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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Panels of mRNAs and miRNAs for decoding molecular mechanisms of Renal Cell Carcinoma (RCC) subtypes utilizing Artificial Intelligence approaches.

Renal Cell Carcinoma (RCC) encompasses three histological subtypes, including clear cell RCC (KIRC), papillary RCC (KIRP), and chromophobe RCC (KICH) each of which has different clinical courses, genetic/epigenetic drivers, and therapeutic responses. This study aimed to identify the significant mRNAs and microRNA panels involved in the pathogenesis of RCC subtypes. The mRNA and microRNA transcripts profile were obtained from The Cancer Genome Atlas (TCGA), which were included 611 ccRCC patients, 321 pRCC patients, and 89 chRCC patients for mRNA data and 616 patients in the ccRCC subtype, 326 patients in the pRCC subtype, and 91 patients in the chRCC for miRNA data, respectively. To identify mRNAs and miRNAs, feature selection based on filter and graph algorithms was applied. Then, a deep model was used to classify the subtypes of the RCC. Finally, an association rule mining algorithm was used to disclose features with significant roles to trigger molecular mechanisms to cause RCC subtypes. Panels of 77 mRNAs and 73 miRNAs could discriminate the KIRC, KIRP, and KICH subtypes from each other with 92% (F1-score ≥ 0.9, AUC ≥ 0.89) and 95% accuracy (F1-score ≥ 0.93, AUC ≥ 0.95), respectively. The Association Rule Mining analysis could identify miR-28 (repeat count = 2642) and CSN7A (repeat count = 5794) along with the miR-125a (repeat count = 2591) and NMD3 (repeat count = 2306) with the highest repeat counts, in the KIRC and KIRP rules, respectively. This study found new panels of mRNAs and miRNAs to distinguish among RCC subtypes, which were able to provide new insights into the underlying responsible mechanisms for the initiation and progression of KIRC and KIRP. The proposed mRNA and miRNA panels have a high potential to be as biomarkers of RCC subtypes and should be examined in future clinical studies.

Curcumin-Loaded Silica Nanoparticles: Applications in Infectious Disease and Food Industry.

Curcumin has multiple properties that are used to cure different diseases such as cancer, infections, inflammatory, arthritic disease, etc. Despite having many effects, the inherent physicochemical properties-such as poor water solubility, chemical instability, low bioavailability, photodegradation, fast metabolism, and short half-life-of curcumin's derivatives have limited its medical importance. Recently, unprecedented advances in biomedical nanotechnology have led to the development of nanomaterial-based drug delivery systems in the treatment of diseases and diagnostic goals that simultaneously enhance therapeutic outcomes and avoid side effects. Mesoporous silica nanoparticles (MSNs) are promising drug delivery systems for more effective and safer treatment of several diseases, such as infections, cancers, and osteoporosis. Achieving a high drug loading in MSNs is critical to the success of this type of treatment. Their notable inherent properties-such as adjustable size and porosity, high pore volume, large surface area, functionality of versatile surfaces, as well as biocompatibility-have prompted extraordinary research on MSNs as multi-purpose delivery platforms. In this review, we focused on curcumin-loaded silica nanoparticles and their effects on the diagnosis and treatment of infections as well as their use in food packaging.

Microbiota and glomerulonephritis: An immunological point of view.

Glomerular injury is the major cause of chronic kidney diseases (CKD) worldwide and is characterized by proteinuria. Glomerulonephritis (GN) has a wide spectrum of etiologies, the intensity of glomerular damage, histopathology, and clinical outcomes that can be associated with the landscape of the nephritogenic immune response. Beyond impaired immune responses and genetic factors, recent evidence indicates that microbiota can be contributed to the pathogenesis of GN and patients' outcomes by impacting many aspects of the innate and adaptive immune systems. It is still unknown whether dysbiosis induces GN or it is a secondary effect of the disease. Several factors such as drugs and nutritional problems can lead to dysbiosis in GN patients. It has been postulated that gut dysbiosis activates immune responses, promotes a state of systemic inflammation, and produces uremic toxins contributing to kidney tissue inflammation, apoptosis, and subsequent proteinuric nephropathy. In this review, the impact of gastrointestinal tract (GI) microbiota on the pathogenesis of the primary GN will be highlighted. The application of therapeutic interventions based on the manipulation of gut microbiota with special diets and probiotic supplementation can be effective in GN.

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.

Targeting chronic COVID-19 lung injury; Tofacitinib can be used against tissue-resident memory T cells.

Post-Covid pulmonary fibrosis is evident following severe COVID-19. There is an urgent need to identify the cellular and pathophysiological characteristics of chronic lung squeals of Covid-19 for the development of future preventive and/or therapeutic interventions. Tissue-resident memory T (TRM) cells can mediate local immune protection against infections and cancer. Less beneficially, lung TRM cells cause chronic airway inflammation and fibrosis by stimulating pathologic inflammation. The effects of Janus kinase (JAK), an inducer pathway of cytokine storm, inhibition on acute Covid-19 cases have been previously evaluated. Here, we propose that Tofacitinib by targeting the CD8+ TRM cells could be a potential candidate for the treatment of chronic lung diseases induced by acute SARS-CoV-2 infection.

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.

Host Serine Proteases: A Potential Targeted Therapy for COVID-19 and Influenza.

The ongoing pandemic illustrates limited therapeutic options for controlling SARS-CoV-2 infections, calling a need for additional therapeutic targets. The viral spike S glycoprotein binds to the human receptor angiotensin-converting enzyme 2 (ACE2) and then is activated by the host proteases. Based on the accessibility of the cellular proteases needed for SARS-S activation, SARS-CoV-2 entrance and activation can be mediated by endosomal (such as cathepsin L) and non-endosomal pathways. Evidence indicates that in the non-endosomal pathway, the viral S protein is cleaved by the furin enzyme in infected host cells. To help the virus enter efficiently, the S protein is further activated by the serine protease 2 (TMPRSS2), provided that the S has been cleaved by furin previously. In this review, important roles for host proteases within host cells will be outlined in SARS-CoV-2 infection and antiviral therapeutic strategies will be highlighted. Although there are at least five highly effective vaccines at this time, the appearance of the new viral mutations demands the development of therapeutic agents. Targeted inhibition of host proteases can be used as a therapeutic approach for viral infection.

Podocyte-derived microparticles in IgA nephropathy.

Microparticles are a general term for different types of cell plasma membrane-originated vesicles that are released into the extracellular environment. The paracrine action of these nano-sized vesicles is crucial for intercellular communications through the transfer of diverse lipids, cytosolic proteins, RNA as well as microRNAs. The progression of different diseases influences the composition, occurrence, and functions of these cell-derived particles. Podocyte injury has been shown to have an important role in the pathophysiology of many glomerular diseases including IgA nephropathy (IgAN). This review would focus on the possible potential of podocyte-derived microparticles detected in urine to be used as a diagnostic tool in IgAN.

Application of Advanced Nanomaterials for Kidney Failure Treatment and Regeneration.

The implementation of nanomedicine not only provides enhanced drug solubility and reduced off-target adverse effects, but also offers novel theranostic approaches in clinical practice. The increasing number of studies on the application of nanomaterials in kidney therapies has provided hope in a more efficient strategy for the treatment of renal diseases. The combination of biotechnology, material science and nanotechnology has rapidly gained momentum in the realm of therapeutic medicine. The establishment of the bedrock of this emerging field has been initiated and an exponential progress is observed which might significantly improve the quality of human life. In this context, several approaches based on nanomaterials have been applied in the treatment and regeneration of renal tissue. The presented review article in detail describes novel strategies for renal failure treatment with the use of various nanomaterials (including carbon nanotubes, nanofibrous membranes), mesenchymal stem cells-derived nanovesicles, and nanomaterial-based adsorbents and membranes that are used in wearable blood purification systems and synthetic kidneys.

Stem cell-derived biofactors fight against coronavirus infection.

Despite various treatment protocols and newly recognized therapeutics, there are no effective treatment approaches against coronavirus disease. New therapeutic strategies including the use of stem cells-derived secretome as a cell-free therapy have been recommended for patients with critical illness. The pro-regenerative, pro-angiogenic, anti-inflammatory, anti-apoptotic, immunomodulatory, and trophic properties of stem cells-derived secretome, extracellular vesicles (EVs), and bioactive factors have made them suitable candidates for respiratory tract regeneration in coronavirus disease 2019 (COVID-19) patients. EVs including microvesicles and exosomes can be applied for communication at the intercellular level due to their abilities in the long-distance transfer of biological messages such as mRNAs, growth factors, transcription factors, microRNAs, and cytokines, and therefore, simulate the specifications of the parent cell, influencing target cells upon internalization and/or binding. EVs exhibit both anti-inflammatory and tolerogenic immune responses by regulation of proliferation, polarization, activation, and migration of different immune cells. Due to effective immunomodulatory and high safety including a minimum risk of immunogenicity and tumorigenicity, mesenchymal stem cell (MSC)-EVs are more preferable to MSC-based therapies. Thus, as an endogenous repair and inflammation-reducing agent, MSC-EVs could be used against COVID-19 induced morbidity and mortality after further mechanistic and preclinical/clinical investigations. This review is focused on the therapeutic perspective of the secretome of stem cells in alleviating the cytokine storm and organ injury in COVID-19 patients.