Introduction: Obesity has emerged as a major global public health concern. It is a multifactorial condition encompassing genetic, environmental, socioeconomic, and psychosocial factors. This narrative review aims to highlight the key pathophysiological processes associated with chronic low-grade inflammation (CLGI) in obesity. Methods: Data collection was performed using the PubMed, Scopus, Web of Science, and Google Scholar databases, using the search terms “chronic low-grade inflammation”, “pathophysiology of obesity,” and “metabolic syndrome” to obtain relevant articles. Results: The pathophysiological sequence underlying CLGI-associated obesity begins with adipose tissue expansion, during which hypertrophic adipocytes trigger cellular stress manifested as hypoxia and ER stress, accompanied by the release of damage-associated molecular patterns (DAMPs). This initiates a vicious cycle involving the recruitment of macrophages and their proinflammatory M1 polarization, with activation of inflammatory pathways, such as NF-κB and the NLRP3 inflammasome. These changes further contribute to the induction of systemic insulin resistance and metabolic dysregulation. Discussion: Both tissue and systemic biomarkers are valuable in identifying and monitoring CLGI-associated obesity. Treatment approaches ranging from pharmacological agents and bariatric surgery to dietary modifications, exercise, and microbiome-based therapies are relevant for managing inflammation and metabolic health. Conclusion: In conclusion, strategic immunotargeting of CLGI through context-specific interventions can serve as an innovative therapeutic strategy to treat CLGI-associated obesity and potentially mitigate the resulting comorbid metabolic burden. Future efforts should prioritize the development of multi-marker approaches within precision medicine frameworks to enable more individualized care for patients with CLGI-associated obesity.
Introduction: The direct-to-consumer (DTC) genetic testing industry has grown substantially, enabling consumers to obtain information regarding ancestry, disease predisposition, pharmacogenomics, and various traits without the necessity of healthcare provider intervention. Marketed as tools aimed for democratizing personal health insights, direct-to-consumer genetic tests may improve genetic knowledge, promote preventative healthcare, and encourage proactive health management. Methods: The study utilized medical databases such as PubMed, Scopus, Web of Science, ScienceDirect, and Google Scholar. Results: Challenges like inadequate variant coverage, demographic bias in reference databases, inconsistent interpretation standards, and restricted access to genetic counseling raise concerns around false positives, increased anxiety, and suboptimal health decisions. Ethical and legal dilemmas about privacy, consent, and third-party data sharing intensify concerns about confidentiality, participant rights, and regulatory compliance. Discussion: Numerous tests lack recognized clinical importance and utility, while state-level regulatory control limits wider implementation. This mini-review assesses the advantages and disadvantages of direct-to-consumer genetic testing, focusing on scientific, clinical, and societal ramifications. It emphasizes the equilibrium between consumer empowerment and the dangers of disinformation, highlighting the necessity for stringent validation, transparent communication, and professional genetic counseling. Conclusion: As direct-to-consumer genetic testing becomes more accessible, it is crucial to acknowledge its advantages and drawbacks to ensure responsible utilization and to enhance its contribution to precision medicine while protecting individual and public health.
Introduction: Polycystic ovary syndrome (PCOS) is a complicated endocrinemetabolic disorder that occurs in between 6-13% of women of reproductive age. There is a growing body of evidence that dysregulation of the mitogen-activated protein kinase (MAPK) signaling pathway is a major factor in the pathophysiology of PCOS. Methods: A narrative literature review was conducted in PubMed, Scopus, Web of Science, ScienceDirect, and Google Scholar. Original research articles, clinical studies, and relevant reviews in English were included, while duplicate, non-English, and irrelevant studies were excluded Results: There is evidence that MAPK kinase families, such as extracellular signal-regulated kinase (ERK1/2), c-Jun N-terminal kinase (JNK), and phosphorylated p38 (p38), play a role in insulin resistance, hyperandrogenism, follicular dysfunction, and chronic inflammation in PCOS. Interactions with phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt), mechanistic target of rapamycin (mTOR), adenosine monophosphate-activated protein kinase (AMPK), and nuclear factor kappa B (NF-κB) pathways and signals also enhance metabolic and reproductive pathological changes. Some molecules related to MAPK that include phosphorylated ERK and MAPK-associated microRNAs (miRNAs) have become diagnostic biomarkers. It is also shown through preclinical research that MAPK modulators have therapeutic effects, be it synthetic or natural compounds (curcumin, resveratrol, and berberine). Discussion: Modulation of the MAPK signaling pathway can be effective in treating the multifactorial PCOS. MAPK pathways can be modulated to enhance insulin sensitivity, lower androgen excess, and restore normal ovarian functioning. Conclusion: Altogether, MAPK signaling is a highly important molecular target in the pathogenesis of PCOS and can become an available biomarker and therapeutic target in the future, and be used in making a personalized treatment strategy
Introduction:: Status epilepticus (SE) is a serious neurological emergency defined by prolonged or recurring seizures that frequently do not respond to standard antiepileptic medications. Recent revelations into the molecular underpinnings of SE, including neuroinflammation, oxidative stress, angiogenesis, and disruption of the blood-brain barrier, have stimulated research into targeted therapeutics. Lenvatinib, a multi-kinase inhibitor sanctioned for many cancers, has demonstrated potential neuroprotective and anti-inflammatory effects by targeting the VEGFR, FGFR, and PDGFR pathways, which are also involved in epileptogenesis. Methods:: This review examines the therapeutic potential of repurposing lenvatinib in the pilocarpine- induced status epilepticus model, a well-established preclinical framework that simulates human temporal lobe epilepsy. Preclinical evidence, mechanistic relevance, pharmacodynamics, blood-brain barrier permeability, and safety profiles were reviewed to determine the viability of lenvatinib as an adjunct or alternative therapy. Results:: Furthermore, the function of angiogenic signaling in the advancement of seizures and how lenvatinib's multitargeted mechanism may influence critical pathogenic pathways were also examined. Discussion:: Although existing evidence is insufficient, in silico and in vivo investigations indicate that lenvatinib may disrupt neuroinflammatory and vascular alterations essential to SE pathogenesis. Additional preclinical validation is necessary to verify its efficacy and safety. Conclusion:: This review seeks to establish a thorough basis for subsequent research on the repurposing of lenvatinib in neurotherapeutics.
Introduction: Advances in neurotechnology, micro- and nanotechnology, and biocompatible materials have enabled the design of bioelectronic devices that modify Autonomic Nervous System (ANS) activity and are used to treat a multitude of disorders. The paper explains the preclinical and clinical uses, highlights new technologies in electrode production, and addresses topics such as the neuromodulation mechanism and patient-specific needs. The current paper, with the help of the current progress in neurotechnology, micro/nano-engineering, and biocompatible materials, discusses how bioelectronic devices can, potentially, be used to manipulate ANS activity to cure all sorts of diseases. Method: The paper examines preclinical and clinical applications, reviews proven developments in electrode technology, and evaluates the efficacy of the technique in the treatment of metabolic, inflammatory, cardiovascular, and pelvic diseases. Results: The challenges are the inability to meet patients' needs, the lack of normalisation of neuromodulation methods, and the lack of understanding of the processes. To expand the treatment scope of BM, future endeavours will focus on integrating research and technology development. Discussion: Results indicate that although Bioelectronic Medicine has great promise in the noncancerous treatment of a variety of ANS-related diseases, it faces challenges in standardising stimulation parameters, improving biocompatibility, and personalising treatment. To achieve the aim of transferring current experimental advances to safe and efficient clinical implementation, the issues will be addressed. Conclusion: The exception is that a few case studies are summarised in the manuscript to illustrate the use of bioelectronic medicines in Autonomic disorders. Conclusion: The exception is that a few case studies are summarised in the manuscript to illustrate the use of bioelectronic medicines in Autonomic disorders.
Introduction: Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β deposition, tau hyperphosphorylation, mitochondrial dysfunction, and synaptic loss, leading to cognitive and behavioral impairment. Despite extensive research, disease-modifying therapies remain limited. Recent advances in genetics, biomarker discovery, immunotherapy, and stem cell research have reshaped the understanding of AD pathophysiology and therapeutic opportunities. This review aims to summarize recent advances in Alzheimer’s disease pathogenesis, emerging fluid and imaging biomarkers, and stem cell–based therapeutic strategies, highlighting their integrated role in early diagnosis, disease monitoring, and precision medicine. Methods: A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science databases. Peer-reviewed articles published in English focusing on AD genetics, biomarkers, immunotherapies, and stem cell–based interventions were included. Preclinical and clinical studies relevant to diagnosis, prognosis, and therapeutic development were critically analyzed. Results: Key biomarkers, including cerebrospinal fluid amyloid-β1-42, total tau, phosphorylated tau (p-Tau181), and neurofilament light chain, demonstrate high diagnostic and prognostic value. Advances in neuroimaging further enhance disease characterization. While CSF biomarkers remain the diagnostic gold standard, blood-based biomarkers offer promising, minimally invasive alternatives. Concurrently, stem cell therapies have shown neuroprotective, anti-inflammatory, and regenerative effects in preclinical AD models, supporting their potential role in disease modification. Conclusion: The convergence of biomarker-guided diagnostics and stem cell-based therapeutic strategies represents a promising direction for precision medicine in Alzheimer’s disease. Although translational challenges remain, integrating these approaches may improve early detection, disease progression monitoring, and the development of personalized therapeutic interventions.
Introduction: A combination of environmental variables, a genetic background, and exposure to sunlight is causing the rate of skin cancer to rise worldwide. The most often diagnosed cancers are non-melanoma skin cancers, especially cancers of the squamous cells (SCC) and basal cell carcinoma (BCC). Although aggressive and surgical therapies are successful, they frequently cause relapse, impairment in functioning, or scarring. A less intrusive option with good cosmetic results is photodynamic treatment (PDT), which uses a light-activated photosensitizer to generate reactive oxygen species (ROS). The purpose of this study is to provide an overview of the mechanisms, developments, efficacy in clinical settings, and constraints of PDT in the treatment of skin cancer. Methods: The databases PubMed, Scopus, Web of Science, and Google Scholar were used to do a narrative review of the literature. "Photodynamic therapy", "the skin cancer", photosensitizers", and "nanotechnology" were among the phrases used. To assess PDT mechanisms, pigment development, clinical outcomes, and new technical tactics, Englishlanguage peer-reviewed literature, research, and review studies were examined. Results: PDT offers superior cosmetic outcomes and selective tumor eradication for actinic keratosis, intermediate BCC, and initial SCC. Tumor hypoxia, uneven photosensitizer absorption, and limited penetration into the tissues are some of the associated limitations. The precision of therapy has been strengthened by recent developments in nanocarrier systems, advanced photosensitizers, and efficient light-delivery methods. In order to overcome resistance and improve medical response, mixed methods that incorporate PDT with immune therapy, chemotherapy, or biological strategies show possibility. Discussion: PDT's growing use in dermatological oncology has been reinforced by its tailored activity and advantageous aesthetic profile. Treatment of deeper or malignancies caused by still presents difficulties, necessitating the use of improved exposure systems, near-infrared photosensitizers, and nanotechnology. Multiple therapies may improve effectiveness even more and lower the chance of reappearance. Conclusion: PDT is a cutting-edge, successful treatment for superficial skin cancers. It is anticipated that collaborative treatment approaches and technological advancements would increase its practical utility and enhance patient results and quality of life.
Introduction: Cancer remains a leading global cause of death, with clear genderspecific patterns. Women face a higher incidence of breast, cervical, and ovarian cancers, while men have greater mortality from lung, liver, and prostate cancers. Delayed diagnosis continues to drive advanced-stage presentation and poorer outcomes. Genetic and epigenetic alterations, including chromosomal instability, DNA methylation changes, oncogene activation, and tumour suppressor loss, further accelerate cancer progression. Advances in biomarkers and gene-editing technologies offer new opportunities for early detection and targeted therapy. Objectives: To examine how diagnostic delays and genomic alterations influence cancer progression and to evaluate the potential of integrating biomarkers with gene-editing tools for improved outcomes. Method: A narrative review of peer-reviewed literature was conducted, focusing on genderbased mortality patterns, the impact of diagnostic delays, key genetic and epigenetic alterations, the utility of biomarkers such as ctDNA, CTCs, and microRNAs, and the therapeutic promise of CRISPR-based gene editing. Results: Findings reveal strong associations between delayed diagnosis, higher tumour burden, and reduced survival. Circulating biomarkers demonstrate value for early detection and monitoring, while CRISPR and related editing technologies show preclinical potential in correcting oncogenic mutations and restoring tumour suppressor function. Discussion: Integrating biomarker-guided diagnostics with precise gene-editing strategies may enhance early intervention and personalized therapy, though challenges remain related to offtarget effects, delivery efficiency, assay variability, and ethical considerations. Conclusion: Biomarker-driven detection combined with emerging gene-editing tools represents a promising direction for earlier diagnosis and more effective, individualized cancer treatment.
Introduction: Artificial Intelligence (AI) is increasingly shaping healthcare, particularly through Clinical Decision Support Systems (AI-CDSS). These tools help physicians interpret complex data and guide patient management. Despite their promise, adoption remains limited due to concerns about trust, professional autonomy, and usability. Existing studies often examine these issues in isolation, leaving gaps in understanding how they interact. Methods: This narrative review applied the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology-Organization-Environment (TOE) frameworks to synthesize findings from literature published between 2010 and 2025. Databases searched included Pub- Med, Scopus, IEEE Xplore, SpringerLink, and ScienceDirect. Studies addressing adoption, trust, and usability of AI-CDSS were mapped to UTAUT constructs (e.g., performance expectancy, social influence, technology anxiety) and TOE dimensions (technological, organizational, environmental). Results: The review highlights that the successful adoption of AI-CDSS depends on more than technical accuracy. Physicians’ trust is shaped by system transparency, explainability, and perceived reliability. Organizational support, including training and infrastructure, strongly influences readiness. Concerns about autonomy and liability remain central barriers, while personal innovativeness and social influence encourage adoption. Discussion: Findings suggest that AI is best positioned as a supportive “co-pilot” rather than a replacement for clinicians. Explainable and user-friendly designs, combined with humancentered interfaces, can mitigate technology anxiety and preserve professional judgment. Ethical oversight, bias mitigation, and data governance remain essential to responsible integration. Conclusion: Adoption of AI-CDSS requires a balance of innovation and empathy. By aligning technical performance with trust, autonomy, and institutional readiness, AI can be integrated responsibly into healthcare. Future efforts should focus on interdisciplinary design, continuous training, and patient-centered transparency to ensure equitable and ethical use.
Introduction:: The small non-coding RNAs (sRNAs), such as microRNAs and piRNAs, have been discovered as key regulators of gene expression and potential biomarkers of cancer, infectious, cardiovascular, and neurological diseases. These conventional methods of detection (RT-qPCR, microarrays, next-generation sequencing) are highly sensitive for analysis but are clinically translationable only due to high cost, extended turnaround times, complex workflows, and their inability to be used in decentralized diagnostics. Biosensor-based systems have also been in the limelight as an alternative technology for detecting sRNA in a rapid, sensitive, and point-of-care manner. Method:: The present narrative review is a systematic review of peer-reviewed articles published between 2019 and 2025, sourced from databases such as PubMed, Scopus, Web of Science, and Google Scholar. Articles were sampled based on their relevance to sRNA biosensor design, biorecognition, signal transduction, and analytical and clinical/translational applicability. Data synthesis was conducted qualitatively due to heterogeneity in experimental design and reporting standards. Results:: Recent developments indicate that biosensors based on electrochemical, optical, piezoelectric, and nanomaterials can achieve high sensitivity, low detection limits, and improved specificity in the detection of sRNA. The use of aptamers, Cas9/CRISPR systems, nanostructured surfaces, and microfluidic systems has increased signal amplification, assay speed, and portability. In spite of these achievements, issues of reproducibility, long-term stability, massscale production, and clinical validation remain. Discussion:: Sensors based on biosensor sRNA detection platforms demonstrate strong prospects for closing the gap between analysis and clinical applications. Nevertheless, to become popular, they should have standardized performance measures, rigorous validation in clinical samples, and direct comparison with the gold-standard diagnostic tools. It will be necessary to overcome these limitations to translate biosensor technologies into routine clinical and point-of-care applications. Conclusion:: Biosensor-based sRNA detection represents a transformative approach for nextgeneration diagnostics, bridging molecular biology with precision medicine. Continued integration of nanotechnology, bioinformatics, and artificial intelligence will further advance biosensor performance, enabling early disease detection, personalized therapy, and global health monitoring.
Introduction: Serine proteases play pivotal roles in physiological and pathological processes, including cancer, cardiovascular dysfunction, inflammation, and neurodegeneration. Methods: This review systematically explores therapeutic strategies targeting serine proteases, emphasizing mechanisms of inhibition, clinical relevance, and recent advancements in inhibitor design. Results: Inhibitors include small molecules (dabigatran, which displays strong inhibitory effects, although its binding affinity depends on the peptide chain length), peptides (macrocyclic compounds), antibodies, and protein therapeutics such as native serine protease inhibitors (serpins), including antithrombin, α1-antitrypsin, and C1-inhibitor, which play critical regulatory and therapeutic roles. These agents utilize covalent and non-covalent mechanisms, transitionstate mimicry, and steric or allosteric inhibition. Clinical data support their efficacy, but limitations include off-target effects, pharmacokinetic instability, and resistance (e.g., HCV protease mutations). Discussion: Emerging solutions involve targeting novel proteases like furin and mesotrypsin, dual-action inhibitors that engage both serine and metallo-carbapenemases, and delivery via nanotechnology. PROTACs and activity-based probes enhance target validation and drug design. Conclusion: Serine protease inhibitors offer promising therapeutic benefits across diseases. Advancements in selectivity, delivery, and resistance management will drive future clinical applications.
Introduction: The cannabinoid receptor 2 (CB2), part of the endocannabinoid system, is a key regulator of immune function whose peripheral expression makes it an attractive therapeutic target in oncology, avoiding the psychoactive effects of the CB1 receptor. Methods: This mini-review comprehensively summarizes the current understanding of the CB2 receptor's multifaceted role in cancer, integrating preclinical studies with bioinformatics network validation. Results: Literature synthesis reveals that CB2 expression and prognostic value are highly context- dependent, correlating with improved survival in hepatocellular carcinoma but poor prognosis in HER2+ breast cancer. Network analysis confirms the CNR2 gene as a central hub suppressing the PI3K/AKT/mTOR axis and interacting with CXCR4 and TLR4. Discussion: The contradictory roles of CB2 across malignancies, such as immunosuppression in NSCLC versus protective immune roles in melanoma, highlight the importance of the tumor microenvironment (TME). Conclusion: The CB2 receptor is a promising pharmacological target in oncology. However, its complex, context-dependent effects underscore the need for further research, informed by system- level bioinformatics, to fully understand its cell-specific functions and develop tailored, effective anti-cancer therapies.
Medical imaging has long played a pivotal role in healthcare, from early detection to disease monitoring, making its importance in diagnosis undeniable. Given this critical role, the incorporation of Artificial Intelligence (AI) and Machine Learning (ML) has become essential to enhance diagnostic accuracy and support clinical decision-making. This study focuses on recent advancements in medical imaging and diagnostics following this integration, emphasizing current trends, novel methodologies, clinical applications, and future challenges. Based on an extensive literature search of databases including IEEE Xplore, PubMed, Web of Science, and Scopus from 2015 to 2024, the review highlights the significant utility of supervised and unsupervised learning models, as well as deep learning architectures such as CNNs, U-Net, and Transformers, across diverse fields including radiology, pathology, ophthalmology, cardiology, and dermatology. Innovations such as federated learning and explainable AI are discussed alongside practical challenges including data scarcity, generalizability, and model interpretability. In conclusion, Machine Learning continues to revolutionize medical imaging by offering automated, accurate, and scalable diagnostic solutions. Despite existing limitations, emerging technologies such as quantum computing and edge AI provide a glimpse into the future of personalized and decentralized healthcare. However, widespread clinical adoption requires further research to address critical ethical, regulatory, and data-standardization issues to ensure these powerful tools are implemented effectively and responsibly.
Neurodegenerative diseases are a group of inherited and sporadic illnesses associated with progressive nervous system dysfunction and neuronal death. For disorders affecting peripheral tissues, protein kinases are a class of pharmacological targets that are gaining popularity. However, due to issues with drug discovery, developing kinase-targeted treatments for disorders affecting the Central Nervous System (CNS) remains challenging. The Receptor Tyrosine Kinases (RTKs) are a class of membrane-bound receptors consisting of an extracellular ligandbinding domain, a transmembrane domain, and an intracellular catalytic domain. Various biological processes, such as growth, differentiation, motility, and metabolism, are reliant on RTKs. The deregulation of receptor tyrosine kinase function plays a significant role in the pathogenesis of various neurodegenerative disorders. The investigation revealed modifications in the Tropomyosin receptor kinase (Trk), Epidermal Growth Factor Receptor 1 (EGFR1), and vascular endothelial growth factor-B (VEGF-B) TAM receptors associated with neurological disorders. Additionally, the data suggest that Receptor Tyrosine Kinases (RTKs) initiate two critical signaling pathways that contribute to neuronal survival and neurite expansion: PI3K/Akt/GSK-3β pathway and Wnt/β-catenin pathway. This chapter outlines the key traits of RTK subdivisions and the associated intraneuronal signaling pathways in various neurodegenerative diseases. It's important to understand the fundamental principles underlying RTKs in neurodegenerative diseases to select the appropriate neuroprotective medication.
Introduction: Non-Small Cell Lung Carcinoma (NSCLC) specifically is still one of the top causes of cancer-related death globally. The multi-targeted mechanisms and lower toxicity of natural products make them intriguing pharmacological candidates. Using a combination of in vitro and in silico methods, the current study assessed the anticancer potential of the Ethanol Extract of Carica papaya Linn. roots (EECP). Methods: Phytochemical profiling and High-Performance Thin-Layer Chromatography (HPTLC) analysis confirmed the presence of flavonoids, including rutin. The 2,2-diphenyl-1- picrylhydrazyl (DPPH) assay was used to assess antioxidant activity. Cytotoxicity against Human lung adenocarcinoma cell line (A549) and normal human lung fibroblast cell line (WI-38) cells was evaluated, along with apoptosis via nuclear condensation, Deoxyribonucleic Acid (DNA) fragmentation, and Reactive Oxygen Species (ROS) accumulation. Molecular docking (SwissDock) and Absorption, Distribution, Metabolism, and Excretion (ADME) predictions were performed to assess protein interactions, drug-likeness, and oral bioavailability. results: EECP exhibited strong antioxidant activity (IC₅₀ = 4.07 μg/mL) and selective cytotoxicity toward A549 cells (IC₅₀ = 89.96 ± 0.24 μg/mL) with lower toxicity in WI-38 fibroblasts. Treatment induced significant ROS generation (213% at 300 μg/mL) and apoptotic changes. Docking studies revealed strong interactions of quercetin (–9.758 kcal/mol) and kaempferol (–9.353 kcal/mol) with oncogenic proteins, comparable to staurosporine (–10.439 kcal/mol). ADME predictions supported favorable bioavailability and drug-likeness. Results: Ethanolic extract demonstrated potent antioxidant activity (IC50 = 4.07 μg/mL) and selective cytotoxicity against A549 cells (IC50 = 89.96±0.24 μg/mL), with comparatively lower toxicity in WI-38 cells (IC50 = 75.83±0.34 μg/mL). Apoptosis was associated with nuclear condensation, DNA fragmentation, and a 213% increase in ROS at 300 μg/mL. Docking studies indicated strong binding of quercetin (-9.758 kcal/mol) and kaempferol (-9.353 kcal/mol) to oncogenic proteins, comparable to that of staurosporine (-10.439 kcal/mol), mediated by hydrogen bonds and hydrophobic interactions. Phenolic acids showed moderate interactions, and carpaine/ ergosta derivatives showed weaker interactions. ADME analyses revealed favourable oral bioavailability and high gastrointestinal absorption for key flavonoids. Discussion: Ethanolic extract induces oxidative stress-mediated apoptosis and regulates key signalling proteins, including Protein Kinase B (Akt) and tumor suppressor p53 (p53). Conclusion: Overall, the EECP exhibits strong anticancer potential by inducing ROS-mediated apoptosis and regulating Akt and p53, supporting further preclinical evaluation of C. papaya Linn. root flavonoids for lung cancer.
Telomestatin is known for its potent telomerase inhibition and anticancer activity; however, its clinical translation has been hindered by poor pharmacokinetic properties. In this study, we aimed to evaluate the pharmacokinetics, toxicity, and G-quadruplex binding affinity of telomestatin analogues using a suite of computational tools. The ADME profiles of the telomestatin analogues were assessed using SwissADME, ADMETlab, and vNN, which predict physicochemical properties, pharmacokinetics, and druglikeness. The toxicity profiles of the compounds were predicted using the ProTox-II server, which provides LD₂⁽ values, toxicity class assignments, and potential effects on stress-response pathways. Finally, binding affinities between the analogues and the G-quadruplex structure were evaluated using AutoDock Tools 1.5.6. Computational ADME analyses showed that the telomestatin analogues possessed low gastrointestinal absorption, suggesting that oral administration would not be suitable. Compounds TN9–TN14 did not exhibit P-gp substrate activity, a desirable property for cytotoxic drugs. Predicted LD₂⁽ values ranged from 800 to 1210 mg/kg. Docking studies indicated that TN9 had the strongest binding affinity toward the G-quadruplex, with a binding energy of – 10.08 kcal/mol. Among the analogues evaluated, TN9 demonstrated the most favorable overall profile, including desirable pharmacokinetic predictions, a benign toxicity profile, and strong binding affinity. These findings suggest that TN9 warrants further investigation in in vitro and in vivo systems to assess its pharmacokinetics, safety, and anticancer efficacy. Telomestatin analogues, particularly TN9, display promising characteristics and should be further explored as potential anticancer agents.
Cardiovascular diseases (CVDs) represent a significant global health burden, frequently leading to compromised arterial blood supply to vital organs. Timely and accurate detection is paramount for effective clinical intervention and improved patient outcomes. While traditional deep learning methodologies have shown promise in CVD detection from physiological signals, they often face limitations in predictive accuracy, model interpretability, and generalization across diverse data distributions. This study introduces a novel Adaptive Hybrid Activation (ADHA) based Deep Convolutional Neural Network model. The primary aim is to advance the state-of-the-art in CVD detection and classification by addressing existing limitations in accuracy, enhancing model generalization, and improving the inherent interpretability of the predictive framework. The ADHA architecture is meticulously designed with an innovation: an adaptive hybrid activation function module. The adaptive hybrid activation function is engineered to dynamically optimize non-linearity and pattern learning, thereby bolstering the model's classification efficacy. Empirical evaluation, conducted on a single, publicly available dataset (Challenge 2015), demonstrates that the proposed ADHA model achieves notable performance metrics, including 98.05% accuracy, 98.00% F1-score, 98.60% sensitivity, 98.20% specificity, 98.54% negative predictive value (NPV), and 97.56% positive predictive value (PPV). These results indicate superior performance compared to several established state-of-the-art CVD detection methodologies on the evaluated dataset. The ADHA model significantly contributes to the enhancement of CVD detection and classification by addressing challenges related to generalization, feature sparsity, and overfitting inherent in deep learning applications. The presented results underscore the model's compelling performance and suggest its potential for future clinical investigation and application in cardiovascular health monitoring.
Toll-Like Receptor 4 (TLR4) is vital for the innate immune system as it recognizes a wide array of pathogens, such as bacteria, fungi, and viruses. TLR4 activates downstream signaling pathways upon recognizing microbial components, triggering and regulating the immune response. With improvements in genomic technologies, it has become possible to identify Single-Nucleotide Polymorphisms (SNPs) in genes coding for immune receptors, such as TLR4. These genetic differences may affect the way TLR4 reacts to various pathogens and thus the intensity and outcome of immune responses. It is essential to have a comprehensive understanding of SNPs associated with TLR4 to assess individual susceptibility to infection and inform personalized medicine strategies. Multiple scientific literature review databases were utilized to examine TLR4 SNPs and their roles in pathogen recognition, immune signaling, and disease outcomes. These studies elaborated the role of TLR4 polymorphisms in various forms of infections involving bacteria, fungi, and viruses. Some polymorphisms in the TLR4 gene, including rs4986790 [Asp299Gly] and rs4986791 [Thr399Ile], have been associated with differing immune responses and increased susceptibility to septic shock, candidiasis, tuberculosis, and viral infections. This inhibition of TLR4 signaling by the mutant alleles augments some arms of immune response while inhibiting others, which in turn affects the severity of the infection and the response to treatment. This review focuses on the identification and examination of SNPs in TLR4 and their association with infectious diseases caused by pathogens. The review also examines the impact of these SNPs on TLR4 signaling pathways and the immune response. Polymorphisms in the TLR4 gene, including rs4986790 [Asp299Gly] and rs4986791 [Thr399Ile], have been associated with differing immune responses and increased susceptibility to septic shock, candidiasis, tuberculosis, and viral infections. Recognition of TLR4 SNPs would provide information on susceptibility to various infections and immune modulation. Current knowledge of genetic variations will lead to the identification of biomarkers for infectious diseases, and consequently, patient-specific treatment and vaccine generation targeted toward specific genotypes in precision medicine, particularly in immunology.
Breast cancer is one of the most prevalent cancers among women worldwide. In recent years, a significant proportion of breast cancer research in Pakistan, accounting for nearly two-thirds, has focused on this disease. Nanotechnology has emerged as a promising tool in the detection, diagnosis, and treatment of breast cancer. This study presents an analysis of traditional breast cancer therapies and compares them with recent developments in nanomedicine. The data were collected from online databases, including Google Scholar, PubMed, and Web of Science, to support the current study. Various treatments face challenges, including complications and drug resistance. A new approach has been developed to overcome chemoresistance in breast cancer patients. Nanotechnology utilizes both organic and inorganic methods to address breast cancer, aiming to reduce tumor size and impede its development. The nanomedicine treatment involves active, passive, and stimuli-responsive targeting of nanocarriers to tumor cells. Although nanomedicine shows high effectiveness, careful consideration must be given to the potential toxicity of nanomaterials, particularly their impact on the immune system. Nanomedicine offers a promising solution to overcome chemoresistance in breast cancer by targeted drug delivery through nanocarriers. While effective in reducing tumors, concerns about nanomaterial toxicity, especially its impact on the immune system, must be addressed. In summary, nanomedicine proves to be an efficient method for treating breast cancer tumor growth. Further work is necessary to design safer and more effective medicines through nanomedicine.
In the originally published article [1], reference number 61 in the reference list contained an incorrect DOI link. It has now been corrected, which leads to the accessible online search. The original article can be found online at: https://www.eurekaselect.com/article/150537 The specific correction details are as follows: Original: Incorrect Link: [61] Bezerra Morais PA, Barbosa Silva JA, Javarini CL. State-of-art on the synthesis of heterocyclic compounds targeting SARS-CoV-2. Curr Org Chem 2024; 29(8). http://dx.doi.org/0.2174/011385272824876240812075831 Corrected Link: [61] Bezerra Morais PA, Barbosa Silva JA, Javarini CL. State-of-art on the synthesis of heterocyclic compounds targeting SARS-CoV-2. Curr Org Chem 2024; 29(8). http://dx.doi.org/10.2174/0113852728248762240812075831 The article has been updated to reflect this correction. The authors apologize for any inconvenience caused to the readers.
