Amplification-free CRISPR/Cas detection technology: challenges, strategies, and perspectives.

Rapid and accurate molecular diagnosis is a prerequisite for precision medicine, food safety, and environmental monitoring. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas)-based detection, as a cutting-edged technique, has become an immensely effective tool for molecular diagnosis because of its outstanding advantages including attomolar level sensitivity, sequence-targeted single-base specificity, and rapid turnover time. However, the CRISPR/Cas-based detection methods typically require a pre-amplification step to elevate the concentration of the analyte, which may produce non-specific amplicons, prolong the detection time, and raise the risk of carryover contamination. Hence, various strategies for target amplification-free CRISPR/Cas-based detection have been developed, aiming to minimize the sensitivity loss due to lack of pre-amplification, enable detection for non-nucleic acid targets, and facilitate integration in portable devices. In this review, the current status and challenges of target amplification-free CRISPR/Cas-based detection are first summarized, followed by highlighting the four main strategies to promote the performance of target amplification-free CRISPR/Cas-based technology. Furthermore, we discuss future perspectives that will contribute to developing more efficient amplification-free CRISPR/Cas detection systems.

CRISPR-based Biosensors for Human Health: A Novel Strategy to Detect Emerging Infectious Diseases.

Infectious diseases (such as sepsis, influenza, and malaria), caused by various pathogenic bacteria and viruses, are widespread across the world. Early and rapid detection of disease-related pathogens is necessary to reduce their spread in the world and prevent their potential global pandemics. The clustered regularly interspaced short palindromic repeats (CRISPR) technology, as the next-generation molecular diagnosis technique, holds immense promise in the detection of infectious diseases because of its remarkable advantages, including supreme flexibility, sensitivity, and specificity. While numerous CRISPR-based biosensors have been developed for application in environmental monitoring, food safety, and point-of-care diagnosis, there remains a critical need to summarize and explore their potential in human health. This review aims to address this gap by focusing on the latest advancements in CRISPR-based biosensors for infectious disease detection. We provide an overview of the current status, pre-amplification methods, the unique feature of each CRISPR system, and the design of CRISPR-based biosensing strategies to detect disease-associated nucleic acids. Last but not least, the review analyzes the current challenges and provides future perspectives, which will contribute to developing more effective CRISPR-based biosensors for human health.

Transfer learning in high-dimensional semiparametric graphical models with application to brain connectivity analysis.

Transfer learning has drawn growing attention with the target of improving statistical efficiency of one study (dataset) by digging up information from similar and related auxiliary studies (datasets). In this article, we consider transfer learning problem in estimating undirected semiparametric graphical model. We propose an algorithm called Trans-Copula-CLIME for estimating an undirected graphical model while uncovering information from similar auxiliary studies, characterizing the similarity between the target graph and each auxiliary graph by the sparsity of a divergence matrix. The proposed method relaxes the restrictive Gaussian distribution assumption, which deviates from reality for the fMRI dataset related to attention deficit hyperactivity disorder (ADHD) considered here. Nonparametric rank-based correlation coefficient estimators are utilized in the Trans-Copula-CLIME procedure to achieve robustness against normality. We establish the convergence rate of the Trans-Copula-CLIME estimator under some mild conditions, which demonstrates that if the similarity between the auxiliary studies and the target study is sufficiently high and the number of informative auxiliary samples is sufficiently large, the Trans-Copula-CLIME estimator shows great advantage over the existing non-transfer-learning ones. Simulation studies also show that Trans-Copula-CLIME estimator has better performance especially when data are not from Gaussian distribution. Finally, the proposed method is applied to infer functional brain connectivity pattern for ADHD patients in the target Beijing site by leveraging the fMRI datasets from some other sites.

A Multiplexed Self-Powered Dual-Photoelectrode Biosensor for Detecting Dual Analytes Based on an Electron-Transfer-Regulated Conversion Strategy.

Due to the inherent mechanism limitation of photocatalytic fuel cell based self-powered biosensors (PFC-SPBs), it was difficult to distinguish the power density of various photoactive materials or recognition events in one detection process, which made it lack multitarget quantitative capacity. In order to solve this problem, we proposed an electron-transfer-regulated conversion strategy for the construction of multiplexed PFC-SPBs. Herein, the n-type CdS/Fe2O3 nanorod array (NR) heterojunction and p-type CuBr semiconductor were used as photoactive materials to prepare the photoanode and photocathode. Based on the appropriate Fermi level differentiation between these two photoelectrodes, a self-powered sensing platform driven by visible light without external energy supply was achieved. In this design, two kinds of common and easily coexisting mycotoxins OTA and AFB1 acted as model analytes. The coupling of "signal off" and "signal on" was realized by controlling the electronic transmission on the interface between the photoanode and photocathode, so as to achieve the simultaneous detection of two mycotoxins. This work established a proof-of-concept for the integration of a dual-photoelectrode with dual-assay that could provide the innovative inspiration for the formation of a general multiplexed self-powered sensing platform.

Novel Anti-Interference Strategy for a Self-Powered Sensor: Mediator-Free and Biospecific Photocathode Interface.

As a new electrochemical sensing concept, a self-powered sensor shows a good application prospect in the field of analysis. However, it is still a great challenge to improve the anti-interference capability of sensors through reasonable design. In this study, we investigated the difference between the single photoanode and photocathode self-powered sensor and combined the advantages of these two aspects to fabricate a mediator-free self-powered aptasensor based on the dual-photoelectrode system, which combined the biological events from the photocathode. The biological events occurred at the photocathode could avoid the interference caused by the generated hole oxidation of reducing small molecules in the real sample on the photoanode surface, which was helpful to enhance the anti-interference capability of the sensor. Moreover, due to the sufficient Fermi level differentiation between two photoelectrodes, the redox mediator was not necessary. This could avoid the redox reaction caused by the introduction of extra electron donors or electron acceptors occurring before the photoelectrical behavior, thus improving the accuracy of the sensor. According to the influence of the generated biological conjugate on the external circuit, electron transmission between interfaces, and the obstruction of visible light irradiation, the sensitive and accurate detection of the analytical model was achieved. This work provided a proof-of-concept for the establishment of a mediator-free dual-photoelectrode self-powered sensing platform with high sensitivity and strong anti-interference performance.

Visible transparency tuning and corresponding sensing application of opal photonic crystals.

The development of optical refractive index sensors for label-free sensing is beneficial for both chemical and biochemical applications. Lots of efforts have been devoted to narrow the resonance peaks of periodic nanostructures and, therefore, improve the figures of merit. The substrates with high-quality factor resonances always come at the expense of not only complicated fabrication processes but also the requirement of sophisticated optical measuring systems. It is demonstrated in this work that Fabry-Perot resonance based broadband sensing with figure of merit of 83 can be achieved using low-cost self-assembled opal photonic crystals. It is seen by the naked eye that the transparency of photonic crystal dots can be gradually improved by increasing the refractive index of the filling liquid. The loop-mediated isothermal amplification induced refractive index variation of biological samples has also been recognized using the prepared photonic crystal dots, which are capable of fluorescence enhancement as well.

DNA Nanotechnology-Enabled Drug Delivery Systems.

Over the past decade, we have seen rapid advances in applying nanotechnology in biomedical areas including bioimaging, biodetection, and drug delivery. As an emerging field, DNA nanotechnology offers simple yet powerful design techniques for self-assembly of nanostructures with unique advantages and high potential in enhancing drug targeting and reducing drug toxicity. Various sequence programming and optimization approaches have been developed to design DNA nanostructures with precisely engineered, controllable size, shape, surface chemistry, and function. Potent anticancer drug molecules, including Doxorubicin and CpG oligonucleotides, have been successfully loaded on DNA nanostructures to increase their cell uptake efficiency. These advances have implicated the bright future of DNA nanotechnology-enabled nanomedicine. In this review, we begin with the origin of DNA nanotechnology, followed by summarizing state-of-the-art strategies for the construction of DNA nanostructures and drug payloads delivered by DNA nanovehicles. Further, we discuss the cellular fates of DNA nanostructures as well as challenges and opportunities for DNA nanostructure-based drug delivery.

Electrocatalytic Water Oxidation by an Unsymmetrical Di-Copper Complex.

An unsymmetrical di-copper complex, ([Cu2(TPMAN)(µ-OH)(H2O)]3+, was prepared and used for electrocatalytic water oxidation in neutral conditions. This complex is a stable and efficient homogeneous catalyst during the electrocatalytic oxygen evolution process ( kcat = 0.78 s-1) with 780 mV onset overpotential in 0.1 M phosphate buffer (pH 7.0). The water oxidation mechanism of the unsymmetrical catalyst [Cu2(TPMAN)(µ-OH)]3+ exhibits different behaviors than that of [Cu2(BPMAN)(µ-OH)]3+, such as two redox steps with different pH dependences, a significant kinetic isotope effect, and buffer concentration dependence. All these changes were ascribed to the open site on the Cu center that is formed by removal of the hemilabile pyridyl site, which acts as an intramolecular proton acceptor to assist the O-O bond formation step.

A colorimetric detection of acrylamide in potato chips based on nucleophile-initiated thiol-ene Michael addition.

Acrylamide (AA), a neurotoxin and a potential carcinogen, has been found in various thermally processed foods such as potato chips, biscuits, and coffee. Simple, cost-effective, and sensitive methods for the rapid detection of AA are needed to ensure food safety. Herein, a novel colorimetric method was proposed for the visual detection of AA based on a nucleophile-initiated thiol-ene Michael addition reaction. Gold nanoparticles (AuNPs) were aggregated by glutathione (GSH) because of a ligand-replacement, accompanied by a color change from red to purple. In the presence of AA, after the thiol-ene Michael addition reaction between GSH and AA with the catalysis of a nucleophile, the sulfhydryl group of GSH was consumed by AA, which hindered the subsequent ligand-replacement and the aggregation of AuNPs. Therefore, the concentration of AA could be determined by the visible color change caused by dispersion/aggregation of AuNPs. This new method showed high sensitivity with a linear range from 0.1 µmol L(-1) to 80 µmol L(-1) and a detection limit of 28.6 nmol L(-1), and especially revealed better selectivity than the fluorescence sensing method reported previously. Moreover, this new method was used to detect AA in potato chips with a satisfactory result in comparison with the standard methods based on chromatography, which indicated that the colorimetric method can be expanded for the rapid detection of AA in thermally processed foods.

Analysis of Gut Microbiota as a Diagnostic Biomarker for Lung Adenocarcinoma with Qi-Deficiency and Phlegm-Turbid Stagnation.

BACKGROUND: In lung adenocarcinoma (LUAD), Qi-deficiency and Phlegm-turbid stagnation (QP) are the most prevalent Traditional Chinese medicine (TCM) syndrome. METHODS: Herein, we collected 90 fecal samples (Healthy individual (H): 30; other syndrome (O): 30; QP: 30) and explored the composition and diversity of gut microbiota in LUAD patients with QP syndrome using 16s-rRNA sequencing. Then, we identified biomarkers for QP syndrome in LUAD patients with linear discriminant analysis (LDA) effect size (LEfSe) and applied logistic regression analysis to construct a diagnostic model evaluated with the area under the receiver operating characteristic curve (AUC) and validated with data from metagenomics. RESULTS: The α diversity and ß diversity revealed that the microbiota community structure in LUAD patients with QP syndrome was different from that with healthy individuals and LUAD patients with other syndromes. At the phylum level, the QP group had more abundance of Bacteroidetes and less Proteobacteria than the O group. At the genus level, the abundance of 4 genera (Bacteroides, Parabacteroides, Prevotella, and Flavonifractor) was different between the QP group and O group. Moreover, LEfSe indicated that those 4 genera might be the biomarkers for LUAD patients with QP syndrome. Then, we used those 4 genera to develop a diagnostic model. The AUC based on 16s-rRNA sequencing and metagenomics was 0.989 and 1, respectively. CONCLUSION: A diagnostic model was developed, which would be an available tool for the clinical diagnosis of LUAD with QP syndrome.

A retrospective cohort study to observe the efficacy and safety of Endoscopic Submucosal Dissection (ESD) with adjuvant radiotherapy for T1a-MM/T1b-SM Esophageal Squamous Cell Carcinoma (ESCC).

BACKGROUND AND AIM: The clinical outcome of endoscopy submucosal dissection with subsequent radiotherapy for esophageal squamous cell carcinoma remain unclear. In this study we aim to investigate the efficacy and safety of endoscopic submucosal dissection with adjuvant radiotherapy in the treatment of superficial esophageal squamous cell carcinoma involving the muscularis mucosae (T1a-MM) or the submucosa < 200 µm (T1b-SM1). METHODS: We analyzed 20 patients with pathologically confirmed T1a-MM or T1b-SM1 esophageal squamous cell carcinoma treated by endoscopic submucosal dissection from 2016 to 2020 in Lihuili Hospital, 9 patients received adjuvant radiotherapy (RT group) and 11 patients received did not (non-RT group). RESULTS: All 20 patients underwent en bloc resection, and both the vertical and horizontal margins were negative. There was no recurrence or lymph node metastasis in the RT group, and no serious complications or death were observed. In the non-RT group, 2 patients had local recurrence and 1 had distant metastasis. None of the 20 patients died of esophageal carcinoma. CONCLUSIONS: Adjuvant radiotherapy following endoscopic submucosal dissection may be a safe and effective method for the treatment of T1a-MM/T1b-SM1 superficial esophageal squamous cell carcinoma.

Fully Integrated Microfluidic Platform for Multiplexed Detection of Hunov by a Dynamic Confined-Space-Implemented One-Pot Rpa-Lamp System.

Human norovirus (HuNoV) is the leading cause of nonbacterial acute gastroenteritis, which is highly infectious, rapidly evolving, and easily transmitted through feces. The accurate and early detection of HuNoV subtypes is essential for effective treatment, early surveillance, risk assessment, and disease prevention. In this study, a portable multiplex HuNoV detection platform that combines integrated microfluidics and cascade isothermal amplification, using a streamlined protocol for clinical fecal-based diagnosis is presented. To overcome the problems of carryover contamination and the incompatibility between recombinase polymerase amplification (RPA) and loop-mediated isothermal amplification (LAMP), a Dynamic confined-space-implemented One-pot RPA-LAMP colorimetric detection system (DORLA) is developed by creating a hydrogen bond network. The DORLA system exhibits excellent sensitivity, with detection limits of 10 copies µL-1 and 1 copy µL-1 for HuNoV GI and GII, respectively. In addition, a portable diagnostic platform consisting of a thermostatic control module and an integrated 3D-printed microfluidic chip for specific HuNoV capture, nucleic acid pretreatment, and DORLA detection, which enables simultaneous diagnosis of HuNoV GI and GII is developed. A DORLA-based microfluidic platform exhibits satisfactory performance with high sensitivity and portability, and has high potential for the rapid point-of-care detection of HuNoV in clinical fecal samples, particularly in resource-limited settings.

[Assessment of carbon reduction and sink enhancement potential of photovoltaic+mining ecological restoration model]. / å ‰ä¼+矿山生态修复模式的减碳增汇潜力评估.

The energy oriented mine ecological restoration mode of photovoltaic+ecological restoration provides a breakthrough for alleviating the dilemma of photovoltaic land development and solving the urgent need for restoration of abandoned mining land. Taking a mining area in central Liaoning Province as an example, we established three photovoltaic+mining ecological restoration modes, including forest-photovoltaic complementary, agriculture-photovoltaic, and grass photovoltaic complementation. Combined with the life cycle assessment method, we calculated and assessed the potential of photovoltaic+mining ecological restoration in carbon reduction and sink enhancement. The average annual carbon reduction and sink increase was 514.93 t CO2·hm-2 under the photovoltaic+mining ecological restoration mode, while the average annual carbon reduction per megawatt photovoltaic power station was 1242.94 t CO2. The adoption of photovoltaic+ecological restoration mode in this mining area could make carbon reduction and sink enhancement 6.30-7.79 Mt CO2 during 25 years. The carbon reduction and sink increment mainly stemmed from the photovoltaic clean power generation induced carbon reduction, accounting for 96.4%-99.4%, while the contribution of ecosystem carbon sink increment was small, accounting for only 0.6%-3.7% of the total. Among different photovoltaic+ecological restoration modes, the carbon reduction and sink increment was the largest in forest-photovoltaic complementary (7.11 Mt CO2), followed by agriculture-photovoltaic (7.04 Mt CO2), and the least in grass photovoltaic complementation (6.98 Mt CO2). Constructing the development mode of "photovoltaic+mining ecological restoration" could effectively leverage the dual benefits of reducing emissions from photovoltaic power generation and increase sinks from mining ecological restoration, which would be helpful for achieving the goal of carbon neutrality in China.

Alternations of antibiotic resistance genes and microbial community dynamics on shared bicycles before and after pandemic lockdown.

The prevalence of shared bicycles has raised concerns over their potential to transmit pathogens and microbes harboring antibiotic resistance genes (ARGs), which pose significant human health risks. This study investigated the impact of anthropogenic activities on the composition of ARGs and microbial communities on shared bicycles during the COVID-19 pandemic and subsequent lockdown when shared bicycle usage was altered. A total of 600 swab samples from shared bicycle surfaces were collected in Shanghai before and during COVID-19 lockdown periods. Even during lockdown, 12 out of 14 initially detected ARG subtypes persisted, indicating their tenacity in the face of reduced anthropogenic activities. These ARGs displayed significantly higher absolute and relative abundance levels before the lockdown. In addition, the percentage of potential pathogens in the total microbial abundance remained at 0.029 % during the lockdown, which was lower than the pre-lockdown percentage of 0.035 % and suggested that these risks persist within shared bicycle systems. Interestingly, although microbial abundance decreased without the consecutive use of shared bicycles during lockdown, the microbial diversity increased under the impact of restricted anthropogenic activities (p < 0.001). This emphasizes the need for continuous monitoring and research to comprehend microbial community behaviors in various environments. This study uncovered the underlying impacts of the COVID-19 lockdown on the microbial and ARG communities of shared bicycles, providing comprehensive insights into the health management of shared transportation. Although lockdown can decrease the abundance of ARGs and potential pathogens, additional interventions are needed to prevent their continued spread.

DNAzyme-based faithful probing and pulldown to identify candidate biomarkers of low abundance.

Biomarker discovery is essential for the understanding, diagnosis, targeted therapy and prognosis assessment of malignant diseases. However, it remains a huge challenge due to the lack of sensitive methods to identify disease-specific rare molecules. Here we present MORAC, molecular recognition based on affinity and catalysis, which enables the effective identification of candidate biomarkers with low abundance. MORAC relies on a class of DNAzymes, each cleaving a sole RNA linkage embedded in their DNA chain upon specifically sensing a complex system with no prior knowledge of the system's molecular content. We show that signal amplification from catalysis ensures the DNAzymes high sensitivity (for target probing); meanwhile, a simple RNA-to-DNA mutation can shut down their RNA cleavage ability and turn them into a pure affinity tool (for target pulldown). Using MORAC, we identify previously unknown, low-abundance candidate biomarkers with clear clinical value, including apolipoprotein L6 in breast cancer and seryl-tRNA synthetase 1 in polyps preceding colon cancer.

Internal reference self-powered aptasensor for on-site detection of MC-RR used sunlight as light source and CoMoS4 hollow nanospheres as photocathode.

As a liver toxin, long-term exposure of microcystin-arginine-arginine (MC-RR) is harmful to the ecological environment and human health, so it is necessary to realize on-site detection of MC-RR. The self-powered sensor has enormous potential for on-site detection in battery-free devices. However, due to the low photoelectric conversion efficiency and poor anti-interference ability to environmental fluctuation, the field detection of self-powered sensor is limited. Herein, we tackled above problems according to the following two aspects. For one hand, CoMoS4 hollow nanospheres modified internal reference electrode was arranged in the self-powered sensor, which effectively avoided the influence of unstable sunlight caused by different space, time, weather and other factors. For the other hand, dual-photoelectrode could absorb and convert sunlight, so as to improve the solar capture and energy utilization, and realized the sunlight instead of traditional external light source (Xenon lamp or LED, etc.). This method effectively simplified the sensing device and solved the interference of environment in on-site detection. In addition, multimeter was used to measure the output voltage instead of electrochemical workstation, achieving the purpose of portability. This work established a sunlight-driven internal reference self-powered sensor with miniaturization, portability and anti-interference to realize MC-RR on-site monitoring in lake water.

Multiplex Detection of Infectious Diseases on Microfluidic Platforms.

Infectious diseases contribute significantly to the global disease burden. Sensitive and accurate screening methods are some of the most effective means of identifying sources of infection and controlling infectivity. Conventional detecting strategies such as quantitative polymerase chain reaction (qPCR), DNA sequencing, and mass spectrometry typically require bulky equipment and well-trained personnel. Therefore, mass screening of a large population using conventional strategies during pandemic periods often requires additional manpower, resources, and time, which cannot be guaranteed in resource-limited settings. Recently, emerging microfluidic technologies have shown the potential to replace conventional methods in performing point-of-care detection because they are automated, miniaturized, and integrated. By exploiting the spatial separation of detection sites, microfluidic platforms can enable the multiplex detection of infectious diseases to reduce the possibility of misdiagnosis and incomplete diagnosis of infectious diseases with similar symptoms. This review presents the recent advances in microfluidic platforms used for multiplex detection of infectious diseases, including microfluidic immunosensors and microfluidic nucleic acid sensors. As representative microfluidic platforms, lateral flow immunoassay (LFIA) platforms, polymer-based chips, paper-based devices, and droplet-based devices will be discussed in detail. In addition, the current challenges, commercialization, and prospects are proposed to promote the application of microfluidic platforms in infectious disease detection.

Benefit analysis of multi-approach biomass energy utilization toward carbon neutrality.

To reduce greenhouse gas (GHG) emissions, biomass has been increasingly developed as a renewable and clean alternative to fossil fuels because of its carbon-neutral characteristics. China has been investigating the rational development and use of bioenergy for developing its clean energy and achieving carbon neutrality. Substituting fossil fuels with multi-source and multi-approach utilized bioenergy and corresponding carbon reduction in China remain largely unexplored. Here, a comprehensive bioenergy accounting model with a multi-dimensional analysis was developed by combining spatial, life cycle, and multi-path analyses. Accordingly, the bioenergy production potential and GHG emission reduction for each distinct type of biomass feedstock through different conversion pathways were estimated. The sum of all available organic waste (21.55 EJ yr-1) and energy plants on marginal land (11.77 EJ yr-1) in China produced 23.30 EJ of bioenergy and reduced 2,535.32 Mt CO2-eq emissions, accounting for 19.48% and 25.61% of China's total energy production and carbon emissions in 2020, respectively. When focusing on the carbon emission mitigation potential of substituting bioenergy for conventional counterparts, bioelectricity was the most effective, and its potential was 4.45 and 8.58 times higher than that of gaseous and liquid fuel alternatives, respectively. In this study, life cycle emission reductions were maximized by a mix of bioenergy end uses based on biomass properties, with an optimal 78.56% bioenergy allocation from biodiesel, densified solid biofuel, biohydrogen, and biochar. The main regional bioenergy GHG mitigation focused on the Jiangsu, Sichuan, Guangxi, Henan, and Guangdong provinces, contributing to 31.32% of the total GHG mitigation potential. This study provides valuable guidance on exploiting untapped biomass resources in China to secure carbon neutrality by 2060.

A versatile microfluidic platform for malaria infection screening and Plasmodium species genotyping.

BACKGROUND: Malaria, a widespread parasitic disease caused by Plasmodium species, remains a significant global health concern. Rapid and accurate detection, as well as species genotyping, are critical for effective malaria control. METHODS: We have developed a Flexible, Robust, Equipment-free Microfluidic (FREM) platform, which integrates recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR)-based detection, enabling simultaneous malaria infection screening and Plasmodium species genotyping. The microfluidic chip enabled the parallel detection of multiple Plasmodium species, each amplified by universal RPA primers and genotyped by specific crRNAs. The inclusion of a sucrose solution effectively created spatial separation between the RPA and CRISPR assays within a one-pot system, effectively resolving compatibility issues. FINDINGS: Clinical assessment of DNA extracts from patients with suspected malaria demonstrates the FREM platform's superior sensitivity (98.41%) and specificity (92.86%), yielding consistent results with PCR-sequencing for malaria detection, which achieved a positive predictive agreement of 98.41% and a negative predictive agreement of 92.86%. Additionally, the accuracy of species genotyping was validated through concordance rates of 90.91% between the FREM platform and PCR-sequencing. INTERPRETATION: The FREM platform offers a promising solution for point-of-care malaria screening and Plasmodium species genotyping. It highlights the possibility of improving malaria control efforts and expanding its applicability to address other infectious diseases. FUNDING: This work was financially supported by International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion, National Natural Science Foundation of China, the Natural Science Foundation of Shanghai, Bill & Melinda Gates Foundation and National Research and Development Plan of China.

Etiology and clinical features of non-O1/non-O139 Vibrio cholerae infection in an inland city in China.

Non-O1/non-O139 Vibrio cholerae (NOVC) causes various illnesses ranging in severity from mild to life-threatening but were ignored previously. Knowledge of the NOVC infection, particularly bacteremia, is limited because of its rarity. Here we first retrospectively reported the demographic, clinical, and therapy characteristics of patients with NOVC infection. Isolated NOVC stains were identified by a series of biochemical, mass spectrometry (MS), and serum agglutination tests. The results of 11 patients with NOVC infection (including 8 with bacteremia) with a median age of 68 years were included in this report. Most isolated NOVC strains had antibiotic susceptibility. Patients with NOVC-positive were distributed in various departments, most occurring in gastroenterology (6 cases). Hepatic disease was the most common comorbid disease, followed by diabetes (3 cases) and biliary tract disease (3 cases). Two cases were previously healthy. The most common symptom at presentation was fever. All patients presented with abnormal changes in hematology and inflammatory parameters. Cephalosporins were the most frequently used antibiotics. Ten patients had a favorable outcome after treatment; one died from complicated underlying diseases. In summary, we recommend the timely identification of NOVC strains using MALDI-TOF-MS. The suspicion of NOVC bacteremia cannot be ruled out regardless of the host's immune status. An alternative therapeutic regimen for this infection may be ß-lactam antibiotics or combined with ß-lactamase inhibitors. Regardless, the specific therapeutic regimen should be based on the antibiogram data.