Xiaodong Chen, Nanyang Technological University, Singapore, Singapore João Conde, Universidade Nova de Lisboa, Lisbon, Portugal Wenguo Cui, Shanghai Jiao Tong University, Shanghai, China Chunhai Fan, Shanghai Jiao Tong University, Shanghai, China Qinghua He, Nanchang University, Nanchang, China Aleksandar Ivanov, Imperial College London, London, UK Ali Khademhosseini, University of California-Los Angeles, Los Angeles, USA Luke Lee, University of California, Berkeley, USA Chwee Teck Lim, National University of Singapore, Singapore, Singapore Yuehe Lin, Washington State University, Pullman, USA Qingjun Liu, Zhejiang University, Hangzhou, China Zhe Liu, Tianjin University, Tianjin, China Niren Murthy, University of California, Berkeley, USA Je-Kyun Park, Korea Advanced Institute of Science and Technology, Daejeon, Korea Kanyi Pu, Nanyang Technological University, Singapore, Singapore Jianhua Qin, Dalian Institute of Chemical Physics, CAS, Dalian, China Milica Radisic, University of Toronto, Toronto, Canada Hélder A. Santos, University of Helsinki, Helsinki, Finland Amy Shen, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan Patrick M Sluss, Massachusetts General Hospital/Harvard Medical School ⋅ Pathology, Boston, USA Joseph Wang, University California-San Diego, La Jolla, USA Jingjuan Xu, Nanjing University, Nanjing, China Yingwei Yang, Jilin University, Changchun, China Radek Zbořil, Palacky University in Olomouc, Olomouc, Czech Republic Xiao-Bing Zhang, Hunan University, Changsha, China Lei Zheng, Southern Medical University, Guangzhou, China
Artificial intelligence (AI) has reformed the healthcare system with its compelling capabilities of processing biomedical data for disease diagnosis, prediction, and individualized management. The eye, as a non‐invasive observation window for many systemic diseases, can be used to detect the signs of chronic kidney diseases, and other diseases like hypertension and type 2 diabetes mellitus, based on specific manifestations of retinal images. Recent advances using AI technology have posed a great potential of using retinal images for rapid mass screening and prognosis prediction of kidney diseases. Herein, we outlined the key applications of AI in ophthalmology and the detection of systemic diseases based on retinal imaging, especially the current progress of retinal image‐based AI models for the detection and prediction of kidney diseases. We hope to shed light on the current opportunities and future challenges in this field to provide suggestions for further improvement and applications.
Abstract Angiotensin converting enzyme 2 (ACE2) played a critical role in regulating renin‐angiotensin‐aldosterone system (RAAS). In this research, 68Ga‐cyc‐DX600 was synthesized as PET tracer of ACE2 imaging. ACE2 positron emission tomography/magnetic resonance (PET/MR) was preliminary administered on twelve healthy volunteers, and the images were normalized and registered to establish the standard model of ACE2 PET. In diseased conditions, 68Ga‐cyc‐DX600 PET and 18F‐FDG PET were compared for COVID‐19 (one in acute phase and three in post‐COVID), anemia (n = 1) and malignancies (n = 2) to evaluate the diagnostic efficiency. 68Ga‐cyc‐DX600 PET was of a definite ACE2 dependence. For the tracer uptake of ACE2 PET/MR of female and male, differences existed in salivary glands, upper respiratory tract and kidneys, meanwhile, age, and body mass index (BMI) were also the confounding factors. RAAS‐related tissue and organs were of the relatively higher tracer uptake, such as SUVmean of cardiac chamber (3.786 ± 1.495), liver (5.342 ± 2.267), spleen (4.465 ± 2.508), and kidney (4.906 ± 1.619 for female and 8.431 ± 5.179 for male). For COVID‐19, ACE2 PET revealed ACE2 fluctuations, particularly in the susceptible organs, including liver, spleen and testis. In the case of anemia, the activated local RAS in the bone marrow was of diffuse high tracer uptake. ACE2 PET of malignancies added supplementary information to FDG PET. 68Ga‐cyc‐DX600‐based ACE2 PET models were established for visually monitoring of whole‐body ACE2 expression. The feasibility of ACE2 PET in supervising disease was primarily proved in COVID‐19, anemia and malignancies as providing a comprehensive view on the disease process and functional recovery.
Abstract Single‐atom catalysts (SACs) have attracted extensive interest owing to their maximized atomic utilization, low cost as well as outstanding catalytic activity, selectivity, and stability for diverse applications. Due to their excellent performance in electrocatalysis, SACs can be applied to electrochemical sensors, which have been a predominant tool employed in biosensing. In very recent studies, SAC‐based electrochemical biosensors have demonstrated enhanced sensing performances in biomarker detection and in vivo analysis. However, a comprehensive review of SAC‐based electrochemical biosensors has not been reported yet. Herein, we present a summary of the synthesis methods of SACs with their application in electrochemical sensor establishment and electrochemical characterization methods in electrochemical sensing. Biomedical applications utilizing SAC‐based electrochemical biosensors are introduced. Finally, the existing challenges and future prospects of SACs in the field of electrochemical biosensing are discussed.
Abstract Genetic testing plays an important role in human health management and disease prevention. However, traditional genetic testing methods have been unable to fulfill the current diagnostic needs owing to several limitations, including high cost, complexity, and difficulty in performing. Smartphones have multiple inherent advantages, such as easy portability, ubiquity, fast processing speed, and excellent imaging capabilities, and have enormous potential in realizing rapid on‐site genetic testing. The present review documents the research progress of smartphone‐based optical imaging biosensors in the fields of colorimetry, fluorescence, and microscopic imaging for genetic testing. Furthermore, the review describes their potential applications in diagnostics, which range from infectious diseases to hereditary diseases and cancers. Finally, the challenges and perspectives of smartphone‐based optical imaging biosensors regarding genetic testing are discussed.
Abstract Visual interpretation is considered the gold standard for amyloid scans in clinical practice. However, dichotomous classification of amyloid deposition by visual reading always results in bias due to rater experience. Therefore, there is a need for a more lenient and flexible amyloid‐equivocal classification in clinical practice. A total of 461 participants were included in this study. Amyloid and glucose positron‐emission tomography was performed, and neuropsychological tests were evaluated. A disease‐specific deep‐learning method was used to identify amyloid equivocality. Amyloid deposition, glucose metabolism, and cognitive performance were analyzed and compared among amyloid‐positive, amyloid‐negative, and amyloid‐equivocal groups. Clinically diagnosed Alzheimer's disease individuals and subjects with normal cognition were used to create amyloid biomarker cut points to support the definition of equivocal amyloid deposition. A total of 139 amyloid‐equivocal individuals were identified by deep learning methods. They displayed intermediate amyloid deposition between that of amyloid‐positive (standardized uptake value ratio [SUVr]: 1.25 ± 0.10 vs. 1.47 ± 0.20, p < 0.001) and amyloid‐negative (SUVr: 1.25 ± 0.10 vs. 1.18 ± 0.07, p < 0.001) individuals. No difference in glucose metabolism or cognitive performance was observed between amyloid negativity and equivocality. Furthermore, the SUVr for the whole cortex, the precuneus, and the frontal lobe served as auxiliary criteria supporting the diagnosis of equivocal amyloid deposition. We also established a guide to assist in the interpretation of amyloid equivocality by visual reading with auxiliary criteria including two cut points and deep learning methods.
Noninvasive detection of deep lesions remains a long‐standing goal for clinical applications, with depth estimation of a single lesion in heterogeneous tissues being a key challenge. Currently, optical techniques are widely applied for lesion detection, but they face difficulties in achieving rapid and precise lesion depth estimation, particularly when the lesions are buried in thick heterogeneous tissues and the applied irradiance is below clinically maximum permissible exposure. Herein, we theoretically and experimentally demonstrate a universal method for depth prediction of phantom lesions labeled with surface‐enhanced Raman scattering nanotags in thick biological tissues using ratiometric transmission Raman spectroscopy (TRS). We begin by highlighting the linear relationship between the natural logarithm of Raman peak‐to‐peak ratio and the lesion depth and establishing a home‐built TRS system with the clinically safe irradiance. We achieve an accurate depth prediction for phantom lesions hidden in 6‐cm‐thick ex vivo homogeneous tissue with a root mean squared error (RMSE) as low as 2.42%. Additionally, we predict the depth of phantom lesions buried in 5‐cm‐thick ex vivo heterogeneous tissues with an RMSE of down to 8.35%. We also demonstrate the applicability of this method theoretically for highly heterogeneous tissues such as complex in vivo environments. This work provides a rapid, robust, and universal method to estimate the depth of lesions in complex biological samples, demonstrating the potential of ratiometric Raman spectroscopy for lesion localization in clinical applications.
A low-cost microfluidic platform integrated with a flexible heater was developed for in situ temperature-dependent spectroscopic measurement at the point of care. After verifying the system by comparing on-chip spectroscopic measurement of methylene blue with the conventional spectroscopy, we demonstrated its applications in temperature-dependent absorption spectroscopy of a model biomolecule, curcumin. The system is portable, battery-powered and requires ultra-low volumes of analytes, which is highly suitable for point-of-care characterization.
Dongxue Zhang and Liang Qiao describe intestine-on-a-chip and its application in intestinal disease study and pharmacological research. In this cover, intestine-on-a-chip is established to construct human intestinal microenvironment and mimic human intestinal physiology. Intestinal epithelium with intestinal villi and mucus, as well as vascular endothelium are formed in the intestine-on-a-chip. Pathogenic bacteria, viruses, and tumor cells are cocultured with intestinal epithelium to simulate various intestinal diseases such as intestinal inflammation and cancer. The intestine-on-a-chip is also used to conduct pharmacological studies and proceed drug screening.
Serum/plasma proteome analysis can monitor physiological and pathological changes in the human population. In addition to the proteins secreted by tissues, the common blood proteins, including some inherently high‐abundance proteins, also play an important role in the process of the physiological process of organisms. Herein, we establish a Common Serum Protein Database (1090 proteins and 1727 peptides) and integrate it with the Cancer Serum Atlas ( www.cancerserumatlas.com ) we built before to construct the deep and comprehensive cancer serum protein atlas (DCCSP Atlas). This atlas contains over 2700 proteins with targeted mass spectrometry assays and spectra of corresponding unique peptides. We simultaneously targeted 539 proteins in 29 sera of two hardly distinguishable cancer types (breast and lung) and non‐tumor controls using the DCCSP Atlas and the pan‐targeted proteomic strategy. Areas under the receiver operating characteristic curve exceeded 0.96 for cancer detection and classification. The DCCSP Atlas will enable the pan‐targeting of common serum proteins and cancer‐secreted proteins to improve the sensitivity and specificity of proteomics‐based multi‐cancer detection and classification.
Cuproptosis, the current form of regulated cell death characterized by copper overload, oligomerization of lipoacylated proteins, and loss of the Fe-S cluster proteins, has been proposed to function closely with human diseases including cancer. Since the first identification in 2022, a wide range of strategies have been developed to induce cuproptosis for cancer therapy, such as small-molecule drugs and nanomaterials. Although many reviews related to cuproptosis have been reported, they remain at a basic mechanism level and a summary covering recent progress in the field of nanotechnologies in cuproptosis-based cancer therapy has not yet been presented. Therefore, it is time to fill the gap and shed light on future directions for the application of this promising tool to fight against cancer. In this minireview, we first expounded the mechanism of action of cuproptosis and emphasized the feasibility of triggering cuproptosis for cancer therapy. The recent progress of cancer treatments based on nanoparticle-induced cuproptosis was then described. Finally, the challenges and future development directions of the emerging field of cuproptosis were also discussed.
Abstract The cellular uptake of drug carriers to the cytosol of a specific cell remains challenging, and a non‐classical supramolecular strategy is motivated. Here, we select a model host–guest complex in which a diamino‐viologen (1,1′‐bis(4‐aminophenyl)‐[4,4′‐bipyridine]−1,1′‐diium dichloride [VG]) fluorescent tag was engulfed by cucurbit[8]uril (CB8) and covalently linked to alginate polysaccharides (alginic acid [ALG]) as the modified drug vehicle. When adsorbed on the ALG surface, the encapsulation of VG was first confirmed utilizing Fourier transform infrared and nuclear magnetic resonance spectroscopic methods. Solid optical measurements (diffuse reflectance spectroscopy, photoluminescence, and time‐resolved photoluminescence) revealed emissive materials at around 650 nm and that CB8 enhanced the rigidity of the modified hydrogel. The molar composition of 2:1 for the complexation of VG to CB8 on the alginate surface and the thermal stabilities were also confirmed using thermogravimetric analysis and differential scanning calorimetry techniques. CB8 induced a dramatic decrease in the average size of the VGALG polysaccharides from 485 to 165 nm and a turnover in their charge from –19.8 to +14.4 mV. Flow cytometry with inhibitors of various endocytosis pathways was employed to track the cellular uptake across different blood cell types: human T‐cell leukemia 1301 and peripheral blood mononuclear cells. Noticeably, complexation of VG with the CB8 host on top of the sugar platform dramatically enhanced the internalization into 1301 cells (viz. from 1% to 99%) at a concentration of 1.8 mg/mL via caveolae‐mediated endocytosis because of the size reduction, turnover in the charge from negative to positive, and rigidity induction. These observations reveal a more profound understanding of the macrocyclic effects on drug delivery.
Extracellular vesicles (EVs) provide real-time information about the physiological and pathological states of parental cells and are potential biomarkers for disease diagnosis. Many methods for isolating EVs from body fluids and techniques for analyzing EVs biomolecules, including protein, nucleic acids, and lipids, have emerged with potential for clinical application.
Abstract Organoids are three‐dimensional cell aggregates with near‐physiologic cell behaviors and can undergo long‐term expansion in vitro. They are amenable to high‐throughput drug screening processes, which renders them a viable preclinical model for drug development. The procedure of organoid‐based high‐throughput screening has been extensively employed to discover small‐molecule drugs, encompassing the steps of generating organoids, examining efficient drugs in organoid cultures, and data assessment. Compared to small molecules, peptides are more straightforward to synthesize, can be modified chemically, and demonstrate high target specificity and low cytotoxicity. Therefore, they have emerged as promising carriers to deliver drugs to disease‐associated targets and could be efficient therapeutic drugs for various diseases. To date, organoids have been used to evaluate the efficacy of certain peptide agents; however, no organoid‐based high‐throughput screening of peptide drugs has been reported. Given the advantages of peptide drugs, there is an urgent need to establish organoid‐based peptide high‐throughput screening platforms. In this review, we discuss the typical approach of screening small‐molecular drugs with the use of organoid cultures, as well as provide an overview of the studies that have incorporated organoids in peptide research. Drawing on the knowledge from small molecular screens, we explore the difficulties and potential avenues for creating new platforms to identify peptide agents using organoid models.
Future nanofluidics-based mass spectrometry would open up exciting avenues for exploring the unknown complex and heterogenous subcellular worlds.
VIEWVolume 4, Issue 2 e281 INSIDE FRONT COVEROpen Access Inside Front Cover: Theranostic applications of multifunctional carbon nanomaterials (View 2/2023) Shima Masoudi Asil, Shima Masoudi AsilSearch for more papers by this authorErick Damian Guerrero, Erick Damian GuerreroSearch for more papers by this authorGeorgina Bugarini, Georgina BugariniSearch for more papers by this authorJoshua Cayme, Joshua CaymeSearch for more papers by this authorNydia De Avila, Nydia De AvilaSearch for more papers by this authorJaime Garcia, Jaime GarciaSearch for more papers by this authorAdrian Hernandez, Adrian HernandezSearch for more papers by this authorJulia Mecado, Julia MecadoSearch for more papers by this authorYazeneth Madero, Yazeneth MaderoSearch for more papers by this authorFrida Moncayo, Frida MoncayoSearch for more papers by this authorRosario Olmos, Rosario OlmosSearch for more papers by this authorDavid Perches, David PerchesSearch for more papers by this authorJacob Roman, Jacob RomanSearch for more papers by this authorDiana Salcido-Padilla, Diana Salcido-PadillaSearch for more papers by this authorEfrain Sanchez, Efrain SanchezSearch for more papers by this authorChristopher Trejo, Christopher TrejoSearch for more papers by this authorPaulina Trevino, Paulina TrevinoSearch for more papers by this authorMd Nurunnabi, Md NurunnabiSearch for more papers by this authorMahesh Narayan, Mahesh NarayanSearch for more papers by this author Shima Masoudi Asil, Shima Masoudi AsilSearch for more papers by this authorErick Damian Guerrero, Erick Damian GuerreroSearch for more papers by this authorGeorgina Bugarini, Georgina BugariniSearch for more papers by this authorJoshua Cayme, Joshua CaymeSearch for more papers by this authorNydia De Avila, Nydia De AvilaSearch for more papers by this authorJaime Garcia, Jaime GarciaSearch for more papers by this authorAdrian Hernandez, Adrian HernandezSearch for more papers by this authorJulia Mecado, Julia MecadoSearch for more papers by this authorYazeneth Madero, Yazeneth MaderoSearch for more papers by this authorFrida Moncayo, Frida MoncayoSearch for more papers by this authorRosario Olmos, Rosario OlmosSearch for more papers by this authorDavid Perches, David PerchesSearch for more papers by this authorJacob Roman, Jacob RomanSearch for more papers by this authorDiana Salcido-Padilla, Diana Salcido-PadillaSearch for more papers by this authorEfrain Sanchez, Efrain SanchezSearch for more papers by this authorChristopher Trejo, Christopher TrejoSearch for more papers by this authorPaulina Trevino, Paulina TrevinoSearch for more papers by this authorMd Nurunnabi, Md NurunnabiSearch for more papers by this authorMahesh Narayan, Mahesh NarayanSearch for more papers by this author First published: 24 April 2023 https://doi.org/10.1002/viw2.281AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Graphical Abstract Carbon nanomaterials are potent multifunctional materials with diverse biomedical applications in theranostic techniques. They can be considered as safe and efficient tools for non-invasive diagnostic techniques such as magnetic resonance imaging (MRI). Various functionalized CNMs exhibit a great capacity to improve cell targeting of anticancer drugs. These therapeutic carbon-based materials bring new hope for advancing the diagnosis sector for a wide range of diseases such as brain disorders, cardiovascular diseases, and cancer in the near future. Volume4, Issue2April 2023e281 RelatedInformation
The accurate evaluation of telomerase activity, a typical cancer biomarker, is vital for early cancer screening. In this study, we developed a dark‐field microscopy (DFM) visual single‐particle detection scheme to detect telomerase activity based on automatic counting gold nanoparticles (AuNPs). This method started with attaching the telomerase substrate (TS) primer to the magnetic beads (MBs) through streptavidin‐biotin interaction. In the presence of telomerase and dNTPs, the TS primer was expanded with (TTAGGG) n repeat units to form the telomerase extension product (MBs‐telomerase extension product), which could be hybridized with the complementary DNA (cDNA) modified with AuNPs through Au‐S bonds (AuNPs‐SH‐cDNA). After magnetic separation and DNA double‐strand unwinding, AuNPs were collected from the supernatant, and the telomerase activity was quantitatively measured by visually counting bright spots based on DFM. This strategy achieved a limit of detection as low as 1 HeLa cell and distinguished telomerase activity among different cell lines, thus verifying its excellent sensitivity and specificity. Further, two common telomerase inhibitors (BIBR1532 and curcumin) were screened with the consistent IC 50 values with other methods, respectively. It is worth mentioning that this strategy can clearly identify bladder cancer among various urinary diseases. Consequently, the visualized automatic particle counting strategy is potential as a powerful tool in early and noninvasive diagnosis of bladder cancer.
Derived from the D‐luciferin regeneration pathway in firefly body, the click condensation reaction between 2‐cyanobenzothiazole (CBT) and D‐cysteine (Cys) (CBT‐Cys click reaction) possesses unique advantages, including superior biocompatibility, high second order reaction rate, and metal‐free mild conditions, emerging as a powerful bioorthogonal tool for a variety of chemical biological applications. Moreover, owing to its programmable controllability (e.g., pH, reduction, or enzyme), CBT‐Cys click reaction is exploited to fabricate stimuli‐activatable imaging probes with self‐assembling behaviors in physiological context. At stimuli‐rich pathological lesions of interest, these probes undergo CBT‐Cys click reaction to form cyclic dimers/oligomers or linear polymers, and further self‐assemble into nanostructures. The in situ formed nanostructures promote the selective accumulation and retention of imaging agent cargos at pathological lesions, thus enabling precise and enhanced in vivo imaging of diseases (especially tumors). To address the significance and recent breakthroughs of smart CBT‐Cys probes for enhanced optical imaging of tumors/other diseases, we herein propose this mini‐review, in which advances (particularly in recent 5 years) and potential challenges (or chances) in this field are emphasized.
In article number 20220078, Ying Tan and co-workers describe a convenient visualized automatic gold nanoparticles (AuNPs) counting strategy based on dark-field microscopy (DFM) for single-cell level telomerase activity detection. In this cover, after magnetic separation and DNA double-strand unwinding, AuNPs were collected, and the telomerase activity was quantitatively measured by visually counting bright spots based on DFM. This strategy can clearly identify bladder cancer in various urinary diseases, indicating its potential for early and non-invasive diagnosis of bladder cancer.
