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Studies have demonstrated that methylene blue exhibits significant antiviral activity against SARS-CoV-2 or related coronaviruses at the cellular level, suggesting its potential as an anti-SARS-CoV-2 drug. Herein, we report that methylene blue does not exhibit noticeable antiviral activity in a lethal model involving SARS-CoV-2-related pangolin coronavirus GX_P2V (short_3UTR) infection in CAG-hACE2 transgenic mice. We employed plaque reduction assays and cell infection experiments to compare the extracellular virucidal activity of the compound and its ability to inhibit viral replication in cells to those of nirmatrelvir. Methylene blue demonstrated strong virucidal activity but did not inhibit viral replication in cells. The control compound nirmatrelvir lacked virucidal activity but exhibited strong abilities to inhibit viral replication. The virucidal activity of methylene blue was further tested in mouse plasma. Incubation in mouse plasma increased the virucidal EC50 value of methylene blue, indicating that mouse plasma can affect the stability of the compound, although mouse plasma has some extent of natural virucidal activity. These findings elucidate why methylene blue lacks antiviral efficacy in vivo and provide insights for the development of antiviral drugs.

BackgroundKlebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied.MethodsA total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages.ResultsDuring K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1β, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease’s stages, and the expression of IFN-γ gene was upregulated.ConclusionThe proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment.

The biosynthetic potential of actinobacteria to produce novel natural products is still regarded as immense. In this paper, we correlated a cryptic biosynthetic gene cluster to chemical molecules by genome mining and chemical analyses, leading to the discovery of a new group of catecholate-hydroxamate siderophores, nobachelins, from Nocardiopsis baichengensis DSM 44845. Nobachelin biosynthesis genes are conserved in several bacteria from the family Nocardiopsidaceae. Structurally, nobachelins feature fatty-acylated hydroxy-ornithine and a rare chlorinated catecholate group. Intriguingly, nobachelins rescued Caenorhabditis elegans from Pseudomonas aeruginosa-mediated killing.

Abstract Background Early availability of pathogen identification in urinary tract infections (UTIs) has critical importance in disease management. Metagenomic next-generation sequencing (mNGS) has the potential to transform how acute and serious infections are diagnosed by offering unbiased and culture-free pathogen detection. However, clinical experience with application of the mNGS test is relatively limited. Methods We therefore established a MinION-based mNGS pathogens diagnostic platform and evaluated its potential for clinical implementation in UTIs with clinical samples. 213 urine samples from patients with suspected UTIs were included and subjected to mNGS testing using the MinION platform. mNGS results were compared to the gold standard of clinical culture and composite standard of combining clinical testing, confirmatory qPCR testing, and clinical adjudication by doctors. Results The mNGS exhibited a sensitivity of 81.4% and a specificity of 92.3%, along with a positive predictive value of 96.6%, a negative predictive value of 64.9%, and an overall accuracy of 84.4%, all of which were determined based on the gold standard of routine culture results. When assessed against the composite standard, the sensitivity and specificity both increased to 89.9% and 100%, respectively, while the accuracy rose to 92.4%. Notably, the positive predictive value and negative predictive value also saw improvements, reaching 100% and 76.8%, respectively. Moreover, this diagnostic platform successfully identified dsDNA viruses. Among the 65 culture-negative samples, the viral detection rate reached 33.8% (22/65) and was subsequently validated through qPCR. Furthermore, the automatic bioinformatics pipeline we developed enabled one-click analysis from data to results, leading to a significant reduction in diagnosis time. Conclusion These results demonstrate that the pathogen detection performance of mNGS is sufficient for diagnostic testing in clinical settings. As the method is generally unbiased, it can improve diagnostic testing of UTIs and other microbial infections.

Abstract Background Epilepsy is a neurological disorder that is usually detected by electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a laborious and time-consuming process, lots of automatic epilepsy detection algorithms have been proposed. However, most of the available classification algorithms for epilepsy EEG signals adopted a single feature extraction, in turn to result in low classification accuracy. Although a small account of studies have carried out feature fusion, the computational efficiency is reduced due to too many features, because there are also some poor features that interfere with the classification results. Methods In order to solve the above problems, an automatic recognition method of epilepsy EEG signals based on feature fusion and selection is proposed in this paper. Firstly, the Approximate Entropy (ApEn), Fuzzy Entropy (FuzzyEn), Sample Entropy (SampEn), and Standard Deviation (STD) mixed features of the subband obtained by the Discrete Wavelet Transform (DWT) decomposition of EEG signals are extracted. Secondly, the random forest algorithm is used for feature selection. Finally, the Convolutional Neural Network (CNN) is used to classify epilepsy EEG signals. Results The empirical evaluation of the presented algorithm is performed on the benchmark Bonn EEG datasets and New Delhi datasets. In the interictal and ictal classification tasks of Bonn datasets, the proposed model achieves an accuracy of 99.9%, a sensitivity of 100%, a precision of 99.81%, and a specificity of 99.8%. For the interictal-ictal case of New Delhi datasets, the proposed model achieves a classification accuracy of 100%, a sensitivity of 100%, a specificity of 100%, and a precision of 100%. Conclusion The proposed model can effectively realize the high-precision automatic detection and classification of epilepsy EEG signals. This model can provide high-precision automatic detection capability for clinical epilepsy EEG detection. We hope to provide positive implications for the prediction of seizure EEG.

We show that the photon dynamics and lifetimes in asymmetric optical microcavities are greatly modified if the cavity is constructed in a topologically curved space.

Enhancing the efficiency of quantum emitters is essential for exploring new functionalities. Here the authors show Si cuboids that sustain bound states in the continuum enable the injection of dense electron-hole plasma and provide high quantum efficiency.

Millimeter Wave(mmWave) radar has been widely used in vital sign monitoring with non-contact and privacy protection. To reduce the effect of random body motion, respiration, and its harmonics on heart rate estimation, the heart rate monitoring based on frequency-modulated continuous-wave (FMCW) radar is researched in this paper. First, a vital sign signal extraction algorithm is designed for the Range Bin variation caused by random body motion and heavy breathing. Second, a heartbeat signal extraction algorithm is designed based on Adaptive Notch Filter (ANF) and Empirical Wavelet Transform (EWT). The harmonic of respiration will be suppressed, and the heartbeat signal will be separated. Finally, the weighted estimation is performed according to the relationship of harmonics of the heartbeat signal to obtain the heart rate. Twenty subjects are invited to the experiment. The experimental results show that the proposed method can improve the signal-to-noise ratio (SNR), reduce the harmonic interference, and estimate the heart rate with a mean absolute error less than 4 BPM.

The life-threatening disease streptococcal toxic shock-like syndrome (STSLS), caused by the bacterial pathogen Streptococcus suis (S. suis). Proinflammatory markers, bacterial load, granulocyte recruitment, and neutrophil extracellular traps (NETs) levels were monitored in wild-type (WT) and Fpr2-/- mice suffering from STSLS. LXA4 and AnxA1, anti-inflammatory mediators related to Fpr2, were used to identity a potential role of the Fpr2 in STSLS development. We also elucidated the function of Fpr2 at different infection sites by comparing the STSLS model with the S. suis-meningitis model. Compared with the WT mice, Fpr2-/- mice exhibited a reduced inflammatory response and bacterial load, and increased neutrophil recruitment. Pretreatment with AnxA1 or LXA4 impaired leukocyte recruitment and increased both bacterial load and inflammatory reactions in WT but not Fpr2-/- mice experiencing STSLS. These results indicated that Fpr2 impairs neutrophil recruitment during STSLS, and this impairment is enhanced by AnxA1 or LXA4. By comparing the functions of Fpr2 in different S. suis infection models, inflammation and NETs was found to hinder bacterial clearance in S. suis meningitis, and conversely accelerate bacterial clearance in STSLS. Therefore, interference with neutrophil recruitment could potentially be harnessed to develop new treatments for this infectious disease.

Metagenomic next-generation sequencing (mNGS) is a novel useful strategy that is increasingly used for pathogens detection in clinic. Some emerging mNGS technologies with long-read ability are useful to decrease sequencing time and increase diagnosed accuracy, which is of great significance in rapid pathogen diagnosis. Reliable DNA extraction is considered critical for the success of sequencing; hence, there is thus an urgent need of gentle DNA extraction method to get unbiased and more integrate DNA from all kinds of pathogens. In this study, we systematically compared three DNA extraction methods (enzymatic cell lysis based on MetaPolyzyme, mechanical cell lysis based on bead beating, and the control method without pre–cell lysis, respectively) by assessing DNA yield, integrity, and the microbial diversity based on long-read nanopore sequencing of urine samples with microbial infections. Compared with the control method, the enzymatic-based method increased the average length of microbial reads by a median of 2.1-fold [Inter Quartile Range (IQR), 1.7–2.5; maximum, 4.8) in 18 of the 20 samples and the mapped reads proportion of specific species by a median of 11.8-fold (Inter Quartile Range (IQR), 6.9–32.2; maximum, 79.27]. Moreover, it provided fully (20 of 20) consistent diagnosed results to the clinical culture and more representative microbial profiles (P < 0.05), which all strongly proves the excellent performance of enzymatic-based method in long-read mNGS–based pathogen identification and potential diseases diagnosis of microbiome related.

Urinary tract infections (UTIs) are among the most common acquired bacterial infections in humans. The current gold standard method for identification of uropathogens in clinical laboratories is cultivation. However, culture-based assays have substantial drawbacks, including long turnaround time and limited culturability of many potential pathogens. Nanopore sequencing technology can overcome these limitations and detect pathogens while also providing reliable predictions of drug susceptibility in clinical samples. Here, we optimized a metagenomic nanopore sequencing (mNPS) test for pathogen detection and identification in urine samples of 76 patients with acute uncomplicated UTIs. We first used twenty of these samples to show that library preparation by the PCR Barcoding Kit (PBK) led to the highest agreement of positive results with gold standard clinical culture tests, and enabled antibiotic resistance detection in downstream analyses. We then compared the detection results of mNPS with those of culture-based diagnostics and found that mNPS sensitivity and specificity of detection were 86.7% [95% confidence interval (CI), 73.5–94.1%] and 96.8% (95% CI, 82.4–99.9%), respectively, indicating that the mNPS method is a valid approach for rapid and specific detection of UTI pathogens. The mNPS results also performed well at predicting antibiotic susceptibility phenotypes. These results demonstrate that our workflow can accurately diagnose UTI-causative pathogens and enable successful prediction of drug-resistant phenotypes within 6 h of sample receipt. Rapid mNPS testing is thus a promising clinical diagnostic tool for infectious diseases, based on clinical urine samples from UTI patients, and shows considerable potential for application in other clinical infections.

Serious diseases caused by Streptococcus suis serotype 2 (S. suis 2) include septicaemia and meningitis, which are associated with high morbidity and mortality. Proliferation in the blood can result in a breach of the blood–brain barrier (BBB) and provide entry into the cerebrospinal fluid (CSF), where bacteria cause inflammation of the meningeal membranes resulting in meningitis. The molecular mechanisms of how this pathogen crosses the BBB remain unclear. Suilysin (SLY) has been identified as an important secreted virulence factor of S. suis 2 and may play a vital role in provoking meningitis. In this investigation, we demonstrate that SLY can increase the paracellular permeability of BBB, both in vivo and in vitro, via the activation of group III secretory phospholipase A2 (PLA2G3). Our results indicate that at lower, sublytic concentrations, the toxin can stimulate cerebral microvascular endothelial cells to release TNF-α, thereby inducing high level expressions of PLA2G3. Abnormal elevations of PLA2G3 might further injure tissues through direct cytolytic effectors or other responses.

Single microbelt (MB) photodetectors with metal–semiconductor-metal structure have been demonstrated and characterized comprehensively. For single-photon absorption, the maximum responsivity of ZnO-MB photodetector can reach as high as 1.4  ×  105 A W−1 at 20 V bias. The results about photoresponse of MB-detector reveals that two relaxation mechanisms contribute to the carrier decay time. Moreover, the two-photon absorption upconversion photoresponsivity in the single-MB detector has also been realized, which is the first report about the two-photon absorption detector to the best of our knowledge. The excellent two-photon absorption photoresponsivity characteristic of the MB device can be available not only for detector but also for solar cell and biomedical imaging. The above results present a significant step towards future fabrication of single micro/nano-structure based multiphoton excitation optoelectronic devices. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the first exploitation of the vibrational resonance (VR) effect to detect weak signals in the presence of strong background noise. By injecting a series of sinusoidal interference signals of the same amplitude but with different frequencies into a generalized correlation detector, we show that the detection probability can be maximized at an appropriate interference amplitude. Based on a dual-Dirac probability density model, we compare the VR method with the stochastic resonance approach via adding dichotomous noise. The compared results indicate that the VR method can achieve a higher detection probability for a wider variety of noise distributions. [ABSTRACT FROM AUTHOR]