Noninvasive Multiplexed Analysis of Bladder Cancer-Derived Urine Exosomes via Janus Magnetic Microspheres

Multispectral 3D DNA Machine Combined with Multimodal Machine Learning for Noninvasive Precise Diagnosis of Bladder Cancer

Extracellular vesicle (EV) molecular phenotyping offers enormous opportunities for cancer diagnostics. However, the majority of the associated studies adopted biomarker-based unimodal analysis to achieve cancer diagnosis, which has high false positives and low precision. Herein, we report a multimodal platform for the high-precision diagnosis of bladder cancer (BCa) through a multispectral 3D DNA machine in combination with a multimodal machine learning (ML) algorithm. The DNA machine was constructed using magnetic microparticles (MNPs) functionalized with aptamers that specifically identify the target of interest, i.e., five protein markers on bladder-cancer-derived urinary EVs (uEVs). The aptamers were hybridized with DNA-stabilized silver nanoclusters (DNA/AgNCs) and a G-quadruplex/hemin complex to form a sensing module. Such a DNA machine ensured multispectral detection of protein markers by fluorescence (FL), inductively coupled plasma mass spectrometry (ICP-MS), and UV-vis absorption (Abs). The obtained data sets then underwent uni- or multimodal ML for BCa diagnosis to compare the analytical performance. In this study, urine samples were obtained from our prospective cohort (n = 45). Our analytical results showed that the 3D DNA machine provided a detection limit of 9.2 × 103 particles mL-1 with a linear range of 4 × 104 to 5 × 107 particles mL-1 for uEVs. Moreover, the multimodal data fusion model exhibited an accuracy of 95.0%, a precision of 93.1%, and a recall rate of 93.2% on average, while those of the three types of unimodal models were no more than 91%. The elevated diagnosis precision by using the present fusion platform offers a perspective approach to diminishing the rate of misdiagnosis and overtreatment of BCa.

Polymer Microspheres and Their Application in Cancer Diagnosis and Treatment

Cancer is a significant global public health issue with increasing morbidity and mortality rates. To address this challenge, novel drug carriers such as nano-materials, liposomes, hydrogels, fibers, and microspheres have been extensively researched and utilized in oncology. Among them, polymer microspheres are gaining popularity due to their ease of preparation, excellent performance, biocompatibility, and drug-release capabilities. This paper categorizes commonly used materials for polymer microsphere preparation, summarizes various preparation methods (emulsification, phase separation, spray drying, electrospray, microfluidics, and membrane emulsification), and reviews the applications of polymer microspheres in cancer diagnosis, therapy, and postoperative care. The current status and future development directions of polymer microspheres in cancer treatment are analyzed, highlighting their importance and potential for improving patient outcomes.

Advances of machine learning-assisted small extracellular vesicles detection strategy

Detection of extracellular vesicles (EVs), particularly small EVs (sEVs), is of great significance in exploring their physiological characteristics and clinical applications. The heterogeneity of sEVs plays a crucial role in distinguishing different types of cells and diseases. Machine learning, with its exceptional data processing capabilities, offers a solution to overcome the limitations of conventional detection methods for accurately classifying sEV subtypes and sources. Principal component analysis, linear discriminant analysis, partial least squares discriminant analysis, XGBoost, support vector machine, k-nearest neighbor, and deep learning, along with some combined methods such as principal component-linear discriminant analysis, have been successfully applied in the detection and identification of sEVs. This review focuses on machine learning-assisted detection strategies for cell identification and disease prediction via sEVs, and summarizes the integration of these strategies with surface-enhanced Raman scattering, electrochemistry, inductively coupled plasma mass spectrometry and fluorescence. The performance of different machine learning-based detection strategies is compared, and the advantages and limitations of various machine learning models are also evaluated. Finally, we discuss the merits and limitations of the current approaches and briefly outline the perspective of potential research directions in the field of sEV analysis based on machine learning.

Microfluidics-derived hierarchical microparticles for the delivery of dienogest for localized endometriosis therapy

Drug therapy is one of the most important strategies for treating gynecological diseases. Local drug delivery is promising for achieving optimal regional drug exposure, considering the complex anatomy and dynamic environment of the upper genital tract. Here, we present microparticle-based microcarriers with a hierarchical structure for localized dienogest (DNG) delivery and endometriosis treatment. The microparticles were fabricated by microfluidics and consisted of photo-crosslinked bovine serum albumin hydrogel particles (D@P-B MPs) encapsulating DNG-loaded PLGA (poly lactic-co-glycolic acid) microspheres. Such design enables the microparticles to have sustained release capacity and cell adhesion ability. Based on this, the microparticles were applied for the treatment of peritoneal endometriosis through intraperitoneal injection. The performance of the microparticles in inhibiting the growth of ectopic lesions as well as their anti-inflammatory, anti-angiogenesis, and pelvic pain-relieving effects are well demonstrated in vivo. These findings indicate that the present hierarchical microparticles are good candidates for localized treatment of endometriosis and are promising for the management of gynecological diseases. STATEMENT OF SIGNIFICANCE: We prepared photo-crosslinked bovine serum albumin hydrogel particles (D@P-B MPs) encapsulating DNG-loaded PLGA microspheres using microfluidic electrospray. Such hierarchical structure provided multiple functions of the particles as drug carriers. The hierarchical microparticles not only supported the sustained release of drugs but also provided adhesion to human ectopic endometrial stromal cells. The hierarchical microparticles represented a localized treatment method for endometriosis and is promising for the management of gynecological diseases.

Amplification-Free Analysis of Bladder Cancer MicroRNAs on Wrinkled Silica Nanoparticles with DNA-Functionalized Quantum Dots

Bladder cancer (BC) occurrence and progression are accompanied by alterations in microRNAs (miRNAs) expression levels. Simultaneous detection of multiple miRNAs contributes to the accuracy and reliability of the BC diagnosis. In this work, wrinkled silica nanoparticles (WSNs) were applied as the microreactor for multiplex miRNAs analysis without enzymes or nucleic acid amplification. Conjugated on the surface of WSNs, the S9.6 antibody was adopted as the universal module for binding DNA/miRNA duplexes, regardless of their sequence. Furthermore, single-stranded DNA (ssDNA) was labeled with quantum dots (QDs) for identifying a given miRNA to form QDs-ssDNA/miRNA, which enabled the specific capture of the corresponding QDs on the wrinkled surface of WSNs. Based on the detection of fluorescence signals that were ultimately focused on WSNs, target miRNAs could be sensitively identified to a femtomolar level (5 fM) with a wide dynamic range of up to 6 orders of magnitude. The proposed strategy achieved high specificity to obviously distinguish single-base mutation sequences and possessed multiplex assay capability. Moreover, the assay exhibited excellent practicability in the multiplex detection of miRNAs in clinical serum specimens.

Exosomes: Toward a potential application in bladder cancer diagnosis and treatment

Bladder cancer (BC) is a prevalent malignant tumor of the urinary system, known for its rapid progression and high likelihood of recurrence. Despite ongoing efforts, clinical diagnosis and treatment of BC remain limited. As such, there is an urgent need to investigate potential mechanisms underlying this disease. Exosomes, which contain a variety of bioactive molecules such as nucleic acids, proteins, and lipids, are regarded as extracellular messengers because they are implicated in facilitating intercellular communication in various diseases and are pivotal in tumor advancement, serving as a promising avenue for such researches. Nevertheless, the heterogeneous nature of BC necessitates further exploration of the potential involvement of exosomes in disease progression. This review comprehensively outlines the biological attributes of exosomes and their critical roles in tumorigenesis, while also discussing their potential applications in regulating the progression of BC involving clinical diagnosis, prognostication and treatment.

Recent Advances in Electrochemical Detection of Cell Energy Metabolism

Cell energy metabolism is a complex and multifaceted process by which some of the most important nutrients, particularly glucose and other sugars, are transformed into energy. This complexity is a result of dynamic interactions between multiple components, including ions, metabolic intermediates, and products that arise from biochemical reactions, such as glycolysis and mitochondrial oxidative phosphorylation (OXPHOS), the two main metabolic pathways that provide adenosine triphosphate (ATP), the main source of chemical energy driving various physiological activities. Impaired cell energy metabolism and perturbations or dysfunctions in associated metabolites are frequently implicated in numerous diseases, such as diabetes, cancer, and neurodegenerative and cardiovascular disorders. As a result, altered metabolites hold value as potential disease biomarkers. Electrochemical biosensors are attractive devices for the early diagnosis of many diseases and disorders based on biomarkers due to their advantages of efficiency, simplicity, low cost, high sensitivity, and high selectivity in the detection of anomalies in cellular energy metabolism, including key metabolites involved in glycolysis and mitochondrial processes, such as glucose, lactate, nicotinamide adenine dinucleotide (NADH), reactive oxygen species (ROS), glutamate, and ATP, both in vivo and in vitro. This paper offers a detailed examination of electrochemical biosensors for the detection of glycolytic and mitochondrial metabolites, along with their many applications in cell chips and wearable sensors.

Designing Bioorthogonal Reactions for Biomedical Applications

Bioorthogonal reactions are a class of chemical reactions that can be carried out in living organisms without interfering with other reactions, possessing high yield, high selectivity, and high efficiency. Since the first proposal of the conception by Professor Carolyn Bertozzi in 2003, bioorthogonal chemistry has attracted great attention and has been quickly developed. As an important chemical biology tool, bioorthogonal reactions have been applied broadly in biomedicine, including bio-labeling, nucleic acid functionalization, drug discovery, drug activation, synthesis of antibody-drug conjugates, and proteolysis-targeting chimeras. Given this, we summarized the basic knowledge, development history, research status, and prospects of bioorthogonal reactions and their biomedical applications. The main purpose of this paper is to furnish an overview of the intriguing bioorthogonal reactions in a variety of biomedical applications and to provide guidance for the design of novel reactions to enrich bioorthogonal chemistry toolkits.

Preparation and Analysis of Structured Color Janus Droplets Based on Microfluidic 3D Droplet Printing

The microfluidic technique for the three-dimensional (3D) printing of Janus droplets offers precise control over their size, orientation, and positioning. The proposed approach investigates the impact of variables such as the volume ratio of the oil phase, droplet size, and the ratio of nonionic surfactants on the dimensions of the structured color apertures of Janus droplets. The findings reveal that structured color apertures modulate accurately. Furthermore, fabricating color patterns facilitates cat, fish, and various other specific shapes using structured color Janus droplets. The color patterns exhibit temperature-sensitive properties, enabling them to transition between display and concealed states. Herein, the adopted microfluidic technique creates Janus droplets with customizable characteristics and uniform size, solving orientation as well as space arrangement problems. This approach holds promising applications for optical devices, sensors, and biomimetic systems.

Cobalt Iron Oxide (CoFe2O4) Nanoparticles Induced Toxicity in Rabbits

The market for nanoparticles has grown significantly over the past few decades due to a number of unique qualities, including antibacterial capabilities. It is still unclear how nanoparticle toxicity works. In order to ascertain the toxicity of synthetic cobalt iron oxide (CoFe2O4) nanoparticles (CIONPs) in rabbits, this study was carried out. Sixteen rabbits in total were purchased from the neighborhood market and divided into two groups (A and B), each of which contained eight rabbits. The CIONPs were synthesized by the co-precipitation method. Crystallinity and phase identification were confirmed by X-ray diffraction (XRD). The average size of the nanoparticles (13.2 nm) was calculated by Scherrer formula (Dhkl = 0.9 λ/β cos θ) and confirmed by TEM images. The saturation magnetization, 50.1 emug-1, was measured by vibrating sample magnetometer (VSM). CIONPs were investigated as contrast agents (CA) for magnetic resonance images (MRI). The relaxivity (r = 1/T) of the MRI was also investigated at a field strength of 0.35 T (Tesla), and the ratio r2/r1 for the CIONPs contrast agent was 6.63. The CIONPs were administrated intravenously into the rabbits through the ear vein. Blood was collected at days 5 and 10 post-exposure for hematological and serum biochemistry analyses. The intensities of the signal experienced by CA with CIONPs were 1427 for the liver and 1702 for the spleen. The treated group showed significantly lower hematological parameters, but significantly higher total white blood cell counts and neutrophils. The results of the serum biochemistry analyses showed significantly higher and lower quantities of different serum biochemical parameters in the treated rabbits at day 10 of the trial. At the microscopic level, different histological ailments were observed in the visceral organs of treated rabbits, including the liver, kidneys, spleen, heart, and brain. In conclusion, the results revealed that cobalt iron oxide (CoFe2O4) nanoparticles induced toxicity via alterations in multiple tissues of rabbits.

A novel platelet risk score for stratifing the tumor immunophenotypes, treatment responses and prognosis in bladder carcinoma: results from real-world cohorts

Background: Although the durable efficacy of immune checkpoint inhibitors (ICIs) in BLCA has been confirmed in numerous studies, not all patients benefit from their application in the clinic. Platelets are increasingly being found to be closely associated with cancer progression and metastasis; however, their comprehensive role in BLCA remains unclear. Methods: We comprehensively explored platelet expression patterns in BLCA patients using an integrated set of 244 related genes. Correlations between these platelet patterns with tumor microenvironment (TME) subtypes, immune characteristics and immunotherapy efficacies were explored. In addition, a platelet risk score (PRS) was generated for individual prognosis and verified the ability to predict prognosis, precise TME phenotypes, and immunotherapy efficacies. Results: Genes were clustered into two patterns that represented different TME phenotypes and had the ability to predict immunotherapy efficacy. We constructed a PRS that could predict individual prognosis with satisfactory accuracy using TCGA-BLCA. The results remained consistent when PRS was validated in the GSE32894 and Xiangya cohort. Moreover, we found that our PRS was positively related to tumor-infiltrating lymphocytes (TILs) in the TCGA-BLCA and Xiangya cohort. As expected, patients with higher PRS exhibited more sensitive to immunotherapy than patients with lower PRS. Finally, we discovered that a high PRS indicated a basal subtype of BLCA, whereas a low PRS indicated a luminal subtype. Conclusion: Platelet-related genes could predict TME phenotypes in BLCA. We constructed a PRS that could predict the TME, prognosis, immunotherapy efficacy, and molecular subtypes in BLCA.

Extracellularly Detectable Electrochemical Signals of Living Cells Originate from Metabolic Reactions

Direct detection of cellular redox signals has shown immense potential as a novel living cell analysis tool. However, the origin of such signals remains unknown, which hinders the widespread use of electrochemical methods for cellular research. In this study, the authors found that intracellular metabolic pathways that generate adenosine triphosphate (ATP) are the main contributors to extracellularly detectable electrochemical signals. This is achieved through the detection of living cells (4,706 cells/chip, linearity: 0.985) at a linear range of 7,466-48,866. Based on this discovery, the authors demonstrated that the cellular signals detected by differential pulse voltammetry (DPV) can be rapidly amplified with a developed medium containing metabolic activator cocktails (MACs). The DPV approach combined with MAC treatment shows a remarkable performance to detect the effects of the anticancer drug CPI-613 on cervical cancer both at a low drug concentration (2 µm) and an extremely short treatment time (1 hour). Furthermore, the senescence of mesenchymal stem cells could also be sensitively quantified using the DPV+MAC method even at a low passage number (P6). Collectively, their findings unveiled the origin of redox signals in living cells, which has important implications for the characterization of various cellular functions and behaviors using electrochemical approaches.