CRISPR-Hg: Rapid and visual detection of Hg2+ based on PCR coupled with CRISPR/Cas12a.

Mercury (Hg) is a notorious toxic heavy metal, causing neurotoxicity and liver damage, posing grave threats to human health and environmental safety. There is an urgent imperative for developing novel Hg2+ detection methods. In this work, we developed a CRISPR-based method for Hg2+ detection named CRISPR-Hg. A CRISPR/Cas12a system was employed and could be activated by the PCR product, generating fluorescence signals based on the trans-cleavage activity. CRISPR-Hg exhibited remarkable selectivity and specificity, achieving a detection limit of 10 pM and minimal interference with background signals. This approach has been successfully applied to detect Hg2+ in real samples, including water, soil, and mushroom. Ulteriorly, a portable device was devised to streamline the readout of fluorescence signals by a smartphone within 30 min. We offer an affordable, highly selective and visually interpretable method for Hg2+ detection, with the potential for broad application in Hg2+ monitoring for food safety and public health.

Rapid Separation and Detection of Drugs in Complex Biological Matrix Using TD-CDI Mass Spectrometer.

The drug detection technology plays a pivotal role in the domains of pharmaceutical regulation and law enforcement. In this study, we introduce a method that combines thermal desorption corona discharge ionization (TD-CDI) with mass spectrometry for efficient drug detection. The TD-CDI module, characterized by its compact and simple design, enables the separation of analytes within seconds and real-time presentation of one or two analyte peaks on the mass spectrum most of the time, which reduces matrix interference and improves detection performance. Through experimental investigation, we studied the characteristics of TD-CDI for analyte separation and detection, even with the same mass number, and optimized the TD-CDI approach. TD-CDI-MS was employed for the rapid detection of drugs in various traditional medicine, food products, and human samples. Additionally, by utilizing TD-CDI for segmented hair direct analysis, it becomes possible to trace the drug usage cycle of individuals. This underscores the feasibility of the proposed analytical method within the realm of drug detection.

Label-free Colorimetric Detection of Viral RNA Based on Clustered Regularly Interspaced Short Palindromic Repeats and Gold Nanoparticles with a Portable Device.

Viral infections, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are some of the most dangerous threats to humans. SARS-CoV-2 has caused a global pandemic, highlighting the unprecedented demand for rapid and portable diagnostic methods. To meet these requirements, we designed a label-free colorimetric platform that combines the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated proteins (Cas) 12a system for naked-eye detection (named LFP). This method utilizes reverse transcription loop-mediated isothermal amplification (RT-LAMP) and the trans-cleavage activity of the CRISPR/Cas12a system to increase the sensitivity and specificity of the reaction. This platform can detect as few as 4 copies/µL of RNA and produces no false positive results when tested against the influenza virus. To better meet the requirements of point-of-care (POC) detection, we developed a portable device that can be applied in resource-poor and densely populated regions. The LFP assay holds great potential for application in resource-limited settings, and the label-free gold nanoparticle (AuNPs) probe can reduce costs, making it suitable for large-scale screening. We expect that the LFP assay will be promising for the POC screening of COVID-19.

A low-voltage alternant direct current electroporation chip for ultrafast releasing the genome DNA of Helicobacter pylori bacterium.

Nucleic acid detection, as an important molecular diagnostic method, is widely used in bacterial identification, disease diagnosis. For detecting the nucleic acid of bacteria, the prerequisite is to release nucleic acids inside the bacteria. The common means to release nucleic acids is the chemical method, which involves complex processes, is time-consuming, and remains chemical inhibitors. Compared with chemical methods, electroporation as a physical method has the advantages of easy operation, short-time consumption, and chemical reagents free. However, the current works using electroporation often necessitates high-frequency or high-voltage conditions, entailing bulky power devices. Herein, we propose a low-voltage alternant direct current (LADC) electroporation chip and the corresponding miniature device for ultrafast releasing the genome DNA from Helicobacter pylori (H. pylori) for detection. We connected a micrometer-interdigital electrode in the chip with a 20 V portable battery to make the miniature device. Using this low-voltage device, our chip released genome DNA of H. pylori within only 5 ms, achieving a cell lysis rate of 99.5%. We further combined this chip with a colorimetric loop-mediated isothermal amplification assay to visually detect H. pylori within ~ 25 min at 10 CFU/µL. We detected 11 clinical samples using the chip, and the detection results were consistent with those of the clinical standard. The results indicate that the LADC electroporation chip is useful for ultrafast release of genome DNA from bacteria and is expected to promote the development of nucleic acid detection in POCT and other scenarios.

A radiomics and genomics-derived model for predicting metastasis and prognosis in colorectal cancer.

Approximately 50% of colorectal cancer (CRC) patients would develop metastasis with poor prognosis, therefore, it is necessary to effectively predict metastasis in clinical treatment. In this study, we aimed to establish a machine-learning model for predicting metastasis in CRC patients by considering radiomics and transcriptomics simultaneously. Here, 1023 patients with CRC from three centers were collected and divided into five queues (Dazhou Central Hospital n = 517, Nanchong Central Hospital n = 120 and the Cancer Genome Atlas (TCGA) n = 386). A total of 854 radiomics features were extracted from tumor lesions on CT images, and 217 differentially expressed genes were obtained from non-metastasis and metastasis tumor tissues using RNA sequencing. Based on radiotranscriptomic (RT) analysis, a novel RT model was developed and verified through genetic algorithms (GA). Interleukin (IL)-26, a biomarker in RT model, was verified for its biological function in CRC metastasis. Furthermore, 15 radiomics variables were screened through stepwise regression, which was highly correlated with the IL26 expression level. Finally, a radiomics model (RA) was established by combining GA and stepwise regression analysis with radiomics features. The RA model exhibited favorable discriminatory ability and accuracy for metastasis prediction in two independent verification cohorts. We designed multicenter, multi-scale cohorts to construct and verify novel combined radiomics and genomics models for predicting metastasis in CRC. Overall, RT model and RA model might help clinicians in directing personalized diagnosis and therapeutic regimen selection for patients with CRC.

Rapid On-Site Detection of SARS-CoV-2 Using RT-LAMP Assay with a Portable Low-Cost Device.

Emerging infectious diseases pose a serious threat to human health and affect social stability. In recent years, the epidemic situation of emerging infectious diseases is very serious; among these infectious diseases, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected many countries and regions in a short time. The prevention and treatment of these diseases require rapid on-site detection methods. However, the common detection method, RT-PCR, requires expensive instruments, complex operations, and professional operators. Here, we developed a portable low-cost assay for rapid on-site detection of viral nucleic acid using reverse transcription-loop-mediated isothermal amplification (RT-LAMP). The SARS-CoV-2 RNA can be successfully amplified within 15 min in a thermos, and the detection result is read rapidly in a portable low-cost device with a sensitivity of 100 copies/µL. The portable low-cost device consists of a black box, a laser or LED and a filter, costing only a few cents. The rapid on-site detection method can provide strong support for the control of biological threats such as infectious diseases. It is also an emergency detection method for low-resource settings, relieving the huge pressure on health care.

A Cas12a-based platform combined with gold nanoparticles for sensitive and visual detection of Alternaria solani.

Alternaria solani (A. solani), the causal agent of early blight in potatoes, poses a serious and persistent threat to potato production worldwide. Therefore, developing a method that can accurately detect A. solani in the early stage to avoid further spread is urgent. However, the conventional PCR-based method is not appropriate for application in the fields. Recently, the CRISPR-Cas system has been developed for nucleic acids analysis at point-of-care. Here, we propose a gold nanoparticles-based visual assay combining loop-mediated isothermal amplification with CRISPR-Cas12a to detect A. solani. After optimization, the method could detect 10-3 ng/µL genomic gene of A. solani. The specificity of the method was confirmed by discriminating A. solani from other three highly homologous pathogens. We also developed a portable device that could be used in the fields. By integrating with the smartphone readout, this platform holds significant potential in high-throughput detection of multiple pathogens in the fields.

Microneedle system for tissue engineering and regenerative medicine.

Global increasing demand for high life quality and length facilitates the development of tissue engineering and regenerative medicine, which apply multidisciplinary theories and techniques to achieve the structural reconstruction and functional recovery of disordered or damaged tissues and organs. However, the clinical performances of adopted drugs, materials, and powerful cells in the laboratory are inescapably limited by the currently available technologies. To tackle the problems, versatile microneedles are developed as the new platform for local delivery of diverse cargos with minimal invasion. The efficient delivery, as well as painless and convenient procedure endow microneedles with good patient compliance in clinic. In this review, we first categorize different microneedle systems and delivery models, and then summarize their applications in tissue engineering and regenerative medicine mainly involving maintenance and rehabilitation of damaged tissues and organs. In the end, we discuss the advantages, challenges, and prospects of microneedles in depth for future clinical translations.

Ultrasensitive and Rapid Visual Detection of Escherichia coli O157:H7 Based on RAA-CRISPR/Cas12a System.

Escherichia coli (E. coli) O157:H7 is a major foodborne and waterborne pathogen that can threaten human health. Due to its high toxicity at low concentrations, it is crucial to establish a time-saving and highly sensitive in situ detection method. Herein, we developed a rapid, ultrasensitive, and visualized method for detecting E. coli O157:H7 based on a combination of Recombinase-Aided Amplification (RAA) and CRISPR/Cas12a technology. The CRISPR/Cas12a-based system was pre-amplified using the RAA method, which showed high sensitivity and enabled detecting as low as ~1 CFU/mL (fluorescence method) and 1 × 102 CFU/mL (lateral flow assay) of E. coli O157:H7, which was much lower than the detection limit of the traditional real-time PCR technology (103 CFU/mL) and ELISA (104~107 CFU/mL). In addition, we demonstrated that this method still has good applicability in practical samples by simulating the detection in real milk and drinking water samples. Importantly, our RAA-CRISPR/Cas12a detection system could complete the overall process (including extraction, amplification, and detection) within 55 min under optimized conditions, which is faster than most other reported sensors, which take several hours to several days. The signal readout could also be visualized by fluorescence generated with a handheld UV lamp or a naked-eye-detected lateral flow assay depending on the DNA reporters used. Because of the advantages of being fast, having high sensitivity, and not requiring sophisticated equipment, this method has a promising application prospect for in situ detection of trace amounts of pathogens.

Conjugated Polymer Nanoparticles for Tumor Theranostics.

Water-dispersible conjugated polymer nanoparticles (CPNs) have demonstrated great capabilities in biological applications, such as in vitro cell/subcellular imaging and biosensing, or in vivo tissue imaging and disease treatment. In this review, we summarized the recent advances of CPNs used for tumor imaging and treatment during the past five years. CPNs with different structures, which have been applied to in vivo solid tumor imaging (fluorescence, photoacoustic, and dual-modal) and treatment (phototherapy, drug carriers, and synergistic therapy), are discussed in detail. We also demonstrated the potential of CPNs as cancer theranostic nanoplatforms. Finally, we discussed current challenges and outlooks in this field.

Rapid and Sensitive Diagnosis of COVID-19 Using an Electricity-Free Self-Testing System.

Rapid and sensitive detection of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for early diagnosis and effective treatment. Nucleic acid testing has been considered the gold standard method for the diagnosis of COVID-19 for its high sensitivity and specificity. However, the polymerase chain reaction (PCR)-based method in the central lab requires expensive equipment and well-trained personnel, which makes it difficult to be used in resource-limited settings. It highlights the need for a sensitive and simple assay that allows potential patients to detect SARS-CoV-2 by themselves. Here, we developed an electricity-free self-testing system based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) that allows for rapid and accurate detection of SARS-CoV-2. Our system employs a heating bag as the heat source, and a 3D-printed box filled with phase change material (PCM) that successfully regulates the temperature for the RT-LAMP. The colorimetric method could be completed in 40 min and the results could be read out by the naked eye. A ratiometric measurement for exact readout was also incorporated to improve the detection accuracy of the system. This self-testing system is a promising tool for point-of-care testing (POCT) that enables rapid and sensitive diagnosis of SARS-CoV-2 in the real world and will improve the current COVID-19 screening efforts for control and mitigation of the pandemic.

PddCas: A Polydisperse Droplet Digital CRISPR/Cas-Based Assay for the Rapid and Ultrasensitive Amplification-Free Detection of Viral DNA/RNA.

Clustered regularly interspaced short palindromic repeats (CRISPR)-based assays have been an emerging diagnostic technology for pathogen diagnosis. In this work, we developed a polydisperse droplet digital CRISPR-Cas-based assay (PddCas) for the rapid and ultrasensitive amplification-free detection of viral DNA/RNA with minimum instruments. LbaCas12a and LbuCas13a were used for the direct detection of viral DNA and RNA, respectively. The reaction mixtures were partitioned with a common vortex mixer to generate picoliter-scale polydisperse droplets in several seconds. The limit of detection (LoD) for the target DNA and RNA is approximately 100 aM and 10 aM, respectively, which is about 3 × 104-105 fold more sensitive than corresponding bulk CRISPR assays. We applied the PddCas to successfully detect severe acute respiratory syndrome coronavirus (SARS-CoV-2) and human papillomavirus type 18 (HPV 18) in clinical samples. For the 23 HPV 18-suspected cervical epithelial cell samples and 32 nasopharyngeal swabs for SARS-CoV-2, 100% sensitivity and 100% specificity were demonstrated. The dual-gene virus detection with PddCas was also established and verified. Therefore, PddCas has potential for point-of-care application and is envisioned to be readily deployed for frequent testing as part of an integrated public health surveillance program.

Recent Advances of NIR-II Emissive Semiconducting Polymer Dots for In Vivo Tumor Fluorescence Imaging and Theranostics.

Accurate diagnosis and treatment of tumors, one of the top global health problems, has always been the research focus of scientists and doctors. Near-infrared (NIR) emissive semiconducting polymers dots (Pdots) have demonstrated bright prospects in field of in vivo tumor fluorescence imaging owing to some of their intrinsic advantages, including good water-dispersibility, facile surface-functionalization, easily tunable optical properties, and good biocompatibility. During recent years, much effort has been devoted to developing Pdots with emission bands located in the second near-infrared (NIR-II, 1000-1700 nm) region, which hold great advantages of higher spatial resolution, better signal-to-background ratios (SBR), and deeper tissue penetration for solid-tumor imaging in comparison with the visible region (400-680 nm) and the first near-infrared (NIR-I, 680-900 nm) window, by virtue of the reduced tissue autofluorescence, minimal photon scattering, and low photon absorption. In this review, we mainly summarize the latest advances of NIR-II emissive semiconducting Pdots for in vivo tumor fluorescence imaging, including molecular engineering to improve the fluorescence quantum yields and surface functionalization to elevate the tumor-targeting capability. We also present several NIR-II theranostic Pdots used for integrated tumor fluorescence diagnosis and photothermal/photodynamic therapy. Finally, we give our perspectives on future developments in this field.

A Variable-Clustering-Based Feature Selection to Improve Positive and Negative Discrimination of P53 Protein in Colorectal Cancer Patients.

P53 protein tumor suppressor gene plays a guiding role in the treatment and prognosis of colorectal cancer (CRC). This paper aimed at proposing a feature selection method based on variable clustering to improve positive and negative discrimination of P53 protein in CRC patients. In this approach, we cluster the preprocessed dataset with variables, and then find the features with the largest information value (IV) for each cluster to form a feature subset. We call this method as IV_Cluster. In the actual medical data test, compared with the information value feature selection method, the accuracy of the 10-fold cross-validation logistic regression model increased by 4.4%, 2.0%, and 5.8%, and Kappa values increased by 21.8%, 8.6%, and 22.4%, respectively, under 5, 10, and 15 feature sets.

Clinlabomics: leveraging clinical laboratory data by data mining strategies.

The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.

Semiconducting polymer dots as fluorescent probes for in vitro biosensing.

Semiconducting polymer dots (Pdots) have emerged as novel fluorescent probes with excellent characteristics, such as ultrahigh molar extinction coefficient, easy tunable absorption and emission bands, high brightness, and excellent photostability. Combined with good biocompatibility properties, much effort has been devoted to Pdots for in vivo biological imaging and therapy applications, such as deep-tissue fluorescent imaging, photodynamic therapy, photothermal therapy, and nanocarriers of genes or chemical drugs. Many reviews have been presented in these fields. On the other hand, a large number of studies employing Pdots for in vitro biosensing applications have been reported during the past few years, and there are barely any relevant reports to summarize the progress in this area. Hence, it is necessary to review these studies to promote the comprehensive application of Pdots. Herein, we introduce the properties and functionalization of Pdots, and systematically summarize the progress in the in vitro applications of Pdots, including the detection of DNAs, microRNAs, proteins, enzymatic activity, and some biological small molecules and ions. Finally, we share our perspectives on the future direction of this field.

A model of multiple tumor marker for lymph node metastasis assessment in colorectal cancer: a retrospective study.

Background: Assessment of colorectal cancer (CRC) lymph node metastasis (LNM) is critical to the decision of surgery, prognosis, and therapy strategy. In this study, we aimed to develop and validate a multiple tumor marker nomogram for predicting LNM in CRC patients. Methods: A total of 674 patients who met the inclusion criteria were collected and randomly divided into primary cohort and internal test cohort at a ratio of 7:3. An external test cohort enrolled 178 CRC patients from the West China Hospital. Clinicopathologic variables were obtained from electronic medical records. The least absolute shrinkage and selection operator (LASSO) and interquartile range analysis were carried out for variable dimensionality reduction and feature selection. Multivariate logistic regression analysis was conducted to develop predictive models of LNM. The performance of the established models was evaluated by the receiver operating characteristic (ROC) curve, calibration belt, and clinical usefulness. Results: Based on minimum criteria, 18 potential features were reduced to six predictors by LASSO and interquartile range in the primary cohort. The model demonstrated good discrimination and ROC curve (AUC = 0.721 in the internal test cohort, AUC = 0.758 in the external test cohort) in LNM assessment. Good calibration was shown for the probability of CRC LNM in the internal and external test cohorts. Decision curve analysis illustrated that multi-tumor markers nomogram was clinically useful. Conclusions: The study proposed a reliable nomogram that could be efficiently and conveniently utilized to facilitate the assessment of individually-tailored LNM in patients with CRC, complementing imaging and biopsy tests.

Digital CRISPR/Cas12b-based platform enabled absolute quantification of viral RNA.

Early and accurate diagnosis of viruses is critical for control of the pandemic. CRISPR/Cas-based detection of nucleic acid is an emerging technology for molecular diagnostics, and has been applied for virus detection. Though these methods have excellent sensitivity and specificity, most of them were not able to measure the quantity of virus. We here developed a droplet digital reverse transcription loop-mediated isothermal amplification (RT-LAMP) enhanced Cas12b-based RNA detection platform (RECD), for quantitative detection of viral RNA. CRISPR/Cas12b, which is more thermally stable than other family members in CRISPR systems, is combined with digital RT-LAMP. Due to the innate characteristic of digital format detection and CRISPR/Cas system, droplet digital RECD (ddRECD) assay enables absolute quantification of viral RNA, with single-molecule sensitivity. We expect the ddRECD assay will be a powerful tool for molecular diagnostics.

Digital Quantification of Human Viral RNA and DNA Using a Self-Digitization Chip.

Digital nucleic acid quantitation methods show excellent sensitivity and specificity for pathogen detection. Droplet digital PCR (ddPCR) is the most advanced digital nucleic acid quantitation method and has been commercialized, but is not suitable for many point-of-care applications due to its complex instrumentation. Here we describe a simple microfluidics-based self-digitization (SD) chip for quantifying nucleic acids at the point of care with minimal instrumentation. We demonstrate the clinical diagnostic capability of this platform by applying it to quantifying human viral DNA and RNA. SD chips with a range of well numbers and volumes are tested, and isothermal methods are used to amplify the DNA and RNA to a detectable level. Sample concentration is determined based on the measured volume in the wells and the number of wells with fluorescence greater than a threshold based on a Poisson distribution. Concentration measurements over the low concentration range of 0-100 molecules/µL showed a strong correlation (R2 = 0.99) with measurements using a real-time PCR assay, demonstrating the sensitivity and specificity of the SD chip platform.

Benzotrithiophene-based MOFs: interchromophoric interactions affected Ln(III) crystallization selectivity and optoelectronic properties.

Metal-organic frameworks (MOFs) provide an ideal platform for the assembly of chromophores and thus show wide potential applications in optoelectronic devices. The spatial arrangement and interaction of the incorporated chromophores play a key role in the generation of coherent optical and electronic properties. In this work, two series of benzo-(1,2;3,4;5,6)-tristhiophene (BTT) based Ln-MOFs (Ln-1s and Ln-2s) were synthesized. These two series of MOFs present different assembly states of BTT chromophores, that is, BTT-containing ligands exist as separated monomers in Ln-1s but gather as dimers in Ln-2s. From the comparison between these two series of MOFs and theoretical calculations, we show for the first time that this chromophore assembly state difference could affect the crystallization selectivity of MOFs towards different Ln3+ ions. In addition, the interaction between BTT chromophores in the dimer also leads to the red-shifted photoluminescence and enhanced photocurrent of Ln-2s relative to those of Ln-1s. The results of this work demonstrate the multiple functions of interchromophoric interactions in the structures and optoelectronic properties of MOFs.