Defect and Heterostructure engineering assisted S-scheme Nb2O5 nanosystems-based solutions for environmental pollution and energy conversion.

This review explores the crystallographic versatility of niobium pentoxide (Nb2O5) at the nanoscale, showcasing enhanced catalytic efficiency for cutting-edge sustainable energy and environmental applications. The synthesis strategies explored encompass defect engineering, doping engineering, s-scheme formation, and heterojunction engineering to fine-tune the physicochemical attributes of diverse dimensional (0-D, 1-D, 2-D, and 3-D) Nb2O5 nanosystems as per targeted application. In addressing escalating environmental challenges, Nb2O5 emerges as a semiconductor photocatalyst with transformative potential, spanning applications from dye degradation to antibiotic and metal removal. Beyond its environmental impact, Nb2O5 is pivotal in sustainable energy applications, specifically in carbon dioxide and hydrogen conversion. However, challenges such as limited light absorption efficiency and scalability in production methods prompt the need for targeted research endeavors. The review details the state-of-the-art Nb2O5 nanosystems engineering, tuning their physicochemical properties employing material engineering, and their high catalytic performance in environment remediation and energy generation. It outlines challenges, potential mitigation strategies, and prospects, urging for developing greener synthesis routes, advanced charge transfer techniques, targeted optimization for specific pollutants, and application for micro/nano plastics photocatalytic reduction. As researchers and environmental stewards collaborate, Nb2O5 stands poised at the intersection of environmental remediation, energy harvesting, and nanomaterial advancements, offering a beacon of progress toward a cleaner, more sustainable future.

Exploring bio-nanomaterials as antibiotic allies to combat antimicrobial resistance.

Antimicrobial resistance (AMR) poses an emergent threat to global health due to antibiotic abuse, overuse and misuse, necessitating urgent innovative and sustainable solutions. The utilization of bio-nanomaterials as antibiotic allies is a green, economic, sustainable and renewable strategy to combat this pressing issue. These biomaterials involve green precursors (e.g. biowaste, plant extracts, essential oil, microbes, and agricultural residue) and techniques for their fabrication, which reduce their cyto/environmental toxicity and exhibit economic manufacturing, enabling a waste-to-wealth circular economy module. Their nanoscale dimensions with augmented biocompatibility characterize bio-nanomaterials and offer distinctive advantages in addressing AMR. Their ability to target pathogens, such as bacteria and viruses, at the molecular level, coupled with their diverse functionalities and bio-functionality doping from natural precursors, allows for a multifaceted approach to combat resistance. Furthermore, bio-nanomaterials can be tailored to enhance the efficacy of existing antimicrobial agents or deliver novel therapies, presenting a versatile platform for innovation. Their use in combination with traditional antibiotics can mitigate resistance mechanisms, prolong the effectiveness of existing treatments, and reduce side effects. This review aims to shed light on the potential of bio-nanomaterials in countering AMR, related mechanisms, and their applications in various domains. These roles encompass co-therapy, nanoencapsulation, and antimicrobial stewardship, each offering a distinct avenue for overcoming AMR. Besides, it addresses the challenges associated with bio-nanomaterials, emphasizing the importance of regulatory considerations. These green biomaterials are the near future of One Health Care, which will have economic, non-polluting, non-toxic, anti-resistant, biocompatible, degradable, and repurposable avenues, contributing to sustainable development goals.

Facile synthesis of elastin nanogels encapsulated decursin for castrated resistance prostate cancer therapy.

Nanogels offer hope for precise drug delivery, while addressing drug delivery hurdles is vital for effective prostate cancer (PCa) management. We developed an injectable elastin nanogels (ENG) for efficient drug delivery system to overcome castration-resistant prostate cancer (CRPC) by delivering Decursin, a small molecule inhibitor that blocks Wnt/ßcatenin pathways for PCa. The ENG exhibited favourable characteristics such as biocompatibility, flexibility, and low toxicity. In this study, size, shape, surface charge, chemical composition, thermal stability, and other properties of ENG were used to confirm the successful synthesis and incorporation of Decursin (DEC) into elastin nanogels (ENG) for prostate cancer therapy. In vitro studies demonstrated sustained release of DEC from the ENG over 120 h, with a pH-dependent release pattern. DU145 cell line induces moderate cytotoxicity of DEC-ENG indicates that nanomedicine has an impact on cell viability and helps strike a balance between therapeutics efficacy and safety while the EPR effect enables targeted drug delivery to prostate tumor sites compared to free DEC. Morphological analysis further supported the effectiveness of DEC-ENG in inducing cell death. Overall, these findings highlight the promising role of ENG-encapsulated decursin as a targeted drug delivery system for CRPC.

Electrochemical and Plasmonic Detection of Myocardial Infarction Using Microfluidic Biochip Incorporated with Mesoporous Nanoscaffolds.

This paper reports a microfluidic device for the electrochemical and plasmonic detection of cardiac myoglobin (cMb) and cardiac troponin I (cTnI) with noticeable limits of detection (LoD) as low as a few picograms per milliliter (pg/mL) ranges, achieved in a short detection time. The device features two working electrodes, each with a mesoporous Ni3V2O8 nanoscaffold grafted with reduced graphene oxide (rGO) that improves the interaction of diffusing analyte molecules with the sensing surface by providing a high surface area and reaction kinetics. Electrochemical studies reveal sensitivities as high as 9.68 µA ng/mL and a LoD of 2.0 pg/mL for cTnI, and 8.98 µA ng/mL and 4.7 pg/mL for cMb. Additionally, the surface plasmon resonance (SPR) studies demonstrate a low-level LoD of 8.8 pg/mL for cMb and 7.3 pg/mL for cTnI. The dual-modality sensor enables dynamic tracking of kinetic antigen-antibody interactions during sensing, self-verification through providing signals of two modes, and reduced false readout. This study demonstrates the complementary nature of the electrochemical and SPR modes in biosensing, with the electrochemical mode being highly sensitive and the SPR mode providing superior tracking of molecular recognition behaviors. The presented sensor represents a significant innovation in cardiovascular disease management and can be applied to monitor other clinically important biomolecules.

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis.

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

Electron Beam-Supported Fabrication of Biocompatible Silver/iota-Carrageenan for Wound Healing Application.

Silver nanoparticles (AgNPs) are a potent antibacterial agent, especially when used to treat bacteria that are multidrug resistant. However, it is challenging to eliminate the hazardous reducing agents that remain in AgNPs produced by the conventional chemical reduction process. To overcome these challenges, the presented research demonstrates the fabrication of AgNPs using iota-carrageenan (ι-carra) as a carbohydrate polymer using electron beam (EB) irradiation. Well-characterized ι-carra@AgNPs have a face-centered cubic (FCC) structure with spherical morphology and an average size of 26 nm. Herein we explored the approach for fabricating ι-carra@AgNPs that is suitable for scaling up the production of nanoparticles that exhibit excellent water stability. Further, the optimized ι-carra@AgNPs exhibited considerable antibacterial activity of 40% and 30% inhibition when tested with Gram-negative Escherichia coli ATCC 43895 and Gram-positive Staphylococcus aureus (S. aureus) (ATCC 6538), respectively, and low cytotoxicity at 10-50 µg/mL. To establish the potential biomedical application, as proof of the concept, the ι-carra@AgNPs showed significant antibiofilm activity at 20 µg/mL and also showed 95% wound healing abilities at 50 µg/mL compared to the nontreated control groups. Electron beam assisted ι-carra@AgNPs showed significant beneficial effects against specific bacterial strains and may provide a guide for the development of new antibacterial materials for wound dressing for large-scale production for biomedical applications.

Exploring Curcumin-Loaded Lipid-Based Nanomedicine as Efficient Targeted Therapy for Alzheimer's Diseases.

Alzheimer's disease (AD) is a neurological condition currently with 47 million people suffering from it globally. AD might have many reasons such as genetic issues, environmental factors, and Aß accumulation, which is the biomarker of the disease. Since the primary reason is unknown, there is no targeted treatment at the moment, but ongoing research aims to slow its progression by managing amyloid-beta peptide production rather than symptomatic improvement. Since phytochemicals have been demonstrated to possess antioxidant, anti-inflammatory, and neuroprotective properties, they may target multiple pathological factors and can reduce the risk of the disease. Curcumin, as a phytochemical found in turmeric known for its antioxidant, free radical scavenging properties, and as an antiamyloid in treating AD, has come under investigation. Although its low bioavailability limits its efficacy, a prominent drug delivery system (DDS) is desired to overcome it. Hence, the potency of lipid-based nanoparticles encapsulating curcumin (LNPs-CUR) is considered in this study as a promising DDS. In vivo studies in animal models indicate LNPs-CUR effectively slow amyloid plaque formation, leading to cognitive enhancement and reduced toxicity compared to free CUR. However, a deeper understanding of CUR's pharmacokinetics and safety profile is crucial before LNPs-CUR can be considered as a medicine. Future investigations may explore the combination of NPs with other therapeutic agents to increase their efficacy in AD cases. This review provides the current position of CUR in the AD therapy paradigm, the DDS suggestions for CUR, and the previous research from the point of analytical view focused on the advantages and challenges.

Nano/micro-plastic, an invisible threat getting into the brain.

Due to weather and working/operational conditions, plastic degradation produces toxic and non-biodegradable nano and microplastics (N/M-Ps, ranging from 10 nm to 5 mm), and over time these N/M-Ps have integrated with the human cycle through ingestion and inhalation. These N/M-Ps, as serious emerging pollutants, are causing considerable adverse health issues due to up-taken by the cells, tissue, and organs, including the brain. It has been proven that N/M-Ps can cross the blood-brain barrier (via olfactory and blood vessels) and affect the secretion of neuroinflammatory (cytokine and chemokine), transporters, and receptor markers. Neurotoxicity, neuroinflammation, and brain injury, which may result in such scenarios are a serious concern and may cause brain disorders. However, the related pathways and pathogenesis are not well-explored but are the focus of upcoming emerging research. Therefore, as a focus of this editorial, well-organized multidisciplinary research is required to explore associated pathways and pathogenesis, leading to brain mapping and nano-enabled therapeutics in acute and chronic N/M - Ps exposure.

Electrochemically microplastic detection using chitosan-magnesium oxide nanosheet.

Microplastics, an invisible threat, are emerging as serious pollutants that continuously affect health by interrupting/contaminating the human cycle, mainly involving food, water, and air. Such serious scenarios raised the demand for developing efficient sensing systems to detect them at an early stage efficiently and selectively. In this direction, the proposed research reports an electrochemical hexamethylenetetramine (HMT) sensing utilizing a sensing platform fabricated using chitosan-magnesium oxide nanosheets (CHIT-MgO NS) nanocomposite. HMT is considered as a hazardous microplastic, which is used as an additive in plastic manufacturers and has been selected as a target analyte. To fabricate sensing electrodes, a facile co-precipitation technique was employed to synthesize MgO NS, which was further mixed with 1% CHIT solution to form a CHIT_MgO NS composite. Such prepared nanocomposite solution was then drop casted to an indium tin oxide (ITO) to fabricate CHIT_MgO NS/ITO sensing electrode to detect HMT electrochemically using cyclic voltammetry (CV) and differential pulse voltammetry (DPV) techniques. To determine the limit of detection (LOD) and sensitivity, DPV was performed. The resulting calibrated curve for HMT, ranging from 0.5 µM to 4.0 µM, exhibited a sensitivity of 12.908 µA (µM)-1 cm-2 with a detection limit of 0.03 µM and a limit of quantitation (LOQ) of 0.10 µM. Further, the CHIT_MgO NS/ITO modified electrode was applied to analyze HMT in various real samples, including river water, drain water, packaged water, and tertiary processed food. The results demonstrated the method's high sensitivity and suggested its potential applications in the field of microplastic surveillance, with a focus on health management.

Exploring the fluorescence properties of tellurium-containing molecules and their advanced applications.

This review article explores the fascinating realm of fluorescence using organochalcogen molecules, with a particular emphasis on tellurium (Te). The discussion encompasses the underlying mechanisms, structural motifs influencing fluorescence, and the applications of these intriguing phenomena. This review not only elucidates the current state of knowledge but also identifies avenues for future research, thereby serving as a valuable resource for researchers and enthusiasts in the field of fluorescence chemistry with a focus on Te-based molecules. By highlighting challenges and prospects, this review sparks a conversation on the transformative potential of Te-containing compounds across different fields, ranging from environmental solutions to healthcare and materials science applications. This review aims to provide a comprehensive understanding of the distinct fluorescence behaviors exhibited by Te-containing compounds, contributing valuable insights to the evolving landscape of chalcogen-based fluorescence research.

Machine Learning-based Deep Analysis of Human Blood using NIR Spectrophotometry Signatures.

BACKGROUND: Non-invasive bio-diagnostics are essential for providing patients with safer treatment. In this subject, significant growth is attained for noninvasive anaemia detection in terms of Hb concentration by means of spectroscopic and image analysis. The lower satisfaction rate is found due to inconsistent results in various patient settings. OBJECTIVE: This observational study aims to present an adaptable point-of-care Near-Infrared (NIR) spectrophotometric approach with a constructive Machine Learning (ML) algorithm for monitoring Haemoglobin (Hb) concentration by considering dominating influencing factors into account. METHODS: To accomplish this objective, 121 subjects (19.2-55.4 years) were enrolled in the study, having a wide range of Hb concentrations (8.2-17.4 g/dL) obtained from two standard Laboratory analyzers. To inspect the performance, the unique dimensionality reduction approaches are applied with numerous regression models using 5-fold cross-validation. RESULTS: The optimum accuracy is found using support vector regression (SVR) and mutual information having 3 independent features i.e. Pearson correlation (r)= 0.79, standard deviation (SD)= 1.07 g/dL, bias=-0.13 g/dL and limits of agreement (LoA)=-2.22 to 1.97 g/dL. Additionally, comparability between two standard laboratory analyzers is found as; r=0.97, SD=0.50 g/dL, bias=0.21 g/dL, and LoA= -0.77 to 1.19 g/dL. CONCLUSION: The precision of ±1 g/dL in 5-fold cross-validation ensures the same performance irrespective of different age groups, gender, BMI, smoking level, drinking level, and skin type. The outcomes with the offered NIR sensing system and an exclusive ML algorithm can accelerate its' requirement at remote locative rural areas and critical care units where continuous Hb monitoring is compulsory.

Employing nano-enabled artificial intelligence (AI)-based smart technologies for prediction, screening, and detection of cancer.

Cancer has been classified as a diverse illness with a wide range of subgroups. Its early identification and prognosis, which have become a requirement of cancer research, are essential for clinical treatment. Patients have already benefited greatly from the use of artificial intelligence (AI), machine learning (ML), and deep learning (DL) algorithms in the field of healthcare. AI simulates and combines data, pre-programmed rules, and knowledge to produce predictions. Data are used to improve efficiency across several pursuits and tasks through the art of ML. DL is a larger family of ML methods based on representational learning and simulated neural networks. Support vector machines, convulsion neural networks, and artificial neural networks, among others, have been widely used in cancer research to construct prediction models that enable precise and effective decision-making. Although using these innovative methods can enhance our comprehension of how cancer progresses, further validation is required before these techniques can be used in routine clinical practice. We cover contemporary methods used in the modelling of cancer development in this article. The presented prediction models are built using a variety of guided ML approaches, as well as numerous input attributes and data collections. Early identification and cost-effective detection of cancer's progression are equally necessary for successful treatment of the disease. Smart material-based detection techniques can give end consumers a portable, affordable instrument to easily detect and monitor their health issues without the need for specialized knowledge. Owing to their cost-effectiveness, excellent sensitivity, multimodal detection capacity, and miniaturization aptitude, two-dimensional (2D) materials have a lot of prospects for clinical examination of various compounds as well as cancer biomarkers. The effectiveness of traditional devices is moving faster towards more useful techniques thanks to developments in 2D material-based biosensors/sensors. The most current developments in the design of 2D material-based biosensors/sensors-the next wave of cancer screening instruments-are also outlined in this article.

Recent advances in stimuli-responsive tailored nanogels for cancer therapy; from bench to personalized treatment.

To improve the quality of health in a personalized manner, better control over pharmacologically relevant cargo formulation, organ-specific targeted delivery, and on-demand release of therapeutic agents is crucial. Significant work has been put into designing and developing revolutionary nanotherapeutics approaches for the effective monitoring and personalized treatment of disease. Nanogel (NG) has attracted significant interest because of its tremendous potential in cancer therapy and its environmental stimuli responsiveness. NG is considered a next-generation delivery technology due to its benefits like as size tunability, high loading, stimuli responsiveness, prolonged drug release via in situ gelling mechanisms, stability, and its potential to provide personalized therapy from the investigation of human genes and the genes in various types of cancers and its association with a selective anticancer drug. Stimuli-responsive NGs can be used as smart nanomedicines to detect and treat cancer and can be tuned as personalized medicine as well. This comprehensive review article's major objectives include the challenges of NGs' clinical translation for cancer treatment as well as its early preclinical successes and prospects.

Pathophysiology to advanced intra-articular drug delivery strategies: Unravelling rheumatoid arthritis.

Rheumatoid arthritis (RA) is one of the most prevalent life-long autoimmune diseases with an unknown genesis. It primarily causes chronic inflammation, pain, and synovial joint-associated cartilage and bone degradation. Unfortunately, limited information is available regarding the etiology and pathogenesis of this chronic joint disorder. In the last few decades, an improved understanding of RA pathophysiology about key immune cells, antibodies, and cytokines has inspired the development of several anti-rheumatic drugs and biopharmaceuticals to act on RA-affected joints. However, life-long frequent systemic high doses of commercially available drugs are currently a limiting factor in the efficient management of RA. To address this issue, various single and double-barrier intra-articular drug delivery systems (IA-DDSs) such as nanocarriers, microparticles, hydrogels, and particles-hybrid hydrogel composite have been developed which can exclusively target the RA-affected joint cavity and release the precisely controlled therapeutic drug concentration for prolonged time whilst avoiding the systemic toxicity. This review provides a comprehensive overview of the pathogenesis of RA and discusses the rational design and development of biomaterials-based novel IA-DDs, ranging from conventional to advanced systems, for improved treatment of RA. Therefore, this review aims to unravel the pathophysiology of rheumatoid arthritis and explore cutting-edge IA-DD strategies exploiting biomaterials. It offers researchers a consolidated and up-to-date resource platform to analyze existing knowledge, identify research gaps, and contribute to the scientific literature.

Trends and prospects of 2-D tungsten disulphide (WS2) hybrid nanosystems for environmental and biomedical applications.

Recently, 2D layered transition metal dichalcogenides (TMDCs) with their ultrathin sheet nanostructure and diversified electronic structure have drawn attention for various advanced applications to achieve high-performance parameters. Unique 2D TMDCs mainly comprise transition metal and chalcogen element where chalcogen element layers sandwich the transition metal element layer. In such a case, various properties can be enhanced and controlled depending on the targeted application. Among manipulative 2D TMDCs, tungsten disulphide (WS2) is one of the emerging nano-system due to its fascinating properties in terms of direct band gap, higher mobility, strong photoluminescence, good thermal stability, and strong magnetic field interaction. The advancement in characterization techniques, especially scattering techniques, can help in study of opto-electronic properties of 2D TMDCs along with determination of layer variations and investigation of defect. In this review, the fabrication and applications are well summarized to optimize an appropriate WS2-TMDCs assembly according to focused field of research. Here, the scientific investigations on 2D WS2 are studied in terms of its structure, role of scattering techniques to study its properties, and synthesis routes followed by its potential applications for environmental remediation (e.g., photocatalytic degradation of pollutants, gas sensing, and wastewater treatment) and biomedical domain (e.g., drug delivery, photothermal therapy, biomedical imaging, and biosensing). Further, a special emphasis is given to the significance of 2D WS2 as a substrate for surface-enhanced Raman scattering (SERS). The discussion is further extended to commercial and industrial aspects, keeping in view major research gaps in existing research studies.

Chitosan-Grafted-Poly(N-vinylcaprolactam)-Decorated Fe3O4@SiO2 Core-Shell Nanoformulation as an Efficient Drug Delivery System for Poorly Soluble Drugs.

Hydrocortisone, a commonly used anti-inflammatory drug, has limited aqueous solubility and several side effects. To address this challenge, as a proof-of-concept, this article demonstrates the development of a controlled-release drug delivery system (DDS) for hydrocortisone using chitosan-grafted poly(N-vinylcaprolactam) (CS-g-PNVCL)-coated core-shell Fe3O4@SiO2 nanoformulations (NFs). Reported magnetic nanoparticles (NPs) were synthesized and modified with silica, PNVCL, and CS precursors to enhance the biocompatibility of DDS and drug-loading efficiency. The release rate of hydrocortisone from Fe3O4@SiO2@CS-g-PNVCL NFs was observed to be higher at lower pH values, and the smart polymer coating demonstrated temperature responsiveness, facilitating drug release at higher temperatures. Fe3O4@SiO2@CS-g-PNVCL NFs exhibited a cell viability of around 97.2 to 87.3% (5-100 µg/mL) after 24-48 h, while the hydrocortisone-NFs had a cell viability of around 93.2 to 82.3%. Our findings suggest that CS-g-PNVCL-coated Fe3O4@SiO2 NPs effectively enhance the solubility, loading capacity, and targeted delivery of poorly soluble drugs, thereby improving their therapeutic efficacy and bioavailability.

Current Status and Emerging Trends in Colorectal Cancer Screening and Diagnostics.

Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high incidences and mortality rates, which raised the need for effective diagnostic strategies for the early detection and management of CRC. While there are several conventional cancer diagnostics available, they have certain limitations that hinder their effectiveness. Significant research efforts are currently being dedicated to elucidating novel methodologies that aim at comprehending the intricate molecular mechanism that underlies CRC. Recently, microfluidic diagnostics have emerged as a pivotal solution, offering non-invasive approaches to real-time monitoring of disease progression and treatment response. Microfluidic devices enable the integration of multiple sample preparation steps into a single platform, which speeds up processing and improves sensitivity. Such advancements in diagnostic technologies hold immense promise for revolutionizing the field of CRC diagnosis and enabling efficient detection and monitoring strategies. This article elucidates several of the latest developments in microfluidic technology for CRC diagnostics. In addition to the advancements in microfluidic technology for CRC diagnostics, the integration of artificial intelligence (AI) holds great promise for further enhancing diagnostic capabilities. Advancements in microfluidic systems and AI-driven approaches can revolutionize colorectal cancer diagnostics, offering accurate, efficient, and personalized strategies to improve patient outcomes and transform cancer management.

Optimizing Pix2Pix GAN with Attention Mechanisms for AI-Driven Polyp Segmentation in IoMT-Enabled Smart Healthcare.

This paper introduces an innovative approach for automated polyp segmentation in colonoscopy images, deploying an enhanced Pix2Pix Generative Adversarial Network (GAN) equipped with an integrated attention mechanism in the discriminator. Addressing prevalent challenges in conventional segmentation methods, such as variable polyp appearances, inconsistent image quality, and limited training data, our model significantly augments the precision and reliability of polyp segmentation. The integration of an attention mechanism enables our model to meticulously focus on the intricate features of polyps, improving segmentation accuracy. A unique training strategy, employing both real and synthetic data, is adopted to ensure the model's robust performance under a variety of conditions. The results, validated through rigorous tests on multiple public colonoscopy datasets, indicate a notable improvement in segmentation performance over existing state-of-the-art methods. Our model's enhanced ability to detect critical details early plays a pivotal role in proactive colorectal cancer detection, a key aspect of smart healthcare systems. This work represents an effective amalgamation of advanced AI techniques and the Internet of Medical Things (IoMT), signifying a noteworthy contribution to the evolution of smart healthcare systems. In conclusion, our attention-enhanced Pix2Pix GAN not only offers efficient and reliable polyp segmentation, but also showcases considerable potential for seamless integration into remote health monitoring systems, underlining the increasing relevance and efficacy of AI in advancing IoMT-enabled healthcare.