Recent advances in biosensor for detection of lung cancer biomarkers

Dual-mode biosensor using Tb-Cu MOF@Au nanoenzyme to effectively quench the photocurrent of Bi2O3/Bi2S3/AgBiS2 heterojunction and emit fluorescence for neuron-specific enolases detection

A novel dual-mode biosensor was constructed for the ultrasensitive detection of neuron-specific enolase (NSE), utilizing Tb-Cu MOF@Au nanozyme as the signal label to effectively quench the photoelectrochemical (PEC) signals of Bi2O3/Bi2S3/AgBiS2 composites and initiate fluorescent (FL) signals. First, Bi2O3/Bi2S3/AgBiS2 heterojunction with excellent photoelectric activity was selected as the substrate material to provide a stable photocurrent. The well-matched energy levels significantly enhanced the separation and transfer of photogenerated carriers. Second, a strategy of consuming ascorbic acid (AA) by Tb-Cu MOF@Au nanozyme was introduced to improve the sensitivity of the PEC/FL biosensor. Tb-Cu MOF@Au not only could catalyze the oxidation of AA, but the steric effect further reduced the contact of AA with the substrate. More importantly, in the presence of H2O2, a significant fluorescence was produced from Tb3+ sensitized by the oxidation products of AA. Based on the above strategies, a highly stable and sensitive dual-mode biosensor was proposed for accurate NSE determination. Third, the developed dual-mode biosensor demonstrated excellent performance in detecting NSE. In this study, the PEC method demonstrated a wide detection range from 0.00005 to 200 ng/mL with a low detection limit of 20 fg/mL. The FL method exhibited a linear range from 0.001 to 200 ng/mL with a detection limit of 0.65 pg/mL. The designed biosensor showed potential practical implications in the accurate detection of disease markers.

A new insight into the early detection of HER2 protein in breast cancer patients with a focus on electrochemical biosensors approaches: A review

Breast cancer is one of the leading causes of death in women and is a prevalent kind of cancerous growth, representing a substantial risk to women's health. Early detection of breast cancer is essential for effective treatment and improved survival rates. Biomarkers, active substances that signal the existence and advancement of a tumor, play a significant role in the early detection of breast cancer. Hence, accurate identification of biomarkers for tumors is crucial for diagnosing and treating breast cancer. However, the primary diagnostic methods used for the detection of breast cancer require specific equipment, skilled professionals, and specialized analysis, leading to elevated detection expenses. Regarding this obstacle, recent studies emphasize electrochemical biosensors as more advanced and sensitive detection tools compared to traditional methods. Electrochemical biosensors are employed to identify biomarkers that act as unique indicators for the onset, recurrence, and monitoring of therapeutic interventions for breast cancer. This study aims to provide a summary of the electrochemical biosensors that have been employed for the detection of breast cancer at an early stage over the past decade. Initially, the text provides concise information about breast cancer and tumor biomarkers. Subsequently, an in-depth analysis is conducted to systematically review the progress of electrochemical biosensors developed for the stable, specific, and sensitive identification of biomarkers associated with breast cancer. Particular emphasis was given to crucial clinical biomarkers, specifically the human epidermal growth factor receptor-2 (HER2). The analysis then explores the limitations and challenges inherent in the design of effective biosensors for diagnosing and treating breast cancer. Ultimately, we provided an overview of future research directions and concluded by outlining the advantages of electrochemical biosensor approaches.

Multiplexed electrochemical nucleic acid sensor based on visible light-mediated metal-free thiol-yne click reaction for simultaneous detection of different nucleic acid targets

Simultaneous detection of multiple tumor biomarkers with a simple and low-cost assay is crucial for early cancer detection and diagnosis. Herein, we presented a low-cost and simple assay for multiplexed detection of tumor biomarkers using a spatially separated electrodes strategy. The sensor is fabricated based on a metal-free thiol-yne click reaction, which is mediated by visible light, on commercially available indium tin oxide (ITO) electrodes. Four biomarkers, including p53 DNA, Brca2 DNA, K-ras DNA, and MicroRNA-204 RNA, were used as model analytes, and the corresponding oligonucleotide probes were modified on the desired electrode units sequentially with 530 nm irradiation light in the presence of photosensitizer Eosin Y. By this visible light-mediated coupling reaction, oligonucleotide probe densities of up to 9.2 ± 0.7 × 1010 molecules/cm2 were readily obtained on the ITO electrode surface. The proposed multiplexed E-NA sensor could detect four different nucleic acid targets concurrently without crosstalk among adjacent electrodes and was also successfully applied for detecting targets in a 20% fetal calf serum sample. The detection limits for p53 DNA, Brca2 DNA, K-ras DNA, and MicroRNA-204 RNA were 0.72 nM, 0.97 nM, 2.15 nM, and 1.73 nM, respectively. The developed approach not only has a great potential for developing cost-effective biosensors on affordable substrates for nucleic acid target detection, but also be easily extended to detect other targets by modifying the specific oligonucleotide probes anchored on the electrode.

The role of seven tumor-associated autoantibodies in the diagnosis, staging and treatment guidance of lung cancer

BACKGROUND

This study assessed the diagnosis, staging and treatment guidance of lung cancer (LC) based on seven tumor-associated autoantibodies (TAAbs) -p53, PGP9.5, SOX2, GBU4-5, MAGE A1, CAGE, and GAGE7.

METHODS

ELISA was used to determine the TAAb serum levels in 433 patients diagnosed with LC (161 surgical patients) and 76 patients with benign lung disease (16 surgical patients). The statistical characteristic of the TAAbs was compared among patients with different clinicopathological features. Pre- to postoperative changes in TAAb levels were analyzed to determine their value of LC.

RESULTS

Among all patients, the positive rate of the seven TAAbs was 23.4%, sensitivity was 26.3%, accuracy was 36.3%, specificity was 93.4%, positive predictive value was 95.8%, and negative predictive value was 18.2%; the positive rate for the LC group (26.3%) was significantly higher than that for the benign group (6.6%; P < 0.001). Significant differences in the positive rate of the seven autoantibodies according to age (P < 0.001), smoking history (P = 0.009) and clinical LC stage (P < 0.001) were found. Smoking was positively associated with the positive of TAAbs (Τ = 0.118, P = 0.008). The positive rates of the seven TAAbs for squamous carcinoma (54.5%), other pathological types (44.4%) and poorly differentiated LC (57.1%) were significantly higher than those for the other types. The positive rate of GBU4-5 was highest among all TAAbs, and the SOX2 level in stage III-IV patients was much higher than that in other stages. For patients undergoing surgery, compared with the preoperative levels, the postoperative levels of the 7 markers, particularly p53 (P = 0.027), PGP9.5 (P = 0.007), GAGE7 (P = 0.014), and GBU4-5 (P = 0.002), were significantly different in the malignant group, especially in stage I-II patients, while no clear pre- to postoperative difference was observed in the benign group.

CONCLUSIONS

When the seven TAAbs was positive, it was very helpful for the diagnosis of LC. The 7 TAAbs was valuable for staging and guiding treatment of LC in surgical patients.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

2,5-Thiophenedicarboxylic Acid Bridging Hexameric CeIII-Substituted Selenotungstate and Its Application for Detecting Mucin 1

The development of polyoxometalate chemistry not only is derived from the continuous discovery of novel polyoxometalates (POMs) but also stems from the exploitation of their new functionalities. In this work, we obtained a rigid sulfur-containing heterocyclic ligand-linking aggregate [N(CH3)4]10Na6H6[Ce8(H2O)26W8(HTDA)2(TDA)2O20][SeW4O18]2[SeW9O33]4·112H2O (1) (H2TDA = 2,5-thiophenedicarboxylic acid). Its polyanionic unit consists of one [Ce4(H2O)13W4O10(HTDA)(TDA)O10]18+ cluster and two kinds of Keggin-type [SeW4O18] and [SeW9O33] segments. It is noteworthy that H2TDA ligands not only work as connectors to link two symmetrical {[Ce4(H2O)13W4(HTDA)(TDA)O10][SeW4O18][SeW9O33]2}11- units but also function as ornaments to graft to the polyanionic backbone. Furthermore, 1 and 3,4-ethylenedioxythiophene (EDOT) were deposited on the glassy carbon electrode (GCE) by the electropolymerization (EPM) method, resulting in a 1-poly(3,4-ethylenedioxythiophene) (1-PEDOT) composite film, which can provide sufficient binding sites to immobilize Au nanoparticles (Au NPs). Hereafter, the Au NPs-immobilized 1-PEDOT modified electrode (Au/1-PEDOT/GCE) was used to construct an electrochemical aptasensor to detect mucin 1, showing a low detection limit of 29.5 fM in the Tris solution. This work not only demonstrates that rigid heterocyclic ligands are beneficial for the creation of novel rare-earth-substituted selenotungstate hybrids but also provides more enlightenment for POM-based materials used for electrochemical detection of cancer markers.

Machine Learning in Diagnosis and Prognosis of Lung Cancer by PET-CT

As a disease with high morbidity and high mortality, lung cancer has seriously harmed people's health. Therefore, early diagnosis and treatment are more important. PET/CT is usually used to obtain the early diagnosis, staging, and curative effect evaluation of tumors, especially lung cancer, due to the heterogeneity of tumors and the differences in artificial image interpretation and other reasons, it also fails to entirely reflect the real situation of tumors. Artificial intelligence (AI) has been applied to all aspects of life. Machine learning (ML) is one of the important ways to realize AI. With the help of the ML method used by PET/CT imaging technology, there are many studies in the diagnosis and treatment of lung cancer. This article summarizes the application progress of ML based on PET/CT in lung cancer, in order to better serve the clinical. In this study, we searched PubMed using machine learning, lung cancer, and PET/CT as keywords to find relevant articles in the past 5 years or more. We found that PET/CT-based ML approaches have achieved significant results in the detection, delineation, classification of pathology, molecular subtyping, staging, and response assessment with survival and prognosis of lung cancer, which can provide clinicians a powerful tool to support and assist in critical daily clinical decisions. However, ML has some shortcomings such as slightly poor repeatability and reliability.

Concentration Enrichment in a Dissolving Microdroplet: Accessing Sub-nanomolar Electroanalysis

Droplet evaporation has previously been used as a concentration enrichment strategy; however, the measurement technique of choice requires quantification in rather large volumes. Electrochemistry has recently emerged as a method to robustly probe volumes even down to the attoliter (10-18 L) level. We present a concentration enrichment strategy based on the dissolution of a microdroplet placed on the surface of a Au ultramicroelectrode (radius ∼ 6.25 μm). By precisely positioning a 1,2-dichloroethane microdroplet onto the ultramicroelectrode with a microinjector, we are able to track the droplet's behavior optically and electrochemically. Because the droplet spontaneously dissolves over time, given the relative solubility of 1,2-dichloroethane in the water continuous phase, the change in volume with time enriches the concentration of the redox probe (Cp2*(Fe)II) in the droplet. We demonstrate robust electrochemical detection down to sub-nM (800 pM) concentrations of Cp2*(Fe)II. For this droplet, 800 pM constitutes only about 106 molecules. We extend the strategy in a single-blind study to determine unknown concentrations, emphasizing the promise of the new methodology. These results take voltammetric quantification easily to the sub-μM regime.

The sensor applications for prostate and lung cancer biomarkers in terms of electrochemical analysis

Prostate and lung cancers are the most common types of cancer and affect a large part of the population around the world, causing deaths. Therefore, the rapid identification of cancer can profoundly impact reducing cancer-related death rates and protecting human lives. Significant resources have been dedicated to investigating new methods for early disease detection. Cancer biomarkers encompass various biochemical entities, including nucleic acids, proteins, sugars, small metabolites, cytogenetic and cytokinetic parameters, and whole tumor cells in bodily fluids. These tools can be utilized for various purposes, such as risk assessment, diagnosis, prognosis, treatment efficacy, toxicity evaluation, and predicting a return. Due to these versatile and critical purposes, there are widespread studies on the development of new, sensitive, and selective approaches for the determination of cancer biomarkers. This review illustrates the significant lung and prostate cancer biomarkers and their determination utilizing electrochemical sensors, which have the advantage of improved sensitivity, low cost, and simple analysis. Additionally, approaches such as improving sensitivity with nanomaterials and ensuring selectivity with MIPs are used to increase the performance of the sensor. This review aims to overview the most recent electrochemical biosensor applications for determining vital biomarkers of prostate and lung cancers in terms of nanobiosensors and molecularly imprinted polymer (MIP)-based biosensors.

The role of long noncoding RNA DGCR5 in cancers: Focus on molecular targets

Long noncoding RNAs (lncRNAs) are major components of cellular transcripts that are emerging as important players in various biological pathways. Due to their specific expression and functional diversity in a variety of cancers, lncRNAs have promising applications in cancer diagnosis, prognosis, and therapy. Studies have shown that lncRNA DiGeorge syndrome critical region gene 5 (DGCR5) with high specificity and accuracy has the potential to become biomarkers in cancers. LncRNA DGCR5 can be noninvasively extracted from body fluids, tissues, and cells, and can be used as independent or auxiliary biomarkers to improve the accuracy of diagnosis or prognosis. Now, the underlying mechanisms of lncRNAs such as DGCR5 were explored as therapeutic targets, which have been investigated in clinical trials of several cancers. The DGCR5 lacks an appropriate animal model, which is necessary to gain greater knowledge of their functions. While some studies on the uses of DGCR5 have been carried out, the small sample size makes them unreliable. In this review, we presented a compilation of recent publications addressing the potential of lncRNA DGCR5 that could be considered as biomarkers or therapeutic targets, with the hopes of providing promised implications for future cancer therapy.

Fusion of laser-induced breakdown spectroscopy technology and deep learning: a new method to identify malignant and benign lung tumors with high accuracy

Precisely distinguishing between malignant and benign lung tumors is pivotal for suggesting therapeutic strategies and enhancing prognosis, yet this differentiation remains a daunting task. The growth rates, metastatic potentials, and prognoses of benign and malignant tumors differ significantly. Developing specialized treatment protocols tailored to various tumor types is essential for enhancing patient survival outcomes. Employing laser-induced breakdown spectroscopy (LIBS) in conjunction with a deep learning methodology, we attained a high-precision differential diagnosis of malignant and benign lung tumors. First, LIBS spectra of malignant tumors, benign tumors, and normal tissues were collected. The spectra were preprocessed and Z score normalized. Then, the intensities of the Mg II 279.6, Mg I 285.2, Ca II 393.4, Cu II 518.3, and Na I 589.6 nm lines were analyzed in the spectra of the three tissues. The analytical results show that the elemental lines have different contents in the three tissues and can be used as a basis for distinguishing between the three tissues. Finally, the RF-1D ResNet model was constructed by combining the feature importance assessment method of random forest (RF) and one-dimensional residual network (1D ResNet). The classification accuracy, precision, sensitivity, and specificity of the RF-1D ResNet model were 91.1%, 91.6%, 91.3%, and 91.3%, respectively. And the model demonstrates superior performance with an area under the curve (AUC) value of 0.99. The above results show that combining LIBS with deep learning is an effective way to diagnose malignant and benign tumors.

Applications of Pyrrole and Pyridine-based Heterocycles in Cancer Diagnosis and Treatment

BACKGROUND

The escalation of cancer worldwide is one of the major causes of economy burden and loss of human resources. According to the American Cancer Society, there will be 1,958,310 new cancer cases and 609,820 projected cancer deaths in 2023 in the United States. It is projected that by 2040, the burden of global cancer is expected to rise to 29.5 million per year, causing a death toll of 16.4 million. The hemostasis regulation by cellular protein synthesis and their targeted degradation is required for normal cell growth. The imbalance in hemostasis causes unbridled growth in cells and results in cancer. The DNA of cells needs to be targeted by chemotherapeutic agents for cancer treatment, but at the same time, their efficacy and toxicity also need to be considered for successful treatment.

OBJECTIVE

The objective of this study is to review the published work on pyrrole and pyridine, which have been prominent in the diagnosis and possess anticancer activity, to obtain some novel lead molecules of improved cancer therapeutic.

METHODS

A literature search was carried out using different search engines, like Sci-finder, Elsevier, ScienceDirect, RSC etc., for small molecules based on pyrrole and pyridine helpful in diagnosis and inducing apoptosis in cancer cells. The research findings on the application of these compounds from 2018-2023 were reviewed on a variety of cell lines, such as breast cancer, liver cancer, epithelial cancer, etc. Results: In this review, the published small molecules, pyrrole and pyridine and their derivatives, which have roles in the diagnosis and treatment of cancers, were discussed to provide some insight into the structural features responsible for diagnosis and treatment. The analogues with the chromeno-furo-pyridine skeleton showed the highest anticancer activity against breast cancer. The compound 5-amino-N-(1-(pyridin-4- yl)ethylidene)-1H-pyrazole-4-carbohydrazides was highly potent against HEPG2 cancer cell. Redaporfin is used for the treatment of cholangiocarcinoma, biliary tract cancer, cisplatin-resistant head and neck squamous cell carcinoma, and pigmentation melanoma, and it is in clinical trials for phase II. These structural features present a high potential for designing novel anticancer agents for diagnosis and drug development.

CONCLUSION

Therefore, the N- and C-substituted pyrrole and pyridine-based novel privileged small Nheterocyclic scaffolds are potential molecules used in the diagnosis and treatment of cancer. This review discusses the reports on the synthesis of such molecules during 2018-2023. The review mainly discusses various diagnostic techniques for cancer, which employ pyrrole and pyridine heterocyclic scaffolds. Furthermore, the anticancer activity of N- and C-substituted pyrrole and pyridine-based scaffolds has been described, which works against different cancer cell lines, such as MCF-7, A549, A2780, HepG2, MDA-MB-231, K562, HT- 29, Caco-2 cells, Hela, Huh-7, WSU-DLCL2, HCT-116, HBL-100, H23, HCC827, SKOV3, etc. This review will help the researchers to obtain a critical insight into the structural aspects of pyrrole and pyridine-based scaffolds useful in cancer diagnosis as well as treatment and design pathways to develop novel drugs in the future.

An insight into biosensing platforms used for the diagnosis of various lung diseases: A review

Many of the infectious diseases are ubiquitous in nature and pose a threat to global and public health. The original cause for such type of serious maladies can be summarized as the scarcity of appropriate analysis and treatment methods. Pulmonary diseases are considered one of the life-threatening lung diseases that affect millions of people globally. It consists of several types, namely, asthma, lung cancer, tuberculosis, chronic obstructive pulmonary disease, and several respiratory-related infections. This is due to the limited access to well-equipped healthcare facilities for early disease diagnosis. This needs the availability of processes and technologies that can help to stop this harmful disease-diagnosing practice. Various approaches for diagnosing various lung diseases have been developed over time, namely, autopsy, chest X-rays, low-dose CT scans, and so forth. The need of the hour is to develop a rapid, simple, portable, and low-cost method for the diagnosis of pulmonary diseases. So nowadays, biosensors have been becoming one of the highest priority research areas as a potentially useful tool for the early diagnosis and detection of many pulmonary lung diseases. In this review article, various types of biosensors and their applications in the diagnosis of lung-related disorders are expansively explained.

Revolutionizing cancer monitoring with carbon-based electrochemical biosensors

Cancer monitoring plays a critical role in improving patient outcomes by providing early detection, personalized treatment options, and treatment response tracking. Carbon-based electrochemical biosensors have emerged in recent years as a revolutionary technology with the potential to revolutionize cancer monitoring. These sensors are useful for clinical applications because of their high sensitivity, selectivity, rapid response, and compatibility with miniaturized equipment. This review paper gives an in-depth look at the latest developments and the possibilities of carbon-based electrochemical sensors in cancer surveillance. The essential principles of carbon-based electrochemical sensors are discussed, including their structure, operating mechanisms, and critical qualities that make them suited for cancer surveillance. Furthermore, we investigate their applicability in detecting specific cancer biomarkers, evaluating therapy responses, and detecting cancer recurrence early. Additionally, a comparison of carbon-based electrochemical sensor performance measures, including sensitivity, selectivity, accuracy, and limit of detection, is presented in contrast to existing monitoring methods and upcoming technologies. Finally, we discuss prospective tactics, future initiatives, and commercialization opportunities for improving the capabilities of these sensors and integrating them into normal clinical practice. The review highlights the potential impact of carbon-based electrochemical sensors on cancer diagnosis, treatment, and patient outcomes, as well as the importance of ongoing research, collaboration, and validation studies to fully realize their potential in revolutionizing cancer monitoring.

Clinical role of serum tumor markers SCC, NSE, CA 125, CA 19-9, and CYFRA 21-1 in patients with lung cancer

OBJECTIVE

The aim of the study was to assess the diagnostic value of tumor markers in discriminating between lung cancer and benign chest diseases (BCDs).

METHODS

There were 322 patients enrolled in this investigation including 180 cases of lung cancer and 142 cases of BCD. Serum neuron-specific enolase (NSE), cancer antigen 125, cancer antigen 19-9, squamous cell carcinoma-related antigen, and cytokeratin fragment 19 (CYFRA 21-1) were compared between different populations, cancer stages, and before and after treatment. Logistic regression and receiver operating characteristic curves were used to evaluate the diagnostic markers.

RESULTS

Both NSE and CYFRA 21-1 were significantly associated with lung cancer. The CYFRA 21-1 showed the best performance, as well as its combinations, for lung cancer diagnosis. It also showed significant change 6 months after radical surgery in lung cancer patients.

CONCLUSION

The marker CYFRA 21-1 could be developed as an adjuvant marker for the early diagnosis of lung cancer and as a prognostic marker for lung cancer treatment.

Advances in paper-based electrochemical immunosensors: review of fabrication strategies and biomedical applications

Cellulose paper-based sensing devices have shown promise in addressing the accuracy, sensitivity, selectivity, analysis time and cost of current disease diagnostic tools owing to their excellent physical and physiochemical properties, high surface-area-to-volume ratio, strong adsorption capabilities, ease of chemical functionalization for immobilization, biodegradability, biocompatibility and liquid transport by simple capillary action. This review provides a comprehensive overview of recent advancements in the field of electrochemical immunosensing for various diseases, particularly in underdeveloped regions and globally. It highlights the significant progress in fabrication techniques, fluid control, signal transduction and paper substrates, shedding light on their respective advantages and disadvantages. The primary objective of this review article is to compile recent advances in the field of electrochemical immunosensing for the early detection of diseases prevalent in underdeveloped regions and globally, including cancer biomarkers, bacteria, proteins and viruses. Herein, the critical need for new, simplistic early detection strategies to combat future disease outbreaks and prevent global pandemics is addressed. Moreover, recent advancements in fabrication techniques, including lithography, printing and electrodeposition as well as device orientation, substrate type and electrode modification, have highlighted their potential for enhancing sensitivity and accuracy.

Fragmented antibodies in non-small cell lung cancer: A novel nano-engineered delivery system for detection and treatment of cancer

Non-small cell lung cancer (NSCLC) has a long history of defying traditional cytotoxic treatment. Significant advancements in biotechnology, cancer biology, and immunotherapy have provided new insights that have altered the landscape for the management of NSCLC, clearing the way for a new era of pharmaceuticals in the form of monoclonal antibodies and their fragments. Antibody fragments are superior to monoclonal antibodies because of their small size, which allows them to penetrate cells and tissues effectively. When combined with functional nanocarriers, antibody fragments can target cancer cells while offering improved efficacy and fewer off-target effects. We discuss current topics of interest including anti-CTLA-4 mAbs, Talactoferrin alfa (TLF), and the CYFRA 21-1 biomarker, with brief insights into its novel detection system.

Development of recombinant secondary antibody mimics (rSAMs) for immunoassays through genetic fusion of monomeric alkaline phosphatase with antibody binders

In conventional immunoassays, a secondary antibody is used to amplify the signal generated by the binding of the primary antibody to the target analyte. Due to concerns regarding animal use and cost-inefficiency of secondary antibody productions, there is a significant demand for the development of recombinant secondary antibody mimics (rSAMs). Here, we developed rSAMs using a signal-generating enzyme, monomeric alkaline phosphatase (mALP), and antibody-binders, including monomeric streptavidin (mSA2) and mouse IgG1- or rabbit IgG-binding nanobodies (MG1Nb or RNb). The mALP-MG1Nb, mALP-RNb, and mALP-mSA2 were genetically constructed and produced in large quantities using bacterial overexpression systems, which reduced manufacturing costs and time without the use of animals. Each rSAM exhibited high and selective binding to its respective primary antibody, generating linear band signals corresponding to the amounts of target analytes in western blots. The rSAMs also successfully generated sigmoidal signal curves that increased as the sample concentration increased. Moreover, they generated stronger signals than conventional ALP-conjugated secondary antibodies and SA, particularly in the medium to high sample concentration range, in both indirect and sandwich-type indirect ELISAs at the same sample concentration. The rSAMs we developed here may provide new insights to develop novel immunoassay-based analytical and diagnostic tools.

Biosensors for the detection of lung cancer biomarkers: A review on biomarkers, transducing techniques and recent graphene-based implementations

Lung cancer remains the leading cause of cancer-related death. In addition to chest X-rays and computerised tomography, the detection of cancer biomarkers serves as an emerging diagnostic tool for lung cancer. This review explores biomarkers including the rat sarcoma gene, the tumour protein 53 gene, the epidermal growth factor receptor, the neuron-specific enolase, the cytokeratin-19 fragment 21-1 and carcinoembryonic antigen as potential indicators of lung cancer. Biosensors, which utilise various transduction techniques, present a promising solution for the detection of lung cancer biomarkers. Therefore, this review also explores the working principles and recent implementations of transducers in the detection of lung cancer biomarkers. The transducing techniques explored include optical techniques, electrochemical techniques and mass-based techniques for detecting biomarkers and cancer-related volatile organic compounds. Graphene has outstanding properties in terms of charge transfer, surface area, thermal conductivity and optical characteristics, on top of allowing easy incorporation of other nanomaterials. Exploiting the collective merits of both graphene and biosensor is an emerging trend, as evidenced by the growing number of studies on graphene-based biosensors for the detection of lung cancer biomarkers. This work provides a comprehensive review of these studies, including information on modification schemes, nanomaterials, amplification strategies, real sample applications, and sensor performance. The paper concludes with a discussion of the challenges and future outlook of lung cancer biosensors, including scalable graphene synthesis, multi-biomarker detection, portability, miniaturisation, financial support, and commercialisation.

Construction of High-Active SERS Cavities in a TiO2 Nanochannels-Based Membrane: A Selective Device for Identifying Volatile Aldehyde Biomarkers

The accurate, sensitive, and selective on-site screening of volatile aldehyde biomarkers for lung cancer is of utmost significance for preclinical cancer diagnosis and treatment. Applying surface-enhanced Raman scattering (SERS) for gas sensing remains difficult due to the small Raman cross section of most gaseous molecules and interference from other components in exhaled breath. Using an Au asymmetrically coated TiO2 nanochannel membrane (Au/TiO2 NM) as the substrate, a ZIF-8-covered Au/TiO2 NM SERS sensing substrate is designed for the detection of exhaled volatile organic compounds (VOCs). Au/TiO2 NM provides uniformly amplified Raman signals for trace measurements in this design. Importantly, the interfacial nanocavities between Au nanoparticles (NPs) and metal-organic frameworks (MOFs) served as gaseous confinement cavities, which is the key to enhancing the capture and adsorption ability toward gaseous analytes. Both ends of the membrane are left open, allowing gas molecules to pass through. This facilitates the diffusion of gaseous molecules and efficient capture of the target analyte. Using benzaldehyde as a typical gas marker model of lung cancer, the Schiff base reaction with a Raman-active probe molecule 4-aminothiophene (4-ATP) pregrafted on Au NPs enabled trace and multicomponent detection. Moreover, the combination of machine learning (ML) and Raman spectroscopy eliminates subjective assessments of gaseous aldehyde species with the use of a single feature peak, allowing for more accurate identification. This membrane sensing device offers a promising design for the development of a desktop SERS analysis system for lung cancer point-of-care testing (POCT).

Development and Analytical Evaluation of a Point-of-Care Electrochemical Biosensor for Rapid and Accurate SARS-CoV-2 Detection

The COVID-19 pandemic has underscored the critical need for rapid and accurate screening and diagnostic methods for potential respiratory viruses. Existing COVID-19 diagnostic approaches face limitations either in terms of turnaround time or accuracy. In this study, we present an electrochemical biosensor that offers nearly instantaneous and precise SARS-CoV-2 detection, suitable for point-of-care and environmental monitoring applications. The biosensor employs a stapled hACE-2 N-terminal alpha helix peptide to functionalize an in situ grown polypyrrole conductive polymer on a nitrocellulose membrane backbone through a chemical process. We assessed the biosensor's analytical performance using heat-inactivated omicron and delta variants of the SARS-CoV-2 virus in artificial saliva (AS) and nasal swab (NS) samples diluted in a strong ionic solution, as well as clinical specimens with known Ct values. Virus identification was achieved through electrochemical impedance spectroscopy (EIS) and frequency analyses. The assay demonstrated a limit of detection (LoD) of 40 TCID50/mL, with 95% sensitivity and 100% specificity. Notably, the biosensor exhibited no cross-reactivity when tested against the influenza virus. The entire testing process using the biosensor takes less than a minute. In summary, our biosensor exhibits promising potential in the battle against pandemic respiratory viruses, offering a platform for the development of rapid, compact, portable, and point-of-care devices capable of multiplexing various viruses. The biosensor has the capacity to significantly bolster our readiness and response to future viral outbreaks.

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

Cancer is a fatal disease and a significant cause of millions of deaths. Traditional methods for cancer detection often have limitations in identifying the disease in its early stages, and they can be expensive and time-consuming. Since cancer typically lacks symptoms and is often only detected at advanced stages, it is crucial to use affordable technologies that can provide quick results at the point of care for early diagnosis. Biosensors that target specific biomarkers associated with different types of cancer offer an alternative diagnostic approach at the point of care. Recent advancements in manufacturing and design technologies have enabled the miniaturization and cost reduction of point-of-care devices, making them practical for diagnosing various cancer diseases. Furthermore, machine learning (ML) algorithms have been employed to analyze sensor data and extract valuable information through the use of statistical techniques. In this review paper, we provide details on how various machine learning algorithms contribute to the ongoing development of advanced data processing techniques for biosensors, which are continually emerging. We also provide information on the various technologies used in point-of-care cancer diagnostic biosensors, along with a comparison of the performance of different ML algorithms and sensing modalities in terms of classification accuracy.

Molybdenum Disulfide as Tunable Electrochemical and Optical Biosensing Platforms for Cancer Biomarker Detection: A Review

Cancer is a common illness with a high mortality. Compared with traditional technologies, biomarker detection, with its low cost and simple operation, has a higher sensitivity and faster speed in the early screening and prognosis of cancer. Therefore, extensive research has focused on the development of biosensors and the construction of sensing interfaces. Molybdenum disulfide (MoS2) is a promising two-dimensional (2D) nanomaterial, whose unique adjustable bandgap shows excellent electronic and optical properties in the construction of biosensor interfaces. It not only has the advantages of a high catalytic activity and low manufacturing costs, but it can also further expand the application of hybrid structures through different functionalization, and it is widely used in various biosensors fields. Herein, we provide a detailed introduction to the structure and synthesis methods of MoS2, and explore the unique properties and advantages/disadvantages exhibited by different structures. Specifically, we focus on the excellent properties and application performance of MoS2 and its composite structures, and discuss the widespread application of MoS2 in cancer biomarkers detection from both electrochemical and optical dimensions. Additionally, with the cross development of emerging technologies, we have also expanded the application of other emerging sensors based on MoS2 for early cancer diagnosis. Finally, we summarized the challenges and prospects of MoS2 in the synthesis, functionalization of composite groups, and applications, and provided some insights into the potential applications of these emerging nanomaterials in a wider range of fields.

An automatic classification of pulmonary nodules for lung cancer diagnosis using novel LLXcepNN classifier

INTRODUCTION

A critical step to ameliorate diagnosis and extend patient survival is Benign-malignant Pulmonary Nodule (PN) classification at earlier detection. On account of the noise of Computed Tomography (CT) images, the prevailing Lung Nodule (LN) detection techniques exhibit broad variation in accurate prediction.

METHODS

Thus, a novel Nodule Detection along with Classification algorithm for early diagnosis of Lung Cancer (LC) has been proposed. Initially, employing the Adaptive Mode Ostu Binarization (AMOB) technique, the Lung Volumes (LVs) isextortedas of the image together with the extracted lung regions is pre-processed. Then, detection of LNs takes place, and utilizing Geodesic Fuzzy C-Means Clustering (GFCM) Segmentation Algorithm, it is segmented.Next, the vital features are extracted, and the Nodules are classified by utilizing Logarithmic Layer Xception Neural Network (LLXcepNN) Classifier grounded on the extracted feature.

RESULTS

The nodules are classified as Benign Nodules (BN) and Malignant Nodules (MN) by the proposed classifier. Lastly, the Lung CT images are scrutinized.

DISCUSSION

Thus, when weighed against the prevailing techniques, the proposed systems' acquired outcomes exhibit that the rate of accuracy of classification is enhanced.

Electrochemical aptasensors for pathogenic detection toward point-of-care diagnostics

A biosensor system refers to a biomedical device, which detects biological, chemical, or biochemical components by converting those signals to an electrical signal by utilizing and uniting physical or chemical transducer with biorecognition elements. An electrochemical biosensor is generally based on the reaction of either production or consumption of electrons under a three-electrode system. Biosensor systems are exploited in a wide range of areas, such as medicine, agriculture, husbandry, food, industry, environment protection, quality control, waste disposal, and the military. Pathogenic infections are the third leading cause of death worldwide after cardiovascular diseases and cancer. Therefore, there is an urgent need for effective diagnostic tools to control food, water, and soil contamination result in protecting human life and health. Aptamers are peptide or oligonucleotide-based molecules that show very high affinity to their targets that are produced from large pools of random amino acid or oligonucleotide sequences. Generally, aptamers have been utilized for fundamental sciences and clinical implementations for their target-specific affinity and have been intensely exploited for different kinds of biosensor applications for approximately 30 years. The convergence of aptamers with biosensor systems enabled the construction of voltammetric, amperometric, and impedimetric biosensors for the detection of specific pathogens. In this review, electrochemical aptamer biosensors were evaluated by discussing the definition, types, and production techniques of aptamers, the advantages of aptamers as a biological recognition element against their alternatives, and a wide range of aptasensor examples from literature in the detection of specific pathogens.

Emerging Biosensing Methods to Monitor Lung Cancer Biomarkers in Biological Samples: A Comprehensive Review

Lung cancer is the most commonly diagnosed of all cancers and one of the leading causes of cancer deaths among men and women worldwide, causing 1.5 million deaths every year. Despite developments in cancer treatment technologies and new pharmaceutical products, high mortality and morbidity remain major challenges for researchers. More than 75% of lung cancer patients are diagnosed in advanced stages, leading to poor prognosis. Lung cancer is a multistep process associated with genetic and epigenetic abnormalities. Rapid, accurate, precise, and reliable detection of lung cancer biomarkers in biological fluids is essential for risk assessment for a given individual and mortality reduction. Traditional diagnostic tools are not sensitive enough to detect and diagnose lung cancer in the early stages. Therefore, the development of novel bioanalytical methods for early-stage screening and diagnosis is extremely important. Recently, biosensors have gained tremendous attention as an alternative to conventional methods because of their robustness, high sensitivity, inexpensiveness, and easy handling and deployment in point-of-care testing. This review provides an overview of the conventional methods currently used for lung cancer screening, classification, diagnosis, and prognosis, providing updates on research and developments in biosensor technology for the detection of lung cancer biomarkers in biological samples. Finally, it comments on recent advances and potential future challenges in the field of biosensors in the context of lung cancer diagnosis and point-of-care applications.

Evaluation of Linkers' Influence on Peptide-Based Piezoelectric Biosensors' Sensitivity to Aldehydes in the Gas Phase

Recent findings qualified aldehydes as potential biomarkers for disease diagnosis. One of the possibilities is to use electrochemical biosensors in point-of-care (PoC), but these need further development to overcome some limitations. Currently, the primary goal is to enhance their metrological parameters in terms of sensitivity and selectivity. Previous findings indicate that peptide OBPP4 (KLLFDSLTDLKKKMSEC-NH₂) is a promising candidate for further development of aldehyde-sensitive biosensors. To increase the affinity of a receptor layer to long-chain aldehydes, a structure stabilization of the peptide active site via the incorporation of different linkers was studied. Indeed, the incorporation of linkers improved sensitivity to and binding of aldehydes in comparison to that of the original peptide-based biosensor. The tendency to adopt disordered structures was diminished owing to the implementation of suitable linkers. Therefore, to improve the metrological characteristics of peptide-based piezoelectric biosensors, linkers were added at the C-terminus of OBPP4 peptide (KLLFDSLTDLKKKMSE-linker-C-NH₂). Those linkers consist of proteinogenic amino acids from group one: glycine, L-proline, L-serine, and non proteinogenic amino acids from group two: β-alanine, 4-aminobutyric acid, and 6-aminohexanoic acid. Linkers were evaluated with in silico studies, followed by experimental verification. All studied linkers enhanced the detection of aldehydes in the gas phase. The highest difference in frequency (60 Hz, nonanal) was observed between original peptide-based biosensors and ones based on peptides modified with the GSGSGS linker. It allowed evaluation of the limit of detection for nonanal at the level of 2 ppm, which is nine times lower than that of the original peptide. The highest sensitivity values were also obtained for the GSGSGS linker: 0.3312, 0.4281, and 0.4676 Hz/ppm for pentanal, octanal, and nonanal, respectively. An order of magnitude increase in sensitivity was observed for the six linkers used. Generally, the linker's rigidity and the number of amino acid residues are much more essential for biosensors' metrological characteristics than the amino acid sequence itself. It was found that the longer the linkers, the better the effect on docking efficiency.

Direct detection of neuron-specific enolase using a spectrometer-free colorimetric plasmonic biosensor

Sensitive detection of a tumor marker, neuron-specific enolase (NSE), was performed by a label-free direct immunoassay based on a colorimetric plasmonic biosensor. Reflective plasmonic colors of silver nanodome arrays provided a way for a sensitive refractive index sensor based on spectrometer-free colorimetric detection. The direct detection of NSE was demonstrated by a combination of a sensitive sensor substrate and image processing. The limit of detection (LOD) for NSE was determined to be 270 pM, which is lower than the clinical threshold value of NSE used for medical diagnostics of small-cell lung cancer. Since our substrate-based colorimetric plasmonic biosensor is compatible with smartphone detection, we believe that the presented biosensor will open up a way for biosensor technology for point-of-care testing as well as mobile health applications.

Carbon Nanotube Field-Effect Transistor Biosensor with an Enlarged Gate Area for Ultra-Sensitive Detection of a Lung Cancer Biomarker

Carcinoembryonic antigen (CEA) is a recognized biomarker for lung cancer and can be used for early detection. However, the clinical value of CEA is not fully realized due to the rigorous requirement for high-sensitivity and wide-range detection methods. Field-effect transistor (FET) biosensors, as one of the potentially powerful platforms, may detect CEA with a significantly higher sensitivity than conventional clinical testing equipment, while their sensitivity and detection range for CEA are far below the requirement for early detection. Here, we construct a floating gate FET biosensor to detect CEA based on a semiconducting carbon nanotube (CNT) film combined with an undulating yttrium oxide (Y₂O₃) dielectric layer as the biosensing interface. Utilizing an undulating biosensing interface, the proposed device showed a wider detection range and optimized sensitivity and detection limit, which benefited from an increase of probe-binding sites on the sensing interface and an increase of electric double-layer capacitance, respectively. The outcomes of analytical studies confirm that the undulating Y₂O₃ provided the desired biosensing surface for probe immobilization and performance optimization of a CNT-FET biosensor toward CEA including a wide detection range from 1 fg/mL to 1 ng/mL, good linearity, and high sensitivity of 72 ag/mL. More crucially, the sensing platform can function normally in the complicated environment of fetal bovine serum, indicating its great promise for early lung cancer screening.

A novel electrochemical impedance immunosensor for the quantification of CYFRA 21-1 in human serum

A sensitive, simple, and reliable immunosensor was constructed to detect the lowest alteration of a fragment of cytokeratin subunit 19 (CYFRA 21-1), a protein lung carcinoma biomarker. The proposed immunosensor was manufactured with a carbon black C45/polythiophene polymer-containing amino terminal groups (C45-PTNH₂) conductive nanocomposite, resulting in an excellent, biocompatible, low-cost, and electrically conductive electrode surface. Anti-CYFRA 21-1 biorecognition molecules were attached to the electrode thanks to the amino terminal groups of the used PTNH₂ polymer with a relatively simple procedure. All electrode surfaces after modifications were characterized by electrochemical, chemical, and microscopic techniques. Electrochemical impedance spectroscopy (EIS) was also utilized for the evaluation of the analytical feature of the immunosensor. The charge transfer resistance of the immunosensor signal was correlated with the CYFRA 21-1 concentration in the concentration range 0.03 to 90 pg/mL. The limit of detection (LOD) and the limit of quantification (LOQ) of the suggested system were 4.7 fg/mL and 14.1 fg/mL, respectively. The proposed biosensor had favorable repeatability and reproducibility, long storage stability, excellent selectivity, and low cost. Furthermore, it was applied to determine CYFRA 21-1 in commercial serum samples, and satisfactory recovery results (98.63-106.18%) were obtained. Thus, this immunosensor can be offered for clinical purposes as a rapid, stable, low-cost, selective, reproducible, and reusable tool.

Microfluidic Technology, Artificial Intelligence, and Biosensors As Advanced Technologies in Cancer Screening: A Review Article

Cancer screening techniques aim to detect premalignant lesions and enable early intervention to delay the onset of cancer while keeping incidence constant. Technology advancements have led to the development of powerful tools such as microfluidic technology, artificial intelligence, machine learning algorithms, and electrochemical biosensors to aid in early cancer detection. Non-invasive cancer screening methods like virtual colonoscopy and endoscopic ultrasonography have also been developed to provide comprehensive pictures of organs and detect cancer early. This review article provides an overview of recent advances in cancer screening in microfluidic technology, artificial intelligence, and biomarkers through a narrative literature search. Microfluidic devices enable easy handling of sub-microliter volumes and have become a promising tool for cancer detection, drug screening, and modeling angiogenesis and metastasis in cancer research. Machine learning and artificial intelligence have shown high accuracy in oncology-related diagnostic imaging, reducing the manual steps in lesion detection and providing standardized and accurate results, with potential for global standardization in areas like colon polyps, breast cancer, and primary and metastatic brain cancer. A biomarker-based cancer diagnosis is promising for early detection and effective therapy, and electrochemical biosensors integrated with nanoparticles offer multiplexing and amplification capabilities. Understanding these advanced technologies' basics, achievements, and challenges is crucial for advancing their use in oncology.

Controlled Growth of MoS2 on Dendritic Ferric Oxide to Enhance Electrochemiluminescence of Nitrogen-Doped Carbon Quantum Dots for Sensitive Immunoassay

The essential expansion of electrochemiluminescence (ECL) technology into clinical detection relies on sensitive and stable signal and maintenance of the activity of the immune molecules during the analysis. This poses a critical challenge for an ECL biosensor as a luminophore in general requires high potential excitation resulting in a strong ECL signal; nevertheless, it has an irreversible effect on the activity of the antigen or antibody. Herein, a novel electrochemiluminescence (ECL) biosensor utilizing nitrogen-doped carbon quantum dots (N-CQDs) as emitters and molybdenum sulfide/ferric oxide (MoS₂@Fe₂O₃) nanocomposites as a coreaction accelerator was developed for detection of neuron-specific enolase (NSE), a biomarker of small cell lung cancer. The doping of nitrogen allows the CQDs to exhibit ECL signals with low excitation potential, with a more viable activity possible for immune molecules. MoS₂@Fe₂O₃ nanocomposites exhibit superior coreaction acceleration characteristics in hydrogen peroxide than any single component of them, and the highly branched dendrite microstructure provides a large number of binding sites for immune molecular, which is an inevitable factor for trace detection. In addition, ion beam sputtering gold particle technology is introduced into the sensor fabrication via an Au-N bond, which will provide sufficient density orientation for capturing the antibody load via the Au-N bonds. With excellent repeatability, stability, and specificity, the as-purposed sensing platform showed differentiated ECL responses of NSE range from 10.00 fg/mL to 500 ng/mL, and the limit of detection (LOD) was calculated of 6.30 fg/mL (S/N = 3). The proposed biosensor is prospective to provide a new avenue for the analysis of NSE or other biomarkers.

Ratiometric electrochemical OR gate assay for NSCLC-derived exosomes

Non-small cell lung cancer (NSCLC) is the most common pathological type of LC and ranks as the leading cause of cancer deaths. Circulating exosomes have emerged as a valuable biomarker for the diagnosis of NSCLC, while the performance of current electrochemical assays for exosome detection is constrained by unsatisfactory sensitivity and specificity. Here we integrated a ratiometric biosensor with an OR logic gate to form an assay for surface protein profiling of exosomes from clinical serum samples. By using the specific aptamers for recognition of clinically validated biomarkers (EpCAM and CEA), the assay enabled ultrasensitive detection of trace levels of NSCLC-derived exosomes in complex serum samples (15.1 particles μL^-1 within a linear range of 10²-10⁸ particles μL^-1). The assay outperformed the analysis of six serum biomarkers for the accurate diagnosis, staging, and prognosis of NSCLC, displaying a diagnostic sensitivity of 93.3% even at an early stage (Stage I). The assay provides an advanced tool for exosome quantification and facilitates exosome-based liquid biopsies for cancer management in clinics.

Lab-on-a-chip systems for cancer biomarker diagnosis

Lab-on-a-chip (LOC) or micro total analysis system is one of the microfluidic technologies defined as the adaptation, miniaturization, integration, and automation of analytical laboratory procedures into a single instrument or "chip". In this article, we review developments over the past five years in the application of LOC biosensors for the detection of different types of cancer. Microfluidics encompasses chemistry and biotechnology skills and has revolutionized healthcare diagnosis. Superior to traditional cell culture or animal models, microfluidic technology has made it possible to reconstruct functional units of organs on chips to study human diseases such as cancer. LOCs have found numerous biomedical applications over the past five years, including integrated bioassays, cell analysis, metabolomics, drug discovery and delivery systems, tissue and organ physiology and disease modeling, and personalized medicine. This review provides an overview of the latest developments in microfluidic-based cancer research, with pros, cons, and prospects.

PB@PDA nanocomposites as nanolabels and signal reporters for separate-type cathodic photoelectrochemical immunosensors in the detection of carcinoembryonic antigens

Photoelectrochemical (PEC) immunoassays exhibiting high sensitivity and decent operability have considerable potential in areas such as cancer diagnostics. In particular, cathodic PEC configurations can prevent interference from reductive substances, which can occur in biological samples; however, challenges remain in terms of sensitivity and operability. In this study, separate-type PEC immunoassays were developed for carcinoembryonic antigen (CEA) by combining microplate-based immune recognition and off-on cathodic PEC detection. Polydopamine (PDA)-coated Prussian blue (PB) nanoparticles (PB@PDA NPs) were used as signal tags to label the detection antibody. The PB NPs and PDA captured on the microplates both disassembled under strongly alkaline conditions to generate redox-active electron acceptors. The disassembled products were quantitatively transferred to PEC detection cells and synergistically enhanced the PEC current with microstructured BiOI, which operated as a cathodic semiconductor electrode. As proof of principle, carcinoembryonic antigen (CEA) was applied to elucidate the potential application of PEC immunoassay in clinical diagnosis, and the obtained linear range of the sensor was 0.001-100 ng mL^-1 with the detection limit of 54.9 fg mL^-1 (S/N = 3). The proposed separate-type off-on PEC strategy showed high sensitivity and decent operability for CEA detection, indicating its potential for the identification of other tumor markers.

Recent advances in label-free optical, electrochemical, and electronic biosensors for glioma biomarkers

Gliomas are the most commonly occurring primary brain tumor with poor prognosis and high mortality rate. Currently, the diagnostic and monitoring options for glioma mainly revolve around imaging techniques, which often provide limited information and require supervisory expertise. Liquid biopsy is a great alternative or complementary monitoring protocol that can be implemented along with other standard diagnosis protocols. However, standard detection schemes for sampling and monitoring biomarkers in different biological fluids lack the necessary sensitivity and ability for real-time analysis. Lately, biosensor-based diagnostic and monitoring technology has attracted significant attention due to several advantageous features, including high sensitivity and specificity, high-throughput analysis, minimally invasive, and multiplexing ability. In this review article, we have focused our attention on glioma and presented a literature survey summarizing the diagnostic, prognostic, and predictive biomarkers associated with glioma. Further, we discussed different biosensory approaches reported to date for the detection of specific glioma biomarkers. Current biosensors demonstrate high sensitivity and specificity, which can be used for point-of-care devices or liquid biopsies. However, for real clinical applications, these biosensors lack high-throughput and multiplexed analysis, which can be achieved via integration with microfluidic systems. We shared our perspective on the current state-of-the-art different biosensor-based diagnostic and monitoring technologies reported and the future research scopes. To the best of our knowledge, this is the first review focusing on biosensors for glioma detection, and it is anticipated that the review will offer a new pathway for the development of such biosensors and related diagnostic platforms.

Nanotechnology-Enabled Biosensors: A Review of Fundamentals, Design Principles, Materials, and Applications

Biosensors are modern engineering tools that can be widely used for various technological applications. In the recent past, biosensors have been widely used in a broad application spectrum including industrial process control, the military, environmental monitoring, health care, microbiology, and food quality control. Biosensors are also used specifically for monitoring environmental pollution, detecting toxic elements' presence, the presence of bio-hazardous viruses or bacteria in organic matter, and biomolecule detection in clinical diagnostics. Moreover, deep medical applications such as well-being monitoring, chronic disease treatment, and in vitro medical examination studies such as the screening of infectious diseases for early detection. The scope for expanding the use of biosensors is very high owing to their inherent advantages such as ease of use, scalability, and simple manufacturing process. Biosensor technology is more prevalent as a large-scale, low cost, and enhanced technology in the modern medical field. Integration of nanotechnology with biosensors has shown the development path for the novel sensing mechanisms and biosensors as they enhance the performance and sensing ability of the currently used biosensors. Nanoscale dimensional integration promotes the formulation of biosensors with simple and rapid detection of molecules along with the detection of single biomolecules where they can also be evaluated and analyzed critically. Nanomaterials are used for the manufacturing of nano-biosensors and the nanomaterials commonly used include nanoparticles, nanowires, carbon nanotubes (CNTs), nanorods, and quantum dots (QDs). Nanomaterials possess various advantages such as color tunability, high detection sensitivity, a large surface area, high carrier capacity, high stability, and high thermal and electrical conductivity. The current review focuses on nanotechnology-enabled biosensors, their fundamentals, and architectural design. The review also expands the view on the materials used for fabricating biosensors and the probable applications of nanotechnology-enabled biosensors.

Current Update on Biomarkers for Detection of Cancer: Comprehensive Analysis

Early and effective diagnosis of cancer is decisive for its proper management. In this context biomarker-based cancer diagnosis is budding as one of the promising ways for early detection, disease progression monitoring, and effective cancer therapy. Integration of Biosensing devices with different metallic/nonmetallic nanoparticles offers amplification and multiplexing capabilities for simultaneous detection of cancer biomarkers (CB's). This study provides a comprehensive analysis of the most recent designs and fabrication methodologies designed for developing electrochemical biosensors (EB) for early detection of cancers. The role of biomarkers in cancer therapeutics is also discussed.

Sensitive fluorescence biosensor for SARS-CoV-2 nucleocapsid protein detection in cold-chain food products based on DNA circuit and g-CNQDs@Zn-MOF

SARS-CoV-2 isolation from cold-chain food products confirms the possibility of outbreaks through cold-chain food products. RNA extraction combined with RT-PCR is the primary method currently utilized for the detection of SARS-CoV-2. However, the requirement of hours of analytical time and the high price of RT-PCR hinder its worldwide implementation in food supervision. Here, we report a fluorescence biosensor for detection of SARS-CoV-2 N protein. The fluorescence biosensor was fabricated by aptamer-based conformational entropy-driven circuit where molecular beacon strands were labeled with graphitic carbon nitrides quantum dots@Zn-metal-organic framework (g-CNQDs@Zn-MOF) and Dabcyl. The detection of the N protein was achieved via swabbing followed by competitive assay using a fixed amount of N-48 aptamers in the analytical system. A fluorescence emission spectrum was employed for the detection. The detection limit of our fluorescence biosensor was 1.0 pg/mL for SARS-CoV-2 N protein, indicating very excellent sensitivity. The fluorescence biosensor did not exhibit significant cross-reactivity with other N proteins. Finally, the biosensor was successfully applied for the detection of SARS-CoV-2 N protein in actual cold-chain food products showing same excellent accuracy as RT-PCR method. Thus, our fluorescence biosensor is a promising analytical tool for rapid and sensitive detection of SARS-CoV-2 N protein.

Recent Progress in Biosensors for Detection of Tumor Biomarkers

Cancer is a leading cause of death worldwide, with an increasing mortality rate over the past years. The early detection of cancer contributes to early diagnosis and subsequent treatment. How to detect early cancer has become one of the hot research directions of cancer. Tumor biomarkers, biochemical parameters for reflecting cancer occurrence and progression have caused much attention in cancer early detection. Due to high sensitivity, convenience and low cost, biosensors have been largely developed to detect tumor biomarkers. This review describes the application of various biosensors in detecting tumor markers. Firstly, several typical tumor makers, such as neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), prostate-specific antigen (PSA), squamous cell carcinoma antigen (SCCA), carbohydrate, antigen19-9 (CA19-9) and tumor suppressor p53 (TP53), which may be helpful for early cancer detection in the clinic, are briefly described. Then, various biosensors, mainly focusing on electrochemical biosensors, optical biosensors, photoelectrochemical biosensors, piezoelectric biosensors and aptamer sensors, are discussed. Specifically, the operation principles of biosensors, nanomaterials used in biosensors and the application of biosensors in tumor marker detection have been comprehensively reviewed and provided. Lastly, the challenges and prospects for developing effective biosensors for early cancer diagnosis are discussed.

Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers

Cancer is usually not symptomatic in its early stages. However, early detection can vastly improve prognosis. Liquid biopsy holds great promise for early detection, although it still suffers from many disadvantages, mainly searching for specific cancer biomarkers. Here, a new approach for liquid biopsies is proposed, based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray based on a varied set of chemi-sensitive nano-based structured films is developed and used to detect and stage cancer. As a proof-of-concept, three cancer models are tested showing high incidence and mortality rates in the population: breast cancer, ovarian cancer, and pancreatic cancer. The nanoarray has >84% accuracy, >81% sensitivity, and >80% specificity for early detection and >97% accuracy, 100% sensitivity, and >88% specificity for metastasis detection. Complementary mass spectrometry analysis validates these results. The ability to analyze such a complex biological fluid as blood, while considering data of many VOCs at a time using the artificially intelligent nanoarray, increases the sensitivity of predictive models and leads to a potential efficient early diagnosis and disease-monitoring tool for cancer.

Biosensor-Integrated Drug Delivery Systems as New Materials for Biomedical Applications

Biosensor-integrated drug delivery systems are innovative devices in the health area, enabling continuous monitoring and drug administration. The use of smart polymer, bioMEMS, and electrochemical sensors have been extensively studied for these systems, especially for chronic diseases such as diabetes mellitus, cancer and cardiovascular diseases as well as advances in regenerative medicine. Basically, the technology involves sensors designed for the continuous analysis of biological molecules followed by drug release in response to specific signals. The advantages include high sensitivity and fast drug release. In this work, the main advances of biosensor-integrated drug delivery systems as new biomedical materials to improve the patients’ quality of life with chronic diseases are discussed.

Sensitive Electrochemical Biosensor for Rapid Screening of Tumor Biomarker TP53 Gene Mutation Hotspot

Rapid and sensitive detection of cancer biomarkers is crucial for cancer screening, early detection, and improving patient survival rate. The present study proposes an electrochemical gene-sensor capable of detecting tumor related TP53 gene mutation hotspots by self-assembly of sulfhydryl ended hairpin DNA probes tagged with methylene blue (MB) onto a gold electrode. By performing a hybridization reaction with the target DNA sequence, the gene-sensor can rearrange the probe’s structure, resulting in significant electrochemical signal differences by differential pulse voltammetry. When the DNA biosensor is hybridized with 1 μM target DNA, the peak current response signal can decrease more than 60%, displaying high sensitivity and specificity for the TP53 gene. The biosensor achieved rapid and sensitive detection of the TP53 gene with a detection limit of 10 nmol L⁻¹, and showed good specific recognition ability for single nucleotide polymorphism (SNP) and base sequence mismatches in the TP53 gene affecting residue 248 of the P53 protein. Moreover, the biosensor demonstrated good reproducibility, repeatability, operational stability, and anti-interference ability for target DNA molecule in the complex system of 50% fetal bovine serum. The proposed biosensor provides a powerful tool for the sensitive and specific detection of TP53 gene mutation hotspot sequences and could be used in clinical samples for early diagnosis and detection of cancer.

Artificial photosynthesis systems for solar energy conversion and storage: platforms and their realities

In natural photosynthesis, photosynthetic organisms such as green plants realize efficient solar energy conversion and storage by integrating photosynthetic components on the thylakoid membrane of chloroplasts. Inspired by natural photosynthesis, researchers have developed many artificial photosynthesis systems (APS's) that integrate various photocatalysts and biocatalysts to convert and store solar energy in the fields of resource, environment, food, and energy. To improve the system efficiency and reduce the operation cost, reaction platforms are introduced in APS's since they allow for great stability and continuous processing. A systematic understanding of how a reaction platform affects the performance of artificial photosynthesis is conducive for designing an APS with superb solar energy utilization. In this review, we discuss the recent APS's researches, especially those confined on/in platforms. The importance of different platforms and their influences on APS's performance are emphasized. Generally, confined platforms can enhance the stability and repeatability of both photocatalysts and biocatalysts in APS's as well as improve the photosynthetic performance due to the proximity effect. For functional platforms that can participate in the artificial photosynthesis reactions as active parts, a high integration of APS's components on/in these platforms can lead to efficient electron transfer, enhanced light-harvesting, or synergistic catalysis, resulting in superior photosynthesis performance. Therefore, the integration of APS's components is beneficial for the transfer of substrates and photoexcited electrons in artificial photosynthesis. We finally summarize the current challenges of APS's development and further efforts on the improvement of APS's.