Effects of traditional Chinese medicine on treatment outcomes in severe COVID-19 patients: a single-centre study.

As the search for effective treatments for COVID-19 continues, the high mortality rate among critically ill patients in Intensive Care Units (ICU) presents a profound challenge. This study explores the potential benefits of traditional Chinese medicine (TCM) as a supplementary treatment for severe COVID-19. A total of 110 critically ill COVID-19 patients at the Intensive Care Unit (ICU) of Vulcan Hill Hospital between Feb., 2020, and April, 2020 (Wuhan, China) participated in this observational study. All patients received standard supportive care protocols, with a subset of 81 also receiving TCM as an adjunct treatment. Clinical characteristics during the treatment period and the clinical outcome of each patient were closely monitored and analysed. Our findings indicated that the TCM group exhibited a significantly lower mortality rate compared with the non-TCM group (16 of 81 vs 24 of 29; 0.3 vs 2.3 person/month). In the adjusted Cox proportional hazards models, TCM treatment was associated with improved survival odds (P < 0.001). Furthermore, the analysis also revealed that TCM treatment could partially mitigate inflammatory responses, as evidenced by the reduced levels of proinflammatory cytokines, and contribute to the recovery of multiple organic functions, thereby potentially increasing the survival rate of critically ill COVID-19 patients.

Frequency Domain Channel-Wise Attack to CNN Classifiers in Motor Imagery Brain-Computer Interfaces.

OBJECTIVE: Convolutional neural network (CNN), a classical structure in deep learning, has been commonly deployed in the motor imagery brain-computer interface (MIBCI). Many methods have been proposed to evaluate the vulnerability of such CNN models, primarily by attacking them using direct temporal perturbations. In this work, we propose a novel attacking approach based on perturbations in the frequency domain instead. METHODS: For a given natural MI trial in the frequency domain, the proposed approach, called frequency domain channel-wise attack (FDCA), generates perturbations at each channel one after another to fool the CNN classifiers. The advances of this strategy are two-fold. First, instead of focusing on the temporal domain, perturbations are generated in the frequency domain where discriminative patterns can be extracted for motor imagery (MI) classification tasks. Second, the perturbing optimization is performed based on differential evolution algorithm in a black-box scenario where detailed model knowledge is not required. RESULTS: Experimental results demonstrate the effectiveness of the proposed FDCA which achieves a significantly higher success rate than the baselines and existing methods in attacking three major CNN classifiers on four public MI benchmarks. CONCLUSION: Perturbations generated in the frequency domain yield highly competitive results in attacking MIBCI deployed by CNN models even in a black-box setting, where the model information is well-protected. SIGNIFICANCE: To our best knowledge, existing MIBCI attack approaches are all gradient-based methods and require details about the victim model, e.g., the parameters and objective function. We provide a more flexible strategy that does not require model details but still produces an effective attack outcome.

Chinese Oral Cancer Patients' Pain Beliefs: An Application of Leventhal's Common-Sense Model.

BACKGROUND: Patients' pain beliefs are the main obstacle to effective pain management. Assessing and correcting negative perceptions is important for improving pain intensity and quality of life of patients with cancer pain. AIMS: To explore pain beliefs among oral cancer patients using the Common-Sense Model of Self-Regulation as a theoretical framework. The primary components of the model, cognitive representations, emotional representations, and coping responses, were examined. DESIGN: A qualitative method was used. SETTINGS: PARTICIPANTS/SUBJECTS:   METHODS: Semi-structured, qualitative, in-depth interviews were conducted with patients newly diagnosed with oral cancer in a tertiary care hospital. The interviews were analyzed using thematic analysis. RESULTS: Interviews with 15 patients revealed that the pain beliefs of patients with oral cancer included three themes: pain cognitive representations of oral cancer, pain emotional representations of oral cancer, and pain coping responses. CONCLUSIONS: Negative pain beliefs are common among oral cancer patients. This novel application of the self-regulatory model demonstrates that it can be used to capture the key pain beliefs (i.e., cognitions, emotions, and coping responses) of oral cancer patients within a single, unifying framework.

The development of a Cancer Pain Belief Modification Program for patients with oral cancer in China: a feasibility study.

BACKGROUND: Acceptance-based pain management interventions have been receiving growing attention in cancer pain care. This study aimed to develop a cancer pain management program based on belief modification to improve the cancer pain experience of Chinese oral cancer survivors and to explore the acceptability and preliminary outcomes of the Cancer Pain Belief Modification Program (CPBMP). METHODS: A mixed-methods approach was applied to develop and revise the program. The CPBMP was developed and revised using the Delphi technique, and its further improvement was explored with a one-group pre- and post-trial designed with a sample of 16 Chinese oral cancer survivors, and semi-structured interviews. Research instruments included Numeric Rating Scale (NRS), Chinese version of Illness Perception Questionnaire-Revised for Cancer Pain (IPQ-CaCP), and the University of Washington Quality of Life assessment scale (UW-QOL). Descriptive statistics, t-test, and Mann-Whitney U test were used to analyse the data. The semi-structured questions were analysed using content analysis. RESULTS: The six-module CPBMP was endorsed by most experts and patients. The expert authority coefficient value was 0.75 in the first round of the Delphi survey and 0.78 in the second round. The "pain intense", "negative pain beliefs" scores of pre- and post-testing decreased from 5.63 ± 0.48 to 0.81 ± 0.54 (t = -3.746, p < 0.001); from 140.63 ± 9.02 to 52.75 ± 7.27 (Z = 12.406, p < 0.001); and the "positive pain beliefs", "quality of life" scores increased from 55.13 ± 4.54 to 66.00 ± 4.70 (Z = -6.983, p < 0.001); from 66.97 ± 15.01 to 86.69 ± 8.42 (Z = 7.283, p < 0.001). The qualitative data also indicated that CPBMP was well acceptable. CONCLUSION: Our study showed the acceptability and preliminary outcomes of CPBMP patients. CPBMP improves the pain experience of Chinese oral cancer patients and provides a reference for cancer pain management in the future. TRIAL REGISTRATION: The feasibility study has already been registered on the Chinese Clinical Trial Registry (ChiCTR) ( www.chictr.org.cn ) in 11/09/2021. (ChiCTR2100051065).

Engineering Bifunctional Calcium Alendronate Gene-Delivery Nanoneedle for Synergistic Chemo/Immuno-Therapy Against HER2 Positive Ovarian Cancer.

Ovarian cancer is the most lethal gynecological malignancy. Most patients are diagnosed at an advanced stage with widespread peritoneal dissemination and ascites. Bispecific T-cell engagers (BiTEs) have demonstrated impressive antitumor efficacy in hematological malignancies, but the clinical potency is limited by their short half-life, inconvenient continuous intravenous infusion, and severe toxicity at relevant therapeutic levels in solid tumors. To address these critical issues, the design and engineering of alendronate calcium (CaALN) based gene-delivery system is reported to express therapeutic level of BiTE (HER2×CD3) for efficient ovarian cancer immunotherapy. Controllable construction of CaALN nanosphere and nanoneedle is achieved by the simple and green coordination reactions that the distinct nanoneedle-like alendronate calcium (CaALN-N) with a high aspect ratio enabled efficient gene delivery to the peritoneum without system in vivo toxicity. Especially, CaALN-N induced apoptosis of SKOV3-luc cell via down-regulation of HER2 signaling pathway and synergized with HER2×CD3 to generate high antitumor response. In vivo administration of CaALN-N/minicircle DNA encoding HER2×CD3 (MC-HER2×CD3) produces sustained therapeutic levels of BiTE and suppresses tumor growth in a human ovarian cancer xenograft model. Collectively, the engineered alendronate calcium nanoneedle represents a bifunctional gene delivery platform for the efficient and synergistic treatment of ovarian cancer.

Center transfer for supervised domain adaptation.

Domain adaptation (DA) is a popular strategy for pattern recognition and classification tasks. It leverages a large amount of data from the source domain to help train the model applied in the target domain. Supervised domain adaptation (SDA) approaches are desirable when only few labeled samples from the target domain are available. They can be easily adopted in many real-world applications where data collection is expensive. In this study, we propose a new supervision signal, namely center transfer loss (CTL), to efficiently align features under the SDA setting in the deep learning (DL) field. Unlike most previous SDA methods that rely on pairing up training samples, the proposed loss is trainable only using one-stream input based on the mini-batch strategy. The CTL exhibits two main functionalities in training to increase the performance of DL models, i.e., domain alignment and increasing the feature's discriminative power. The hyper-parameter to balance these two functionalities is waived in CTL, which is the second improvement from the previous approaches. Extensive experiments completed on well-known public datasets show that the proposed method performs better than recent state-of-the-art approaches.

Dual attentive fusion for EEG-based brain-computer interfaces.

The classification based on Electroencephalogram (EEG) is a challenging task in the brain-computer interface (BCI) field due to data with a low signal-to-noise ratio. Most current deep learning based studies in this challenge focus on designing a desired convolutional neural network (CNN) to learn and classify the raw EEG signals. However, only CNN itself may not capture the highly discriminative patterns of EEG due to a lack of exploration of attentive spatial and temporal dynamics. To improve information utilization, this study proposes a Dual Attentive Fusion Model (DAFM) for the EEG-based BCI. DAFM is employed to capture the spatial and temporal information by modeling the interdependencies between the features from the EEG signals. To our best knowledge, our method is the first to fuse spatial and temporal dimensions in an interactive attention module. This module improves the expression ability of the extracted features. Extensive experiments implemented on four publicly available datasets demonstrate that our method outperforms state-of-the-art methods. Meanwhile, this work also indicates the effectiveness of Dual Attentive Fusion Module.

Engineering Alendronate-Composed Iron Nanochelator for Efficient Peritoneal Carcinomatosis Treatment.

Iron is an essential element for various cellular metabolism. Cancer cells also have high requirement of iron in their proliferation, invasion, and metastasis processes. Alendronate (ALN), a kind of FDA-approved bisphosphonates with metal-chelating capability, is initially certified to selectively bind to intracellular Fe3+ theoretically and experimentally in this study. Hence, CaALN iron nanochelator is rationally designed to kill cancer cells by synergism of Fe-depletion and calcium accumulation. In vitro experiments and RNA sequencing analysis indicate that CaALN nanomedicine inhibits the proliferation of cancer cells by depleting Fe, interfering with DNA replication, and triggering intracellular reactive oxygen species (ROS). Meanwhile, released Ca2+ and ROS mutually promote and induce damage of cellular macromolecules, which leads to mitochondrial apoptosis of cancer cells. In an intraperitoneal disseminated mouse model with the human ovarian cancer cells SKOV3, CaALN nanoparticles selectively accumulate in tumor tissues and result in significant retardation of tumor growth and ascites formation. The mean survival time of SKOV3-bearing mice in treatment group is prolonged from 33 to 90 d. These results indicate that the alendronate-originated iron chelator can serve as an efficient strategy for the treatment of peritoneal carcinomatosis.

EEG-based vibrotactile evoked brain-computer interfaces system: A systematic review.

Recently, a novel electroencephalogram-based brain-computer interface (EVE-BCI) using the vibrotactile stimulus shows great potential for an alternative to other typical motor imagery and visual-based ones. (i) Objective: in this review, crucial aspects of EVE-BCI are extracted from the literature to summarize its key factors, investigate the synthetic evidence of feasibility, and generate recommendations for further studies. (ii) Method: five major databases were searched for relevant publications. Multiple key concepts of EVE-BCI, including data collection, stimulation paradigm, vibrotactile control, EEG signal processing, and reported performance, were derived from each eligible article. We then analyzed these concepts to reach our objective. (iii) Results: (a) seventy-nine studies are eligible for inclusion; (b) EEG data are mostly collected among healthy people with an embodiment of EEG cap in EVE-BCI development; (c) P300 and Steady-State Somatosensory Evoked Potential are the two most popular paradigms; (d) only locations of vibration are heavily explored by previous researchers, while other vibrating factors draw little interest. (e) temporal features of EEG signal are usually extracted and used as the input to linear predictive models for EVE-BCI setup; (f) subject-dependent and offline evaluations remain popular assessments of EVE-BCI performance; (g) accuracies of EVE-BCI are significantly higher than chance levels among different populations. (iv) Significance: we summarize trends and gaps in the current EVE-BCI by identifying influential factors. A comprehensive overview of EVE-BCI can be quickly gained by reading this review. We also provide recommendations for the EVE-BCI design and formulate a checklist for a clear presentation of the research work. They are useful references for researchers to develop a more sophisticated and practical EVE-BCI in future studies.

Engineering Chemotherapeutic-Augmented Calcium Phosphate Nanoparticles for Treatment of Intraperitoneal Disseminated Ovarian Cancer.

Ovarian cancer is a common gynecologic malignancy with a high fatality rate. Intraperitoneal chemotherapy has been proved as an efficient clinical treatment for disseminated ovarian cancer. However, there are limitations for conventional small molecule drugs to achieve an ideal therapeutic effect. Herein, a synergistic treatment for intraperitoneally disseminated ovarian cancer was achieved by Arg-Gly-Asp (RGD)-modified amorphous calcium phosphate loading with doxorubicin (designated as RGD-CaPO/DOX). The engineered calcium-involved nanomedicine augmented the therapeutic effect of DOX by aggravating endoplasmic reticulum stress, calcium overload, and mitochondrial dysfunction, ultimately triggering mitochondrial apoptosis in the SKOV3 (human ovarian cancer) cell line. In an intraperitoneally disseminated tumor model, RGD modification and the weak negative surface potential of the NPs were beneficial for intraperitoneal retention and tumor targeting. Moreover, intraperitoneal injection of RGD-CaPO/DOX NPs resulted in a favorable antitumor effect. The mean survival time of SKOV3-bearing mice was significantly extended from 29 to 59 days with negligible toxicity. Therefore, this study has been designed to provide an effective chemotherapeutic-augmented treatment for intraperitoneally disseminated ovarian cancer.

Carrier-free multifunctional nanomedicine for intraperitoneal disseminated ovarian cancer therapy.

BACKGROUND: Ovarian cancer is the most lethal gynecological cancer which is characterized by extensive peritoneal implantation metastasis and malignant ascites. Despite advances in diagnosis and treatment in recent years, the five-year survival rate is only 25-30%. Therefore, developing multifunctional nanomedicine with abilities of promoting apoptosis and inhibiting migration on tumor cells would be a promising strategy to improve the antitumor effect. METHODS AND RESULTS: In this study, we developed a novel ACaT nanomedicine composed of alendronate, calcium ions and cyclin-dependent kinase 7 (CDK7) inhibitor THZ1. With the average size of 164 nm and zeta potential of 12.4 mV, the spherical ACaT nanoparticles were selectively internalized by tumor cells and effectively accumulated in the tumor site. Results of RNA-sequencing and in vitro experiments showed that ACaT promoted tumor cell apoptosis and inhibited tumor cell migration by arresting the cell cycle, increasing ROS and affecting calcium homeostasis. Weekly intraperitoneally administered of ACaT for 8 cycles significantly inhibited the growth of tumor and prolonged the survival of intraperitoneal xenograft mice. CONCLUSION: In summary, this study presents a new self-assembly nanomedicine with favorable tumor targeting, antitumor activity and good biocompatibility, providing a novel therapeutic strategy for advanced ovarian cancer.

A calcium phosphate drug carrier loading with 5-fluorouracil achieving a synergistic effect for pancreatic cancer therapy.

Calcium based biomaterials were widely used for drug delivery application due to their biodegradability, biocompatibility, and high drug loading capacity. Herein, amino-capped polyamidoamine (PAMAM) dendrimer was applied as a macromolecular template to form amino-modified calcium phosphate hollow sphere (CaPO-NH2). After loading with 5-fluorouracil (5Fu), this system performed synergistic cancer chemotherapy. In this study, the 5Fu/CaPO-NH2 particles could be efficiently uptaken by cancer cells, and then decompose into Ca2+ and release 5Fu drug in the cytoplasm; therefore calcium overload and reactive oxygen species (ROS) accumulation were found in PSN1 cells that could induce cell membrane damage and elicit cell apoptosis through a series of biochemical reactions including endoplasmic reticulum stress, lipid peroxidation and mitochondrial apoptosis. In the PSN1 pancreatic cancer xenograft model, the 5Fu/CaPO-NH2 system performed high tumor inhibition via chemotherapy and calcium overload induced apoptosis. Comparingly, the normal cells and organs were insensitive to this synergistic therapy, which indicated the well biocompatibility of delivery system. Thus, this study provided a promising CaPO-NH2 drug delivery platform for enhanced 5Fu chemotherapeutic effect.

Relation Learning Using Temporal Episodes for Motor Imagery Brain-Computer Interfaces.

For practical motor imagery (MI) brain-computer interface (BCI) applications, generating a reliable model for a target subject with few MI trials is important since the data collection process is labour-intensive and expensive. In this paper, we address this issue by proposing a few-shot learning method called temporal episode relation learning (TERL). TERL models MI with only limited trials from the target subject by the ability to compare MI trials through episode-based training. It can be directly applied to a new user without being re-trained, which is vital to improve user experience and realize real-world MIBCI applications. We develop a new and effective approach where, unlike the original episode learning, the temporal pattern between trials in each episode is encoded during the learning to boost the classification performance. We also perform an online evaluation simulation, in addition to the offline analysis that the previous studies only conduct, to better understand the performance of different approaches in real-world scenario. Extensive experiments are completed on four publicly available MIBCI datasets to evaluate the proposed TERL. Results show that TERL outperforms baseline and recent state-of-the-art methods, demonstrating competitive performance for subject-specific MIBCI where few trials are available from a target subject and a considerable number of trials from other source subjects.

A Generalizable and Discriminative Learning Method for Deep EEG-Based Motor Imagery Classification.

Convolutional neural networks (CNNs) have been widely applied to the motor imagery (MI) classification field, significantly improving the state-of-the-art (SoA) performance in terms of classification accuracy. Although innovative model structures are thoroughly explored, little attention was drawn toward the objective function. In most of the available CNNs in the MI area, the standard cross-entropy loss is usually performed as the objective function, which only ensures deep feature separability. Corresponding to the limitation of current objective functions, a new loss function with a combination of smoothed cross-entropy (with label smoothing) and center loss is proposed as the supervision signal for the model in the MI recognition task. Specifically, the smoothed cross-entropy is calculated by the entropy between the predicted labels and the one-hot hard labels regularized by a noise of uniform distribution. The center loss learns a deep feature center for each class and minimizes the distance between deep features and their corresponding centers. The proposed loss tries to optimize the model in two learning objectives, preventing overconfident predictions and increasing deep feature discriminative capacity (interclass separability and intraclass invariant), which guarantee the effectiveness of MI recognition models. We conduct extensive experiments on two well-known benchmarks (BCI competition IV-2a and IV-2b) to evaluate our method. The result indicates that the proposed approach achieves better performance than other SoA models on both datasets. The proposed learning scheme offers a more robust optimization for the CNN model in the MI classification task, simultaneously decreasing the risk of overfitting and increasing the discriminative power of deeply learned features.

Social Support and Academic Burnout Among University Students: A Moderated Mediation Model.

PURPOSE: An increasing number of studies have been carried out to investigate the relationship between social support and study motivation among university students, but underlying mechanisms behind this pathway have not been fully verified. In the present study, we aimed to test the effect of social support on academic burnout (decrease in study motivation); examine the mediating effect of life satisfaction on the association between social support and academic burnout; and explore whether this mediating effect varied across (moderated mediation) students of different socioeconomic status (SES). MATERIALS AND METHODS: Data for 503 students were collected in a Chinese university through a composited survey regarding social support, life satisfaction, SES, and academic burnout. Data analysis and the investigation of combined effects in the model were carried out via conditional process modeling. RESULTS: Results indicated that social support was negatively associated with academic burnout. In addition, life satisfaction had a partial mediation effect on the relationship between social support and academic burnout, and SES moderated this mediation effect. Specifically, the mediation effect was found to be more significant among students in the high SES group than those in the lower one. CONCLUSION: This study is novel in that it establishes empirically how academic burnout is associated with a typical society analytical variable (ie, social support) among students in tertiary education. It also investigates an alternative scenario to explain the underlying mechanism of social support on academic burnout against the most popular explaining model. Implications of the study for effective elimination of the decrease in study motivation across students with different SES are discussed.

Multiple Plasmid Vectors Mediate the Spread of fosA3 in Extended-Spectrum-ß-Lactamase-Producing Enterobacterales Isolates from Retail Vegetables in China.

The plasmid-mediated fosfomycin resistance gene fosA3 has been detected in Enterobacterales from various sources but has rarely been reported in vegetables. In this study, the aim was to investigate the prevalence of and, subsequently, to characterize fosA3-positive Enterobacterales isolates from retail vegetables. Seventeen (7.3%) fosA3-carrying strains were identified from 233 extended-spectrum-ß-lactamase-producing Enterobacterales isolates from vegetables. All 17 isolates, including six Escherichia coli, seven Klebsiella pneumoniae, two Raoultella ornithinolytica, and two Citrobacter freundii isolates, carried blaCTX-M S1-nuclease pulsed-field gel electrophoresis (S1-PFGE) and hybridization confirmed that the fosA3 genes in 16 isolates were located on plasmids ranging in size from ∼40 kb to ∼250 kb, except one located on chromosome of C. freundii All the fosA3-carrying plasmids from 16 fosA3-positive isolates were successfully transferred into the recipient bacteria by transformation or conjugation. In agreement with data determined with isolates from food animals, the IncHI2/ST3 and IncN-F33:A-:B-/F33:A-:B plasmids were the main vectors of fosA3 in E. coli Additionally, F24:A-:B1, IncFIIK-IncR, IncFIIS, IncR, and two untypeable plasmids were found for the first time to be vectors for fosA3 in Enterobacterales The genetic contexts of fosA3 in 15 Enterobacterales isolates differed due to insertion and/or loss of molecular modules mediated by mobile elements. However, all fosA3 genes were flanked by IS26, as commonly observed in other fosA3-carrying plasmids. Here, we report a high rate of detection of fosA3 genes, mediated by multiple plasmid vectors, in ESBL-producing Enterobacterales from retail vegetables. FosA3-producing Enterobacterales could be transmitted to the human body by direct contact or consumption of vegetables, which might pose a potential threat to public health.IMPORTANCE This report provides important information on the transmission and epidemiology of fosA3 among Enterobacterales isolates from vegetables. The rate of occurrence of fosA3 in ESBL-producing Enterobacterales from retail vegetables is high, and fosA3 was found to be carried by diverse plasmids. Some novel genetic contexts of fosA3 and novel fosA3-carrying plasmids, including several plasmid types common in K. pneumoniae, were identified, increasing the number of known transfer vectors for the fosA3 gene and reflecting the complexity of fosA3 transmission in Enterobacterales The capture of fosA3 by the resident plasmid of K. pneumoniae will accelerate the spread of fosA3 in K. pneumoniae, one of the most pathogenic species in clinical medicine. Considering the clinical importance of fosfomycin, and the fact that vegetables are directly consumed, the fosfomycin resistance genes present a risk of transmission to the human body through the food chain and thus pose a threat to public health.

Mesenchymal stem cells: current clinical progress in ARDS and COVID-19.

Acute respiratory distress syndrome (ARDS) develops rapidly and has a high mortality rate. Survivors usually have low quality of life. Current clinical management strategies are respiratory support and restricted fluid input, and there is no suggested pharmacological treatment. Mesenchymal stromal cells (MSCs) have been reported to be promising treatments for lung diseases. MSCs have been shown to have a number of protective effects in some animal models of ARDS by releasing soluble, biologically active factors. In this review, we will focus on clinical progress in the use of MSCs as a cell therapy for ARDS, which may have clinical implications during the coronavirus disease 2019 (COVID-19) pandemic.

Rapid Increase in Carbapenemase-Producing Enterobacteriaceae in Retail Meat Driven by the Spread of the blaNDM-5-Carrying IncX3 Plasmid in China from 2016 to 2018.

The presence and molecular characteristics of carbapenemase-producing Enterobacteriaceae (CPE) among meat products in China were investigated. A total of 110 carbapenem-resistant Enterobacteriaceae (CRE) isolates, including 94 Escherichia coli and 10 Klebsiella pneumoniae isolates, were identified from 105 of 794 (13.2%) samples. The positive rates markedly increased from 2016 (9.4%) to 2018 (22.2%). Only blaNDM genes were detected; 79.1% of blaNDM genes were carried by IncX3 plasmids. Routine monitoring of carbapenemase-producing Enterobacteriaceae in the animal food supply is highly recommended.

Emergence of mcr-1 in Raoultella ornithinolytica and Escherichia coli Isolates from Retail Vegetables in China.

The presence of mcr-1 among Enterobacteriaceae isolates collected from retail vegetables in China between 2015 and 2016 was investigated. Two Raoultella ornithinolytica and seven Escherichia coli strains recovered from lettuce and tomato samples were identified as MCR-1-producers. Similar to isolates from animals and humans, the mcr-1 gene was located on the IncHI2/ST3, IncI2, or IncX4 plasmids. The presence of MCR-1-producing organisms in ready-to-eat food samples represents a serious risk for human health.