Development of point-of-care nanobiosensors for breast cancers diagnosis

Recent Advancements in the Application of Circulating Tumor DNA as Biomarkers for Early Detection of Cancers

Early detection of cancer is vital for increasing patient survivability chances. The three major techniques used to diagnose cancers are instrumental examination, tissue biopsy, and tumor biomarker detection. Circulating tumor DNA (ctDNA) has gained much attention in recent years due to advantages over traditional technology, such as high sensitivity, high specificity, and noninvasive nature. Through the mechanism of apoptosis, necrosis, and circulating exosome release in tumor cells, ctDNA can spread throughout the circulatory system and carry modifications such as methylations, mutations, gene rearrangements, and microsatellite instability. Traditional gene-detection technology struggles to achieve real-time, low-cost, and portable ctDNA measurement, whereas electrochemical biosensors offer low cost, high specificity alongside sensitivity, and portability for the detection of ctDNA. Therefore, this review focuses on describing the recent advancements in ctDNA biomarkers for various cancer types and biosensor developments for real-time, noninvasive, and rapid ctDNA detection. Further in the review, ctDNA sensors are also discussed in regards to their selections of probes for receptors based on the electrode surface recognition elements.

2D graphene-based advanced nanoarchitectonics for electrochemical biosensors: Applications in cancer biomarker detection

Low-cost, rapid, and easy-to-use biosensors for various cancer biomarkers are of utmost importance in detecting cancer biomarkers for early-stage metastasis control and efficient diagnosis. The molecular complexity of cancer biomarkers is overwhelming, thus, the repeatability and reproducibility of measurements by biosensors are critical factors. Electrochemical biosensors are attractive alternatives in cancer diagnosis due to their low cost, simple operation, and promising analytical figures of merit. Recently graphene-derived nanostructures have been used extensively for the fabrication of electrochemical biosensors because of their unique physicochemical properties, including the high electrical conductivity, adsorption capacity, low cost and ease of mass production, presence of oxygen-containing functional groups that facilitate the bioreceptor immobilization, increased flexibility and mechanical strength, low cellular toxicity. Indeed, these properties make them advantageous compared to other alternatives. However, some drawbacks must be overcome to extend their use, such as poor and uncontrollable deposition on the substrate due to the low dispersity of some graphene materials and irreproducibility of the results because of the differences in various batches of the produced graphene materials. This review has documented the most recently developed strategies for electrochemical sensor fabrication. It differs in the categorization method compared to published works to draw greater attention to the wide opportunities of graphene nanomaterials for biological applications. Limitations and future scopes are discussed to advance the integration of novel technologies such as artificial intelligence, the internet of medical things, and triboelectric nanogenerators to eventually increase efficacy and efficiency.

Hydroxyapatite: A journey from biomaterials to advanced functional materials

Hydroxyapatite (HAp), a well-known biomaterial, has witnessed a remarkable evolution over the years, transforming from a simple biocompatible substance to an advanced functional material with a wide range of applications. This abstract provides an overview of the significant advancements in the field of HAp and its journey towards becoming a multifunctional material. Initially recognized for its exceptional biocompatibility and bioactivity, HAp gained prominence in the field of bone tissue engineering and dental applications. Its ability to integrate with surrounding tissues, promote cellular adhesion, and facilitate osseointegration made it an ideal candidate for various biomedical implants and coatings. As the understanding of HAp grew, researchers explored its potential beyond traditional biomaterial applications. With advances in material synthesis and engineering, HAp began to exhibit unique properties that extended its utility to other disciplines. Researchers successfully tailored the composition, morphology, and surface characteristics of HAp, leading to enhanced mechanical strength, controlled drug release capabilities, and improved biodegradability. These modifications enabled the utilization of HAp in drug delivery systems, biosensors, tissue engineering scaffolds, and regenerative medicine applications. Moreover, the exceptional biomineralization properties of HAp allowed for the incorporation of functional ions and molecules during synthesis, leading to the development of bioactive coatings and composites with specific therapeutic functionalities. These functionalized HAp materials have demonstrated promising results in antimicrobial coatings, controlled release systems for growth factors and therapeutic agents, and even as catalysts in chemical reactions. In recent years, HAp nanoparticles and nanostructured materials have emerged as a focal point of research due to their unique physicochemical properties and potential for targeted drug delivery, imaging, and theranostic applications. The ability to manipulate the size, shape, and surface chemistry of HAp at the nanoscale has paved the way for innovative approaches in personalized medicine and regenerative therapies. This abstract highlights the exceptional evolution of HAp, from a traditional biomaterial to an advanced functional material. The exploration of novel synthesis methods, surface modifications, and nanoengineering techniques has expanded the horizon of HAp applications, enabling its integration into diverse fields ranging from biomedicine to catalysis. Additionally, this manuscript discusses the emerging prospects of HAp-based materials in photocatalysis, sensing, and energy storage, showcasing its potential as an advanced functional material beyond the realm of biomedical applications. As research in this field progresses, the future holds tremendous potential for HAp-based materials to revolutionize medical treatments and contribute to the advancement of science and technology.

Electrochemical aptasensor based on the engineered core-shell MOF nanostructures for the detection of tumor antigens

It is essential to develop ultrasensitive biosensors for cancer detection and treatment monitoring. In the development of sensing platforms, metal-organic frameworks (MOFs) have received considerable attention as potential porous crystalline nanostructures. Core-shell MOF nanoparticles (NPs) have shown different diversities, complexities, and biological functionalities, as well as significant electrochemical (EC) properties and potential bio-affinity to aptamers. As a result, the developed core-shell MOF-based aptasensors serve as highly sensitive platforms for sensing cancer biomarkers with an extremely low limit of detection (LOD). This paper aimed to provide an overview of different strategies for improving selectivity, sensitivity, and signal strength of MOF nanostructures. Then, aptamers and aptamers-modified core-shell MOFs were reviewed to address their functionalization and application in biosensing platforms. Additionally, the application of core-shell MOF-assisted EC aptasensors for detection of several tumor antigens such as prostate-specific antigen (PSA), carbohydrate antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), human epidermal growth factor receptor-2 (HER2), cancer antigen 125 (CA-125), cytokeratin 19 fragment (CYFRA21-1), and other tumor markers were discussed. In conclusion, the present article reviews the advancement of potential biosensing platforms toward the detection of specific cancer biomarkers through the development of core-shell MOFs-based EC aptasensors.

Efficient Preparation of a Magnetic Helical Carbon Nanomotor for Targeted Anticancer Drug Delivery

The applications of nanomotors in the biomedical field have been attracting extensive attention. However, it remains a challenge to fabricate nanomotors in a facile way and effectively load drugs for active targeted therapy. In this work, we combine the microwave heating method and chemical vapor deposition (CVD) to fabricate magnetic helical nanomotors efficiently. The microwave heating method can accelerate intermolecular movement, which converts kinetic energy into heat energy and shortens the preparation time of the catalyst used for carbon nanocoil (CNC) synthesis by 15 times. Fe₃O₄ nanoparticles are in situ nucleated on the CNC surface by the microwave heating method to fabricate magnetically driven CNC/Fe₃O₄ nanomotors. In addition, we achieved precise control of the magnetically driven CNC/Fe₃O₄ nanomotors through remote manipulation of magnetic fields. Anticancer drug doxorubicin (DOX) is then efficiently loaded onto the nanomotors via π-π stacking interactions. Finally, the drug-loaded CNC/Fe₃O₄@DOX nanomotor can accurately accomplish cell targeting under external magnetic field control. Under short-time irradiation of near-infrared light, DOX can be quickly released onto target cells to effectively kill the cells. More importantly, CNC/Fe₃O₄@DOX nanomotors allow for single-cell or cell-cluster-targeted anticancer drug delivery, providing a dexterous platform to potentially perform many medically relevant tasks in vivo. The efficient preparation method and application in drug delivery are beneficial for future industrial production and provide inspiration for advanced micro/nanorobotic systems using the CNC as a carrier for a wide range of biomedical applications.

Serum Raman spectroscopy combined with convolutional neural network for rapid diagnosis of HER2-positive and triple-negative breast cancer

Breast cancer is common in women, and its number of patients ranks first among female malignant tumors. Breast cancer is highly heterogeneous, and different types of breast cancer have different biological behaviors and prognoses. Therefore, identifying the different types of breast cancer is of great help in formulating individualized treatment plans. Based on serum Raman spectroscopy and deep learning algorithms, we propose a fast and low-cost diagnosis method for screening triple-negative breast cancer, human epidermal growth factor receptor 2 (HER2)-positive breast cancer, and healthy controls. We collected 75 serum samples in this study, including 23 triple-negative breast cancers, 22 HER2-positive breast cancers, and 30 healthy controls. Using the preprocessed Raman spectra as the input of deep learning, three deep learning models, neural network language model (NNLM), bidirectional long-short-term memory network (BiLSTM), and convolutional neural network (CNN), were established, and the accuracy rates of the three models were 87.78%, 90.37%, and 91.11%, respectively. The experimental results demonstrate the feasibility of serum Raman spectroscopy combined with deep learning algorithms to diagnose breast cancer, which can be used as an effective auxiliary diagnosis method for breast cancer.

Application of serum SERS technology based on thermally annealed silver nanoparticle composite substrate in breast cancer

Liquid biopsy is currently a non-destructive and convenient method of cancer screening, due to human blood containing a variety of cancer-related biomolecules. Therefore, the development of an accurate and rapid breast cancer screening technique combined with breast cancer serum is crucial for the treatment and prognosis of breast cancer patients. In this study, the surface enhanced Raman spectroscopy (SERS) technique is used to enhance the Raman spectroscopy (RS) signal of serum based on a high sensitivity thermally annealed silver nanoparticle/porous silicon bragg mirror (AgNPs/PSB) composite substrate. Compared with RS, SERS reflects more and stronger spectral peak information, which is beneficial to discover new biomarkers of breast cancer. At the same time, to further explore the diagnostic ability of SERS technology for breast cancer. In this study, the raw spectral data are processed by baseline correction, polynomial smoothing, and normalization. Then, the relevant feature information of SERS and RS is extracted by principal component analysis (PCA), and five classification models are established to compare the diagnostic performance of SERS and RS models respectively. The experimental results show that the breast cancer diagnosis model based on the improved SERS substrate combined with the machine learning algorithm can be used to distinguish breast cancer patients from controls. The accuracy, sensitivity, specificity and AUC values of the SVM model are 100%, 100%, 100% and 100%, respectively, as well as the training time of 4ms. The above experimental results show that the SERS technology based on AgNPs/PSB composite substrate, combined with machine learning methods, has great potential in the rapid and accurate identification of breast cancer patients.

Serum Raman spectroscopy combined with multiple classification models for rapid diagnosis of breast cancer

Breast cancer is a malignant tumor with the highest incidence rate in women. Current diagnostic methods are time-consuming, costly, and dependent on physician experience. In this study, we used serum Raman spectroscopy combined with multiple classification algorithms to implement an auxiliary diagnosis method for breast cancer, which will help in the early diagnosis of breast cancer patients. We analyzed the serum Raman spectra of 171 invasive ductal carcinoma (IDC) and 100 healthy volunteers; The analysis showed differences in nucleic acids, carotenoids, amino acids, and lipid concentrations in their blood. These differences provide a theoretical basis for this experiment. First, we used adaptive iteratively reweighted penalized least squares (airPLS) and Savitzky-Golay (SG) for baseline correction and smoothing denoising to remove the effect of noise on the experiment. Then, the Principal component analysis (PCA) algorithm was used to extract features. Finally, we built four classification models: support vector machine (SVM), decision tree (DT), linear discriminant analysis (LDA), and Neural Network Language Model (NNLM). The LDA, SVM, and NNLM achieve 100% accuracy. As supplementary, we added the classification experiment of the raw data. By comparing the experimental results of the two groups, We concluded that the NNLM was the best model. The results show the reliability of the combination of serum Raman spectroscopy and classification models under large sample conditions.

Application of Janus Particles in Point-of-Care Testing

Janus particles (JPs), named after the two-faced Roman god, are asymmetric particles with different chemical properties or polarities. JPs have been widely used in the biomedical field in recent years, including as drug carriers for targeted controlled drug release and as biosensors for biological imaging and biomarker detection, which is crucial in the early detection and treatment of diseases. In this review, we highlight the most recent advancements made with regard to Janus particles in point-of-care testing (POCT). Firstly, we introduce several commonly used methods for preparing Janus particles. Secondly, we present biomarker detection using JPs based on various detection methods to achieve the goal of POCT. Finally, we discuss the challenges and opportunities for developing Janus particles in POCT. This review will facilitate the development of POCT biosensing devices based on the unique properties of Janus particles.

Electrochemical Biosensors for Circulating Tumor DNA Detection

Early diagnosis and treatment have always been highly desired in the fight against cancer, and detection of circulating tumor DNA (ctDNA) has recently been touted as highly promising for early cancer-screening. Consequently, the detection of ctDNA in liquid biopsy is gaining much attention in the field of tumor diagnosis and treatment, which has also attracted research interest from industry. However, it is difficult to achieve low-cost, real-time, and portable measurement of ctDNA in traditional gene-detection technology. Electrochemical biosensors have become a highly promising solution to ctDNA detection due to their unique advantages such as high sensitivity, high specificity, low cost, and good portability. Therefore, this review aims to discuss the latest developments in biosensors for minimally invasive, rapid, and real-time ctDNA detection. Various ctDNA sensors are reviewed with respect to their choices of receptor probes, designs of electrodes, detection strategies, preparation of samples, and figures of merit, sorted by type of electrode surface recognition elements. The development of biosensors for the Internet of Things, point-of-care testing, big data, and big health is analyzed, with a focus on their portable, real-time, and non-destructive characteristics.

Multi-modal imaging probe for EpCAM overexpressed in breast cancer

Breast cancer is a highly lethal and aggressive form of cancer. Early-stager diagnosis and intraoperative guidance are important endeavors for reducing associated morbidity and mortality among breast cancer patients. Epithelial cell adhesion molecule (EpCAM) is aberrantly expressed in the majority of breast carcinoma, making it an attractive imaging biomarker. Herein, we have designed novel EpCAM-targeting peptides (denoted as YQ-S) for precise breast carcinoma detection. The greater binding affinity of the designed peptide YQ-S2 over YQ-S1 and the reported peptide SNF was displayed on different cell lines with flow cytometry analysis, showing a positive correlation with the expression of EpCAM. Besides, YQ-S2 displayed an ideal biosafety profile with no evidence of any acute toxicity. Thus, YQ-S2 was chosen to represent YQ-S. By linking with the near-infrared fluorescent dye (MPA), we further developed the EpCAM-targeting probe (YQ-S2-MPA) for real-time imaging and fluorescence-guided resection of breast cancer tumors. In vivo imaging of the MCF-7 tumor-bearing model demonstrated higher tumor uptake of YQ-S2-MPA compared with that of SNF-MPA. The maximum tumor-to-normal tissue signal ratio of YQ-S2-MPA was 5.1, which was about 2 times that of SNF-MPA. Meanwhile, the metastatic lesions in 4T1 lung metastasis, and lymph node metastasis (LNM) mice were successfully detected under this imaging system. Notably, YQ-S2-MPA had excellent performance in surgical navigation studies in the preclinical models. Moreover, we exploited the ^99mTc-HYNIC-YQ-S2 to localize EpCAM positive tumors successfully. These data proved that YQ-S2 can distinguish EpCAM-positive orthotopic and metastatic tumors from surrounding normal tissues accurately, and possesses the clinical potential as a surgical navigation probe.

Colorimetric Aptasensor Based on Fe₃O₄-Cu2+ Nanozyme with Intrinsic Peroxidase-Like Activity in the Detection of Breast Cancer Exosomes

Because breast cancer cells such as MCF-7, exhibit vital and developmental signs by exosome secretion, diagnosing them in the blood can provide a good index of the presence of breast cancer. However, accurate and inexpensive detection of exosomes in clinical practice faces challenges. Therefore, in the presents study, an aptasensor based on CD63 aptameriron oxide-copper ion nanozymes (Fe₃O₄-Cu²⁺-NZs) was designed with the ability of the CD63 aptamer to interact with the exosome and the release of the Fe₃O₄-Cu²⁺-NZs for peroxidase-like activity on the tetramethylbenzidine (TMB). After fabrication of CD63 aptamer-Fe₃O₄-Cu²⁺-NZs based on hydrothermal method, their physicochemical properties were investigated with the SEM, TEM, DLS, Zeta, XRD and magnetization. To investigate the interaction of CD63 aptamer-Fe₃O₄-Cu²⁺-NZs with exosomes, the required exosomes were extracted from cultured MCF-7 cells. The performance of CD63 aptamer-Fe₃O₄-Cu²⁺-NZs on TMB degradation in the presence and absence of exosomes was investigated through UV-vis adsorption and ocular observations based on colour changes on laboratory and real samples. The results show that the absence of exosomes significantly inhibited the peroxidase-like activity of CD63 aptamer-Fe₃O₄-Cu²⁺-NZs due to the aptamer coating. Under optimal conditions, the designed CD63 aptamer-Fe₃O₄-Cu²⁺-NZs is capable of detecting exosomes in the range of 1.4 × 10⁴-5.6 × 10⁵ particles/μL with a detection limit of 5.91 × 10³ particles/μL. Also, this method showed a satisfactory outcome in detection of cancer cells in real samples. Overall, this colorimetric aptasensor can be used to diagnose breast cancer cells based on a simple and inexpensive approach.

Design of a Ratiometric Plasmonic Biosensor for Herceptin Detection in HER2-Positive Breast Cancer

Breast cancer is the most common cause of cancer death in women; therefore, its early detection and treatment are crucial. To achieve this goal, we designed an optical sensor based on direct interaction of trastuzumab [Herceptin (HER)], a monoclonal antibody used to treat HER2-positive breast cancer, with plasmonic nanoparticles. Surface-modified gold nanoparticles (AuNPs) have gained considerable attention in biosensing techniques over the last years, which actuated these nanoparticles to the heart of various biosensing notions. We have exploited the localized surface plasmon resonance (LSPR) of gold nanoparticles to determine HER in human serum. AuNPs were decorated with negatively charged citrate ions, yielding enhanced direct-surface interaction with HER antibodies. The AuNPs are mixed with silver nanoparticles (AgNPs) in an optimized ratio to increase selectivity and sensitivity further. AuNPs detect the HER antibodies using LSPR, whereas AgNPs help monitor interferences' effect on the sensing media. The three effective factors in HER sensing, including the nanoparticle ratio, temperature, and pH were optimized via response surface methodology (RSM) based on the central composite design (CCD). The sensor's response toward HER was achieved in the linear range of 0.5 × 10^-7 to 40 × 10^-7 M with the detection limit of 3.7 × 10^-9 M and relative standard deviation (RSD) less than 5%. The selectivity of the LSPR sensor was assessed by monitoring its response toward HER in the presence of other biological molecules with similar physicochemical properties. Rapid response time (less than 1 min), selectivity, and the simplicity of the developed LSPR-based sensor are the key advantages of the developed sensor.

Biosensors as Nano-Analytical Tools for COVID-19 Detection

Selective, sensitive and affordable techniques to detect disease and underlying health issues have been developed recently. Biosensors as nanoanalytical tools have taken a front seat in this context. Nanotechnology-enabled progress in the health sector has aided in disease and pandemic management at a very early stage efficiently. This report reflects the state-of-the-art of nanobiosensor-based virus detection technology in terms of their detection methods, targets, limits of detection, range, sensitivity, assay time, etc. The article effectively summarizes the challenges with traditional technologies and newly emerging biosensors, including the nanotechnology-based detection kit for COVID-19; optically enhanced technology; and electrochemical, smart and wearable enabled nanobiosensors. The less explored but crucial piezoelectric nanobiosensor and the reverse transcription-loop mediated isothermal amplification (RT-LAMP)-based biosensor are also discussed here. The article could be of significance to researchers and doctors dedicated to developing potent, versatile biosensors for the rapid identification of COVID-19. This kind of report is needed for selecting suitable treatments and to avert epidemics.

Laser-triggered combination therapy by iron sulfide-doxorubicin@functionalized nanozymes for breast cancer therapy

Background

The use of magnetic nanozymes (NZs) with the ability to synchronize gas therapy through photodynamic and chemotherapy in the treatment of breast cancer has received much attention.

Results

Hence, in this study, we designed a bovine lactoferrin-coated iron sulfide NZs containing doxorubicin (abbreviated as: FeS-Dox@bLf NZs) by wet-chemical synthesis method. Then, the physicochemical characteristics of synthesized NZs were explored by several methods. Also, the level of Fe²⁺, H₂S and Dox releases from FeS-Dox@Lf NZs. Also, the cytotoxic effects of FeS-Dox@Lf NZs were investigated by cellular assays. After intravenous injections of NZs and laser irradiation, significant effects of FeS-Dox@Lf NZs on mice weight and tumor status were observed. Afterwards, not only the distribution of Dox in the body was examined by fluorescent, but also the time of Fe clearance and the amount of Dox and Fe retention in vital tissues were determined. The findings confirm that FeS-Dox@Lf NZs, in addition to targeted drug distribution in tumor tissue, resulted in superior therapeutic performance compared to free Dox due to reduced Dox side effects in vital tissues, and increased level of free radicals in 4T1 cells.

Conclusion

Overall, FeS-Dox@Lf NZs with the ability to synchronize chemotherapy and gas therapy raised hopes for more effective treatment of breast cancer.

Graphic abstract

Diagnostic and drug release systems based on microneedle arrays in breast cancer therapy

Microneedle arrays have recently received much attention as cancer detection and treatment platforms, because invasive injections and detection of the biopsy are not needed, and drug metabolism by the liver, as well as adverse effects of systemic drug administration, are diminished. Microneedles have been used for diagnosis, vaccination, and in targeted drug delivery of breast cancer. In this review, we summarize the recent progress in diagnosis and targeted drug delivery for breast cancer treatment, using microneedle arrays to deliver active molecules through the skin. The results not only suggest that health and well-being of patients are improved, but also that microneedle arrays can deliver anticancer compounds in a relatively noninvasive manner, based on body weight, breast tumor size, and circulation time of the drug. Moreover, microneedles could allow simultaneous loading of multiple drugs and enable controlled release, thus effectively optimizing or preventing drug-drug interactions. This review is designed to encourage the use of microneedles for diagnosis and treatment of breast cancer, by describing general properties of microneedles, materials used for construction, mechanism of action, and principal benefits. Ongoing challenges and future perspectives for the application of microneedle array systems in breast cancer detection and treatment are highlighted.

Recent advances in biosensing approaches for point-of-care breast cancer diagnostics: challenges and future prospects

Timely and accurate diagnosis of breast cancer is essential for efficient treatment and the best possible survival rates. Biosensors have emerged as a smart diagnostic platform for the detection of biomarkers specific to the onset, recurrence, and therapeutic drug monitoring of breast cancer. There have been exciting recent developments, including significant improvements in the validation, sensitivity, specificity, and integration of sample processing steps to develop point-of-care (POC) integrated micro-total analysis systems for clinical settings. The present review highlights various biosensing modalities (electrical, optical, piezoelectric, mass, and acoustic sensing). It provides deep insights into their design principles, signal amplification strategies, and comparative performance analysis. Finally, this review emphasizes the status of existing integrated micro-total analysis systems (μ-TAS) for personalized breast cancer therapeutics and associated challenges and outlines the approach required to realize their successful translation into clinical settings.

3D bioprinting of engineered breast cancer constructs for personalized and targeted cancer therapy

The bioprinting technique with specialized tissue production allows the study of biological, physiological, and behavioral changes of cancerous and non-cancerous tissues in response to pharmacological compounds in personalized medicine. To this end, to evaluate the efficacy of anticancer drugs before entering the clinical setting, tissue engineered 3D scaffolds containing breast cancer and derived from the especially patient, similar to the original tissue architecture, can potentially be used. Despite recent advances in the manufacturing of 3D bioprinted breast cancer tissue (BCT), many studies still suffer from reproducibility primarily because of the uncertainty of the materials used in the scaffolds and lack of printing methods. In this review, we present an overview of the breast cancer environment to optimize personalized treatment by examining and identifying the physiological and biological factors that mimic BCT. We also surveyed the materials and techniques related to 3D bioprinting, i.e, 3D bioprinting systems, current strategies for fabrication of 3D bioprinting tissues, cell adhesion and migration in 3D bioprinted BCT, and 3D bioprinted breast cancer metastasis models. Finally, we emphasized on the prospective future applications of 3D bioprinted cancer models for rapid and accurate drug screening in breast cancer.

Quantitative analysis of various targets based on aptamer and functionalized Fe3O4@graphene oxide in dairy products using pregnancy test strip and smartphone

Pregnancy test strips are one of the most mature and widely used commercial lateral flow devices used to determine pregnancy. Being a simple and rapid detection method, human chorionic gonadotropin (hCG) was used with different aptamers (hCG-apt) as probes for the detection of metal ions, small organic molecules, and proteins. Quantitative detection of target analytes was achieved using a smartphone app and a portable device developed in our laboratory. The results showed detection ranges of 1 nM-1 μM, 0.1 nM-10 μM and 32 nM-500 nM for Pb²⁺, chloramphenicol, and β-lactoglobulin, respectively, and the corresponding visual detection limits in dairy products were 5 nM, 1 nM and 50 nM, respectively. Based on these results, rapid detection of multiple analytes can be realized through aptamer modification, thereby broadening the application range of commercial lateral flow devices for analysis of food chemistry.

Rapid diagnostics of coronavirus disease 2019 in early stages using nanobiosensors: Challenges and opportunities

The rapid outbreak of coronavirus disease 2019 (COVID-19) around the world is a tragic and shocking event that demonstrates the unpreparedness of humans to develop quick diagnostic platforms for novel infectious diseases. In fact, statistical reports of diagnostic tools show that their accuracy, specificity and sensitivity in the detection of COVID hampered by some challenges that can be eliminated by using nanoparticles (NPs). In this study, we aimed to present an overview on the most important ways to diagnose different kinds of viruses followed by the introduction of nanobiosensors. Afterward, some methods of COVID-19 detection such as imaging, laboratory and kit-based diagnostic tests are surveyed. Furthermore, nucleic acids/protein- and immunoglobulin (Ig)-based nanobiosensors for the COVID-19 detection infection are reviewed. Finally, current challenges and future perspective for the development of diagnostic or monitoring technologies in the control of COVID-19 are discussed to persuade the scientists in advancing their technologies beyond imagination. In conclusion, it can be deduced that as rapid COVID-19 detection infection can play a vital role in disease control and treatment, this review may be of great help for controlling the COVID-19 outbreak by providing some necessary information for the development of portable, accurate, selectable and simple nanobiosensors.

Detection of breast cancer of various clinical stages based on serum FT-IR spectroscopy combined with multiple algorithms

BACKGROUND

Breast cancer screening is time consuming, requires expensive equipment, and has demanding requirements for doctors. Hence, a large number of breast cancer patients may miss screening and early treatment, which greatly threatens their health around the world. Infrared spectroscopy may be able to be used as a screening tool for breast cancer detection. Fourier transform infrared (FT-IR) spectroscopy of serum was combined with traditional machine learning algorithms to achieve an auxiliary diagnosis that could quickly and accurately distinguish patients with different stages of breast cancer, including stage 1 disease, from control subjects without breast cancer.

MATERIALS AND METHODS

FT-IR spectroscopy were performed on the serum of 114 non-cancer control subjects, 35 patients with stage I, 43 patients with stage II, and 29 patients with stage III & IV breast cancer. Due to the experimental sample imbalance, we used the oversampling to process the four classes of sample. The oversampling selected Synthetic Minority Oversampling Technique (SMOTE). Subsequently, we used the random discarding method in undersampling to do experiments as well. The average FT-IR spectroscopy results for the four groups showed differences in phospholipids, nucleic acids, lipids, and proteins between non-cancer control subjects and breast cancer patients at different stages. Based on these differences, four classification models were used to classify stage I, II, III & IV breast cancer patients and non-cancer control subjects. First, standard normal variate transformation (SNV) was used to preprocess the original data, and then partial least squares (PLS) was used for feature extraction. Finally, the five models were established including extreme learning machine (ELM), k-nearest neighbor (KNN), genetic algorithms based on support vector machine (GA-SVM), particle swarm optimization-support vector machine (PSO-SVM) and grid search-support vector machine (GS-SVM).

CONCLUSION

In oversampling experiment, the GS-SVM classifier obtained the highest average classification accuracy of 95.45 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 90 %; breast cancer stage II was 84.62 %; and breast cancer stage III & IV was 100 %. In undersampling experiment, the GA-SVM model obtained the highest average classification accuracy of 100 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 100 %; breast cancer stage II was 100 %; and breast cancer stage III & IV was 100 %. The results show that FT-IR spectroscopy combined with powerful classification algorithms has great potential in distinguishing patients with different stages of breast cancer from non-cancer control subjects. In addition, this research provides a reference for future multiclassification studies of cervical cancer, ovarian cancer and other female high-incidence cancers through serum FT-IR spectroscopy.

In vivo nano-biosensing element of red blood cell-mediated delivery

Biosensors based on nanotechnology are developing rapidly and are widely applied in many fields including biomedicine, environmental monitoring, national defense and analytical chemistry, and have achieved vital positions in these fields. Novel nano-materials are intensively developed and manufactured for potential biosensing and theranostic applications while lacking comprehensive assessment of their potential health risks. The integration of diagnostic in vivo biosensors and the DDSs for delivery of therapeutic drugs holds an enormous potential in next-generation theranostic platforms. Controllable, precise, and safe delivery of diagnostic biosensing devices and therapeutic agents to the target tissues, organs, or cells is an important determinant in developing advanced nanobiosensor-based theranostic platforms. Particularly, inspired by the comprehensive biological investigations on the red blood cells (RBCs), advanced strategies of RBC-mediated in vivo delivery have been developed rapidly and are currently in different stages of transforming from research and design to pre-clinical and clinical investigations. In this review, the RBC-mediated delivery of in vivo nanobiosensors for applications of bio-imaging at the single-cell level, advanced medical diagnostics, and analytical detection of biomolecules and cellular activities are presented. A comprehensive perspective of the technical framework of the state-of-the-art RBC-mediated delivery systems is explained in detail to inspire the design and implementation of advanced nanobiosensor-based theranostic platforms taking advantage of RBC-delivery modalities.

Au-coated Fe3O4 core-shell nanohybrids with photothermal activity for point-of-care immunoassay for lipoprotein-associated phospholipase A2 on a digital near-infrared thermometer

A portable photothermal immunoassay based on Au-coated magnetic Fe₃O₄ core-shell nanohybrids (Au-Fe₃O₄) was developed for point-of-care (POC) testing of lipoprotein-associated phospholipase A₂ (Lp-PLA₂) on a digital near-infrared (NIR) thermometer. Au-Fe₃O₄ photothermal materials were first synthesized through reverse micelle method, and then functionalized with polyclonal rabbit anti-human Lp-PLA₂ antibody. A sandwiched immunoreaction was carried out in polyclonal mouse anti-human Lp-PLA₂ antibody-coated microplate using Au-Fe₃O₄-labeled antibody as the detection antibody. With formation of sandwich-type immunocomplex, the captured Au-Fe₃O₄ on the plate converted the light into heat under an 808-nm laser irradiation (1.5 W cm^-2), thereby resulting in the increasing temperature of the detection solution. The temperature variations relative to surrounding temperature was determined on a portable NIR thermometer. Several labeling protocols with gold nanoparticle, Fe₃O₄ nanoparticle, or Au-Fe₃O₄ nanohybrids were investigated for determination of Lp-PLA₂ and improved analytical features were achieved with the core-shell Au-Fe₃O₄ nanohybrids. Under optimum conditions, Au-Fe₃O₄-based immunoassay exhibited good photothermal responses for the detection of Lp-PLA₂ with a dynamic linear range of 0.01-100 ng mL^-1 at a low detection limit of 8.6 pg mL^-1. Good reproducibility and intermediate precision were less than 9.7%. Other biomarkers or proteins did not interfere with responses of this system. An acceptable accuracy was acquired for analysis of human serum sample between Au-Fe₃O₄-based photothermal immunoassay and commercialized human Lp-PLA₂ ELISA kit.

Electrochemical Nanobiosensors for Detection of Breast Cancer Biomarkers

This comprehensive review paper describes recent advances made in the field of electrochemical nanobiosensors for the detection of breast cancer (BC) biomarkers such as specific genes, microRNA, proteins, circulating tumor cells, BC cell lines, and exosomes or exosome-derived biomarkers. Besides the description of key functional characteristics of electrochemical nanobiosensors, the reader can find basic statistic information about BC incidence and mortality, breast pathology, and current clinically used BC biomarkers. The final part of the review is focused on challenges that need to be addressed in order to apply electrochemical nanobiosensors in a clinical practice.