UV-Vis spectrophotometry, XRD, and electron microscopy, were employed to characterize the MOFs containing iron-oxygen clusters on the surface of reduced graphene oxide. Enzyme mimetic activity of rGMOF before and after bioconjugation with antibodies was calculated as 8.4 and 2.5 U mg-1, respectively. The primary anti-PSA was conjugated to a magnetic bead and used as PSA-specific capturing. Then, the secondary anti-PSA was grafted to the rGMOF. In the presence of antigen, an immuno-sandwich was formed between the conjugations mentioned above. Afterward, AuNRs were etched by rGMOF, and the related spectrum was recorded in the wavelength range 350 to 900 nm. By progressing the etching procedure, the longitudinal LSPR peak of AuNRs was gradually blue-shifted with a linear correlation with the PSA concentration from 0.1 pg mL-1 to 100 ng mL-1. The detection limit was 0.09 pg mL-1. The proposed immunosensor was successfully employed to determine PSA levels in real samples. Since the obtained results showed an excellent correlation with those acquired by the chemiluminescence gold standard method, it has the potential for PSA determination in clinical assays.

Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning.

BACKGROUND: Adult T-cell Leukemia/Lymphoma (ATLL) is a cancer disease that is developed due to the infection by human T-cell leukemia virus type 1. It can be classified into four main subtypes including, acute, chronic, smoldering, and lymphoma. Despite the clinical manifestations, there are no reliable diagnostic biomarkers for the classification of these subtypes. METHODS: Herein, we employed a machine learning approach, namely, Support Vector Machine-Recursive Feature Elimination with Cross-Validation (SVM-RFECV) to classify the different ATLL subtypes from Asymptomatic Carriers (ACs). The expression values of multiple mRNAs and miRNAs were used as the features. Afterward, the reliable miRNA-mRNA interactions for each subtype were identified through exploring the experimentally validated-target genes of miRNAs. RESULTS: The results revealed that miR-21 and its interactions with DAAM1 and E2F2 in acute, SMAD7 in chronic, MYEF2 and PARP1 in smoldering subtypes could significantly classify the diverse subtypes. CONCLUSIONS: Considering the high accuracy of the constructed model, the identified mRNAs and miRNA are proposed as the potential therapeutic targets and the prognostic biomarkers for various ATLL subtypes.

Evaluating the cytotoxicity and pathogenicity of multi-walled carbon nanotube through weighted gene co-expression network analysis: a nanotoxicogenomics study.

BACKGROUND: Multi-walled carbon nanotube (MWCNT) is one of the most momentous carbonaceous nanoparticles which is widely used for various applications such as electronics, vehicles, and therapeutics. However, their possible toxicity and adverse effects convert them into a major health threat for humans and animals. RESULTS: In this study, we employed weighted gene co-expression network analysis (WGCNA) to identify the co-expressed gene groups and dysregulated pathways due to the MWCNT exposure. For this purpose, three weighted gene co-expression networks for the microarray gene expression profiles of the mouse after 1, 6, and 12-month post-exposure to MWCNT were constructed. The module-trait analysis specified the significant modules related to different doses (1, 10, 40, and 80 µg) of MWCNT. Afterward, common genes between co-regulated and differentially expressed genes were determined. The further pathway analysis highlighted the enrichment of genes including Actb, Ube2b, Psme3, Ezh2, Alas2, S100a10, Ypel5, Rhoa, Rac1, Ube2l6, Prdx2, Ctsb, Bnip3l, Gp6, Myh9, Ube2k, Mbnl1, Kbtbd8, Riok3, Itgb1, Rap1a, and Atp5h in immune-, inflammation-, and protein metabolism-related pathways. CONCLUSIONS: This study discloses the genotoxicity and cytotoxicity effects of various doses of MWCNT which also affect the metabolism system. The identified genes can serve as potential biomarkers and therapeutic candidates. However, further studies should be performed to validate them in human cells.

Identification of common microRNA between COPD and non-small cell lung cancer through pathway enrichment analysis.

BACKGROUND: Different factors have been introduced which influence the pathogenesis of chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC). COPD as an independent factor is involved in the development of lung cancer. Moreover, there are certain resemblances between NSCLC and COPD, such as growth factors, activation of intracellular pathways, as well as epigenetic factors. One of the best approaches to understand the possible shared pathogenesis routes between COPD and NSCLC is to study the biological pathways that are activated. MicroRNAs (miRNAs) are critical biomolecules that implicate the regulation of several biological and cellular processes. As such, the main goal of this study was to use a systems biology approach to discover common dysregulated miRNAs between COPD and NSCLC, one that targets most genes within common enriched pathways. RESULTS: To reconstruct the miRNA-pathways for each disease, we used the microarray miRNA expression data. Then, we employed "miRNA set enrichment analysis" (MiRSEA) to identify the most significant joint miRNAs between COPD and NSCLC based on the enrichment scores. Overall, our study revealed the involvement of the targets of miRNAs (such as has-miR-15b, hsa-miR-106a, has-miR-17, has-miR-103, and has-miR-107) in the most important common biological pathways. CONCLUSIONS: According to the promising results of the pathway analysis, the identified miRNAs can be utilized as the new potential signatures for therapy through understanding the molecular mechanisms of both diseases.

Identification of joint gene players implicated in the pathogenesis of HTLV-1 and BLV through a comprehensive system biology analysis.

BACKGROUND: Human T-cell lymphotropic virus type 1 (HTLV-1) and bovine leukemia virus (BLV) are oncogenic viruses that induce adult T cell leukemia/lymphoma (ATLL) and enzootic bovine leukosis (EBL), respectively. HTLV-1 principally infects CD4+ T cells comprising regulatory T cells (Tregs), T helper 1 (Th1), and T helper 2 (Th2), while BLV infects B lymphocytes. Both viruses may impel cell proliferation and malignancy. METHODS: To survey the transcriptomic variations due to HTLV-1 and BLV infection and further hematologic malignancies, differential expression genes (DEGs) were explored between leukemia and normal samples using the DESeq2 package. Gene set enrichment analyses (GSEA) were then performed to identify significant gene sets using the FGSEA package. Afterward, the protein-protein interaction (PPI) networks were reconstructed using the STRING online database. Eventually, the hub significant genes and modules were determined through network analysis and MCODE algorithm, respectively. RESULTS: Our results uncloaked that four common functional gene sets including mitotic-spindle, G2M-checkpoint, E2F-targets, and MYC-targets-V1 are involved in the human and ovine hosts. Furthermore, twelve up-regulated hub genes including BIRC5, CCNA2, CCNB2, BUB1, DLGAP5, TOP2A, PBK, ASPM, UBE2C, CEP55, KIF20A, and NUSAP1 were identified which were similarly activated in both human and ovine hosts. They mostly participate in pathways including cell cycle, cell division, DNA damage responses, growth factors production, and p53 signaling pathway. The dysregulated hub genes and pathways seem to be involved in the development and progression of the infected cells toward malignancy. CONCLUSION: There is common gene groups between HTLV-1 and BLV infections that promote viral malignancy through enhancing cell proliferation and overall survival of cancer cells. The dysregulated genes and pathways may be the efficient candidates for the therapy of the mentioned life-threatening diseases.

Potential role of viral infection and B cells as a linker between innate and adaptive immune response in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease that involves several organ systems. Although B cells play a key role in SLE pathogenesis, the mechanisms behind B cell dysregulation in SLE development remained controversial. Finding the modules containing highly co-expressed genes in B cells could explain biological pathways involved in the pathogenesis of SLE, which may further support the reasons for the altered function of B cells in SLE disease. A total of three microarray gene expression datasets were downloaded from Gene Expression Omnibus. SLE samples were prepared from the purified B lymphocyte cells of the patients who have not received immunosuppressive drugs as well as high dose immunocytotoxic therapies or steroids. A weighted gene co-expression network was then constructed to find the relevant modules implicated in the SLE progression. Among 17 identified modules, 3 modules were selected through mapping to STRING and finding the ones that had highly connection at the protein level. These modules clearly indicate the involvement of several pathways in the pathogenesis of SLE including viral infection, adaptive immune response, and innate immune response in B lymphocytes. The WGCN analysis further revealed the co-expressed genes involved in both innate and adaptive immune systems. Mix infections and primary immunodeficiency might also dysregulate B lymphocytes, which may facilitate SLE development. As such, identifying novel biomarkers and pathways in lupus would be of importance.

Deciphering microRNA-mRNA regulatory network in adult T-cell leukemia/lymphoma; the battle between oncogenes and anti-oncogenes.

Adult T-cell leukemia/lymphoma (ATLL) is virus-caused cancer that originates from the infection by human T-cell leukemia virus type 1. ATLL dysregulates various biological pathways related to the viral infection and cancer progression through the dysexpression of miRNAs and mRNAs. In this study, the potential regulatory subnetworks were constructed aiming to shed light on the pathogenesis mechanism of ATLL. For this purpose, two mRNA and one miRNA expression datasets were firstly downloaded from the GEO database. Next, the differentially expressed genes and miRNAs (DEGs and DE-miRNAs, respectively), as well as differentially co-expressed gene pairs (DCGs), were determined. Afterward, common DEGs and DCGs targeted by experimentally validated DE-miRNAs were explored. The oncogenic and anti-oncogenic miRNA-mRNA regulatory subnetworks were then generated. The expression levels of four genes and two miRNAs were examined in the blood samples by qRT-PCR. The members of three oncogenic/anti-oncogenic subnetworks were generally enriched in immune, virus, and cancer-related pathways. Among them, FZD6, THBS4, SIRT1, CPNE3, miR-142-3p, and miR-451a were further validated by real-time PCR. The significant up-regulation of FZD6, THBS4, and miR-451a as well as down-regulation of CPNE3, SIRT1, and miR-142-3p were found in ATLL samples than normal samples. The identified oncogenic/anti-oncogenic subnetworks are pieces of the pathogenesis puzzle of ATLL. The ultimate winner is probably an oncogenic network that determines the final fate of the disease. The identified genes and miRNAs are proposed as novel prognostic biomarkers for ATLL.

Long segment detection of HTLV-1 genome based on the fluorescence quenching technique.

Detecting fluorescence changes due to energy transfer between a quencher and fluorophore is a common method used for the fluorescence-based biosensors. In the present report, a new biosensor for long segment detection of the human T cell-lymphotropic virus 1 genome was constructed based on the fluorescence quenching of graphene oxide by gold nanoparticles. The fluorescence signal of unmodified graphene oxide was measured before and after hybridization of target and probes functionalized with gold nanoparticles. The limit of detection of the biosensor was determined to be around 10 pg/mL. The specific design for long segment of target assures the selectivity of biosensor. Our results proposed that further development may be useful to detect other viruses.

New findings and the current controversies for water oxidation by a copper(ii)-azo complex: homogeneous or heterogeneous?

In this paper, new findings for the water-oxidizing activity of [(L)Cu(II)(NO3)], (L = (E)-3-(pyridin-2-yldiazenyl)naphthalen-2-ol (HL)) under both electro-water oxidation conditions and in the presence of cerium(iv) ammonium nitrate are reported.

The biological water-oxidizing complex at the nano-bio interface.

Photosynthesis is one of the most important processes on our planet, providing food and oxygen for the majority of living organisms on Earth. Over the past 30 years scientists have made great strides in understanding the central photosynthetic process of oxygenic photosynthesis, whereby water is used to provide the hydrogen and reducing equivalents vital to CO2 reduction and sugar formation. A recent crystal structure at 1.9-1.95Å has made possible an unparalleled map of the structure of photosystem II (PSII) and particularly the manganese-calcium (Mn-Ca) cluster, which is responsible for splitting water. Here we review how knowledge of the water-splitting site provides important criteria for the design of artificial Mn-based water-oxidizing catalysts, allowing the development of clean and sustainable solar energy technologies.

An engineered polypeptide around nano-sized manganese-calcium oxide: copying plants for water oxidation.

Synthesis of new efficient catalysts inspired by Nature is a key goal in the production of clean fuel. Different compounds based on manganese oxide have been investigated in order to find their water-oxidation activity. Herein, we introduce a novel engineered polypeptide containing tyrosine around nano-sized manganese-calcium oxide, which was shown to be a highly active catalyst toward water oxidation at low overpotential (240 mV), with high turnover frequency of 1.5 × 10(-2) s(-1) at pH = 6.3 in the Mn(III)/Mn(IV) oxidation range. The compound is a novel structural and efficient functional model for the water-oxidizing complex in Photosystem II. A new proposed clever strategy used by Nature in water oxidation is also discussed. The new model of the water-oxidizing complex opens a new perspective for synthesis of efficient water-oxidation catalysts.

Comparison of nano-sized Mn oxides with the Mn cluster of photosystem II as catalysts for water oxidation.

"Back to Nature" is a promising way to solve the problems that we face today, such as air pollution and shortage of energy supply based on conventional fossil fuels. A Mn cluster inside photosystem II catalyzes light-induced water-splitting leading to the generation of protons, electrons and oxygen in photosynthetic organisms, and has been considered as a good model for the synthesis of new artificial water-oxidizing catalysts. Herein, we surveyed the structural and functional details of this cluster and its surrounding environment. Then, we review the mechanistic findings concerning the cluster and compare this biological catalyst with nano-sized Mn oxides, which are among the best artificial Mn-based water-oxidizing catalysts.

The effect of different metal ions between nanolayers of manganese oxide on water oxidation.

Here, we used a strategy to answer to the question that whether Ca(II) ion is specific for water oxidation or not? In the procedure, first we synthesized layered Mn oxides with K(I) between layers and then replaced K(I) by Ca(II), K(I), Mg(II), La(III) or Ni(II). We proposed that Ca(II), K(I), Mg(II), La(III) and Ni(II), between layers are important to form efficient water-oxidizing catalyst, but not specific in water oxidation. However, Cu(II) ions decrease water-oxidizing activity of layered Mn oxides. The result is important to find critical factors in water oxidation by low-cost and environmentally friendly nanolayered Mn oxides.

Application of supervised Kohonen map and counter propagation neural network for classification of nucleic acid structures based on their circular dichroism spectra.

One of the most popular instrumental methods to detect the DNA structure is circular dichroism. Specific experimental conditions are required to form different structures of DNA. However, there is the possibility of different structures establishing in the similar circumstance. So, methods development to improve the classification and prediction of structures using their spectra information are needed. To this end, we applied unsupervised (PCA) and supervised (PLS-DA, SKN, and CPNN) approaches to classify CD spectra dataset of different DNA sequences (random coil (ss-DNA), duplex, hairpin, reversed and normal triplex, parallel and antiparallel G-quadruplex, and i-motif). The main part of this work concentrates on the application of artificial neural networks and weight analysis to obtain more classification and prediction accuracy. For this purpose, the trained network was run 10 times, and the average weights were taken. Also, weight analysis was done for the prediction of mixture samples include different structures. The results prove that new method of weights analysis based on SKN and CPNN is useful for classification of complicated data such as different types of DNA structures.

A nano-sized manganese oxide in a protein matrix as a natural water-oxidizing site.

The purpose of this review is to present recent advances in the structural and functional studies of water-oxidizing center of Photosystem II and its surrounding protein matrix in order to synthesize artificial catalysts for production of clean and efficient hydrogen fuel.

Conversions of Mn oxides to nanolayered Mn oxide in electrochemical water oxidation at near neutral pH, all to a better catalyst: catalyst evolution.

Here, for the first time, it is reported that some Mn oxides after a few hours convert to a nanolayered Mn oxide when the compounds are used as water-oxidizing catalysts in a water electrolysis device at near neutral pH and in the presence of LiClO4. The new nanolayered Mn oxide is more active than other Mn oxides toward water oxidation. This result is very important for artificial photosynthetic systems that use Mn oxides as water-oxidizing catalysts.

Nanolayered manganese oxide/poly(4-vinylpyridine) as a biomimetic and very efficient water oxidizing catalyst: toward an artificial enzyme in artificial photosynthesis.

Nanolayered Mn oxide/poly(4-vinylpyridine) as a model for Mn cluster in photosystem II was synthesized and characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR) and UV-Visible spectroscopy (UV-Vis). The compound is a very efficient water oxidizing catalyst, and sizable oxygen evolution was detected at 50 mV overpotential at near neutral pH. The number is as low as the overpotential is used by nature in photosystem II of cyanobacteria, algae and green plants for similar reactions.