Investigating the impact of stochasticity on HIV infection dynamics in CD4 + T cells using a reaction-diffusion model.

The disease dynamics affect the human life. When one person is affected with a disease and if it is not treated well, it can weaken the immune system of the body. Human Immunodeficiency Virus (HIV) is a virus that attacks the immune system, of the body which is the defense line against diseases. If it is not treated well then HIV progresses to its advanced stages and it is known as Acquired Immunodeficiency Syndrome (AIDS). HIV is typically a disease that can transferred from one person to another in several ways such as through blood, breastfeeding, sharing needles or syringes, and many others. So, the need of the hour is to consider such important disease dynamics and that will help mankind to save them from such severe disease. For the said purpose the reaction-diffusion HIV CD4 + T cell model with drug therapy under the stochastic environment is considered. The underlying model is numerically investigated with two time-efficient schemes and the effects of various parameters used in the model are analyzed and explained in a real-life scenario. Additionally, the obtained results will help the decision-makers to avoid such diseases. The random version of the HIV model is numerically investigated under the influence of time noise in It o ^ sense. The proposed stochastic backward Euler (SBE) scheme and proposed stochastic Implicit finite difference (SIFD) scheme are developed for the computational study of the underlying model. The consistency of the schemes is proven in the mean square sense and the given system of equations is compatible with both schemes. The stability analysis proves that both schemes and schemes are unconditionally stable. The given system of equations has two equilibria, one is disease-free equilibrium (DFE) and the other is endemic equilibrium. The simulations are drawn for the different values of the parameters. The proposed SBE scheme showed the convergent behavior towards the equilibria for the given values of the parameters but also showed negative behavior that is not biological. The proposed SIFD scheme showed better results as compared with the stochastic SBE scheme. This scheme has convergent and positive behavior towards the equilibria points for the given values of the parameters. The effect of various parameters is also analyzed. Simulations are drawn to evaluate the efficacy of the schemes.

Theoretical insight into physical characteristics of lead-free perovskites Rb2TlSbX6 (X = Cl, Br, I) for optoelectronic devices.

CONTEXT: Novel optoelectronic and thermoelectric properties with broad compositional range, non-toxic nature and structural stability make halide-based double perovskites fascinating for flexible optoelectronic devices. In this work, the structural electronic, optical and transport properties of Rb2TlSbX6 (X = Cl, Br, I) were studied using density functional theory for optoelectronic devices. The elastic analysis demonstrates ductile nature, mechanical stability, anisotropic behaviour and feasibility for flexible optoelectronic devices. The band structure study using Tran-Blaha-modified Becke-Johnson (TB-mBJ) potential shows that all studied materials have direct bandgap. In addition, the bandgap of Rb2TlSbCl6 is more appropriate for optoelectronic devices. The small loss and maximum absorption in visible regions make these materials prime candidates for optoelectronic devices. The transport features indicate that all the studied double perovskites reflect p-type semiconducting behaviour as highlighted by positive Seebeck coefficient values. Furthermore, the high power factor values of Rb2TlSbX6 (X = Cl, Br, I) double perovskites make them suitable for thermoelectric device applications at high temperatures. Based on electronic optical and thermoelectric properties Rb2TlSbCl6 is the best candidate for flexible optoelectronic devices. METHODS: In this paper, structural optimization of Rb2TlSbX6 (X = Cl, Br, I) double perovskites was conducted utilizing the Wien2k software based on first principle calculations with Perdew-Burke-Ernzerhof's generalized-gradient approximation (PBE-sol approximation). The TB-mBJ potential was employed to compute the accurate band gap of studied materials. The thermoelectric properties are evaluated with BoltzTraP code, showing a predominance of P-type charge carriers in all studied perovskites. This methodological strategy verifies the material's remarkable stability and optical properties and offers a solid framework for examining its potential in optoelectronic devices.

Analysis of multi-wave solitary solutions of (2+1)-dimensional coupled system of Boiti-Leon-Pempinelli.

This work examines the (2+1)-dimensional Boiti-Leon-Pempinelli model, which finds its use in hydrodynamics. This model explains how water waves vary over time in hydrodynamics. We provide new explicit solutions to the generalized (2+1)-dimensional Boiti-Leon-Pempinelli equation by applying the Sardar sub-equation technique. This method is shown to be a reliable and practical tool for solving nonlinear wave equations. Furthermore, different types of solitary wave solutions are constructed: w-shaped, breather waved, chirped, dark, bright, kink, unique, periodic, and more. The results obtained with the variable coefficient Boiti-Leon-Pempinelli equation are stable and different from previous methods. As compared to their constant-coefficient counterparts, the variable-coefficient models are more general here. In the current work, the problem is solved using the Sardar Sub-problem Technique to produce distinct soliton solutions with parameters. Plotting these graphs of the solutions will help you better comprehend the model. The outcomes demonstrate how well the method works to solve nonlinear partial differential equations, which are common in mathematical physics.With the help of this method, we may examine a variety of solutions from significant physical perspectives.

Effects of isotropic stress on the band structure elastic, optical, thermal, and x-ray diffraction properties of TiSnO3.

BACKGROUND: Cubic perovskite titanium stannous oxide (TiSnO3) is a promising material for various applications due to its functional properties. However, understanding how these properties change under external stress is crucial for its development and optimization. METHOD: This study employed density functional theory calculations to investigate the structural, electronic, optical, thermal, and mechanical properties of TiSnO3 under varying degrees of external static isotropic stress (0-120 GPa). RESULTS: The study reveals a significant decrease in the bandgap of TiSnO3 with increasing stress due to lattice modifications and the formation of delocalized electrons. Partial density of states analysis indicates that Sn and O states play a key role in shaping the electronic band structure. TiSnO3 exhibits increased light absorption with stress, accompanied by a blue shift in absorption peaks, whereas, both polarizability and refractive index decrease with increasing stress. Mechanically, all elastic moduli (bulk, shear, and Young's) show an increase under stress, signifying a stiffening response of the material under stress. Similarly, the Pugh ratio suggests a transition from ductile to brittle behaviour at elevated stress levels. Phonon dispersion calculations indicate the instability of the cubic phase at 0 K. However, a phonon gap emerges at 30 GPa and widens with increasing stress. X-ray diffraction further supports these findings by demonstrating a shift in diffraction peaks towards higher angles with increasing stress, consistent with the applied stress. CONCLUSION: In conclusion, this computational study offers a thorough understanding of how external stress influences the properties of TiSnO3, providing valuable insights for potential applications in various fields.

Numerical study of diffusive fish farm system under time noise.

In the current study, the fish farm model perturbed with time white noise is numerically examined. This model contains fish and mussel populations with external food supplied. The main aim of this work is to develop time-efficient numerical schemes for such models that preserve the dynamical properties. The stochastic backward Euler (SBE) and stochastic Implicit finite difference (SIFD) schemes are designed for the computational results. In the mean square sense, both schemes are consistent with the underlying model and schemes are von Neumann stable. The underlying model has various equilibria points and all these points are successfully gained by the SIFD scheme. The SIFD scheme showed positive and convergent behavior for the given values of the parameter. As the underlying model is a population model and its solution can attain minimum value zero, so a solution that can attain value less than zero is not biologically possible. So, the numerical solution obtained by the stochastic backward Euler is negative and divergent solution and it is not a biological phenomenon that is useless in such dynamical systems. The graphical behaviors of the system show that external nutrient supply is the important factor that controls the dynamics of the given model. The three-dimensional results are drawn for the various choices of the parameters.

Investigation of ultra wide bandgap Flouro-perovskite materials RBeF3 (R[bond, double bond]K and Li) for smart window applications: A DFT study.

The human body is affected by ultraviolet radiation because it can penetrate and harm bodily cells. Although skin cancer and early aging are consequences of prolonged exposure to ultraviolet (UV) rays, sun rays signify immediate excessive exposure. In this context, some structural, optical, electrical, and mechanical properties of the beryllium-based cubic fluoro-perovskite RBeF3 (R[bond, double bond]K and Li) compounds are examined through the use of density functional theory (DFT) within generalized gradient approximation (GGA) using the Perdew-Burke-Ernzerhof (PBE) approximations (GGA-PBE). The compounds KBeF3 and LiBeF3 have space group 221-pm3m, and their lattice constants and volumes are (3.765, 3.566) Å and (53.380, 45.379) Å3, respectively, based on their structural properties. Computed results indicate that the compounds' bandgaps are 7.35 eV and 7.12 eV, respectively, with an indirect nature for KBeF3 and LiBeF3. The properties of the band structure indicate that both compounds are insulators. The bonding properties of these compounds, RBeF3, are a combination of covalent and ionic. Optical properties of the compounds are examined which reflect the light-matter interaction like reflectivity, conductivity, and absorption. These materials were likely very hard but brittle, based on a higher bulk modulus B from elastic features, the B/G ratio, Pugh's ratio, and Vickers hardness. The compound RBeF3, as determined by the findings, is used as a UV protection and reflection layer for car and room windows.

In Vitro and In Vivo Anti-Inflammatory Activity of a Combination of Extracts from Cinnamomum zeylanicum, Alpinia galanga, and Withania somnifera used in Unani Medicine.

Objectives: Continuous and excessive secretion of pro-inflammatory and anti-inflammatory chemicals and cytokines may further deteriorate inflammation. Anti-inflammatory drugs play an imperative role in inhibiting the evolution of inflammatory diseases. As per the Unani doctrine, a holistic treatment approach is used to treat illnesses. Therefore, drugs having different actions are used to achieve the synergic effect. Three drugs (Cinnamomum zeylanicum, Alpinia galanga, and Withania somnifera), which are frequently used in Unani medicine for joint disorders were selected to evaluate the anti-inflammatory activity of the extract derived from them. Methods: We used RAW 264.7 macrophage cells to see the expression of inflammatory markers IL-1ß, IL-6, and TNF-α. Cytotoxic activity was assessed with MTT assay and Nitric Oxide (NO) was evaluated using Griess reagent. Further, anti-inflammatory activity was evaluated in Wistar Albino rats using carrageenan-induced paw oedema and immunohistochemistry assays for Cyclooxygenase-2 (COX-2). All the data were analyzed using ANOVA and Dunnett t test for multiple comparisons. Results: This extract did not show any cytotoxic effect and the gene expression was significantly reduced for IL-1ß, IL-6, and TNF-α in a dose-dependent manner. Further, NO production was also significantly reduced in the test groups. Immunohistochemistry revealed that the test groups had less inflammation as compared to the control group. Conclusion: It may be inferred that the ethanolic extract of the three herbs has strong anti-inflammatory activity in the tested inflammatory models and the extract is safe as it did not show any cytotoxic effects in both in vitro and in vivo conditions.

Analytical study of reaction diffusion Lengyel-Epstein system by generalized Riccati equation mapping method.

In this study, the Lengyel-Epstein system is under investigation analytically. This is the reaction-diffusion system leading to the concentration of the inhibitor chlorite and the activator iodide, respectively. These concentrations of the inhibitor chlorite and the activator iodide are shown in the form of wave solutions. This is a reaction†"diffusion model which considered for the first time analytically to explore the different abundant families of solitary wave structures. These exact solitary wave solutions are obtained by applying the generalized Riccati equation mapping method. The single and combined wave solutions are observed in shock, complex solitary-shock, shock singular, and periodic-singular forms. The rational solutions also emerged during the derivation. In the Lengyel-Epstein system, solitary waves can propagate at various rates. The harmony of the system's diffusive and reactive effects frequently governs the speed of a single wave. Solitary waves can move at a variety of speeds depending on the factors and reaction kinetics. To show their physical behavior, the 3D and their corresponding contour plots are drawn for the different values of constants.

Speech Emotion Recognition Using Convolution Neural Networks and Multi-Head Convolutional Transformer.

Speech emotion recognition (SER) is a challenging task in human-computer interaction (HCI) systems. One of the key challenges in speech emotion recognition is to extract the emotional features effectively from a speech utterance. Despite the promising results of recent studies, they generally do not leverage advanced fusion algorithms for the generation of effective representations of emotional features in speech utterances. To address this problem, we describe the fusion of spatial and temporal feature representations of speech emotion by parallelizing convolutional neural networks (CNNs) and a Transformer encoder for SER. We stack two parallel CNNs for spatial feature representation in parallel to a Transformer encoder for temporal feature representation, thereby simultaneously expanding the filter depth and reducing the feature map with an expressive hierarchical feature representation at a lower computational cost. We use the RAVDESS dataset to recognize eight different speech emotions. We augment and intensify the variations in the dataset to minimize model overfitting. Additive White Gaussian Noise (AWGN) is used to augment the RAVDESS dataset. With the spatial and sequential feature representations of CNNs and the Transformer, the SER model achieves 82.31% accuracy for eight emotions on a hold-out dataset. In addition, the SER system is evaluated with the IEMOCAP dataset and achieves 79.42% recognition accuracy for five emotions. Experimental results on the RAVDESS and IEMOCAP datasets show the success of the presented SER system and demonstrate an absolute performance improvement over the state-of-the-art (SOTA) models.

Design, synthesis, and biological evaluation of morpholinopyrimidine derivatives as anti-inflammatory agents.

Here, we outline the synthesis of a few 2-methoxy-6-((4-(6-morpholinopyrimidin-4-yl)piperazin-1-yl)(phenyl)methyl)phenol derivatives and assess their anti-inflammatory activity in macrophage cells that have been stimulated by LPS. Among these newly synthesized morpholinopyrimidine derivatives, 2-methoxy-6-((4-methoxyphenyl)(4-(6-morpholinopyrimidin-4-yl)piperazin-1-yl)methyl)phenol (V4) and 2-((4-fluorophenyl)(4-(6-morpholinopyrimidin-4-yl)piperazin-1-yl)methyl)-6-methoxyphenol (V8) are two of the most active compounds which can inhibit the production of NO at non-cytotoxic concentrations. Our findings also showed that compounds V4 and V8 dramatically reduced iNOS and cyclooxygenase mRNA expression (COX-2) in LPS-stimulated RAW 264.7 macrophage cells; western blot analysis showed that the test compounds decreased the amount of iNOS and COX-2 protein expression, hence inhibiting the inflammatory response. We find through molecular docking studies that the chemicals had a strong affinity for the iNOS and COX-2 active sites and formed hydrophobic interactions with them. Therefore, use of these compounds could be suggested as a novel therapeutic strategy for inflammation-associated disorders.

Design of a Planar Sensor Based on Split-Ring Resonators for Non-Invasive Permittivity Measurement.

The permittivity of a material is an important parameter to characterize the degree of polarization of a material and identify components and impurities. This paper presents a non-invasive measurement technique to characterize materials in terms of their permittivity based on a modified metamaterial unit-cell sensor. The sensor consists of a complementary split-ring resonator (C-SRR), but its fringe electric field is contained with a conductive shield to intensify the normal component of the electric field. It is shown that by tightly electromagnetically coupling opposite sides of the unit-cell sensor to the input/output microstrip feedlines, two distinct resonant modes are excited. Perturbation of the fundamental mode is exploited here for determining the permittivity of materials. The sensitivity of the modified metamaterial unit-cell sensor is enhanced four-fold by using it to construct a tri-composite split-ring resonator (TC-SRR). The measured results confirm that the proposed technique provides an accurate and inexpensive solution to determine the permittivity of materials.

NSP4 and ORF9b of SARS-CoV-2 Induce Pro-Inflammatory Mitochondrial DNA Release in Inner Membrane-Derived Vesicles.

Circulating cell-free mitochondrial DNA (cf-mtDNA) has been found in the plasma of severely ill COVID-19 patients and is now known as a strong predictor of mortality. However, the underlying mechanism of mtDNA release is unexplored. Here, we show a novel mechanism of SARS-CoV-2-mediated pro-inflammatory/pro-apoptotic mtDNA release and a rational therapeutic stem cell-based approach to mitigate these effects. We systematically screened the effects of 29 SARS-CoV-2 proteins on mitochondrial damage and cell death and found that NSP4 and ORF9b caused extensive mitochondrial structural changes, outer membrane macropore formation, and the release of inner membrane vesicles loaded with mtDNA. The macropore-forming ability of NSP4 was mediated through its interaction with BCL2 antagonist/killer (BAK), whereas ORF9b was found to inhibit the anti-apoptotic member of the BCL2 family protein myeloid cell leukemia-1 (MCL1) and induce inner membrane vesicle formation containing mtDNA. Knockdown of BAK and/or overexpression of MCL1 significantly reversed SARS-CoV-2-mediated mitochondrial damage. Therapeutically, we engineered human mesenchymal stem cells (MSCs) with a simultaneous knockdown of BAK and overexpression of MCL1 (MSCshBAK+MCL1) and named these cells IMAT-MSCs (intercellular mitochondrial transfer-assisted therapeutic MSCs). Upon co-culture with SARS-CoV-2-infected or NSP4/ORF9b-transduced airway epithelial cells, IMAT-MSCs displayed functional intercellular mitochondrial transfer (IMT) via tunneling nanotubes (TNTs). The mitochondrial donation by IMAT-MSCs attenuated the pro-inflammatory and pro-apoptotic mtDNA release from co-cultured epithelial cells. Our findings thus provide a new mechanistic basis for SARS-CoV-2-induced cell death and a novel therapeutic approach to engineering MSCs for the treatment of COVID-19.

Long non-coding RNA (lncRNA): A potential therapeutic target in acute lung injury.

Acute Lung Injury (ALI) and its severe form Acute Respiratory Distress Syndrome (ARDS) are the major cause of ICU death worldwide. ALI/ARDS is characterized by severe hypoxemia and inflammation that leads to poor lung compliance. Despite many advances in understanding and management, ALI/ARDS is still causing significant morbidity and mortality. Long non-coding RNA (lncRNA) is a fast-growing topic in lung inflammation and injury. lncRNA is a class of non-coding RNA having a length of more than 200 nucleotides. It has been a center of research for understanding the pathophysiology of various diseases in the past few years. Multiple studies have shown that lncRNAs are abundant in acute lung injury/injuries in mouse models and cell lines. By targeting these long non-coding RNAs, many investigators have demonstrated the alleviation of ALI in various mouse models. Therefore, lncRNAs show great promise as a therapeutic target in ALI. This review provides the current state of knowledge about the relationship between lncRNAs in various biological processes in acute lung injury and its use as a potential therapeutic target.

Synthesis, purification and characterization of Plectonema derived AgNPs with elucidation of the role of protein in nanoparticle stabilization.

Driven by the need to biosynthesize alternate biomedical agents to prevent and treat infection, silver nanoparticles have surfaced as a promising avenue. Cyanobacteria-derived nanomaterial synthesis is of substantive interest as it offers an eco-friendly, cost-effective, sustainable, and biocompatible route for further development. In the present study optimal conditions for synthesis of silver nanoparticles (AgNPs) were 1 : 9 v/v [cell extract: AgNO3 (1 mM)], pH 7.4, and 30 °C reaction temperatures. Synthesis of nanoparticles was monitored by UV-vis spectrophotometry and the maximum absorbance was observed at a wavelength of 420 nm. SEM with EDX analysis confirmed 96.85% silver by weight which revealed the purity of AgNPs. TEM & XRD analysis exhibited a particle size of ∼12 nm with crystalline nature. FTIR analysis confirmed the presence of possible biomolecules involved in the synthesis and stabilization of AgNPs. Decapping of AgNPs followed by SDS-PAGE, LCMS and MALDI TOF analysis elucidates the proteinaceous nature of the capping and stabilizing agent. Cyanobacterial-derived capped AgNPs showed more cytotoxicicity towards a non-small cell lung cancer (A549) cell line, free radical scavenger and an antimicrobial than de-capped AgNPs. In addition they showed significant synergistic characteristics with antibiotics and fungicides. The test revealed that the capped AgNPs were biocompatible with good anti-inflammatory properties. The blend of antimicrobial and biocompatible properties, coupled with their intrinsic "green" and facile synthesis, made these biogenic nanoparticles particularly attractive for future applications in nanomedicine.

Identification and Validation of Pathogenic Genes in Sepsis and Associated Diseases by Integrated Bioinformatics Approach.

Sepsis is a clinical syndrome with high mortality and morbidity rates. In sepsis, the abrupt release of cytokines by the innate immune system may cause multiorgan failure, leading to septic shock and associated complications. In the presence of a number of systemic disorders, such as sepsis, infections, diabetes, and systemic lupus erythematosus (SLE), cardiorenal syndrome (CRS) type 5 is defined by concomitant cardiac and renal dysfunctions Thus, our study suggests that certain mRNAs and unexplored pathways may pave a way to unravel critical therapeutic targets in three debilitating and interrelated illnesses, namely, sepsis, SLE, and CRS. Sepsis, SLE, and CRS are closely interrelated complex diseases likely sharing an overlapping pathogenesis caused by erroneous gene network activities. We sought to identify the shared gene networks and the key genes for sepsis, SLE, and CRS by completing an integrative analysis. Initially, 868 DEGs were identified in 16 GSE datasets. Based on degree centrality, 27 hub genes were revealed. The gProfiler webtool was used to perform functional annotations and enriched molecular pathway analyses. Finally, core hub genes (EGR1, MMP9, and CD44) were validated using RT-PCR analysis. Our comprehensive multiplex network approach to hub gene discovery is effective, as evidenced by the findings. This work provides a novel research path for a new research direction in multi-omics biological data analysis.

Revealing new therapeutic opportunities in hypertension through network-driven integrative genetic analysis and drug target prediction approach.

Epidemiological studies have established that untreated hypertension (HTN) is a major independent risk factor for developing cardiovascular diseases (CVD), stroke, renal failure, and other conditions. Several important studies have been published to prevent and manage HTN; however, antihypertensive agents' optimal choice remains controversial. Therefore, the present study is undertaken to update our knowledge in the primary treatment of HTN, specifically in the setting of other three important diseases. MicroRNAs (miRNAs) are remarkably stable short endogenous conserved non-coding RNAs that bind to the mRNA at its (3' UTR) to regulate its gene expression by causing translational repression or mRNA degradation. Through their coordinated activities on different pathways and networks, individual miRNAs control normal and pathological cellular processes. Therefore, to identify the critical miRNA-mRNA-TF interactions, we performed systematic bioinformatics analysis. We have also employed the molecular modelling and docking approach to identify the therapeutic target that delivers novel empathies into Food and Drug Administration approved and herbal drug response physiology. Gene Expression Omnibus (GEO) was employed to identify the differentially expressed genes (DEGs) and hub genes- KNG1, HLA-DPB1, CXCL8, IL1B, and BCL2. The HTN associated feed-forward loop (FFL) network included miR-9-5p, KNG1 and AR. We employed high throughput screening to get the best interacting compounds, telmisartan and limonin, that provided a significant docking score (-13.3 and -12.0 kcal/mol) and a potential protective effect that may help to combat the impact of HTN. The present study provides novel insight into HTN etiology through the identification of mRNAs and miRNAs and associated pathways.

The role of mitophagy in pulmonary sepsis.

Sepsis is a systemic inflammatory disease with an unacceptably high mortality rate caused by an infection or trauma that involves both innate and adaptive immune systems. Inflammatory events activate different downstream pathways leading to tissue damage and ultimately multi-organ failure. Mitochondria are responsible for cellular energy, thermoregulation, metabolite biosynthesis, intracellular calcium regulation, and cell death. Damaged mitochondria induce the high Ca2+ influx through mitochondrial calcium uniporter (MCU). It also generates excessive Reactive oxygen species (ROS) and releases mtDNA into the cytoplasm, which causes induction of NLRP3 inflammasome and apoptosis. Mitophagy (Autophagy of damaged mitochondria) controls mitochondrial dynamics and function. It also maintains cellular homeostasis. This review is about how pulmonary sepsis affects the body. What is the aftermath of sepsis, and how mitophagy affects Acute Lung Injury and macrophage polarisation to overcome the damages.

COVID-19: The Emerging Immunopathological Determinants for Recovery or Death.

Hyperactivation of the host immune system during infection by SARS-CoV-2 is the leading cause of death in COVID-19 patients. It is also evident that patients who develop mild/moderate symptoms and successfully recover display functional and well-regulated immune response. Whereas a delayed initial interferon response is associated with severe disease outcome and can be the tipping point towards immunopathological deterioration, often preceding death in COVID-19 patients. Further, adaptive immune response during COVID-19 is heterogeneous and poorly understood. At the same time, some studies suggest activated T and B cell response in severe and critically ill patients and the presence of SARS-CoV2-specific antibodies. Thus, understanding this problem and the underlying molecular pathways implicated in host immune function/dysfunction is imperative to devise effective therapeutic interventions. In this comprehensive review, we discuss the emerging immunopathological determinants and the mechanism of virus evasion by the host cell immune system. Using the knowledge gained from previous respiratory viruses and the emerging clinical and molecular findings on SARS-CoV-2, we have tried to provide a holistic understanding of the host innate and adaptive immune response that may determine disease outcome. Considering the critical role of the adaptive immune system during the viral clearance, we have presented the molecular insights of the plausible mechanisms involved in impaired T cell function/dysfunction during various stages of COVID-19.

Unravelling host-pathogen interactions: ceRNA network in SARS-CoV-2 infection (COVID-19).

COVID-19 is a lurking calamitous disease caused by an unusual virus, SARS-CoV-2, causing massive deaths worldwide. Nonetheless, explicit therapeutic drugs or clinically approved vaccines are not available for COVID-19. Thus, a comprehensive research is crucially needed to decode the pathogenic tools, plausible drug targets, committed to the development of efficient therapy. Host-pathogen interactions via host cellular components is an emerging field of research in this respect. miRNAs have been established as vital players in host-virus interactions. Moreover, viruses have the capability to manoeuvre the host miRNA networks according to their own obligations. Besides protein coding mRNAs, noncoding RNAs might also be targeted in infected cells and viruses can exploit the host miRNA network via ceRNA effect. We have predicted a ceRNA network involving one miRNA (miR-124-3p), one mRNA (Ddx58), one lncRNA (Gm26917) and two circRNAs (Ppp1r10, C330019G07RiK) in SARS-CoV infected cells. We have identified 4 DEGs-Isg15, Ddx58, Oasl1, Usp18 by analyzing a mRNA GEO dataset. There is no notable induction of IFNs and IFN-induced ACE2, significant receptor responsible for S-protein binding mediated viral entry. Pathway enrichment and GO analysis conceded the enrichment of pathways associated with interferon signalling and antiviral-mechanism by IFN-stimulated genes. Further, we have identified 3 noncoding RNAs, playing as potential ceRNAs to the genes associated with immune mechanisms. This integrative analysis has identified noncoding RNAs and their plausible targets, which could effectively enhance the understanding of molecular mechanisms associated with viral infection. However, validation of these targets is further corroborated to determine their therapeutic efficacy.

Identification of differentially expressed genes in small and non-small cell lung cancer based on meta-analysis of mRNA.

Lung cancer has the lowest survival rate spread globally resulting in a large number of deaths. This is attributed to insufficient measures such as lack of early detection and chemoresistance in the patients. It can be subdivided into two histological groups: Non-Small-Cell Lung Cancer (NSCLC), which is most prevalent (85% of all lung cancers) but less destructive; and Small-Cell Lung Cancer (SCLC), which is intermittently metastatic and less prevalent (15% of all lung cancers). The present study deals with the analysis of gene expression of two subtypes to identify the Differentially Expressed Genes (DEGs). For this study, we selected two datasets from the Omnibus database, which included 50 non-small cell lung cancer samples, 31 small cell lung cancer samples, and 48 samples from normal lung tissue. After DEGs identification using the meta-analysis approach, they were then subjected to further analysis following p-value adjustment via the Benjamini-Hochberg method. We identified 440 overexpressed and 489 underexpressed genes in NSCLC, and 489 overexpressed and 525 underexpressed genes in SCLC, compared with normal lung tissues. Furthermore, we identified 3 overlapping genes between upregulated DEGs in NSCLC and downregulated DEGs in SCLC; and 8 overlapping genes between upregulated DEGs in SCLC and downregulated DEGs in NSCLC. Accordingly, a Protein-Protein Interaction (PPI) network of the overlapping genes was generated, which contained a total of 261 genes, of which the top five were TRIM29, ANK3, CSTA, FGG, and AGR2. These five candidate genes reported herein may prove to be potential therapeutic targets.