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Abstract Ischemic stroke is a common cause of mortality and severe disability in human and currently lacks effective treatment. Neuronal activation and neuroinflammation are the major two causes of neuronal damage. However, little is known about the connection of these two phenomena. This study uses middle cerebral artery occlusion mouse model and chemogenetic techniques to study the underlying mechanisms of neuronal excitotoxicity and severe neuroinflammation after ischemic stroke. Chemogenetic inhibition of neuronal activity in ipsilesional M1 alleviates infarct area and neuroinflammation, and improves motor recovery in ischemia mice. This study identifies that ischemic challenge triggers neuron to produce unique small extracellular vesicles (EVs) to aberrantly activate adjacent neurons which enlarge the neuron damage range. Importantly, these EVs also drive microglia activation to exacerbate neuroinflammation. Mechanistically, EVs from ischemia-evoked neuronal activity induce neuronal apoptosis and innate immune responses by transferring higher miR-100-5p to adjacent neuron and microglia. MiR-100-5p can bind to and activate TLR7 through U18U19G20-motif, thereby activating NF-κB pathway. Furthermore, knock-down of miR-100-5p expression improves poststroke outcomes in mice. Taken together, this study suggests that the combination of inhibiting aberrant neuronal activity and the secretion of specific EVs-miRNAs may serve as novel methods for stroke treatment. Graphical Abstract

Abstract Antibiotic-induced dysbiosis is a major risk factor for Clostridioides difficile infection (CDI), and fecal microbiota transplantation (FMT) is recommended for treating CDI. However, the underlying mechanisms remain unclear. Here, we show that Tritrichomonas musculis (T.mu), an integral member of the mouse gut commensal microbiota, reduces CDI-induced intestinal damage by inhibiting neutrophil recruitment and IL-1β secretion, while promoting Th1 cell differentiation and IFN-γ secretion, which in turn enhances goblet cell production and mucin secretion to protect the intestinal mucosa. T.mu can actively metabolize arginine, not only influencing the host’s arginine-ornithine metabolic pathway, but also shaping the metabolic environment for the microbial community in the host’s intestinal lumen. This leads to a relatively low ornithine state in the intestinal lumen in C. difficile-infected mice. These changes modulate C. difficile’s virulence and the host intestinal immune response, and thus collectively alleviating CDI. These findings strongly suggest interactions between an intestinal commensal eukaryote, a pathogenic bacterium, and the host immune system via inter-related arginine-ornithine metabolism in the regulation of pathogenesis and provide further insights for treating CDI.

Abstract The capacity to identify small amounts of pathogens in real samples is extremely useful. Herein, we proposed a sensitive platform for detecting pathogens using cyclic DNA nanostructure@AuNP tags (CDNA) and a cascade primer exchange reaction (cPER). This platform employs wheat germ agglutinin-modified Fe3O4@Au magnetic nanoparticles (WMRs) to bind the E. coli O157:H7, and then triggers the cPER to generate branched DNA products for CDNA tag hybridization with high stability and amplified SERS signals. It can identify target pathogens as low as 1.91 CFU/mL and discriminate E. coli O157:H7 in complex samples such as water, milk, and serum, demonstrating comparable or greater sensitivity and accuracy than traditional qPCR. Moreover, the developed platform can detect low levels of E. coli O157:H7 in mouse serum, allowing the discrimination of mice with early-stage infection. Thus, this platform holds promise for food analysis and early infection diagnosis.

Lowing blood lipid levels with probiotics has good application prospects. This study aimed to isolate probiotics with hypolipidemic efficacy from homemade na dish and investigate their mechanism of action. In vitro experiments were conducted to determine the cholesterol-lowering ability of five isolates, with results showing that Lactiplantibacillus plantarum N4 exhibited a high cholesterol-lowering rate of 50.27% and significant resistance to acid (87%), bile salt (51.97%), and pepsin (88.28%) in simulated gastrointestinal fluids, indicating promising application prospects for the use of probiotics in lowering blood lipids. The findings from the in vivo experiment demonstrated that the administration of N4 effectively attenuated lipid droplet accumulation and inflammatory cell infiltration in the body weight and liver of hyperlipidemic rats, leading to restoration of liver tissue morphology and structure, as well as improvement in lipid and liver biochemical parameters. 16S analysis indicated that the oral administration of N4 led to significant alterations in the relative abundance of various genera, including Sutterella, Bacteroides, Clostridium, and Ruminococcus, in the gut microbiota of hyperlipidemia rats. Additionally, fecal metabolomic analysis identified a total of 78 metabolites following N4 intervention, with carboxylic acids and their derivatives being the predominant compounds detected. The transcriptomic analysis revealed 156 genes with differential expression following N4 intervention, leading to the identification of 171 metabolic pathways through Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Notably, the glutathione metabolism pathway, PPAR signaling pathway, and bile secretion pathway emerged as the primary enrichment pathways. The findings from a comprehensive multi-omics analysis indicate that N4 influences lipid metabolism and diminishes lipid levels in hyperlipidemic rats through modulation of fumaric acid and γ-aminobutyric acid concentrations, as well as glutathione and other metabolic pathways in the intestinal tract, derived from both the gut microbiota and the host liver. This research offers valuable insights into the therapeutic potential of probiotics for managing lipid metabolism disorders and their utilization in the development of functional foods.

Nocardiosis demonstrates a temporal categorization that includes acute, subacute, and chronic stages alongside distinct typical localizations such as pulmonary, cutaneous, and disseminated forms. Disseminated nocardiosis, commonly caused by Nocardia asteroides, N. brasiliensis, and N. farcinica, continues to result in substantial morbidity and mortality. Herein, we report a life-threatening disseminated nocardiosis caused by Nocardia otitidiscaviarum in a patient with minimal change disease. This study emphasizes the difficulty in the diagnosis and treatment of unknown infections in clinical settings and highlights the important role played by laboratories in solving infectious diseases caused by rare pathogens.

Abstract Adenocarcinoma of the esophagogastric junction (AEG) is a type of tumor that arises at the anatomical junction of the esophagus and stomach. Although AEG is commonly classified as a subtype of gastric adenocarcinoma (GAC), the tumor microenvironment (TME) of AEG remains poorly understood. To address this issue, we conducted single-cell RNA sequencing (scRNA-seq) on tumor and adjacent normal tissues from four AEG patients and performed integrated analysis with publicly available GAC single-cell datasets. Our study for the first time comprehensively deciphered the TME landscape of AEG, where heterogeneous AEG malignant cells were identified with diverse biological functions and intrinsic malignant nature. We also depicted transcriptional signatures and T cell receptor (TCR) repertoires for T cell subclusters, revealing enhanced exhaustion and reduced clone expansion along the developmental trajectory of tumor-infiltrating T cells within AEG. Notably, we observed prominent enrichment of tumorigenic cancer-associated fibroblasts (CAFs) in the AEG TME compared to GAC. These CAFs played a critical regulatory role in the intercellular communication network with other cell types in the AEG TME. Furthermore, we identified that the accumulation of CAFs in AEG might be induced by malignant cells through FGF-FGFR axes. Our findings provide a comprehensive depiction of the AEG TME, which underlies potential therapeutic targets for AEG patient treatment.

Abstract To a certain extent, the development and vaccination of COVID-19 vaccine have reduced the alarming rate of transmission speed and mortality rate. At present, vaccine coverage is quite high in countries around the world. Since individual differences are unavoidable, it is necessary to assess the efficacy of the vaccine in each vaccinated person in order to reflect the protective effect of the vaccine in different populations. In this study, we developed a novel COVID-19 neutralizing antibody detection kit combining lateral flow immunochromatography and novel quantum dot technology with 85.23% sensitivity, 92.50% specificity. The novel QD-ICA could achieve an accurate detection of SARS-CoV-2 neutralizing antibodies with 10 minutes, two steps, small equipment size, and broad testing application, suggesting its capability to assess vaccine effectiveness on a large scale in areas of world that currently affected by the pandemic.

Abstract Background Intestinal flora has been proposed to mediate the occurrence of postmenopausal osteoporosis (PMO). However, the mechanism by which microbes and their metabolites interactively promote PMO remains unknown. Methods This study aimed to investigate changes in the intestinal flora and associated metabolites, and their role in PMO. 16S rRNA gene sequencing and metabolomics were performed to obtain postmenopausal women with osteopenia (lower bone mass, LBM), postmenopausal women with osteoporosis (OST), and healthy women as the control group. Results We identified taxa-specific and metabolite differences in the intestinal flora of the participants of this study. The pathogenic bacteria Klebsiella (0.59% and 0.71%, respectively) and Escherichia-Shigella (2.72% and 4.30%, respectively) were enriched in the LBM and OST groups (p

Objectives: Clinicians often face the challenge of differentially diagnosing febrile patients who are suspected of infectious diseases, since the clinical manifestations of infection and cancer may overlap. A single test that can detect both pathogens and tumor could provide timely and accurate diagnostic clues to aid the treatment and management of these patients. Methods: We enrolled eight patients to evaluate the utility of metagenomic Next-Generation Sequencing for simultaneously detecting pathogens and neoplasms using body fluids and tissue samples. Patients were selected by the following criteria: 1) Tumor was not considered upon hospitalization, but mNGS testing indicated neoplasm; 2) Tumor was not excluded, but microbial infection was primarily suspected according to initial clinical assessment. Results: We detected potential pathogens in five patients, three of whom had progressed into critical infections. Moreover, abnormal chromosomal copy numbers were identified in all patients that indicated presence of neoplasms, which were pathologically confirmed. Conclusions: Although copy number variations do not render a definitive cancer diagnosis, it can prompt clinicians to conduct more focused diagnostic testing for cancer, potentially saving time and cost. As a result, integrating copy number analysis with pathogen detection in mNGS may help establish rapid and accurate diagnosis for febrile patients.

Microbes are critical for flavor formation in fermented foods; however, their mechanisms of action are not fully understood. The microbial composition of 51 dairy and 47 vegetable products was functionally annotated and the carbohydrate-active enzyme (CAZyme) profiles of Lactiplantibacillus plantarum 84-3 (Lp84-3), isolated from dairy samples, can promote resistant starch (RS) degradation, were analyzed. Lactobacillus, Streptococcus, and Lactococcus were the predominant genera in dairy products, whereas the major genera in vegetables were Lactobacillus, Weissella, and Carnimonas. Phages from Siphoviridae, Myoviridae, and Herelleviridae were also present in dairy products. Additionally, the glycosyl hydrolase (GHs) family members GH1 and GH13 and the glycosyltransferase (GTs) family members GT2 and GT4 were abundant in Lp84-3. Moreover, Lp84-3 was enriched in butanoate metabolism enzymes and butanoate metabolite compounds. Therefore, fermented food microbes, especially Lp84-3, have an abundant repertoire of enzymes that promote flavor production, as starter improving the flavor of fermented dairy and vegetable products.

In clinical practice, infections caused by Aspergillus species are common and associated with high mortality rates. However, isolating Aspergillus from clinical samples and cultures is challenging, and serological tests cannot differentiate between strains. Furthermore, the complex cell wall structure in Aspergillus species hinders DNA extraction and subsequent nucleic acid detection. Aspergillus fumigatus, Aspergillus flavus, and Aspergillus niger are common and frequently encountered pathogenic species. This study aimed to establish an efficient and rapid method for detecting Aspergillus species in clinical samples. Fe3O4@PEI.NH2 nanoparticles with large particle sizes were employed to capture Aspergillus from the samples. Flexible silver nanowires (AgNWs) were prepared and used as the surface-enhanced Raman scattering (SERS) substrate for Aspergillus detection. Through SERS spectroscopy, the identification of captured Aspergillus species was confirmed. Furthermore, the SERS spectrum underwent principal component analysis employing orthogonal partial least-squares discrimination analysis (OPLS-DA) as a multivariate analysis technique to distinguish between the various Aspergillus species effectively. After 10-fold cross-validation, the trained model achieved a testing accuracy of 99.15%, indicating excellent classification performance. By utilizing pre-prepared Fe3O4@PEI.NH2 and AgNWs, the detection process was completed within 60 min without disrupting the cell wall of Aspergillus.

Abstract The worldwide distribution of Staphylococcus aureus across food types is an important food safety concern. This study aimed to estimate the prevalence of S. aureus in food products and its relationship with the occurrence and development of diabetes mellitus. A total of 55 articles were included. The pooled prevalence of S. aureus was 30.2%. The highest prevalence of S. aureus was observed in cereals, followed by meat and bean products, and the lowest in confectionery, egg products, and vegetables. The prevalence in dairy and seafood products was similar. Combinations of culture and molecular methods have been used for S. aureus detection. Furthermore, the prevalence of S. aureus in developed countries (Europe and North America) was higher than that in developing countries (Asia and Africa). In addition, the prevalence was higher in the provinces of Xinjiang and Shaanxi than that in Sichuan and Shandong in China, which may be due to the difference in climate and dietary habits. The results revealed that food type, bacterial detection methods, and location can influence the prevalence of S. aureus contamination. Resistance rates to preferred antibiotics against S. aureus were the highest for cephradine, polymyxin B, and penicillin at 82.9%, 82.0%, and 81.3%, respectively. In addition, 17 studies were system reviewed that the S. aureus infections are closely associated with the development of diabetes, and the treatment of probiotic, prebiotic, FMT, and bacteriophage can prevent and control S. aureus infections. This review emphasizes the high prevalence of S. aureus contamination in food, suggesting a potential diabetic infection risk and importance of observing principles of food safety and hygiene to reduce S. aureus.

Abstract Background Cerebral malaria (CM) is a manifestation of malaria caused by plasmodium infection. It has a high mortality rate and severe neurological sequelae, existing a significant research gap and requiring further study at the molecular level. Methods We downloaded the GSE117613 dataset from the Gene Expression Omnibus (GEO) database to determine the differentially expressed genes (DEGs) between the CM group and the control group. Weighted gene coexpression network analysis (WGCNA) was applied to select the module and hub genes most relevant to CM. The common genes of the key module and DEGs were selected to perform further analysis. The least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) were applied to screen and verify the diagnostic markers of CM. Eventually, the hub genes were validated in the external dataset. Gene set enrichment analysis (GSEA) was applied to investigate the possible roles of the hub genes. Results The GO and KEGG results showed that DEGs were enriched in some neutrophil-mediated pathways and associated with some lumen structures. Combining LASSO and the SVM-RFE algorithms, LEF1 and IRAK3 were identified as potential hub genes in CM. Through the GSEA enrichment results, we found that LEF1 and IRAK3 participated in maintaining the integrity of the blood–brain barrier (BBB), which contributed to improving the prognosis of CM. Conclusions This study may help illustrate the pathophysiology of CM at the molecular level. LEF1 and IRAK3 can be used as diagnostic biomarkers, providing new insight into the diagnosis and prognosis prediction in pediatric CM.

Spatial self-phase modulation (SSPM) is widely used to characterize the nonlinear refractive index of two-dimensional layered materials and design passive nonlinear photonic devices. In this work, we investigate the SSPM phenomena of black phosphorus dispersed in agarose solid under the excitation of on-axis and off-axis integer and half-integer vortex beams. It is found that with the increase of the off-axis distance of the Gaussian vortex beam, the pattern of the far-field self-diffraction intensity gradually breaks from the initial ring and finally evolves into a tail outside the self-diffraction ring. Moreover, for half-integer vortex beams, the size of the innermost tail of the self-diffraction ring is nearly half smaller than that of the second outer tail. The underlying mechanism of the observed SSPM phenomenon is also analyzed. Interestingly, the trailing number and rotation direction of the self-diffraction ring pattern quantitatively reflect the magnitude and sign of the topological charge (TC) of the off-axis vortex beam, respectively. This work provides a novel method to measure the TC of off-axis vortex beam in the nonlinear optics regime.

Circular dichroism (CD) spectroscopy is a typical technique to detect the chirality of an object. Due to the mismatch between light wavelength and the size of molecules, CD signal generally tends to be very weak in natural materials. In this work, we demonstrate the generation of superchiral field in free space through multi-beam superposition, without plasmonic/dielectric substrate that required in traditional methods. Through a systematic study of the superposition effect of up to six beams of light, we found that even achiral light fields can obtain optical chirality through superposition, and circularly polarized light fields can most effectively enhance the optical chirality density in the interference field. Generally, a maximal superchiral factor equivalent to the number of superposed beams can be achieved through optimizing the orientation of the illumination. However, when the number of superposed beams is more than three, the initial phase of superposed beams would play a significant role in determining the characteristics of the interference field, which must be carefully treated in modulating both the shape and the optical chiral density of the synthesized subwavelength chiral hotspot. Furthermore, we demonstrate that this technique is suitable to combine optical tweezers and CD spectroscopy. Based on three-beam superposition configuration, we explore the optical force and CD effects from single chiral nanoparticle, which are introduced into the optical standing wave formed by a flat mirror. It is found out that the nanoparticle can be stably trapped by the superchiral hotspot and gives rise to 2.92-fold enhancement of CD signal. This work may serve as a guideline for establishing applications in chirality sorting, chiral imaging, and CD spectroscopy.

Abstract Depression is a common and debilitating condition for which effective treatments are needed. Lepidium meyenii Walp (Maca) is a plant with potential medicinal effects in treating depression. Recently, there has been growing interest in plant‐derived extracellular vesicles (EVs) due to their low toxicity and ability to transport to human cells. Targeting the gut–brain axis, a novel strategy for depression management, may be achieved through the use of Maca‐derived EVs (Maca‐EVs). In this study, we successfully isolated Maca‐EVs using gradient ultracentrifugation and characterized their shape, size, and markers (CD63 and TSG101). The in vivo imaging showed that the Dil‐labeled Maca‐EVs crossed the brain–blood barrier and accumulated in the brain. The behavioral tests revealed that Maca‐EVs dramatically recovered the depression‐like behaviors of unpredictable chronic mild stress (UCMS) mice. UCMS mice fecal were characterized by an elevated abundance of g_Enterococcus, g_Lactobacillus, and g_Escherichia_Shigella, which were significantly restored by administration of Maca‐EVs. The effects of Maca‐EVs on the altered microbial and fecal metabolites in UCMS mice were mapped to biotin, pyrimidine, and amino acid (tyrosine, alanine, aspartate, and glutamate) metabolisms, which were closely associated with the serotonin (5‐HT) production. Maca‐EVs were able to increase serum monoamine neurotransmitter levels in UCMS mice, with 5‐HT showing the most significant changes. We further demonstrated that 5‐HT improved the expression of brain‐derived neurotrophic factor, a key regulator of neuronal plasticity, and its subsequent activation of TrkB/p‐AKT signaling by regulating the GTP‐Cdc42/ERK pathway. These findings suggest that Maca‐EVs enhance 5‐HT release, possibly by modulating the gut–brain axis, to improve depression behavior. Our study sheds light on a novel approach to depression treatment using plant‐derived EVs.

Abstract The type I cGMP-dependent protein kinase (PKG I) is recognized as a tumor suppressor, but its role in EGFR regulated epithelial ovarian cancer (EOC) progression remains unclear. We evaluated the in vivo and in vitro effects of activated PKG I in EGF-induced EOC cell proliferation, migration, and invasion. The expressions of EGFR and PKG I were elevated, but the activated PKG I was decreased in EOC tissues of patients and cells lines. The addition of 8-Br-cGMP, a specific PKG I activator, attenuated the EGF-induced EOC cell proliferation, migration, and invasion in vitro. Similarly, activated PKG I also attenuated EOC progression in vivo using an EOC xenograft nude mouse model. The activated PKG I interacted with EGFR, causing increased threonine (693) phosphorylation and decreased tyrosine (1068) phosphorylation of EGFR, which resulted in disrupted EGFR-SOS1-Grb2 combination. Subsequently, the cytoplasmic phosphorylation of downstream proteins (c-Raf, MEK1/2, and ERK1/2) were declined, impeding the phosphorylated ERK1/2’s nucleus translocation, and this reduction of phosphorylated tyrosine (1068) EGFR and ERK1/2 were also abolished by Rp-8-Br-cGMPS. Our results suggest that the activation of PKG I attenuates EGF-induced EOC progression, and the 8-Br-cGMP-PKG I-EGFR/MEK/ERK axis might be a potential target for EOC therapy.

The highly infectious Delta variant strain of SARS-CoV-2 remains globally dominant and undermines COVID-19 vaccines. Rapid detection of the Delta variant is crucial for the identification and quarantine of infected individuals. In this study, our aim was to design and validate a genotyping RT-LAMP method to detect Delta variants specifically. R203M in the N gene of SARS-CoV-2 was chosen as the Delta variant-specific mutation for genotyping. To target the R203M-harboring region and the conserved sequence of the N gene, two sets of primers were designed, and a Cq (quantification cycle) ratio-based RT-LAMP for SARS-CoV-2 and R203M detection was developed by analyzing the significant discrepancy in amplification efficiency of the two sets of primers. We validated the RT-LAMP method on 498 clinical specimens in parallel with RT-qPCR, and 84 Delta variants from 198 positive samples were determined by sequencing. Compared with traditional RT-qPCR analyses, RT-LAMP appears to be 100% accurate in detecting SARS-CoV-2 clinical samples. RT-LAMP has a good ability to distinguish between Delta and non-Delta variants under a Cq ratio threshold of 1.80. Furthermore, the AUC (area under the curve) of this method was 1.00; the sensitivity, specificity and accuracy were all 100%. In summary, we have proposed a rapid, accurate and cost-effective RT-LAMP method to detect SARS-CoV-2 and Delta variants, which may facilitate the surveillance of COVID-19.

ABSTRACT: Objectives: This study aimed to investigate the annual incidence, molecular epidemiological characteristics, and antimicrobial resistance of group A Streptococcus (GAS) clinical isolates from paediatric patients at Shenzhen Children's Hospital during 2016–2020. Methods: Clinical samples were collected from paediatric patients with a suspected diagnosis of GAS infections. We studied the annual incidence and characteristics of GAS infections using the GAS antigen detection method. Additionally, 250 GAS isolates were randomly selected for genotyping of the emm gene, and antimicrobial susceptibility assay was performed using the Kirby-Bauer paper dispersion strategy. Results: Among 43 593 collected samples, 9313 were positive for the GAS antigen. The main emm type was emm12, followed by emm1, emm6, and emm 4, which were used for distinguishing 90% of the scarlet fever isolated strains. The percentage of emm1 increased from 36% in 2016 to 44% in 2019, whereas the percentage of emm12 decreased from 62% to 50%. Several unusual emm types isolated from scarlet fever patients showed an increase in proportions from 2016 to 2020. These GAS isolates were sensitive to penicillin, ceftriaxone, and vancomycin and were highly resistant to erythromycin and clindamycin. Conclusion: There was a high incidence of GAS infections during 2016–2020 in Shenzhen, China. The GAS isolates had a high resistance rate to erythromycin and clindamycin; penicillin was the antibiotic of choice for GAS infections. The common emm types were emm12 and emm1. Future studies should investigate the clonal structure and superantigen profiles of the population of GAS isolates associated with scarlet fever.

Abstract Background Colon adenocarcinoma (COAD) is one of the leading causes of death worldwide. Cancer stem cells (CSCs) are vital for COAD chemoresistance and recurrence, however little is known about stem cell-related biomarkers in drug resistance and COAD prognosis prediction. Methods To uncover the roles of CSC in COAD tumorigenesis, chemoresistance, and prognosis, we retrieved COAD patients’ RNAseq data from TCGA (The Cancer Genome Atlas). We further performed analysis of differentially expressed genes (DEGs) and mRNA expression-based stemness index (mRNAsi) to identify stemness-related COAD biomarkers. We then evaluated the roles of mRNAsi in tumorigenesis, clinical-stage, overall survival (OS), and chemoresistance. Afterward, we used identified prognostic stemness-related genes (PSRGs) to construct a prediction model. After constructing the prediction model, we used elastic Net regression and area under the curve (AUC) to explore the prediction value of PSRGs based on risk scores and the receiver operator characteristic (ROC) curve. To elucidate the underlying interconnected systems, we examined relationships between the levels of TFs, PSRGs, and 50 cancer hallmarks by a Pearson correlation analysis. Results Twelve thousand one hundred eight DEGs were identified by comparing 456 primary COADs and 41 normal solid tissue samples. Furthermore, we identified 4351 clinical stage-related DEGs, 16,516 stemness-associated DEGs, and 54 chemoresistance-related DEGs from cancer stages: mRNAsi, and COAD chemoresistance. Compared to normal tissue samples, mRNAsi in COAD patients were marked on an elevation and involved in prognosis (p = 0.027), stemness-related DEGs based on chemoresistance (OR = 3.28, p ≤ 0.001) and AJCC clinical stage relating (OR = 4.02, p ≤ 0.001) to COAD patients. The prediction model of prognosis were constructed using the 6 PSRGs with high accuracy (AUC: 0.659). The model identified universal correlation between NRIP2 and FDFT1 (key PRSGs), and some cancer related transcription factors (TFs) and trademarks of cancer gene were in the regulatory network. Conclusion We found that mRNAsi is a reliable predictive biomarker of tumorigenesis and COAD prognosis. Our established prediction model of COAD chemoresistance, which includes the six PSRGs, is effective, as the model provides promising therapeutic targets in the COAD.

Abstract Background Hemorrhagic transformation (HT) is a common complication of delayed tissue plasminogen activator (t-PA) treatment for ischemic stroke. Peroxynitrite plays an important role in the breakdown of blood–brain barrier (BBB) and the development of HT. We tested the hypothesis that Angong Niuhuang Wan (AGNHW), a traditional Chinese medicinal formula, could be used in conjunction with t-PA to protect the BBB, minimize HT, and improve neurological function by suppressing peroxynitrite-mediated matrix metalloproteinase-9 (MMP-9) activation. Methods We first performed quality control study and chemical identification of AGNHW by using UPLC. In animal experiments, male Sprague–Dawley rats were subjected to 5 h of middle cerebral artery occlusion (MCAO) followed by 19 h of reperfusion plus t-PA infusion (10 mg/kg) at 5 h of cerebral ischemia. AGNHW (257 mg/kg) was given orally at 2 h after MCAO. Hemorrhagic transformation was measured using hemorrhagic scores and hemoglobin levels in ischemic brains. Evans blue leakage was utilized to assess the severity of the blood–brain barrier (BBB) damage. The modified neurologic severity score (mNSS) test was used to assess neurological functions. Peroxynitrite and superoxide was detected by using fluorescent probes. MMP-9 activity and expression were examined by gelatin zymography and immunostaining. The antioxidant effects were also studied by using brain microvascular endothelial b.End3 cells exposed to 5 h of oxygen and glucose deprivation (OGD) plus 5 h of reoxygenation with t-PA treatment (20 µg/ml). Results AGNHW significantly reduced the BBB damage, brain edema, reduced hemorrhagic transformation, enhanced neurological function, and reduced mortality rate in the ischemic stroke rats with t-PA treatment. AGNHW reduced peroxynitrite and superoxide in vivo and in vitro and six active chemical compounds were identified from AGNHW with peroxynitrite scavenging activity. Furthermore, AGNHW inhibited MMP-9 activity, and preserved tight junction protein claudin-5 and collagen IV in the ischemic brains. Conclusion AGNHW could be a potential adjuvant therapy with t-PA to protect the BBB integrity, reduce HT, and improve therapeutic outcome in ischemic stroke treatment via inhibiting peroxynitrite-mediated MMP-9 activation. Graphical Abstract

Acinetobacter baumannii (A. baumannii) is among the main pathogens that cause nosocomial infections. The ability to rapidly and accurately detect A. baumannii and its drug resistance is essential for blocking secondary infections and guiding treatments. In this study, we reported a nucleic acid fluorescent lateral flow assay (NFLFA) to identify A. baumannii and carbapenem-resistant A. baumannii (CRAB) in a rapid and quantitative manner by integrating loop-mediated isothermal amplification (LAMP) and silica–based multilayered quantum dot nanobead tag (Si@MQB). First, a rapid LAMP system was established and optimised to support the effective amplification of two bacterial genes in 35 min. Then, the antibody-modified Si@MQB was introduced to capture the two kinds of amplified DNA sequences and simultaneously detect them on two test lines of a LFA strip, which greatly improved the detection sensitivity and stability of the commonly used AuNP-based nucleic acid LFA. With these strategies, the established LAMP-NFLFA achieved detection limits of 199 CFU/mL and 287 CFU/mL for the RecA (house-keeping gene) and blaOXA-23 (drug resistance gene) genes, respectively, within 43 min. Furthermore, the assay exhibited good repeatability and specificity for detecting target pathogens in real complex specimens and environments; thus, the proposed assay undoubtedly provides a promising and low-cost tool for the on-site monitoring of nosocomial infections.

Tumor hypoxia is considered one of the key causes of the ineffectiveness of various strategies for cancer treatment, and the non-specific effects of chemotherapy drugs on tumor treatment often lead to systemic toxicity. Thus, we designed M1 macrophage-biomimetic-targeted nanoparticles (DOX/CAT@PLGA-M1) which contain oxygen self-supplied enzyme (catalase, CAT) and chemo-therapeutic drug (doxorubicin, DOX). The particle size of DOX/CAT@PLGA-M1 was 202.32 ± 2.27 nm (PDI < 0.3). DOX/CAT@PLGA-M1 exhibited a characteristic core-shell bilayer membrane structure. The CAT activity of DOX/CAT@PLGA-M1 was 1000 (U/mL), which indicated that the formation of NPs did not significantly affect its enzymatic activity. And in vitro drug release showed that the cumulative release rate of DOX/CAT@PLGA-M1 was enhanced from 26.93% to 50.10% in the release medium of hydrogen peroxide, which was attributed to the reaction of CAT in the NPs. DOX/CAT@PLGA-M1 displayed a significantly higher uptake in 4T1 cells, because VCAM-1 in tumor cells interacted with specific integrin (α4 and β1), and thereby achieved tumor sites. And the tumor volume of the DOX/CAT@PLGA-M1 group was significantly reduced (0.22 cm3), which further proved the active targeting effect of the M1 macrophage membrane. Above all, a novel multifunctional nano-therapy was developed which improved tumor hypoxia and obtained tumor targeting activity.

Over the past decades, conventional methods and molecular assays have been developed for the detection of tuberculosis (TB). However, these techniques suffer limitations in the identification of Mycobacterium tuberculosis (Mtb), such as long turnaround time and low detection sensitivity, etc., not even mentioning the difficulty in discriminating antibiotics-resistant Mtb strains that cause great challenges in TB treatment and prevention. Thus, techniques with easy implementation for rapid diagnosis of Mtb infection are in high demand for routine TB diagnosis. Due to the label-free, low-cost and non-invasive features, surface enhanced Raman spectroscopy (SERS) has been extensively investigated for its potential in bacterial pathogen identification. However, at current stage, few studies have recruited handheld Raman spectrometer to discriminate sputum samples with or without Mtb, separate pulmonary Mtb strains from extra-pulmonary Mtb strains, or profile Mtb strains with different antibiotic resistance characteristics. In this study, we recruited a set of supervised machine learning algorithms to dissect different SERS spectra generated via a handheld Raman spectrometer with a focus on deep learning algorithms, through which sputum samples with or without Mtb strains were successfully differentiated (5-fold cross-validation accuracy = 94.32%). Meanwhile, Mtb strains isolated from pulmonary and extra-pulmonary samples were effectively separated (5-fold cross-validation accuracy = 99.86%). Moreover, Mtb strains with different drug-resistant profiles were also competently distinguished (5-fold cross-validation accuracy = 99.59%). Taken together, we concluded that, with the assistance of deep learning algorithms, handheld Raman spectrometer has a high application potential for rapid point-of-care diagnosis of Mtb infections in future.

BackgroundInflammatory bowel diseases, including ulcerative colitis (UC) and Crohn’s disease, are some of the most common inflammatory disorders of the gastrointestinal tract. The dysfunction of the immune system in the intestines is suggested to be the underlying cause of the pathogenesis of UC. However, the mechanisms regulating these dysfunctional immune cells and inflammatory phenotypes are still unclear.MethodsThe differential expression analysis on microarray datasets were performed including GSE24287, GSE87466, GSE102133, and GSE107499, including 376 samples. “Gene Ontology” and “Kyoto Encyclopedia of Genes and Genomes” pathway enrichment analyses were conducted to identify the common differentially expressed genes (DEGs) in these datasets and explore their underlying biological mechanisms. Further algorithms like “Cell-type Identification by Estimating Relative Subsets of RNA Transcripts” were used to determine the infiltration status of immune cells in patients with UC. “Cytoscape” and “Gene Set Enrichment Analysis” were used to screen for hub genes and to investigate their biological mechanisms. The Tumor Immune Estimation Resource database was used to study the correlation between hub genes and infiltrating immune cells in patients with UC. A total of three hub genes, CCL3, MMP3, and TIMP1, were identified using Cytoscape.ResultsA positive correlation was observed between these hub genes and patients with active UC. These genes served as a biomarker for active UC. Moreover, a decrease in CCL3, MMP3, and TIMP1 expression was observed in the mucosa of the intestine of patients with active UC who responded to Golimumab therapy. In addition, results show a significant positive correlation between CCL3, MMP3, and TIMP1 expression and different immune cell types including dendritic cells, macrophages, CD8+ T cells, and neutrophils in patients with colon cancer. Moreover, CCL3, MMP3, and TIMP1 expression were strongly correlated with different immune cell markers.ConclusionStudy results show the involvement of hub genes like CCL3, MMP3, and TIMP1 in the pathogenesis of UC. These genes could serve as a novel pharmacological regulator of UC. These could be used as a therapeutic target for treating patients with UC and may serve as biomarkers for immune cell infiltration in colon cancer.

ABSTRACT Klebsiella pneumoniae often causes life-threatening infections in patients globally. Despite its notability, little is known about potential nosocomial outbreak and spread of K. pneumoniae among pediatric patients in low- and middle-income countries. Ninety-eight K. pneumoniae strains isolated from pediatric patients in a large general hospital in China between February 2018 and May 2019 were subjected to nanopore and Illumina sequencing and genomic analysis to elucidate transmission and genetic diversity. The temporal distribution patterns of K. pneumoniae revealed a cluster of sequence type 11 (ST11) strains comprising two clades. Most inferred transmissions were of clade 1, which could be traced to a common ancestor dating to mid-2017. An infant in the coronary care unit played a central role, potentially seeding transmission clusters in other wards. Major genomic changes during the outbreak included chromosomal mutations associated with virulence and gains and losses of plasmids encoding resistance. In summary, we report a nosocomial outbreak among pediatric patients caused by clonal dissemination of KPC-2-producing ST11 K. pneumoniae. Our findings highlight the value of whole-genome sequencing during outbreak investigations and illustrate that transmission chains can be identified during hospital stays. IMPORTANCE We report a nosocomial outbreak among pediatric patients caused by clonal dissemination of blaKPC-2-carrying ST11 K. pneumoniae. Strains of various sequence types coexist in the complex hospital environment; the quick emergence and spread of ST11 strains were mainly due to the plasmid-mediated acquisition of resistance genes. The spread of hospital infection was highly associated with several specific wards, suggesting the importance of genomic surveillance on wards at high risk of infection.

ABSTRACT The rapid and accurate identification of the causing agents during bacterial infections would greatly improve pathogen transmission, prevention, patient care, and medical treatments in clinical settings. Although many conventional and molecular methods have been proven to be efficient and reliable, some of them suffer technical biases and limitations that require the development and application of novel and advanced techniques. Recently, due to its cost affordability, noninvasiveness, and label-free feature, Raman spectroscopy (RS) is emerging as a potential technique for fast bacterial detection. However, the method is still hampered by many technical issues, such as low signal intensity, poor reproducibility, and standard data set insufficiency, among others. Thus, it should be cautiously claimed that Raman spectroscopy could provide practical applications in real-world settings. In order to evaluate the implementation potentials of Raman spectroscopy in the identification of bacterial pathogens, we investigated 30 bacterial species belonging to 9 different bacterial genera that were isolated from clinical samples via surfaced enhanced Raman spectroscopy (SERS). A total of 17,149 SERS spectra were harvested from a Raman spectrometer and were further analyzed via machine learning approaches, which showed that a convolutional neural network (CNN) deep learning algorithm achieved the highest prediction accuracy for recognizing pathogenic bacteria at both the genus and species levels. In summary, the SERS technique holds a promising potential for fast bacterial pathogen identification in clinical laboratories with the integration of machine learning algorithms, which might be further developed and sharpened for the direct identification and prediction of bacterial pathogens from clinical samples. IMPORTANCE In this study, we investigated 30 bacterial species belonging to 9 different bacterial genera that were isolated from clinical samples via surfaced enhanced Raman spectroscopy (SERS). A total of 17,149 SERS spectra were harvested from a Raman spectrometer and were further analyzed via machine learning approaches, the results of which showed that the convolutional neural network (CNN) deep learning algorithm could achieve the highest prediction accuracy for recognizing pathogenic bacteria at both the genus and species levels. Taken together, we concluded that the SERS technique held a promising potential for fast bacterial pathogen diagnosis in clinical laboratories with the integration of deep learning algorithms, which might be further developed and sharpened for the direct identification and prediction of bacterial pathogens from clinical samples.

Background and aims: China has the largest number of chronic kidney disease (CKD) patients. Current CKD definition has been challenged recently. We aim to reassess kidney function in healthy Chinese population, to provide a more appropriate reference range (RIs) for diagnosis, treatment, monitoring (or screening) of kidney disease and related research. Materials and methods: A total of 49627 apparently healthy people aged 18–94 years old were enrolled. Age and sex effects were explored for the kidney function indicators and RIs were calculated non-parametrically. Results: Albumin’s limits were lower than the national RIs, with 5.7 g/L lower in upper limit (UL) and 0.4 g/L lower in lower limit (LL) [RIs: 39.6–49.3 vs 40–55]. The LL of estimate glomerular filtration rate (eGFR) was 80.4 mL/min/1.73 m2 or 63.3 mL/min/1.73 m2 at the age of

Abstract Highly sensitive force measurements of a single microscopic particle with femto-Newton sensitivity have remained elusive owing to the existence of fundamental thermal noise. Now, researchers have proposed an optically controlled hydrodynamic manipulation method, which can measure the weak force of a single microscopic particle with femto-Newton sensitivity.

Abstract Autoantibodies against M-type phospholipase A2 receptor (PLA2R) serve as specific biomarkers for idiopathic membranous nephropathy (IMN), and its quantification helps monitor disease activity. In this study, we describe a rapid and highly sensitive quantum dots-based immunochromatography assay (QD-ICA) for quantifying PLA2R autoantibodies. Serum samples from 135 biopsy-confirmed patients with nephrotic syndrome were analyzed for PLA2R autoantibodies using the novel QD-ICA as well as commercialized enzyme-linked immunosorbent assay (ELISA). Areas under the receiver operating characteristic curve (AUC-ROC) of QD-ICA were significantly greater than those of ELISA (91.1% [95% CI 85.9–96.3%] and 83.9% [95% CI 76.5–91.2%] respectively; p

Quantum states of light open a new avenue for materials characterization. The authors show how entangled photons can be leveraged to enhance the resolution of nonlinear spectroscopy.

Compared with the on-axis vortex beam and the off-axis single vortex beam, the off-axis double vortex beam has more control degrees of freedom and brings rich physical properties. In this work, we investigate theoretically and experimentally the generation, topological charge (TC), and orbital angular momentum (OAM) of off-axis double vortex beams. It is demonstrated that the tilted lens method can detect not only the magnitudes and signs of two TCs of the off-axis double vortex beam but also the spatial distribution of the TCs. Moreover, the average OAM value of the off-axis double vortex beam decreases nonlinearly as the off-axis distance increases, although its TC is independent of the off-axis distance of phase singularities. The results indicate that the average OAM of the off-axis double vortex beam can be easily controlled by changing the relative position of two-phase singularities, thereby realizing the applications of multi-degrees of freedom particle manipulation, optical communication, and material processing.

The aim of the current study was to analyse the distribution of antimicrobial drug resistance (AMR) among Pseudomonas aeruginosa (P. aeruginosa, PA) isolates from Guangdong Provincial People’s Hospital (GDPH) from 2017 to 2021, and the impact of the COVID-19 outbreak on changes in the clinical distribution and drug resistance rate of P. aeruginosa to establish guidelines for empiric therapy. Electronic clinical data registry records from 2017 to 2021 were retrospectively analysed to study the AMR among P. aeruginosa strains from GDPH. The strains were identified by VITEK 2 Compact and MALDI-TOF MS, MIC method or Kirby–Bauer method for antibiotic susceptibility testing. The results were interpreted according to the CLSI 2020 standard, and the data were analysed using WHONET 5.6 and SPSS 23.0 software. A total of 3036 P. aeruginosa strains were detected in the hospital from 2017 to 2021, and they were primarily distributed in the ICU (n = 1207, 39.8%). The most frequent specimens were respiratory tract samples (59.6%). The detection rate for P. aeruginosa in 5 years was highest in September, and the population distribution was primarily male(68.2%). For the trend in the drug resistance rate, the 5-year drug resistance rate of imipenem (22.4%), aztreonam (21.5%) and meropenem (19.3%) remained at high levels. The resistance rate of cefepime decreased from 9.4% to 4.8%, showing a decreasing trend year by year (p < 0.001). The antibiotics with low resistance rates were aminoglycoside antibiotics, which were gentamicin (4.4%), tobramycin (4.3%), and amikacin (1.4%), but amikacin showed an increasing trend year by year (p = 0.008). Our analysis indicated that the detection rate of clinically resistant P. aeruginosa strains showed an upwards trend, and the number of multidrug-resistant (MDR) strains increased year by year, which will lead to stronger pathogenicity and mortality. However, after the outbreak of COVID-19 in 2020, the growth trend in the number of MDR bacteria slowed, presumably due to the strict epidemic prevention and control measures in China. This observation suggests that we should reasonably use antibiotics and treatment programs in the prevention and control of P. aeruginosa infection. Additionally, health prevention and control after the outbreak of the COVID-19 epidemic (such as wearing masks, washing hands with disinfectant, etc., which reduced the prevalence of drug resistance) led to a slowdown in the growth of the drug resistance rate of P. aeruginosa in hospitals, effectively reducing the occurrence and development of drug resistance, and saving patient’s treatment costs and time.

Abstract Background Stroke is the leading cause of long-term motor disability and cognitive impairment. Recently, neurogenesis has become an attractive strategy for the chronic recovery of stroke. It is important to understand the molecular mechanism that promotes neural stem cell (NSC) neurogenesis for future NSC-based therapies. Our previous study showed that Momordica charantia polysaccharides (MCPs) exerted neuroprotective effects on stroke via their anti-oxidant and anti-inflammation activities. However, it remains unknown whether MCPs promote NSC neurogenesis after cerebral ischemic/reperfusion injury (IRI). Methods We investigated MCPs’ function in differentiation of neural stem cells (NSCs) in vivo and in vitro experiments. Based on a middle cerebral artery occlusion (MCAO) rat model, the effect of MCPs on neuronal differentiation after MCAO was analyzed. Primary NSCs and neural stem cell line C17.2 were cultured and subjected to glutamate stimulation to establish the cell model of IRI. We evaluated the effect of MCPs on NSC differentiation in IRI cell model by Western blot and immunofluorescence staining. The SIRT1 activity of NSCs post glutamate stimulation was also evaluated by CELL SIRT1 COLORIMETRY ASSAY KIT. In addition, molecular mechanism was clarified by employing the activator and inhibitor of SIRT1. Results MCPs had no effects on the differentiation of neural stem cells under physiological conditions while shifted NSC differentiation potential from the gliogenic to neurogenic lineage under pathological conditions. Activation of SIRT1 with MCPs was responsible for the neuronal differentiation of C17.2-NSCs. The neuronal differentiation effect of MCPs was attributed to upregulation SIRT1-mediated deacetylation of β-catenin. MCP-induced deacetylation via SIRT1 promoted nuclear accumulation of β-catenin in NSCs. Conclusion Our findings indicate that the deacetylation of β-catenin by SIRT1 represents a critical mechanism of action of MCPs in promoting NSC neuronal differentiation. It provides an improved understanding of molecular mechanism underlying neuroprotective effects of MCPs in IRI, indicating its potential role on treating ischemic stroke especially chronic recovery.

With its low-cost, label-free and non-destructive features, Raman spectroscopy is becoming an attractive technique with high potential to discriminate the causative agent of bacterial infections and bacterial infections per se. However, it is challenging to achieve consistency and accuracy of Raman spectra from numerous bacterial species and phenotypes, which significantly hinders the practical application of the technique. In this study, we analyzed surfaced enhanced Raman spectra (SERS) through machine learning algorithms in order to discriminate bacterial pathogens quickly and accurately. Two unsupervised machine learning methods, K-means Clustering (K-Means) and Agglomerative Nesting (AGNES) were performed for clustering analysis. In addition, eight supervised machine learning methods were compared in terms of bacterial predictions via Raman spectra, which showed that convolutional neural network (CNN) achieved the best prediction accuracy (99.86%) with the highest area (0.9996) under receiver operating characteristic curve (ROC). In sum, machine learning methods can be potentially applied to classify and predict bacterial pathogens via Raman spectra at general level.

Thoracic radiotherapy patients have higher risks of developing radiation-induced heart disease (RIHD). Ionizing radiation generates excessive reactive oxygens species (ROS) causing oxidative stress, while Momordica. charantia and its extract have antioxidant activity. Plant-derived extracellular vesicles (EVs) is emerging as novel therapeutic agent. Therefore, we explored the protective effects of Momordica. charantia-derived EVs-like nanovesicles (MCELNs) against RIHD. Using density gradient centrifugation, we successfully isolated MCELNs with similar shape, size, and markers as EVs. Confocal imaging revealed that rat cardiomyocytes H9C2 cells internalized PKH67 labeled MCELNs time-dependently. In vitro assay identified that MCELNs promoted cell proliferation, suppressed cell apoptosis, and alleviated the DNA damage in irradiated (16 Gy, X-ray) H9C2 cells. Moreover, elevated mitochondria ROS in irradiated H9C2 cells were scavenged by MCELNs, protecting mitochondria function with re-balanced mitochondria membrane potential. Furthermore, the phosphorylation of ROS-related proteins was recovered with increased ratios of p-AKT/AKT and p-ERK/ERK in MCELNs treated irradiated H9C2 cells. Last, intraperitoneal administration of MCELNs mitigated myocardial injury and fibrosis in a thoracic radiation mice model. Our data demonstrated the potential protective effects of MCELNs against RIHD. The MCELNs shed light on preventive regime development for radiation-related toxicity.

ABSTRACT In clinical settings, rapid and accurate diagnosis of antibiotic resistance is essential for the efficient treatment of bacterial infections. Conventional methods for antibiotic resistance testing are time consuming, while molecular methods such as PCR-based testing might not accurately reflect phenotypic resistance. Thus, fast and accurate methods for the analysis of bacterial antibiotic resistance are in high demand for clinical applications. In this pilot study, we isolated 7 carbapenem-sensitive Klebsiella pneumoniae (CSKP) strains and 8 carbapenem-resistant Klebsiella pneumoniae (CRKP) strains from clinical samples. Surface-enhanced Raman spectroscopy (SERS) as a label-free and noninvasive method was employed for discriminating CSKP strains from CRKP strains through computational analysis. Eight supervised machine learning algorithms were applied for sample analysis. According to the results, all supervised machine learning methods could successfully predict carbapenem sensitivity and resistance in K. pneumoniae, with a convolutional neural network (CNN) algorithm on top of all other methods. Taken together, this pilot study confirmed the application potentials of surface-enhanced Raman spectroscopy in fast and accurate discrimination of Klebsiella pneumoniae strains with different antibiotic resistance profiles. IMPORTANCE With the low-cost, label-free, and nondestructive features, Raman spectroscopy is becoming an attractive technique with great potential to discriminate bacterial infections. In this pilot study, we analyzed surfaced-enhanced Raman spectroscopy (SERS) spectra via supervised machine learning algorithms, through which we confirmed the application potentials of the SERS technique in rapid and accurate discrimination of Klebsiella pneumoniae strains with different antibiotic resistance profiles.

Autism Spectrum Disorder (ASD) is a severe neurodevelopmental disorder. To enhance the understanding of the gut microbiota structure in ASD children at different ages as well as the relationship between gut microbiota and fecal metabolites, we first used the 16S rRNA sequencing to evaluate the gut microbial population in a cohort of 143 children aged 2–13 years old. We found that the α-diversity of ASD group showed no significant change with age, while the TD group showed increased α-diversity with age, which indicates that the compositional development of the gut microbiota in ASD varies at different ages in ways that are not consistent with TD group. Recent studies have shown that chronic constipation is one of the most commonly obvious gastrointestinal (GI) symptoms along with ASD core symptoms. To further investigate the potential interaction effects between ASD and GI symptoms, the 30 C-ASD and their aged-matched TD were picked out to perform metagenomics analysis. We observed that C-ASD group displayed decreased diversity, depletion of species of Sutterella, Prevotella, and Bacteroides as well as dysregulation of associated metabolism activities, which may involve in the pathogenesis of C-ASD. Consistent with metagenomic analysis, liquid chromatography-mass spectrometry (LC/MS) revealed some of the differential metabolites between C-ASD and TD group were involved in the metabolic network of neurotransmitters including serotonin, dopamine, histidine, and GABA. Furthermore, we found these differences in metabolites were associated with altered abundance of specific bacteria. The study suggested possible future modalities for ASD intervention through targeting the specific bacteria associated with neurotransmitter metabolism.

Abstract Background Streptococcus suis is a zoonotic pathogen that causes serious systemic infections in pigs and occupation-related infections in humans who contact with pigs or pork products. In China, it has caused two outbreaks of human infection and surveillance for S.suis has been ongoing since last time. Case presentation Two cases of meningitis and sepsis caused by S. suis were reported in this study. Both patients work in relation to the pork trade, a risk factor for S. suis infection. The outcome was favorable after a prolonged ceftriaxone therapy but one patient was left with mild hearing loss. Two isolates were identified as sequencing type (ST) 7, S. suis serotype 2 (SS2), which is one the most prevalent and cause two outbreaks in China. Whole-genome sequencing (WGS) revealed that a high degree identity was noted in the genome organizations and sequences between two sporadic ST7 SS2 isolates in this study and representative epidemic virulent isolates. Major differences among them are two sporadic ST7 SS2 isolates lacked a virulence factor called agglutinin receptor and an 89 K pathogenicity island (PAI), which plays important role in the pathogenesis of streptococcal toxic shock syndrome (STSS). A summary about STs of human infection with S. suis in China was completed. The result showed ST1 and ST7 were still the major STs and several novel STs were successfully discovered in different provinces. Conclusions Our results enhanced the understanding of the ability to cause life-threatening infections in humans and the distribution and evolution of the S. suis in China.

ABSTRACTEffective strategy to mitigate the ongoing pandemic of 2019 novel coronavirus (COVID-19) require a comprehensive understanding of humoral responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the emerging virus causing COVID-19. The dynamic profile of viral replication and shedding along with viral antigen specific antibody responses among COVID-19 patients started to be reported but there is no consensus on their patterns. Here, we conducted a serial investigation on 21 individuals infected with SARS-CoV-2 in two medical centres from Jiangsu Province, including 11 non-severe COVID-19 patients, and 5 severe COVID-19 patients and 5 asymptomatic carriers based on nucleic acid test and clinical symptoms. The longitudinal swab samples and sera were collected from these people for viral RNA testing and antibody responses, respectively. Our data revealed different pattern of seroconversion among these groups. All 11 non-severe COVID-19 patients and 5 severe COVID-19 patients were seroconverted during hospitalization or follow-up period, suggesting that serological testing is a complementary assay to nucleic acid test for those symptomatic COVID-19 patients. Of note, immediate antibody responses were identified among severe cases, compared to non-severe cases. On the other hand, only one were seroconverted for asymptomatic carriers. The SARS-CoV-2 specific antibody responses were well-maintained during the observation period. Such information is of immediate relevance and would assist COVID-19 clinical diagnosis, prognosis and vaccine design.

The advent of cefiderocol provides hope for the clinical treatment of multi-drug resistant gram-negative bacteria (GNB), especially those with carbapenem resistance. Resistance of Klebsiella pneumoniae to cefiderocol can be enhanced by acclimatization. In the present study, we collected cefiderocol resistant K. pneumoniae isolates during a 36-day acclimatization procedure while increasing the cefiderocol concentration in the culture medium. Strains were studied for changes in their biological characteristics using proteomics and transcriptomics. A decrease in biofilm formation ability was the main change observed among the induced isolates. Downregulation of genes involved in biofilm formation including hdeB, stpA, yhjQ, fba, bcsZ, uvrY, bcsE, bcsC, and ibpB were the main factors that reduced the biofilm formation ability. Moreover, downregulation of siderophore transporter proteins including the iron uptake system component efeO, the tonB-dependent receptor fecA, and ferric iron ABC transporter fbpA may be among the determining factors leading to cefiderocol resistance and promoting the reduction of biofilm formation ability of K. pneumoniae. This is the first study to investigate cefiderocol resistance based on comprehensive proteomic and transcriptomic analyses.

Abstract Background Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification. Objective To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes. Methods Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. Results The identification accuracy of MALDI-TOF MS was 84% for species (I2 = 98.0%, P

BackgroundGlucose-6-phosphate isomerase (GPI) plays an important role in glycolysis and gluconeogenesis. However, the role of GPI in lung adenocarcinoma (LUAD) remains unclear.MethodsAll original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and integrated via R 3.2.2. GPI expression was explored with TCGA, GEO, and Oncomine databases. Immunohistochemistry staining was used to analyze GPI expression in clinical specimens. The correlations between GPI and cancer immune characteristics were analyzed via the TIMER and TISIDB databases. GPI-specific siRNAs were used to verify the role of GPI expression on cell proliferation and cell cycle distribution.ResultsIn general, GPI is predominantly overexpressed and has reference value in the diagnosis and prognostic estimation of LUAD. Upregulated GPI was associated with poorer overall survival, clinical stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we identified a hub gene that included a total of 56 GPI-related genes, which were tightly associated with the cell cycle pathway in LUAD patients. Knockdown of GPI induced cell proliferation inhibition and cell cycle arrest. GPI expression was positively correlated with infiltrating levels of Th2 cells and regulatory T cells (Tregs); in contrast, GPI expression was negatively correlated with infiltrating levels of CD8+ T cells, central memory T cells, dendritic cells, macrophages, mast cells, and eosinophils. GPI was negatively correlated with the expression of immunostimulators, such as CD40L, IL6R, and TMEM173, in LUAD.ConclusionGPI may play an important role in the cell cycle and can be used as a prognostic biomarker for determining the prognosis and immune infiltration in LUAD.

With the proposal of China’s green energy strategy, the research and development technologies of green energy such as wind energy and hydrogen energy are becoming more and more mature. However, the phenomenon of wind abandonment and anti-peak shaving characteristics of wind turbines have a great impact on the utilization of wind energy. Therefore, this study firstly builds a distributed wind-hydrogen hybrid energy system model, then proposes the power dispatching optimization technology of a wind-hydrogen integrated energy system. On this basis, a power allocation method based on the AUKF (adaptive unscented Kalman filter) algorithm is proposed. The experiment shows that the power allocation strategy based on the AUKF algorithm can effectively reduce the incidence of battery overcharge and overdischarge. Moreover, it can effectively deal with rapid changes in wind speed. The wind hydrogen integrated energy system proposed in this study is one of the important topics of renewable clean energy technology innovation. Its grid-connected power is stable, with good controllability, and the DC bus is more secure and stable. Compared with previous studies, the system developed in this study has effectively reduced the ratio of abandoned air and its performance is significantly better than the system with separate grid connected fans and single hydrogen energy storage. It is hoped that this research can provide some solutions for the research work on power dispatching optimization of energy systems.

Objectives: This study aimed to explore changes in carbapenem-resistant Klebsiella pneumoniae (CR-KP) isolates collected in Guangdong over the period of 2016–2020.Methods: Antibacterial susceptibility was quantified through VITEK 2 compact and K-B method. Carbapenemase phenotypes and genotypes were characterized by modified carbapenem inactivation method (mCIM), EDTA-carbapenem inactivation method (eCIM), and polymerase chain reaction (PCR). Molecular characteristics and evolutionary trends were analyzed by multilocus sequence typing and evolutionary tree.Results: Isolates (2,847) of K. pneumoniae were separated in 2016–2020, and the separate rate of CR-KP increased from 5.65 to 9.90% (p = 0.009). The top 3 wards were intensive care unit (ICU) (21.92%), neonatal wards (13.70%), and respiratory wards (12.33%). In 146 CR-KP strains, serine carbapenemase was the main phenotype, and KPC was the main genotype, and 57 contained two resistant genes, and 1 contained three resistant genes. Two polygenic strains were first found: IMP + GES and KPC + NDM + VIM, but all the phenotypes were metalloenzyme, which indicated that metalloenzyme was usually the first choice for CR-KP resistance. In addition, all the ST54 of metalloenzyme type contained IMP, and all the ST45, ST37, and ST76 contained OXA. ST11 was the most prevalent (42.47%); ST11 and its mutants proved the predominant sequence type making up 51.1% of the carbapenemase-producing isolates. A novel type of ST11 mutation, the rpoB was mutated from sequence 1 to sequence 146, was in an independent separate branch on the evolutionary tree and was resistant to all antibacterial agents. The other three mutants, rpoB 1–15, infB 3–148, and infB 3–80, are also resistant to all antibacteria. Of note, all the four mutants produced serine carbapenemase and contained KPC, and indicated that the prevalent strain in China, ST11, has serious consequences and potential outbreaks.Conclusion: The infection rate of CR-KP has increased, and ICU and neonatal wards have become the key infection areas. Producing serine enzyme, the KPC genotype, and ST11 are the predominant CR-KP. Polygenic strains and ST11 mutation made clinical treatment difficult and may become a potential threat.

Background: This study analyzed the antimicrobial resistance phenotypes and mechanisms of quinolone, cephalosporins, and colistin resistance in nontyphoidal Salmonella from patients with diarrhea in Jiangsu, China.Methods: A total of 741 nontyphoidal Salmonella isolates were collected from hospitals in major cities of Jiangsu Province, China between 2016 and 2017. Their susceptibility to commonly used antibiotics was evaluated by broth micro-dilution and sequencing analysis of resistance genes screened by a PCR method. For mcr-1 positive isolates, genetic relationship study was carried out by pulsed-field gel electrophoresis and multiloci sequence typing analysis. The transferability of these plasmids was measured with conjugation experiments and the genetic locations of mcr-1 were analyzed by pulsed-field gel electrophoresis profiles of S1-digested genomic DNA and subsequent Southern blot hybridization.Results: Among 741 nontyphoidal Salmonella isolates, the most common serotypes identified were S. Typhimurium (n=257, 34.7%) and S. Enteritidis (n=127, 17.1%), and the isolates showed 21.7, 20.6, and 5.0% resistance to cephalosporins, ciprofloxacin, and colistin, respectively. Among the 335 nalidixic acid-resistant Salmonella, 213 (63.6%) and 45 (13.4%) had at least one mutation in gyrA and parC. Among the plasmid-borne resistance, qnrS1 (85; 41.9%) and aac(6')-Ib-cr4 (75; 36.9%) were the most common quinolone resistance (PMQR) genes, while blaCTX-M-14 (n=35) and blaCTX-M-55 (n=46) were found to be dominant extended-spectrum beta-lactamase (ESBL) genes in nontyphoidal Salmonella. In addition, eight mcr-1-harboring strains were detected since 2016 and they were predominate in children under the age of 7years. Conjugation assays showed the donor Salmonella strain has functional and transferable colistin resistance and Southern blot hybridization revealed that mcr-1 was located in a high molecular weight plasmid.Conclusion: In nontyphoidal Salmonella, there is a rapidly increasing trend of colistin resistance and this is the first report of patients harboring mcr-1-positive Salmonella with a new ST type ST155 and new serotype S. Sinstorf. These findings demonstrate the necessity for cautious use and the continuous monitoring of colistin in clinical applications.

According to the sit-and-wait hypothesis, long-term environmental survival is positively correlated with increased bacterial pathogenicity because high durability reduces the dependence of transmission on host mobility. Many indirectly transmitted bacterial pathogens, such as Mycobacterium tuberculosis and Burkhoderia pseudomallei, have high durability in the external environment and are highly virulent. It is possible that abiotic stresses may activate certain pathways or the expressions of certain genes, which might contribute to bacterial durability and virulence, synergistically. Therefore, exploring how bacterial phenotypes change in response to environmental stresses is important for understanding their potentials in host infections. In this study, we investigated the effects of different concentrations of salt (sodium chloride, NaCl), on survival ability, phenotypes associated with virulence, and energy metabolism of the lab strain Escherichia coli BW25113. In particular, we investigated how NaCl concentrations influenced growth patterns, biofilm formation, oxidative stress resistance, and motile ability. In terms of energy metabolism that is central to bacterial survival, glucose consumption, glycogen accumulation, and trehalose content were measured in order to understand their roles in dealing with the fluctuation of osmolarity. According to the results, trehalose is preferred than glycogen at high NaCl concentration. In order to dissect the molecular mechanisms of NaCl effects on trehalose metabolism, we further checked how the impairment of trehalose synthesis pathway (otsBA operon) via single-gene mutants influenced E. coli durability and virulence under salt stress. After that, we compared the transcriptomes of E. coli cultured at different NaCl concentrations, through which differentially expressed genes (DEGs) and differential pathways with statistical significance were identified, which provided molecular insights into E. coli responses to NaCl concentrations. In sum, this study explored the in vitro effects of NaCl concentrations on E. coli from a variety of aspects and aimed to facilitate our understanding of bacterial physiological changes under salt stress, which might help clarify the linkages between bacterial durability and virulence outside hosts under environmental stresses.

Raman spectroscopy (RS) is a widely used analytical technique based on the detection of molecular vibrations in a defined system, which generates Raman spectra that contain unique and highly resolved fingerprints of the system. However, the low intensity of normal Raman scattering effect greatly hinders its application. Recently, the newly emerged surface enhanced Raman spectroscopy (SERS) technique overcomes the problem by mixing metal nanoparticles such as gold and silver with samples, which greatly enhances signal intensity of Raman effects by orders of magnitudes when compared with regular RS. In clinical and research laboratories, SERS provides a great potential for fast, sensitive, label-free, and non-destructive microbial detection and identification with the assistance of appropriate machine learning (ML) algorithms. However, choosing an appropriate algorithm for a specific group of bacterial species remains challenging, because with the large volumes of data generated during SERS analysis not all algorithms could achieve a relatively high accuracy. In this study, we compared three unsupervised machine learning methods and 10 supervised machine learning methods, respectively, on 2,752 SERS spectra from 117 Staphylococcus strains belonging to nine clinically important Staphylococcus species in order to test the capacity of different machine learning methods for bacterial rapid differentiation and accurate prediction. According to the results, density-based spatial clustering of applications with noise (DBSCAN) showed the best clustering capacity (Rand index 0.9733) while convolutional neural network (CNN) topped all other supervised machine learning methods as the best model for predicting Staphylococcus species via SERS spectra (ACC 98.21%, AUC 99.93%). Taken together, this study shows that machine learning methods are capable of distinguishing closely related Staphylococcus species and therefore have great application potentials for bacterial pathogen diagnosis in clinical settings.