Plant-derived exosomes in therapeutic nanomedicine, paving the path toward precision medicine.

BACKGROUND: Plant-derived exosomes (PDEs), are nanoscale vesicles secreted by multivesicular bodies, play pivotal roles in critical biological processes, including gene regulation, cell communication, and immune defense against pathogens. Recognized for their potential health-promoting properties, PDEs are emerging as innovative components in functional nutrition, poised to enhance dietary health benefits. PURPOSE: To describe the efficacy of PDEs in nanoform and their application as precision therapy in many disorders. STUDY DESIGN: The design of this review was carried out in PICO format using randomized clinical trials and research articles based on in vivo and in vitro studies. METHODS: All the relevant clinical and research studies conducted on plant-derived nanovesicle application and efficacy were included, as retrieved from PubMed and Cochrane, after using specific search terms. This review was performed to determine PDEs' efficacy as nanomedicine and precision therapy. Sub-group analysis and primary data were included to determine the relationship with PDEs. RESULT: PDEs are extracted from plant materials using sophisticated techniques like precipitation, size exclusion, immunoaffinity capture, and ultracentrifugation, encapsulating vital molecules such as lipids, proteins, and predominantly microRNAs. Although their nutritional impact may be minimal in small quantities, the broader application of PDEs in biomedicine, particularly as vehicles for drug delivery, underscores their significance. They offer a promising strategy to improve the bioavailability and efficacy of therapeutic agents carrying nano-bioactive substances that exhibit anti-inflammatory, antioxidant, cardioprotective, and anti-cancer activities. CONCLUSION: PDEs enhance the therapeutic potency of plant-derived phytochemicals, supporting their use in disease prevention and therapy. This comprehensive review explores the multifaceted aspects of PDEs, including their isolation methods, biochemical composition, health implications, and potential to advance medical and nutritional interventions.

Exploring cytokines dynamics: Uncovering therapeutic concepts for metabolic disorders in postmenopausal women- diabetes, metabolic bone diseases, and non-alcohol fatty liver disease.

Menopause is an age-related change that persists for around one-third of a woman's life. Menopause increases the risk of metabolic illnesses such as diabetes, osteoporosis (OP), and nonalcoholic fatty liver disease (NAFLD). Immune mediators (pro-inflammatory cytokines), such as interleukin-1 (IL-1), IL-6, IL-17, transforming growth factor (TGF), and tumor necrosis factor (TNF), exacerbate the challenges of a woman undergoing menopause by causing inflammation and contributing to the development of these metabolic diseases in postmenopausal women. Furthermore, studies have shown that anti-inflammatory cytokines such as interleukin-1 receptor antagonists (IL-1Ra), IL-2, and IL-10 have a double-edged effect on diabetes and OP. Likewise, several interferon (IFN) members are double-edged swords in the OP. Therefore, addressing these immune mediators precisely may be an approach to improving the health of postmenopausal women. Hence, considering the significant changes in these cytokines, the present review focuses on the latest findings concerning the molecular mechanisms by which pro- and anti-inflammatory cytokines (interleukins) impact postmenopausal women with diabetes, OP, and NAFLD. Furthermore, we comprehensively discuss the therapeutic approaches that identify cytokines as therapeutic targets, such as hormonal therapy, physical activities, natural inhibitors (drugs), and others. Finally, this review aims to provide valuable insights into the role of cytokines in postmenopausal women's diabetes, OP, and NAFLD. Deeply investigating the mechanisms and therapeutic interventions involved will address the characteristics of immune mediators (cytokines) and improve the management of these illnesses, thereby enhancing the general quality of life and health of the corresponding populations of women.

Shaping the future of gastrointestinal cancers through metabolic interactions with host gut microbiota.

Gastrointestinal (GI) cancers represent a significant global health challenge, driving relentless efforts to identify innovative diagnostic and therapeutic approaches. Recent strides in microbiome research have unveiled a previously underestimated dimension of cancer progression that revolves around the intricate metabolic interplay between GI cancers and the host's gut microbiota. This review aims to provide a comprehensive overview of these emerging metabolic interactions and their potential to catalyze a paradigm shift in precision diagnosis and therapeutic breakthroughs in GI cancers. The article underscores the groundbreaking impact of microbiome research on oncology by delving into the symbiotic connection between host metabolism and the gut microbiota. It offers valuable insights into tailoring treatment strategies to individual patients, thus moving beyond the traditional one-size-fits-all approach. This review also sheds light on novel diagnostic methodologies that could transform the early detection of GI cancers, potentially leading to more favorable patient outcomes. In conclusion, exploring the metabolic interactions between host gut microbiota and GI cancers showcases a promising frontier in the ongoing battle against these formidable diseases. By comprehending and harnessing the microbiome's influence, the future of precision diagnosis and therapeutic innovation for GI cancers appears more optimistic, opening doors to tailored treatments and enhanced diagnostic precision.

Machine learning guided prediction of warfarin blood levels for personalized medicine based on clinical longitudinal data from cardiac surgery patients: a prospective observational study.

BACKGROUND: Warfarin is a common oral anticoagulant, and its effects vary widely among individuals. Numerous dose-prediction algorithms have been reported based on cross-sectional data generated via multiple linear regression or machine learning. This study aimed to construct an information fusion perturbation theory and machine learning prediction model of warfarin blood levels based on clinical longitudinal data from cardiac surgery patients. METHODS AND MATERIAL: The data of 246 patients were obtained from electronic medical records. Continuous variables were processed by calculating the distance of the raw data with the moving average (MA ∆vki(sj)), and categorical variables in different attribute groups were processed using Euclidean distance (ED ǁ∆vk(sj)ǁ). Regression and classification analyses were performed on the raw data, MA ∆vki(sj), and ED ǁ∆vk(sj)ǁ. Different machine-learning algorithms were chosen for the STATISTICA and WEKA software. RESULTS: The random forest (RF) algorithm was the best for predicting continuous outputs using the raw data. The correlation coefficients of the RF algorithm were 0.978 and 0.595 for the training and validation sets, respectively, and the mean absolute errors were 0.135 and 0.362 for the training and validation sets, respectively. The proportion of ideal predictions of the RF algorithm was 59.0%. General discriminant analysis (GDA) was the best algorithm for predicting the categorical outputs using the MA ∆vki(sj) data. The GDA algorithm's total true positive rate (TPR) was 95.4% and 95.6% for the training and validation sets, respectively, with MA ∆vki(sj) data. CONCLUSIONS: An information fusion perturbation theory and machine learning model for predicting warfarin blood levels was established. A model based on the RF algorithm could be used to predict the target international normalized ratio (INR), and a model based on the GDA algorithm could be used to predict the probability of being within the target INR range under different clinical scenarios.

Role of MMP-9 and NF-κB in Diabetic Retinopathy: Progression and Potential Role of Bioflavonoids in the Mitigation of Diabetic Retinopathy.

"Diabetes mellitus" is a chronic metabolic disorder manifested by elevated blood glucose levels, primarily due to insufficient insulin production or resistance to insulin. Long-term diabetes results in persistent complications like retinopathy, cardiomyopathy, nephropathy, and neuropathy, causing significant health risks. The most alarming microvascular consequence allied with diabetes is "diabetic retinopathy," distinguished by the proliferation of anomalous blood vessels in the eye, mainly in the retina, resulting in visual impairment, diabetic macular edema, and retinal detachment if left untreated. According to estimates, 27.0% of people with diabetes worldwide have retinopathy, which leads to 0.4 million blindness cases. It is believed that mitochondrial damage and the production of inflammatory mediators are the early indicators of diabetic retinopathy before any histological changes occur in the retina. Moreover, it is evident that augmented oxidative stress in the retina further initiates the NF-κB/MMP-9 downstream signaling pathway. Interestingly, these downstream regulators, Nuclear Factor Kappa B [NF- kB] and matrix metalloproteinases 9 [MMP-9], have been recognized as important regulators of the inception and advancement of diabetic retinopathy. This diabetes and oxidative stress-induced MMP-9 are believed to regulate various cellular functions, including angiogenesis and apoptosis, causing blood-retinal barrier breakdown and tight junction protein degradation that further leads to diabetic retinopathy. Thus, there is an emergency need for the treatment of diabetic retinopathy. Emerging treatment options include anti-VEGF, laser treatment, and eye surgery, but these have certain limitations. This comprehensive review explores the mechanisms of MMP-9 and NF-kB involvement in diabetic retinopathy and bioflavonoids' therapeutic potential and mechanisms of action in inhibiting MMP-9 activity and suppressing NF-kB-mediated inflammation. Clinical evidence supporting the use of bioflavonoids in mitigating diabetic complications and future perspectives are also examined.

Pro- and anti-inflammatory cytokines are the game-changers in childhood obesity-associated metabolic disorders (diabetes and non-alcoholic fatty liver diseases).

Childhood obesity is a chronic inflammatory epidemic that affects children worldwide. Obesity affects approximately 1 in 5 children worldwide. Obesity in children can worsen weight gain and raise the risk of obesity-related comorbidities like diabetes and non-alcoholic fatty liver disease (NAFLD). It can also negatively impact the quality of life for these children. Obesity disrupts immune system function, influencing cytokine (interleukins) balance and expression levels, adipokines, and innate and adaptive immune cells. The altered expression of immune system mediators, including interleukin-1 (IL-1), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-17 (IL-17), interleukin-18 (IL-18), transforming growth factor (TGF), tumor necrosis factor (TNF), and others, caused inflammation, progression, and the development of pediatric obesity and linked illnesses such as diabetes and NAFLD. Furthermore, anti-inflammatory cytokines, including interleukin-2 (IL-2), have been shown to have anti-diabetes and IL-1 receptor antagonist (IL-1Ra) anti-diabetic and pro-NAFLFD properties, and interleukin-10 (IL-10) has been shown to have a dual role in managing diabetes and anti-NAFLD. In light of the substantial increase in childhood obesity-associated disorders such as diabetes and NAFLD and the absence of an effective pharmaceutical intervention to inhibit immune modulation factors, it is critical to consider the alteration of immune system components as a preventive and therapeutic approach. Thus, the current review focuses on the most recent information regarding the influence of pro- and anti-inflammatory cytokines (interleukins) and their molecular mechanisms on pediatric obesity-associated disorders (diabetes and NAFLD). Furthermore, we discussed the current therapeutic clinical trials in childhood obesity-associated diseases, diabetes, and NAFLD.

Pro-inflammatory cytokines and CXC chemokines as game-changer in age-associated prostate cancer and ovarian cancer: Insights from preclinical and clinical studies' outcomes.

Prostate cancer (PC) and Ovarian cancer (OC) are two of the most common types of cancer that affect the reproductive systems of older men and women. These cancers are associated with a poor quality of life among the aged population. Therefore, finding new and innovative ways to detect, treat, and prevent these cancers in older patients is essential. Finding biomarkers for these malignancies will increase the chance of early detection and effective treatment, subsequently improving the survival rate. Studies have shown that the prevalence and health of some illnesses are linked to an impaired immune system. However, the age-associated changes in the immune system during malignancies such as PC and OC are poorly understood. Recent research has suggested that the excessive production of inflammatory immune mediators, such as interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor (TGF), tumor necrosis factor (TNF), CXC motif chemokine ligand 1 (CXCL1), CXC motif chemokine ligand 12 (CXCL12), and CXC motif chemokine ligand 13 (CXCL13), etc., significantly impact the development of PC and OC in elderly patients. Our review focuses on the latest functional studies of pro-inflammatory cytokines (interleukins) and CXC chemokines, which serve as biomarkers in elderly patients with PC and OC. Thus, we aim to shed light on how these biomarkers affect the development of PC and OC in elderly patients. We also examine the current status and future perspective of cytokines (interleukins) and CXC chemokines-based therapeutic targets in OC and PC treatment for elderly patients.

Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer.

Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis.

Revolutionizing pediatric neuroblastoma treatment: unraveling new molecular targets for precision interventions.

Neuroblastoma (NB) is the most frequent solid tumor in pediatric cases, contributing to around 15% of childhood cancer-related deaths. The wide-ranging genetic, morphological, and clinical diversity within NB complicates the success of current treatment methods. Acquiring an in-depth understanding of genetic alterations implicated in the development of NB is essential for creating safer and more efficient therapies for this severe condition. Several molecular signatures are being studied as potential targets for developing new treatments for NB patients. In this article, we have examined the molecular factors and genetic irregularities, including those within insulin gene enhancer binding protein 1 (ISL1), dihydropyrimidinase-like 3 (DPYSL3), receptor tyrosine kinase-like orphan receptor 1 (ROR1) and murine double minute 2-tumor protein 53 (MDM2-P53) that play an essential role in the development of NB. A thorough summary of the molecular targeted treatments currently being studied in pre-clinical and clinical trials has been described. Recent studies of immunotherapeutic agents used in NB are also studied in this article. Moreover, we explore potential future directions to discover new targets and treatments to enhance existing therapies and ultimately improve treatment outcomes and survival rates for NB patients.

Unlocking the potential of oncology biomarkers: advancements in clinical theranostics.

INTRODUCTION: Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment. CONTENT: In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack. SUMMARY AND OUTLOOK: We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Involvement of CXC chemokines (CXCL1-CXCL17) in gastric cancer: Prognosis and therapeutic molecules.

Gastric cancer (GC) is the fifth-most prevalent and second-most deadly cancer worldwide. Due to the late onset of symptoms, GC is frequently treated at a mature stage. In order to improve the diagnostic and clinical decision-making processes, it is necessary to establish more specific and sensitive indicators valuable in the early detection of the disease whenever a cancer is asymptomatic. In this work, we gathered information about CXC chemokines and GC by using scientific search engines including Google Scholar, PubMed, SciFinder, and Web of Science. Researchers believe that GC chemokines, small proteins, class CXC chemokines, and chemokine receptors promote GC inflammation, initiation, and progression by facilitating angiogenesis, tumor transformation, invasion, survival, metastatic spread, host response safeguards, and inter-cell interaction. With our absolute best professionalism, the role of CXC chemokines and their respective receptors in GC diagnosis and prognosis has not been fully explained. This review article updates the general characteristics of CXC chemokines, their unique receptors, their function in the pathological process of GC, and their potential application as possible indicators for GC. Although there have only recently been a few studies focusing on the therapeutic efficacy of CXC chemokine inhibitors in GC, growing experimental evidence points to the inhibition of CXC chemokines as a promising targeted therapy. Therefore, further translational studies are warranted to determine whether specific antagonists or antibodies designed to target CXC chemokines alone or in combination with chemotherapy are useful for diagnosing advanced GC.

Opuntia ficus-indica (L.) Mill. - anticancer properties and phytochemicals: current trends and future perspectives.

Cancer is a leading cause of mortality worldwide, and conventional cancer therapies such as chemotherapy and radiotherapy often result in undesirable and adverse effects. Natural products have emerged as a promising alternative for cancer treatment, with comparatively fewer side effects reported. Opuntia ficus-indica (L.) Mill., a member of the Cactaceae family, contains a diverse array of phytochemicals, including flavonoids, polyphenols, betalains, and tannins, which have been shown to exhibit potent anticancer properties. Various parts of the Opuntia plant, including the fruits, stems/cladodes, and roots, have demonstrated cytotoxic effects against malignant cell lines in numerous studies. This review comprehensively summarizes the anticancer attributes of the phytochemicals found in Opuntia ficus-indica (L.) Mill., highlighting their potential as natural cancer prevention and treatment agents. Bibliometric metric analysis of PubMed and Scopus-retrieved data using VOSviewer as well as QDA analysis provide further insights and niche to be explored. Most anticancer studies on Opuntia ficus-indica and its purified metabolites are related to colorectal/colon cancer, followed by melanoma and breast cancer. Very little attention has been paid to leukemia, thyroid, endometrial, liver, and prostate cancer, and it could be considered an opportunity for researchers to explore O. ficus-indica and its metabolites against these cancers. The most notable mechanisms expressed and validated in those studies are apoptosis, cell cycle arrest (G0/G1 and G2/M), Bcl-2 modulation, antiproliferative, oxidative stress-mediated mechanisms, and cytochrome c. We have also observed that cladodes and fruits of O. ficus-indica have been more studied than other plant parts, which again opens the opportunity for the researchers to explore. Further, cell line-based studies dominated, and very few studies were related to animal-based experiments. The Zebrafish model is another platform to explore. However, it seems like more in-depth studies are required to ascertain clinical utility of this biosustainable resource O. ficus-indica.

Nanomedicine: Innovative Strategies and Recent Advances in Targeted Cancer Therapy.

Nanomedicine's application of nanotechnology in medicine holds tremendous potential for diagnosing and treating life-threatening diseases such as cancer. Unlike conventional therapies, nanomedicine offers a promising strategy to enhance clinical outcomes while minimizing severe side effects. The principle of drug targeting enables specific delivery of therapeutic agents to their intended sites, making it a more precise and effective therapy. Combination strategies, such as the co-delivery of chemotherapeutic drugs with nucleic acids or receptor-specific molecules, are being employed to enhance therapeutic outcomes. Nanocarriers and drug delivery systems designed using these approaches offer resourceful co-delivery of therapeutic agents for anticancer therapy. Targeted drug delivery via nanotechnology-based techniques has become an urgent need and has shown significant improvements in therapeutic implications, pharmacokinetics, specificity, reduced toxicity, and biocompatibility. This review discusses the extrapolation of nanomaterials for developing innovative and novel drug delivery systems for effective anticancer therapy. Additionally, we explore the role of nanotechnology-based concepts in drug delivery research.

Exploring the complex relationship between vitamin K, gut microbiota, and warfarin variability in cardiac surgery patients.

BACKGROUND AND OBJECTIVES: Due to the high individual variability of anticoagulant warfarin, this study aimed to investigate the effects of vitamin K concentration and gut microbiota on individual variability of warfarin in 246 cardiac surgery patients. METHODS: The pharmacokinetics and pharmacodynamics (PKPD) model predicted international normalized ratio (INR) and warfarin concentration. Serum and fecal samples were collected to detect warfarin and vitamin K [VK1 and menaquinone-4 (MK4)] concentrations and gut microbiota diversity, respectively. In addition, the patient's medical records were reviewed for demographic characteristics, drug history, and CYP2C9, VKORC1, and CYP4F2 genotypes. RESULTS: The PKPD model predicted ideal values of 62.7% for S-warfarin, 70.4% for R-warfarin, and 76.4% for INR. The normal VK1 level was 1.34±1.12 nmol/ml (95% CI: 0.33-4.08 nmol/ml), and the normal MK4 level was 0.22±0.18 nmol/ml (95% CI: 0.07-0.63 nmol/ml). The MK4 to total vitamin K ratio was 16.5±9.8% (95% CI: 4.3-41.5%). The S-warfarin concentration of producing 50% of maximum anticoagulation and the half-life of prothrombin complex activity tended to increase with vitamin K. Further, Prevotella and Eubacterium of gut microbiota identified as the main bacteria associated with individual variability of warfarin. The results suggest that an increase in vitamin K concentration can decrease anticoagulation, and gut microbiota may influence warfarin anticoagulation through vitamin K2 synthesis. CONCLUSION: This study highlights the importance of considering vitamin K concentration and gut microbiota when prescribing warfarin. The findings may have significant implications for the personalized use of warfarin. Further research is needed to understand better the role of vitamin K and gut microbiota in warfarin anticoagulation.

Identification of a novel 5-methylcytosine-related signature for prognostic prediction of kidney renal papillary cell carcinoma and a Putative target for drug repurposing.

BACKGROUND: Many studies have demonstrated the crucial roles of 5-methylcytosine (m5C) RNA methylation in cancer pathogenesis. METHODS: Two datasets, including TCGA-KIRP and ICGC, and related clinical information were downloaded, where the expression of 13 m5C regulators was examined. We applied LASSO regression to construct a multi-m5C-regulator-based signature in the TCGA cohort, which was further validated using the ICGC cohort. Univariate and multivariate Cox regressions were applied to evaluate the independent prognostic value of our model. The differences in biological functions and immune characterizations between high and low-risk groups divided based on the risk scores were also investigated via multiple approaches, such as enrichment analyses, mutation mining, and immune scoring. Finally, the sensitivities of commonly used targeted drugs were tested, and the connectivity MAP (cMAP) was utilized to screen potentially effective molecules for patients in the high-risk group. Experimental validation was done following qPCR tests in Caki-2 and HK-2 cell lines. RESULTS: 3 m5C regulators, including ALYREF, DNMT3B and YBX1, were involved in our model. Survival analysis revealed a worse prognosis for patients in the high-risk group. Cox regression results indicated our model's superior predictive performance compared to single-factor prognostic evaluation. Functional enrichment analyses indicated a higher mutation frequency and poorer tumor microenvironment of patients in the high-risk group. qPCR-based results revealed that ALYREF, DNMT3B, and YBX1 were significantly up-regulated in Caki-2 cell lines compared with HK-2 cell lines. Molecules like BRD-K72451865, Levosimendan, and BRD-K03515135 were advised by cMAP for patients in the high-risk group. CONCLUSION: Our study presented a novel predictive model for KIRP prognosis. Furthermore, the results of our analysis provide new insights for investigating m5C events in KIRP pathogenesis.

Microbiota dysbiosis and myasthenia gravis: Do all roads lead to Rome?

Dysregulated immune system with a failure to recognize self from non-self-antigens is one of the common pathogeneses seen in autoimmune diseases. The complex interplay of genetic and environmental factors is important for the occurrence and development of the disease. Among the environmental factors, disturbed gut microbiota (gut dysbiosis) has recently attracted particular attention, especially with advancement in human microbiome research. Although the alterations in microbiota have been seen in various autoimmune diseases, including those of nervous system, there is paucity of information on neuromuscular system diseases. Myasthenia gravis (MG) is one such rare autoimmune disease of neuromuscular junction, and is caused by generation of pathogenic autoantibodies to components of the postsynaptic muscle endplate. In the recent years, accumulating evidences have endorsed the key role of host microbiota, particularly those of gut, in the pathogenesis of MG. Differential microbiota composition, characterized by increased abundance of Fusobacteria, Bacteroidetes, and Proteobacteria, and decreased abundance of Actinobacteria and Firmicutes, has been seen in MG patients in comparison to healthy subjects. Disturbance of microbiota composition, particularly reduced ratio of Firmicutes/Bacteroidetes, alter the gut permeability, subsequently triggering the immunological response. Resultant reduction in levels of short chain fatty acids (SCFAs) is another factor contributing to the immunological response in MG patients. Modulation of gut microbiota via intervention of probiotics, prebiotics, synbiotics, postbiotics (metabiotics), and fecal microbiota transplantation (FMT) is considered to be the futuristic approach for the management of MG. This review summarizes the role of gut microbiota and their metabolites (postbiotics) in the progression of MG. Also, various bacteriotherapeutic approaches involving gut microbiota are discussed for the prevention of MG progression.

Advanced Phytochemical-Based Nanocarrier Systems for the Treatment of Breast Cancer.

As the world's most prevalent cancer, breast cancer imposes a significant societal health burden and is among the leading causes of cancer death in women worldwide. Despite the notable improvements in survival in countries with early detection programs, combined with different modes of treatment to eradicate invasive disease, the current chemotherapy regimen faces significant challenges associated with chemotherapy-induced side effects and the development of drug resistance. Therefore, serious concerns regarding current chemotherapeutics are pressuring researchers to develop alternative therapeutics with better efficacy and safety. Due to their extremely biocompatible nature and efficient destruction of cancer cells via numerous mechanisms, phytochemicals have emerged as one of the attractive alternative therapies for chemotherapeutics to treat breast cancer. Additionally, phytofabricated nanocarriers, whether used alone or in conjunction with other loaded phytotherapeutics or chemotherapeutics, showed promising results in treating breast cancer. In the current review, we emphasize the anticancer activity of phytochemical-instigated nanocarriers and phytochemical-loaded nanocarriers against breast cancer both in vitro and in vivo. Since diverse mechanisms are implicated in the anticancer activity of phytochemicals, a strong emphasis is placed on the anticancer pathways underlying their action. Furthermore, we discuss the selective targeted delivery of phytofabricated nanocarriers to cancer cells and consider research gaps, recent developments, and the druggability of phytoceuticals. Combining phytochemical and chemotherapeutic agents with nanotechnology might have far-reaching impacts in the future.

Single-cell RNA-seq analysis to identify potential biomarkers for diagnosis, and prognosis of non-small cell lung cancer by using comprehensive bioinformatics approaches.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and the leading cause of cancer-related deaths worldwide. Identification of gene biomarkers and their regulatory factors and signaling pathways is very essential to reveal the molecular mechanisms of NSCLC initiation and progression. Thus, the goal of this study is to identify gene biomarkers for NSCLC diagnosis and prognosis by using scRNA-seq data through bioinformatics techniques. scRNA-seq data were obtained from the GEO database to identify DEGs. A total of 158 DEGs (including 48 upregulated and 110 downregulated) were detected after gene integration. Gene Ontology enrichment and KEGG pathway analysis of DEGs were performed by FunRich software. A PPI network of DEGs was then constructed using the STRING database and visualized by Cytoscape software. We identified 12 key genes (KGs) including MS4A1, CCL5, and GZMB, by using two topological methods based on the PPI networking results. The diagnostic, expression, and prognostic potentials of the identified 12 key genes were assessed using the receiver operating characteristics (ROC) curve and a web-based tool, SurvExpress. From the regulatory network analysis, we extracted the 7 key transcription factors (TFs) (FOXC1, YY1, CEBPB, TFAP2A, SREBF2, RELA, and GATA2), and 8 key miRNAs (hsa-miR-124-3p, hsa-miR-34a-5p, hsa-miR-21-5p, hsa-miR-155-5p, hsa-miR-449a, hsa-miR-24-3p, hsa-let-7b-5p, and hsa-miR-7-5p) associated with the KGs were evaluated. Functional enrichment and pathway analysis, survival analysis, ROC analysis, and regulatory network analysis highlighted crucial roles of the key genes. Our findings might play a significant role as candidate biomarkers in NSCLC diagnosis and prognosis.