Canonical effects of cytokines on glomerulonephritis: A new outlook in nephrology.

Glomerulonephritis (GN) is an important cause of renal inflammation resulting from kidney-targeted adaptive and innate immune responses and consequent glomerular damage. Given the lack of autoantibodies, immune complexes, or the infiltrating immune cells in some forms of GN, for example, focal segmental glomerulosclerosis and minimal change disease, along with paraneoplastic syndrome and a special form of renal involvement in some viral infections, the likeliest causative scenario would be secreted factors, mainly cytokine(s). Since cytokines can modulate the inflammatory mechanisms, severity, and clinical outcomes of GN, it is rational to consider the umbrella term of cytokine GN as a new outlook to reclassify a group of previously known GN. We focus here, particularly, on cytokines that have the central "canonical effect" in the development of GN.

Biofactors regulating mitochondrial function and dynamics in podocytes and podocytopathies.

Podocytes are terminally differentiated kidney cells acting as the main gatekeepers of the glomerular filtration barrier; hence, inhibiting proteinuria. Podocytopathies are classified as kidney diseases caused by podocyte damage. Different genetic and environmental risk factors can cause podocyte damage and death. Recent evidence shows that mitochondrial dysfunction also contributes to podocyte damage. Understanding alterations in mitochondrial metabolism and function in podocytopathies and whether altered mitochondrial homeostasis/dynamics is a cause or effect of podocyte damage are issues that need in-depth studies. This review highlights the roles of mitochondria and their bioenergetics in podocytes. Then, factors/signalings that regulate mitochondria in podocytes are discussed. After that, the role of mitochondrial dysfunction is reviewed in podocyte injury and the development of different podocytopathies. Finally, the mitochondrial therapeutic targets are considered.

Ischemic tubular injury: Oxygen-sensitive signals and metabolic reprogramming.

The kidneys are the most vulnerable organs to severe ischemic insult that results in cellular hypoxia under pathophysiological conditions. Large amounts of oxygen are consumed by the kidneys, mainly to produce energy for tubular reabsorption. Beyond high oxygen demand and the low oxygen supply, different other factors make kidneys vulnerable to ischemia which is deemed to be a major cause of acute kidney injury (AKI). On the other hand, kidneys are capable of sensing and responding to oxygen alternations to evade harms resulting from inadequate oxygen. The hypoxia-inducible factor (HIF) is the main conserved oxygen-sensing mechanism that maintains homeostasis under hypoxia through direct/indirect regulation of several genes that contribute to metabolic adaptation, angiogenesis, energy conservation, erythropoiesis, and so on. In response to oxygen availability, prolyl-hydroxylases (PHDs) control the HIF stability. This review focuses on the oxygen-sensing mechanisms in kidneys, particularly in proximal tubular cells (PTCs) and discusses the molecules involved in ischemic response and metabolic reprogramming. Moreover, the possible roles of non-coding RNAs (microRNAs and long non-coding RNAs) in the development of ischemic AKI are put forward.

Decoding the Possible Molecular Mechanisms in Pediatric Wilms Tumor and Rhabdoid Tumor of the Kidney through Machine Learning Approaches.

Objective: Wilms tumor (WT) and Rhabdoid tumor (RT) are pediatric renal tumors and their differentiation is based on histopathological and molecular analysis. The present study aimed to introduce the panels of mRNAs and microRNAs involved in the pathogenesis of these cancers using deep learning algorithms. Methods: Filter, graph, and association rule mining algorithms were applied to the mRNAs/microRNAs data. Results: Candidate miRNAs and mRNAs with high accuracy (AUC: 97%/93% and 94%/97%, respectively) could differentiate the WT and RT classes in training and test data. Let-7a-2 and C19orf24 were identified in the WT, while miR-199b and RP1-3E10.2 were detected in the RT by analysis of Association Rule Mining. Conclusion: The application of the machine learning methods could identify mRNA/miRNA patterns to discriminate WT from RT. The identified miRNAs/mRNAs panels could offer novel insights into the underlying molecular mechanisms that are responsible for the initiation and development of these cancers. They may provide further insight into the pathogenesis, prognosis, diagnosis, and molecular-targeted therapy in pediatric renal tumors.

COVID-19 infection: an overview on cytokine storm and related interventions.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has posed a significant threat to global health. This virus affects the respiratory tract and usually leads to pneumonia in most patients and acute respiratory distress syndrome (ARDS) in 15% of cases. ARDS is one of the leading causes of death in patients with COVID-19 and is mainly triggered by elevated levels of pro-inflammatory cytokines, referred to as cytokine storm. Interleukins, such as interleukin-6 (1L-6), interleukin-1 (IL-1), interleukin-17 (IL-17), and tumor necrosis factor-alpha (TNF-α) play a very significant role in lung damage in ARDS patients through the impairments of the respiratory epithelium. Cytokine storm is defined as acute overproduction and uncontrolled release of pro-inflammatory markers, both locally and systemically. The eradication of COVID-19 is currently practically impossible, and there is no specific treatment for critically ill patients with COVID-19; however, suppressing the inflammatory response may be a possible strategy. In light of this, we review the efficacy of specific inhibitors of IL6, IL1, IL-17, and TNF-α for treating COVID-19-related infections to manage COVID-19 and improve the survival rate for patients suffering from severe conditions.

Migrasomes and exosomes; different types of messaging vesicles in podocytes.

Podocytes, highly specified kidney epithelial cells, live under several pathological stimuli and stresses during which they adapt themselves to keep homeostasis. Nevertheless, under extreme stress, a complex scenario of podocyte damage and its consequences occur. Podocyte damage causes foot process effacement and their detachment from the glomerular basement membrane, leading to proteinuria. Podocyte-derived extracellular vesicles (pEVs), mainly microparticles and exosomes are considered as signaling mediators of intercellular communication. Recently, it has been shown that throughout the injury-related migration procedure, podocytes are capable of releasing the injury-related migrasomes. Evidence indicates that at the early stages of glomerular disorders, increased levels of pEVs are observed in urine. At the early stage of nephropathy, pEVs especially migrasomes seem to be more sensitive and reliable indicators of podocyte stress and/or damage than proteinuria. This review highlights the current knowledge of pEVs and their values for the diagnosis of different kidney diseases.

Covid-19 and kidney injury: Pathophysiology and molecular mechanisms.

The novel coronavirus (SARS-CoV-2) has turned into a life-threatening pandemic disease (Covid-19). About 5% of patients with Covid-19 have severe symptoms including septic shock, acute respiratory distress syndrome, and the failure of several organs, while most of them have mild symptoms. Frequently, the kidneys are involved through direct or indirect mechanisms. Kidney involvement mainly manifests itself as proteinuria and acute kidney injury (AKI). The SARS-CoV-2-induced kidney damage is expected to be multifactorial; directly it can infect the kidney podocytes and proximal tubular cells and based on an angiotensin-converting enzyme 2 (ACE2) pathway it can lead to acute tubular necrosis, protein leakage in Bowman's capsule, collapsing glomerulopathy and mitochondrial impairment. The SARS-CoV-2-driven dysregulation of the immune responses including cytokine storm, macrophage activation syndrome, and lymphopenia can be other causes of the AKI. Organ interactions, endothelial dysfunction, hypercoagulability, rhabdomyolysis, and sepsis are other potential mechanisms of AKI. Moreover, lower oxygen delivery to kidney may cause an ischaemic injury. Understanding the fundamental molecular pathways and pathophysiology of kidney injury and AKI in Covid-19 is necessary to develop management strategies and design effective therapies.

Molecular pathophysiology of acute kidney injury: The role of sirtuins and their interactions with other macromolecular players.

Acute kidney injury (AKI), a rapid drop in kidney function, displays high mortality and morbidity, and its repeated or severe status can shift into chronic kidney disease or even end-stage renal disease. How and which events cause AKI still is controversial. In addition, no specific therapies have emerged that can attenuate AKI or expedite recovery. Some central mechanisms including tubular epithelial cells injury, endothelial injury, renal cell apoptosis, and necrosis signaling cascades, and inflammation have been reported in the pathophysiology of AKI. However, the timing of the activation of each pathway, their interactions, and the hierarchy of these pathways remain unknown. The main molecular mechanisms that might be complicated in this process are the mitochondrial impairment and alteration/shifting of cellular metabolites (e.g., acetyl-CoA and NAD+ /NADH) acting as cofactors to alter the activities of many enzymes, for instance, sirtuins. Moreover, alteration of mitochondrial structure over the fusion and fission mechanisms can regulate cellular signaling pathways by modifying the rate of reactive oxygen species generation and metabolic activities. The aim of this review is to better understand the underlying pathophysiological and molecular mechanisms of AKI. In addition, we predicted the main other molecular players in interaction with sirtuins as energy/stresses monitoring proteins for the development of future approaches in the treatment or prevention of ischemic AKI.

Medicinal signaling cells: A potential antimicrobial drug store.

Medicinal signaling cells (MSCs) are multipotent cells derived from mammalian bone marrow and periosteum that can be extended in culture. They can keep their ability in vitro to form a variety of mesodermal phenotypes and tissues. Over recent years, there has been great attention over MSCs since they can impact the organ transplantation as well as autoimmune and bacterial diseases. MSCs can secrete different bioactive factors such as growth factors, antimicrobial peptides/proteins and cytokines that can suppress the immune system and prevent infection via direct and indirect mechanisms. Moreover, MSCs are able to increase bacterial clearance in sepsis models by producing antimicrobial peptides such as defensins, cathelicidins, lipocalin and hepcidin. It is the aim of the present review to focus on the antibacterial effector functions of MSCs and their mechanisms of action against the pathogenic microbes.

Pre-Eclampsia: Microbiota possibly playing a role.

Pre-eclampsia (PE) is a complication of pregnancy that is associated with mortality and morbidity in mothers and fetuses worldwide. Oxygen dysregulation in the placenta, abnormal remodeling of the spiral artery, defective placentation, oxidative stress at the fetal-maternal border, inflammation and angiogenic impairment in the maternal circulation are the main causes of this syndrome. These events result in a systemic and diffuse endothelial cell dysfunction, an essential pathophysiological feature of PE. The impact of bacteria on the multifactorial pathway of PE is the recent focus of scientific inquiry since microbes may cause each of the aforementioned features. Microbes and their derivatives by producing antigens and other inflammatory factors may trigger infection and inflammatory responses. A mother's bacterial communities in the oral cavity, gut, vagina, cervix and uterine along with the placenta and amniotic fluid microbiota may be involved in the development of PE. Here, we review the mechanistic and pathogenic role of bacteria in the development of PE. Then, we highlight the impact of alterations in a set of maternal microbiota (dysbiosis) on the pathogenesis of PE.

Anti-microbial activity of curcumin nanoformulations: New trends and future perspectives.

Curcumin has been used in numerous anti-microbial research because of its low side effects and extensive traditional applications. Despite having a wide range of effects, the intrinsic physicochemical characteristics such as low bioavailability, poor water solubility, photodegradation, chemical instability, short half-life and fast metabolism of curcumin derivatives limit their pharmaceutical importance. To overcome these drawbacks and improve the therapeutic ability of curcuminoids, novel approaches have been attempted recently. Nanoparticulate drug delivery systems can increase the efficiency of curcumin in several diseases, especially infectious diseases. These innovative strategies include polymeric nanoparticles, hydrogels, nanoemulsion, nanocomposite, nanofibers, liposome, nanostructured lipid carriers (NLCs), polymeric micelles, quantum dots, polymeric blend films and nanomaterial-based combination of curcumin with other anti-bacterial agents. Integration of curcumin in these delivery systems has displayed to improve their solubility, bioavailability, transmembrane permeability, prolong plasma half-life, long-term stability, target-specific delivery and upgraded the therapeutic effects. In this review paper, a range of in vitro and in vivo studies have been critically discussed to explore the therapeutic viability and pharmaceutical significance of the nano-formulated delivery systems to elevate the anti-bacterial activities of curcumin and its derivatives.

Stem Cell Therapy: Curcumin Does the Trick.

Curcumin is a dietary polyphenol and a bioactive phytochemical agent that possesses anti-inflammatory, antioxidant, anticancer, and chemopreventive properties. Some of the predominant activities of stem cells include regeneration of identical cells and the ability to maintain the proliferation and multipotentiality. However, these cells could be stimulated to differentiate into specific cell types. Curcumin protects some stem cells from toxicity and can stimulate proliferation and differentiation of stem cells. In the present review, we summarize the antioxidant, stemness activity, antiaging, and neuroprotective as well as wound healing and regenerative effects of curcumin.

An update on Glycerophosphodiester Phosphodiesterases; From Bacteria to Human.

The hydrolysis of deacylated glycerophospholipids into sn-glycerol 3-phosphate and alcohol is facilitated by evolutionarily conserved proteins known as glycerophosphodiester phosphodiesterases (GDPDs). These proteins are crucial for the pathogenicity of bacteria and for bioremediation processes aimed at degrading organophosphorus esters that pose a hazard to both humans and the environment. Additionally, GDPDs are enzymes that respond to multiple nutrients and could potentially serve as candidate genes for addressing deficiencies in zinc, iron, potassium, and especially phosphate in important plants like rice. In mammals, glycerophosphodiesterases (GDEs) play a role in regulating osmolytes, facilitating the biosynthesis of anandamine, contributing to the development of skeletal muscle, promoting the differentiation of neurons and osteoblasts, and influencing pathological states. Due to their capacity to enhance a plant's ability to tolerate various nutrient deficiencies and their potential as pharmaceutical targets in humans, GDPDs have received increased attention in recent times. This review provides an overview of the functions of GDPD families as vital and resilient enzymes that regulate various pathways in bacteria, plants, and humans.

Exploring and exploiting the rice phytobiome to tackle climate change challenges.

The future of agriculture is uncertain under the current climate change scenario. Climate change directly and indirectly affects the biotic and abiotic elements that control agroecosystems, jeopardizing the safety of the world's food supply. A new area that focuses on characterizing the phytobiome is emerging. The phytobiome comprises plants and their immediate surroundings, involving numerous interdependent microscopic and macroscopic organisms that affect the health and productivity of plants. Phytobiome studies primarily focus on the microbial communities associated with plants, which are referred to as the plant microbiome. The development of high-throughput sequencing technologies over the past 10 years has dramatically advanced our understanding of the structure, functionality, and dynamics of the phytobiome; however, comprehensive methods for using this knowledge are lacking, particularly for major crops such as rice. Considering the impact of rice production on world food security, gaining fresh perspectives on the interdependent and interrelated components of the rice phytobiome could enhance rice production and crop health, sustain rice ecosystem function, and combat the effects of climate change. Our review re-conceptualizes the complex dynamics of the microscopic and macroscopic components in the rice phytobiome as influenced by human interventions and changing environmental conditions driven by climate change. We also discuss interdisciplinary and systematic approaches to decipher and reprogram the sophisticated interactions in the rice phytobiome using novel strategies and cutting-edge technology. Merging the gigantic datasets and complex information on the rice phytobiome and their application in the context of regenerative agriculture could lead to sustainable rice farming practices that are resilient to the impacts of climate change.

A diagnostic miRNA panel to detect recurrence of ovarian cancer through artificial intelligence approaches.

BACKGROUND: Ovarian Cancer (OC) is the deadliest gynecology malignancy, whose high recurrence rate in OC patients is a challenging object. Therefore, having deep insights into the genetic and molecular mechanisms of OC recurrence can improve the target therapeutic procedures. This study aimed to discover crucial miRNAs for the detection of tumor recurrence in OC by artificial intelligence approaches. METHOD: Through the ANOVA feature selection method, we selected 100 candidate miRNAs among 588 miRNAs. For their classification, a deep-learning model was employed to validate the significance of the candidate miRNAs. The accuracy, F1-score (high-risk), and AUC-ROC of classification test data based on the 100 miRNAs were 73%, 0.81, and 0.65, respectively. Association rule mining was used to discover hidden relations among the selected miRNAs. RESULT: Five miRNAs, including miR-1914, miR-203, miR-135a-2, miR-149, and miR-9-1, were identified as the most frequent items among high-risk association rules. The identified miRNAs may target genes/proteins involved in epithelial-mesenchymal transition (EMT), resistance to therapy, and cancer stem cells; being responsible for the heterogeneity and plasticity of the tumor. Our conclusion presents mir-1914 as the significant candidate miRNA and the most frequent item. Current knowledge indicates that the dysregulated miR-1914 may function as a tumor suppressor or oncogene in the development of cancer. CONCLUSION: These candidate miRNAs can be considered a powerful tool in the diagnosis of OC recurrence. We hypothesize that mir-1914 might open a new line of research in the realm of managing the recurrence of OC and could be a significant factor in triggering OC recurrence.

Uncovering key molecular mechanisms in the early and late-stage of papillary thyroid carcinoma using association rule mining algorithm.

OBJECTIVE: Thyroid Cancer (TC) is the most frequent endocrine malignancy neoplasm. It is the sixth cause of cancer in women worldwide. The treatment process could be expedited by identifying the controlling molecular mechanisms at the early and late stages, which can contribute to the acceleration of treatment schemes and the improvement of patient survival outcomes. In this work, we study the significant mRNAs through Machine Learning Algorithms in both the early and late stages of Papillary Thyroid Cancer (PTC). METHOD: During the course of our study, we investigated various methods and techniques to obtain suitable results. The sequence of procedures we followed included organizing data, using nested cross-validation, data cleaning, and normalization at the initial stage. Next, to apply feature selection, a t-test and binary Non-Dominated Sorting Genetic Algorithm II (NSGAII) were chosen to be employed. Later on, during the analysis stage, the discriminative power of the selected features was evaluated using machine learning and deep learning algorithms. Finally, we considered the selected features and utilized Association Rule Mining algorithm to identify the most important ones for improving the decoding of dominant molecular mechanisms in PTC through its early and late stages. RESULT: The SVM classifier was able to distinguish between early and late-stage categories with an accuracy of 83.5% and an AUC of 0.78 based on the identified mRNAs. The most significant genes associated with the early and late stages of PTC were identified as (e.g., ZNF518B, DTD2, CCAR1) and (e.g., lnc-DNAJB6-7:7, RP11-484D2.3, MSL3P1), respectively. CONCLUSION: Current study reveals a clear picture of the potential candidate genes that could play a major role not only in the early stage, but also throughout the late one. Hence, the findings could be of help to identify therapeutic targets for more effective PTC drug developments.

Key therapeutic targets implicated at the early stage of hepatocellular carcinoma identified through machine-learning approaches.

Hepatocellular carcinoma (HCC) is the most frequent type of primary liver cancer. Early-stage detection plays an essential role in making treatment decisions and identifying dominant molecular mechanisms. We utilized machine learning algorithms to find significant mRNAs and microRNAs (miRNAs) at the early and late stages of HCC. First, pre-processing approaches, including organization, nested cross-validation, cleaning, and normalization were applied. Next, the t-test/ANOVA methods and binary particle swarm optimization were used as a filter and wrapper method in the feature selection step, respectively. Then, classifiers, based on machine learning and deep learning algorithms were utilized to evaluate the discrimination power of selected features (mRNAs and miRNAs) in the classification step. Finally, the association rule mining algorithm was applied to selected features for identifying key mRNAs and miRNAs that can help decode dominant molecular mechanisms in HCC stages. The applied methods could identify key genes associated with the early (e.g., Vitronectin, thrombin-activatable fibrinolysis inhibitor, lactate dehydrogenase D (LDHD), miR-590) and late-stage (e.g., SPRY domain containing 4, regucalcin, miR-3199-1, miR-194-2, miR-4999) of HCC. This research could establish a clear picture of putative candidate genes, which could be the main actors at the early and late stages of HCC.

Unraveling the link between PTBP1 and severe asthma through machine learning and association rule mining method.

Severe asthma is a chronic inflammatory airway disease with great therapeutic challenges. Understanding the genetic and molecular mechanisms of severe asthma may help identify therapeutic strategies for this complex condition. RNA expression data were analyzed using a combination of artificial intelligence methods to identify novel genes related to severe asthma. Through the ANOVA feature selection approach, 100 candidate genes were selected among 54,715 mRNAs in blood samples of patients with severe asthmatic and healthy groups. A deep learning model was used to validate the significance of the candidate genes. The accuracy, F1-score, AUC-ROC, and precision of the 100 genes were 83%, 0.86, 0.89, and 0.9, respectively. To discover hidden associations among selected genes, association rule mining was applied. The top 20 genes including the PTBP1, RAB11FIP3, APH1A, and MYD88 were recognized as the most frequent items among severe asthma association rules. The PTBP1 was found to be the most frequent gene associated with severe asthma among those 20 genes. PTBP1 was the gene most frequently associated with severe asthma among candidate genes. Identification of master genes involved in the initiation and development of asthma can offer novel targets for its diagnosis, prognosis, and targeted-signaling therapy.

Circular RNAs as novel biomarkers in glomerular diseases.

Circular RNAs (circRNAs) regulate gene expression and biological procedures by controlling target genes or downstream pathways by sponging their related miRNA (s). Three types of circRNAs have been identified; exonic circRNAs (ecircRNAs), intronic RNAs (ciRNAs), and exon-intron circRNAs (ElciRNAs). It is clarified that altered levels of circRNAs have dynamic pathological and physiological functions in kidney diseases. Evidence suggests that circRNAs can be considered novel diagnostic biomarkers and therapeutic targets for renal diseases. Glomerulonephritis (GN) is a general term used to refer to a wide range of glomerular diseases. GN is an important cause of chronic kidney diseases. Here, we review the biogenesis of circRNAs, and their molecular and physiological functions in the kidney. Moreover, the dysregulated expression of circRNAs and their biological functions are discussed in primary and secondary glomerulonephritis. Moreover, diagnostic and therapeutic values of circRNAs in distinguishing or treating different types of GN are highlighted.

Eplerenone reduces renal ischaemia/reperfusion injury by modulating Klotho, NF-κB and SIRT1/SIRT3/PGC-1α signalling pathways.

OBJECTIVES: Acute kidney injury (AKI) is a sudden impairment in kidney function that is associated with high morbidity and mortality. Inflammation, oxidative stress, mitochondrial impairment and energy depletion, along with organ dysfunction are hallmarks of AKI. This study aimed to evaluate the effects of Eplerenone, an aldosterone receptor antagonist, on the kidney injury caused by ischaemia/reperfusion (I/R). METHODS: Male Wistar rats (n = 24) were randomly allocated into four groups: sham, IR, Eplerenone and Eplerenone+IR. Rats in the two last groups 1 h before I/R induction, were treated with Eplerenone (100 mg/kg) via intraperitoneal injection. Protein levels of Klotho, heat shock protein 70 (HSP70), sirtuin1 (SIRT1), SIRT3 and peroxisome proliferator-activated receptor-gamma coactivator 1-α (PGC-1α) along with antioxidant, apoptotic (caspase 3, Bax and Bcl2) and inflammatory [nuclear factor kappa-B (NF-κB) p65, Interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α) and cyclooxygenase-2 (COX-2)] factors were evaluated in the kidney tissues of the experimental groups. KEY FINDINGS: Eplerenone pre-treatment significantly could improve IR-induced pathological changes and kidney function and increase the renal antioxidant factors compared to the IR group (P < 0.05). Furthermore, in the Eplerenone + IR group, significant elevation of the Klotho, SIRT1, SIRT3 and PGC-1α at the protein level was identified compared to the IR group. Eplerenone pretreatment could not only downregulate NF-κB signalling and its downstream inflammatory factors (IL-6, COX-2 and TNF-α) but also could decrease apoptotic factors (P ≤ 0.01). CONCLUSIONS: The results recommended that Eplerenone exerts a protective effect against kidney IR injury by up-regulating Klotho, HSP70, sirtuins and PGC-1α to preserve mitochondrial function and cell survival. Moreover, it hinders renal inflammation by suppressing NF-κB signalling. These results offer insight into the prevention or treatment of AKI in the future.