Highly Sensitive Detection of PIK3CA Mutations by Looping-Out Probes-Based Melting Curve Analysis.

PIK3CA mutations have important therapeutic and prognostic implications in various cancer types. However, highly sensitive detection of PIK3CA hotspot mutations in heterogeneous tumor samples remains a challenge in clinical settings. To establish a rapid PCR assay for highly sensitive detection of multiple PIK3CA hotspot mutations. We described a novel melting curve analysis-based assay using looping-out probes that can enrich target mutations in the background of excess wild-type and concurrently reveal the presence of mutations. The analytical and clinical performance of the assay were evaluated. The developed assay could detect 10 PIK3CA hotspot mutations at a mutant allele fraction of 0.05-0.5% within 2 h in a single step. Analysis of 82 breast cancer tissue samples revealed 43 samples with PIK3CA mutations, 28 of which were confirmed by Sanger sequencing. Further testing of 175 colorectal cancer tissue samples showed that 24 samples contained PIK3CA mutations and 19 samples were confirmed by Sanger sequencing. Droplet digital PCR supported that all mutation-containing samples undetected by sequencing contained mutations with a low allele fraction. The rapidity, ease of use, high sensitivity and accuracy make the new assay a potential screening tool for PIK3CA mutations in clinical laboratories.

Accurate Detection of Multiple Tumor Mutations in Formalin-Fixed Paraffin-Embedded Tissues by Coupling Sequence Artifacts Elimination and Mutation Enrichment With MeltArray.

Formalin-fixed paraffin-embedded (FFPE) tissues are the primary source of DNA for companion diagnostics (CDx) of cancers. Degradation of FFPE tissue DNA and inherent tumor heterogeneity constitute serious challenges in current CDx assays. To address these limitations, we introduced sequence artifact elimination and mutation enrichment to MeltArray, a highly multiplexed PCR approach, to establish an integrated protocol that provides accuracy, ease of use, and rapidness. Using PIK3CA mutations as a model, we established a MeltArray protocol that could eliminate sequence artifacts completely and enrich mutations from 23.5- to 59.4-fold via a single-reaction pretreatment step comprising uracil-DNA-glycosylase excision and PCR clamping. The entire protocol could identify 13 PIK3CA hotspot mutations of 0.05% to 0.5% mutant allele fractions within 5 hours. Evaluation of 106 breast cancer and 40 matched normal FFPE tissue samples showed that all 47 PIK3CA mutant samples were from the cancer tissue, and no false-positive results were detected in the normal samples. Further evaluation of 105 colorectal and 40 matched normal FFPE tissue samples revealed that 11 PIK3CA mutants were solely from the cancer sample. The detection results of our protocol were consistent with those of the droplet digital PCR assays that underwent sequence artifact elimination. Of the 60 colorectal samples with next-generation sequencing results, the MeltArray protocol detected 2 additional mutant samples with low mutant allele fractions. We conclude that the new protocol provides an improved alternative to current CDx assays for detecting tumor mutations in FFPE tissue DNA.

Identification of pneumococcal serotypes with individual recognition of vaccine types by a highly multiplexed real-time PCR-based MeltArray approach.

BACKGROUND: Pneumococcus serotyping is important for monitoring serotype epidemiology, vaccine-induced serotypes replacement and emerging pathogenic serotypes. However, the lack of high-resolution serotyping tools has hindered its widespread implementation. METHODS: We devised a single-step, multiplex real-time polymerase chain reaction (PCR)-based MeltArray approach termed PneumoSero that can identify 92 serotypes with individual recognition of 54 serotypes, including all 24 currently available vaccine types. The limit of detection (LOD) and the ability to coexisting serotypes were studied, followed by analytical evaluation using 92 reference pneumococcal strains and 125 non-pneumococcal strains, and clinical evaluation using 471 pneumococcus isolates and 46 pneumococcus-positive clinical samples. RESULTS: The LODs varied with serotypes from 50 to 100 copies per reaction and 10 % of the minor serotypes were detectable in samples containing two mixed serotypes. Analytical evaluation presented 100 % accuracy in both 92 reference pneumococcal strains and 125 non-pneumococcal strains. Clinical evaluation of 471 pneumococcus isolates displayed full concordance with Sanger sequencing results. The 46 clinical specimens yielded 45 typeable results and one untypeable result. Of the 45 typeable samples, 41 were of a single serotype and four were of mixed serotypes, all of which were confirmed by Sanger sequencing or separate PCR assays. CONCLUSION: We conclude that the PneumoSero assay can be implemented as a routine tool for pneumococcal serotyping in standard microbiology laboratories and even in clinical settings.

Direct identification of pathogens via microbial cellular DNA in whole blood by MeltArray.

Rapid identification of pathogens is critical for early and appropriate treatment of bloodstream infections. The various culture-independent assays that have been developed often have long turnaround times, low sensitivity and narrow pathogen coverage. Here, we propose a new multiplex PCR assay, MeltArray, which uses intact microbial cells as the source of genomic DNA (gDNA). The successive steps of the MeltArray assay, including selective lysis of human cells, microbial cell sedimentation, microbial cellular DNA extraction, target-specific pre-amplification and multiplex PCR detection, allowed the detection of 35 major bloodstream infectious pathogens in whole blood within 5.5 h. The limits of detection varied depending on the pathogen and ranged from 1 to 5 CFU/mL. Of 443 blood culture samples, including 373 positive blood culture samples and 70 negative blood culture samples, the MeltArray assay showed a sensitivity of 93.8% (350/373, 95% confidence interval [CI] = 90.7%-96.0%), specificity of 98.6% (69/70, 95% CI = 91.2%-99.9%), positive predictive value of 99.7% (95% CI = 98.1%-99.9%), and negative predictive value of 75.0% (95% CI = 64.7%-83.2%). The MeltArray detection results of 16 samples differed from MALDI-TOF and were confirmed by Sanger sequencing. Further testing of 110 whole blood samples from patients with suspected bloodstream infections using blood culture results revealed that the MeltArray assay had a clinical sensitivity of 100% (9/9, 95% CI = 62.8%-100.0%), clinical specificity of 74.5% (70/94, 95% CI = 64.2%-82.7%), positive predictive value of 27.3% (95% CI = 13.9%-45.8%), and negative predictive value of 100.0% (95% CI = 93.5%-100.0%). Compared with metagenomic next-generation sequencing, the MeltArray assay displayed a positive agreement of 85.7% (6/7, 95% CI = 42.0%-99.2%) and negative agreement of 100.0% (4/4, 95% CI = 39.6%-100.0%). We conclude that the MeltArray assay can be used as a rapid and reliable tool for direct identification of pathogens in bloodstream infections.

Single-tube protocol for culture-independent spoligotyping of Mycobacterium tuberculosis based on MeltArray.

IMPORTANCE: Spacer oligonucleotide typing (spoligotyping), the first-line genotyping assay for Mycobacterium tuberculosis (MTB), plays a fundamental role in the investigation of its epidemiology and evolution. In this study, we established a single-tube spoligotyping assay using MeltArray, a highly multiplex polymerase chain reaction (PCR) approach that runs on a real-time PCR thermocycler. The MeltArray protocol included an internal positive control, gyrB, to indicate the abundance of MTB via the quantification cycle and 43 spacers to identify the spoligotype via melting curve analysis. The entire protocol was completed in a single step within 2.5 hours. The lowest detectable copy number for the tested strains was 20 copies/reaction and thus sufficient for analyzing both culture and sputum samples. We conclude that MeltArray-based spoligotyping could be used immediately in low- and middle-income countries with a high tuberculosis burden, given its easy access, improved throughput, and potential applicability to clinical samples.

Epidemiological Insights into the Omicron Outbreak via MeltArray-Assisted Real-Time Tracking of SARS-CoV-2 Variants.

The prolonged course of the COVID-19 pandemic necessitates sustained surveillance of emerging variants. This study aimed to develop a multiplex real-time polymerase chain reaction (rt-PCR) suitable for the real-time tracking of Omicron subvariants in clinical and wastewater samples. Plasmids containing variant-specific mutations were used to develop a MeltArray assay. After a comprehensive evaluation of both analytical and clinical performance, the established assay was used to detect Omicron variants in clinical and wastewater samples, and the results were compared with those of next-generation sequencing (NGS) and droplet digital PCR (ddPCR). The MeltArray assay identified 14 variant-specific mutations, enabling the detection of five Omicron sublineages (BA.2*, BA.5.2*, BA.2.75*, BQ.1*, and XBB.1*) and eight subvariants (BF.7, BN.1, BR.2, BQ.1.1, XBB.1.5, XBB.1.16, XBB.1.9, and BA.4.6). The limit of detection (LOD) of the assay was 50 copies/reaction, and no cross-reactivity was observed with 15 other respiratory viruses. Using NGS as the reference method, the clinical evaluation of 232 swab samples exhibited a clinical sensitivity of > 95.12% (95% CI 89.77-97.75%) and a specificity of > 95.21% (95% CI, 91.15-97.46%). When used to evaluate the Omicron outbreak from late 2022 to early 2023, the MeltArray assay performed on 1408 samples revealed that the epidemic was driven by BA.5.2* (883, 62.71%) and BF.7 (525, 37.29%). Additionally, the MeltArray assay demonstrated potential for estimating variant abundance in wastewater samples. The MeltArray assay is a rapid and scalable method for identifying SARS-CoV-2 variants. Integrating this approach with NGS and ddPCR will improve variant surveillance capabilities and ensure preparedness for future variants.

CovidShiny: An Integrated Web Tool for SARS-CoV-2 Mutation Profiling and Molecular Diagnosis Assay Evaluation In Silico.

The coronavirus disease 2019 (COVID-19) pandemic is still ongoing, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continuing to evolve and accumulate mutations. While various bioinformatics tools have been developed for SARS-CoV-2, a well-curated mutation-tracking database integrated with in silico evaluation for molecular diagnostic assays is currently unavailable. To address this, we introduce CovidShiny, a web tool that integrates mutation profiling, in silico evaluation, and data download capabilities for genomic sequence-based SARS-CoV-2 assays and data download. It offers a feasible framework for surveilling the mutation of SARS-CoV-2 and evaluating the coverage of the molecular diagnostic assay for SARS-CoV-2. With CovidShiny, we examined the dynamic mutation pattern of SARS-CoV-2 and evaluated the coverage of commonly used assays on a large scale. Based on our in silico analysis, we stress the importance of using multiple target molecular diagnostic assays for SARS-CoV-2 to avoid potential false-negative results caused by viral mutations. Overall, CovidShiny is a valuable tool for SARS-CoV-2 mutation surveillance and in silico assay design and evaluation.

Using microneedle array electrodes for non-invasive electrophysiological signal acquisition and sensory feedback evoking.

Introduction: Bidirectional transmission of information is needed to realize a closed-loop human-machine interaction (HMI), where electrophysiological signals are recorded for man-machine control and electrical stimulations are used for machine-man feedback. As a neural interface (NI) connecting man and machine, electrodes play an important role in HMI and their characteristics are critical for information transmission. Methods: In this work, we fabricated a kind of microneedle array electrodes (MAEs) by using a magnetization-induced self-assembly method, where microneedles with a length of 500-600 µm and a tip diameter of ∼20 µm were constructed on flexible substrates. Part of the needle length could penetrate through the subjects' stratum corneum and reach the epidermis, but not touch the dermis, establishing a safe and direct communication pathway between external electrical circuit and internal peripheral nervous system. Results: The MAEs showed significantly lower and more stable electrode-skin interface impedance than the metal-based flat array electrodes (FAEs) in various testing scenarios, demonstrating their promising impedance characteristics. With the stable microneedle structure, MAEs exhibited an average SNR of EMG that is more than 30% higher than FAEs, and a motion-intention classification accuracy that is 10% higher than FAEs. The successful sensation evoking demonstrated the feasibility of the MAE-based electrical stimulation for sensory feedback, where a variety of natural and intuitive feelings were generated in the subjects and thereafter objectively verified through EEG analysis. Discussion: This work confirms the application potential of MAEs working as an effective NI, in both electrophysiological recording and electrical stimulation, which may provide a technique support for the development of HMI.

An Approach for EEG Denoising Based on Wasserstein Generative Adversarial Network.

Electroencephalogram (EEG) recordings often contain artifacts that would lower signal quality. Many efforts have been made to eliminate or at least minimize the artifacts, and most of them rely on visual inspection and manual operations, which is time/labor-consuming, subjective, and incompatible to filter massive EEG data in real-time. In this paper, we proposed a deep learning framework named Artifact Removal Wasserstein Generative Adversarial Network (AR-WGAN), where the well-trained model can decompose input EEG, detect and delete artifacts, and then reconstruct denoised signals within a short time. The proposed approach was systematically compared with commonly used denoising methods including Denoised AutoEncoder, Wiener Filter, and Empirical Mode Decomposition, with both public and self-collected datasets. The experimental results proved the promising performance of AR-WGAN on automatic artifact removal for massive data across subjects, with correlation coefficient up to 0.726±0.033, and temporal and spatial relative root-mean-square error as low as 0.176±0.046 and 0.761±0.046, respectively. This work may demonstrate the proposed AR-WGAN as a high-performance end-to-end method for EEG denoising, with many on-line applications in clinical EEG monitoring and brain-computer interfaces.

ST-YOLOA: a Swin-transformer-based YOLO model with an attention mechanism for SAR ship detection under complex background.

A synthetic aperture radar (SAR) image is crucial for ship detection in computer vision. Due to the background clutter, pose variations, and scale changes, it is a challenge to construct a SAR ship detection model with low false-alarm rates and high accuracy. Therefore, this paper proposes a novel SAR ship detection model called ST-YOLOA. First, the Swin Transformer network architecture and coordinate attention (CA) model are embedded in the STCNet backbone network to enhance the feature extraction performance and capture global information. Second, we used the PANet path aggregation network with a residual structure to construct the feature pyramid to increase global feature extraction capability. Next, to cope with the local interference and semantic information loss problems, a novel up/down-sampling method is proposed. Finally, the decoupled detection head is used to achieve the predicted output of the target position and the boundary box to improve convergence speed and detection accuracy. To demonstrate the efficiency of the proposed method, we have constructed three SAR ship detection datasets: a norm test set (NTS), a complex test set (CTS), and a merged test set (MTS). The experimental results show that our ST-YOLOA achieved an accuracy of 97.37%, 75.69%, and 88.50% on the three datasets, respectively, superior to the effects of other state-of-the-art methods. Our ST-YOLOA performs favorably in complex scenarios, and the accuracy is 4.83% higher than YOLOX on the CTS. Moreover, ST-YOLOA achieves real-time detection with a speed of 21.4 FPS.

Ability of the MeltPro MTB/PZA Assay to Detect Susceptibility to Pyrazinamide in Rifampin-Resistant Tuberculosis Patients.

Prediction of susceptibility to pyrazinamide (PZA) directly from sputum has been challenging. The MeltPro MTB/PZA assay, based on melting curve analysis, can simultaneously detect Mycobacterium tuberculosis and the resistance to PZA from sputum. We aimed to evaluate the MeltPro MTB/PZA assay to predict PZA resistance among rifampin-resistant tuberculosis (RR-TB) patients. We prospectively enrolled RR-TB patients in the registered trials, and their baseline sputum samples were obtained to perform the assay and culture. DNA sequencing of culture isolates was analyzed and used as the reference standard. Sanger sequencing was performed for samples with discrepant results between next-generation sequencing (NGS) and the investigational assay. The main analysis was conducted in the population of patients with interpretable results by both NGS and the assay. A total of 239 patients with RR-TB were screened, and 220 underwent the MeltPro MTB/PZA assay. The assay provided no information for 25 of 220 patients (11.4%). Among the remaining 195 patients, 13 had negative culture or insufficient raw NGS sequencing data, and 15 had indeterminate assay results. A total of 167 patients were included in the main analysis. Against DNA sequencing, the sensitivity, specificity, and negative predictive value of the assay for detecting resistance to PZA were 91.4% (95% confidence interval [CI], 87.1% to 95.6%), 89.9% (95% CI, 85.3% to 94.5%), and 95.2% (95% CI, 91.9% to 98.4%), respectively. In conclusion, the MeltPro MTB/PZA assay is a fast semiautomatic molecular platform to rapidly predict resistance to PZA from sputum and holds promise as a screening tool with satisfactory sensitivity. IMPORTANCE This study evaluated the accuracy of the MeltPro MTB/PZA assay at detecting the presence of PZA resistance through registered clinical trials. Compared to DNA sequencing, the assay had high sensitivity and negative predictive value, suggesting its potential utility as a screening tool in clinical practice. The assay could serve as an ideal primary screening tool in low PZA-resistant M. tuberculosis prevalence settings and could be used as an additional test to identify PZA resistance rapidly and initially in the RR-TB population.

Quantification of Isoniazid-Heteroresistant Mycobacterium tuberculosis Using Droplet Digital PCR.

The quantitative detection of drug-resistance mutations in Mycobacterium tuberculosis (MTB) is critical for determining the drug resistance status of a sample. We developed a drop-off droplet digital PCR (ddPCR) assay targeting all major isoniazid (INH)-resistant mutations. The ddPCR assay consisted of three reactions: reaction A detects mutations at katG S315; reaction B detects inhA promoter mutations; and reaction C detects ahpC promoter mutations. All reactions could quantify 1%-50% of mutants in the presence of the wild-type, ranging from 100 to 50,000 copies/reaction. Clinical evaluation with 338 clinical isolates yielded clinical sensitivity of 94.5% (95% confidence interval [CI] = 89.1%-97.3%) and clinical specificity of 97.6% (95% CI = 94.6%-99.0%) compared with the traditional drug susceptibility testing (DST). Further clinical evaluation using 194 nucleic acid-positive MTB sputum samples revealed clinical sensitivity of 87.8% (95% CI = 75.8%-94.3%) and clinical specificity of 96.5% (95% CI = 92.2%-98.5%) in comparison with DST. All the mutant and heteroresistant samples detected by the ddPCR assay but susceptible by DST were confirmed by combined molecular assays, including Sanger sequencing, mutant-enriched Sanger sequencing and a commercial melting curve analysis-based assay. Finally, the ddPCR assay was used to monitor longitudinally the INH-resistance status and the bacterial load in nine patients undergoing treatment. Overall, the developed ddPCR assay could be an indispensable tool for quantification of INH-resistant mutations in MTB and bacterial loads in patients.

The relationship between psychological contract and occupational wellbeing of mother-infant care helpers in Zhejiang Province.

BACKGROUND: Mother-infant care (MIC) helpers have become an indispensable part in hospital services. In order to stabilize the MIC workforce, it is essential for administrators to have a solid understanding of what may influence occupational wellbeing. This article aims to explore how demographic characteristics and psychological contract affect occupational wellbeing among MIC helpers in Zhejiang Province, China. METHODS: This is a quantitative, cross-sectional study with MIC helpers in obstetrics from 20 hospitals in Zhejiang Province. A questionnaire including demographic data, a psychological contract scale and an occupational wellbeing scale was used in this study. Multiple linear regression was conducted to investigate the relationships between demographic characteristics, psychological contract and occupational wellbeing. RESULTS: This study surveyed 260 MIC helpers and found out the mean score of the psychological contract was 4.38 and the mean score of the occupational wellbeing was 4.01. Monthly income and psychological contract were significant predictors of occupational wellbeing (F = 142.167, p < 0.001), which explained 62.1% of the total amount of variance in occupational wellbeing. Psychological contract was the most important predictor of occupational wellbeing. CONCLUSIONS: Administrators should pay attention to the effect of psychological contract on occupational wellbeing of the MIC helpers in China. Focusing on the inner needs should be considered as a strategy for stabilizing the team.

The prevalence and genetic disorders spectrum of thalassemia among breast cancer patients in Jiangxi province, China.

Background: Thalassemia is a common inherited hematological disease with genetic disorders characterized by imbalanced synthesis of the globin chains. Due to the improvement of treatment methods, patients with thalassemia can survive for a long time. Therefore, it is not uncommon for patients with thalassemia suffering from malignant tumors. However, there are quite few reports on thalassemia patients complicated with breast cancer. Herein, we try to investigate the prevalence and genetic disorders spectrum of thalassemia in patients with breast cancer. Methods: Blood routing tests and serum ferritin analysis were conducted in 1887 breast cancer patients treated in the department of radiation oncology during 1 April 2020 and 30 March 2022. The suspected thalassemia carriers with small mean corpuscular volume (MCV), mean corpuscular hemoglobin content (MCH) or mean corpuscular hemoglobin concentration (MCHC) but the concentration of serum ferritin within normal limits were further investigated by polymerase chain reaction (PCR) and flow through hybridization gene chip to detect common mutations of α-globin and ß-globin genes using Thalassemia Geno Array Diagnostic Kit. The prevalence and genetic mutation spectrum of thalassemia among breast cancer patients were analyzed. Results: Four hundred and eighty-nine suspected thalassemia carriers were detected by complete blood cell counts and serum ferritin analysis among 1887 breast cancer patients. One hundred and seven cases (5.7%) were identified as carriers of thalassemia, of which 55 cases (51.4%) were α-thalassemia, 50 cases (46.7%) were ß-thalassemia, and 2 cases (1.9%) were co-inheritance of α-thalassemia and ß-thalassemia simultaneously. In α-thalassemia, the most prevalent genotype is -SEA/αα; as for ß-thalassemia, ßIVS-II-654/ß is the most common genotype. The degree of anemia is more severe in ß-thalassemia than in α-thalassemia. Conclusion: This is the first comprehensive molecular epidemiological investigation on thalassemia among breast cancer patients. Our data indicated that thalassemia was not uncommon in breast cancer patients. The physicians should have the knowledge to avoid misdiagnosis as iron deficiency anemia.

Qualitative and Quantitative Detection of Multiple Sexually Transmitted Infection Pathogens Reveals Distinct Associations with Cervicitis and Vaginitis.

Many diverse pathogens have been discovered from reproductive-tract infections, but the relationship between the presence and abundance of particular pathogen species and disease manifestations is poorly defined. The present work examined the association of multiple common pathogens causing sexually transmitted infections (STIs) with cervicitis and vaginitis. The presence and abundance of 15 STI pathogens and the genotypes of human papillomavirus were determined in a cohort of 944 women that included 159 cervicitis patients, 207 vaginitis patients, and 578 healthy controls. Logistic regression and random forest models were constructed and validated in a separate cohort of 420 women comprising 52 cervicitis patients, 109 vaginitis patients, and 259 healthy controls. The frequency of individual STI pathogen species varied among the symptomatic patients and healthy controls. Abundance determination was necessary for most pathogens that were associated with the studied diseases. STI pathogens were more commonly associated with cervicitis than with vaginitis. Pathogen identification- and quantification-based diagnosis was observed for cervicitis with high sensitivity and specificity, but for vaginitis, the assay results would need to be combined with results of other diagnostic tests to firmly establish the pathogen-disease correlation. Integrated qualitative and quantitative detection of a selected panel of common STI pathogens can reveal their association with cervicitis and vaginitis. STI pathogen identification and quantification can be used to diagnose cervicitis and also help improve correct diagnosis of vaginitis. IMPORTANCE Scarce information exists with regard to whether STI pathogens can be defined as valid microbiological predictive markers for the diagnosis of cervicitis and vaginitis. We therefore conducted this study to assess the presence and abundance of a wide range of STI pathogens among patients having these two diseases and healthy controls as well. High sensitivity and specificity were observed for cervicitis by pathogen identification- and quantification-based diagnosis. In contrast, the assay results obtained for vaginitis would need to be combined with test results obtained by other diagnostic methods to decisively establish the pathogen-disease correlation. Simultaneous qualitative and quantitative detection of a selected panel of common STI pathogens and further coupling with machine learning models is worthwhile for establishing pathogen-based diagnosis of gynecological inflammations, which could be of great value in guiding the rational use of antimicrobials to control the spread of STIs.

Accessible and Adaptable Multiplexed Real-Time PCR Approaches to Identify SARS-CoV-2 Variants of Concern.

Rapid identification and continuous surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are critical for guiding the response to the COVID-19 pandemic. Whole-genome sequencing (WGS) is a preferred tool for this aim, but many laboratories suffer from a lack of resources to support population-level sequencing. Here, we describe two PCR strategies targeting spike protein mutations to identify the Alpha, Delta, and Omicron variants. Signature mutations were selected using a dedicated bioinformatic program. The selected mutations in Alpha and Delta variants were detected using multicolor melting curve analysis (MMCA). Thirty-two mutations of the Omicron variant were targeted using the MeltArray approach in one reaction, which was able to detect the Omicron subvariants BA.1, BA.2, BA.3, and BA.4/5. The limits of detection varied from five to 50 copies of RNA templates/reactions. No cross-reactivity was observed with nine other respiratory viruses, including other coronaviruses. We validated the MMCA and MeltArray assays using 309 SARS-CoV-2 positive samples collected at different time points. These assays exhibited 98.3% to 100% sensitivity and 100% specificity compared with WGS. Multiplexed real-time PCR strategies represent an alternative tool capable of identifying current SARS-CoV-2 VOCs, adaptable for emerging variants and accessible for laboratories using existing equipment and personnel. IMPORTANCE Rapid detection and mutation surveillance of SARS-CoV-2 VOCs is crucial for COVID-19 control, management, and prevention. We developed two rapid molecular assays based on the real-time PCR platform to identify important variants of concern, including the Omicron variant with a large number of mutations. Signature mutations were selected by an R program. Then, MMCA assays were established for Alpha and Delta variants, and a MeltArray assay targeting 32 mutations was developed for Omicron variant. These multiplexed PCR assays could be performed in a 96-well real-time PCR instrument within 2.5 h, offering a high-throughput choice for dynamic monitoring of SARS-CoV-2 VOCs in a standard microbiology laboratory.

Highly multiplex PCR assays by coupling the 5'-flap endonuclease activity of Taq DNA polymerase and molecular beacon reporters.

Real-time PCR is the most utilized nucleic acid testing tool in clinical settings. However, the number of targets detectable per reaction are restricted by current modes. Here, we describe a single-step, multiplex approach capable of detecting dozens of targets per reaction in a real-time PCR thermal cycler. The approach, termed MeltArray, utilizes the 5'-flap endonuclease activity of Taq DNA polymerase to cleave a mediator probe into a mediator primer that can bind to a molecular beacon reporter, which allows for the extension of multiple mediator primers to produce a series of fluorescent hybrids of different melting temperatures unique to each target. Using multiple molecular beacon reporters labeled with different fluorophores, the overall number of targets is equal to the number of the reporters multiplied by that of mediator primers per reporter. The use of MeltArray was explored in various scenarios, including in a 20-plex assay that detects human Y chromosome microdeletions, a 62-plex assay that determines Escherichia coli serovars, a 24-plex assay that simultaneously identifies and quantitates respiratory pathogens, and a minisequencing assay that identifies KRAS mutations, and all of these different assays were validated with clinical samples. MeltArray approach should find widespread use in clinical settings owing to its combined merits of multiplicity, versatility, simplicity, and accessibility.

Using Social Media to Disseminate Effective Pain Treatments for Newborns During Needle-Related Painful Procedures in China.

Social media has become a powerful approach to disseminating evidence to knowledge users. The BSweet2Babies video was developed in multiple languages showing the effectiveness of sweet solutions, skin-to-skin care, and breastfeeding during newborn painful procedures. This study aimed to disseminate the BSweet2Babies video in Chinese through social media platform of WeChat in China; evaluate the reach, acceptability, and recommendation of the video; and assess viewers' previous knowledge and experience of using the 3 strategies and intention to use these strategies in the future. Multiple dissemination strategies were used to maximize views for a 6-month dissemination period. The video received 19 812 views, 4306 "thumbs," and 671 participants completed surveys. Of the survey respondents, 393 were parents. Most respondents did not know these strategies and did not use or help parents use any of them. More healthcare professionals than parents intended to use or advocate for sweet solutions and breastfeeding. More healthcare professionals rated that the 3 strategies were easy to apply in real-life situations, but more parents evaluated that the length of the video was too long. Social media in China can be a promising approach to disseminating evidence on neonatal procedural pain treatments to healthcare professionals and the public.

Segmental duplication as potential biomarkers for non-invasive prenatal testing of aneuploidies.

BACKGROUND: Segmental duplication (SD) regions are distinct targets for aneuploidy detection owing to the virtual elimination of amplification bias. The difficulty of searching SD sequences for assay design has hampered their applications. METHODS: We developed a computational program, ChAPDes, which integrates SD searching, refinement, and design of specific PCR primer/probe sets in a pipeline to remove most of the manual work. The generated primer/probe sets were first tested in a multiplex multicolour melting curve analysis for the detection of five common aneuploidies. The primer/probe sets were then tested in a digital PCR assay for the detection of trisomy 21. Finally, a digital PCR protocol was established to quantify maternal plasma DNA sequences for the non-invasive prenatal detection of fetal trisomy 21. FINDINGS: ChAPDes could output 21,772 candidate primer/probe sets for trisomy 13, 18, 21 and sex chromosome aneuploidies within 2 working days. Clinical evaluation of the multiplex multicolour melting curve analysis involving 463 fetal genomic DNA samples revealed a sensitivity of 100% and specificity of 99.64% in comparison with the reference methods. Using the established digital PCR protocol, we correctly identified two trisomy 21 fetuses and thirteen euploid foetuses from the maternal plasma samples. INTERPRETATION: The combination of ChAPDes with digital PCR detection could facilitate the use of SD as potential biomarkers for the non-invasive prenatal testing of fetal chromosomal aneuploidies. FUNDING: None.

Validating the Implementation Leadership Scale in Chinese nursing context: A cross-sectional study.

AIM: This study aimed to evaluate the validity, reliability and acceptability of the Implementation Leadership Scale in the Chinese nursing context. DESIGN: This study utilized a cross-sectional design. METHODS: This study was conducted in one general tertiary hospital with 234 nurses (85.3% response rate) from 35 clinical units in China. Content validity, structural validity, convergent validity, reliability (internal consistency), agreement indices and acceptability were evaluated. The data collection was from December 1st, 2017 to June 30th, 2018. RESULTS: Confirmatory factor analysis demonstrated a good model fit to the four-factor implementation leadership model. The psychometric testing also indicated good convergent validity, high internal consistency and acceptable aggregation. Most participants completed the scale in two minutes or less and agreed or strongly agreed that the questions were relevant to implementation leadership, clear and easy to answer. CONCLUSIONS: This study demonstrated that the Chinese Implementation Leadership Scale is a valid, reliable and pragmatic tool for measuring strategic leadership for implementing evidence-based practices.