Non-viral, specifically targeted CAR-T cells achieve high safety and efficacy in B-NHL.

Recently, chimeric antigen receptor (CAR)-T cell therapy has shown great promise in treating haematological malignancies1-7. However, CAR-T cell therapy currently has several limitations8-12. Here we successfully developed a two-in-one approach to generate non-viral, gene-specific targeted CAR-T cells through CRISPR-Cas9. Using the optimized protocol, we demonstrated feasibility in a preclinical study by inserting an anti-CD19 CAR cassette into the AAVS1 safe-harbour locus. Furthermore, an innovative type of anti-CD19 CAR-T cell with PD1 integration was developed and showed superior ability to eradicate tumour cells in xenograft models. In adoptive therapy for relapsed/refractory aggressive B cell non-Hodgkin lymphoma (ClinicalTrials.gov, NCT04213469 ), we observed a high rate (87.5%) of complete remission and durable responses without serious adverse events in eight patients. Notably, these enhanced CAR-T cells were effective even at a low infusion dose and with a low percentage of CAR+ cells. Single-cell analysis showed that the electroporation method resulted in a high percentage of memory T cells in infusion products, and PD1 interference enhanced anti-tumour immune functions, further validating the advantages of non-viral, PD1-integrated CAR-T cells. Collectively, our results demonstrate the high safety and efficacy of non-viral, gene-specific integrated CAR-T cells, thus providing an innovative technology for CAR-T cell therapy.

FOXA3 regulates cholesterol metabolism to compensate for low uptake during the progression of lung adenocarcinoma.

Cholesterol metabolism is vital for multiple cancer progression, while how cholesterol affects lung, a low-cholesterol tissue, for cancer metastasis and the underlying mechanism remain unclear. In this study, we found that metastatic lung adenocarcinoma cells acquire cellular dehydrocholesterol and cholesterol by endogenous cholesterol biosynthesis, instead of uptake upon cholesterol treatment. Besides, we demonstrated that exogenous cholesterol functions as signaling molecule to induce FOXA3, a key transcription factor for lipid metabolism via GLI2. Subsequently, ChIP-seq analysis and molecular studies revealed that FOXA3 transcriptionally activated Hmgcs1, an essential enzyme of cholesterol biosynthesis, to induce endogenous dehydrocholesterol and cholesterol level for membrane composition change and cell migration. Conversely, FOXA3 knockdown or knockout blocked cholesterol biosynthesis and lung adenocarcinoma metastasis in mice. In addition, the potent FOXA3 inhibitor magnolol suppressed metastatic gene programs in lung adenocarcinoma patient-derived organoids (PDOs). Altogether, our findings shed light onto unique cholesterol metabolism and FOXA3 contribution to lung adenocarcinoma metastasis.

Correction: The interferon stimulated gene 20 protein (ISG20) is an innate defense antiviral factor that discriminates self versus non-self translation.

[This corrects the article DOI: 10.1371/journal.ppat.1008093.].

DMGL-MDA: A dual-modal graph learning method for microbe-drug association prediction.

The interaction between human microbes and drugs can significantly impact human physiological functions. It is crucial to identify potential microbe-drug associations (MDAs) before drug administration. However, conventional biological experiments to predict MDAs are plagued by drawbacks such as time-consuming, high costs, and potential risks. On the contrary, computational approaches can speed up the screening of MDAs at a low cost. Most computational models usually use a drug similarity matrix as the initial feature representation of drugs and stack the graph neural network layers to extract the features of network nodes. However, different calculation methods result in distinct similarity matrices, and message passing in graph neural networks (GNNs) induces phenomena of over-smoothing and over-squashing, thereby impacting the performance of the model. To address these issues, we proposed a novel graph representation learning model, dual-modal graph learning for microbe-drug association prediction (DMGL-MDA). It comprises a dual-modal embedding module, a bipartite graph network embedding module, and a predictor module. To assess the performance of DMGL-MDA, we compared it against state-of-the-art methods using two benchmark datasets. Through cross-validation, we illustrated the superiority of DMGL-MDA. Furthermore, we conducted ablation experiments and case studies to validate the effective performance of the model.

Development of a Recombinase-Aided Amplification Assay for the Rapid Detection of Candida auris.

Candida auris (C. auris) was first discovered in Japan in 2009 and has since spread worldwide. It exhibits strong transmission ability, high multidrug resistance, blood infectivity, and mortality rates. Traditional diagnostic techniques for C. auris have shortcomings, leading to difficulty in its timely diagnosis and identification. Therefore, timely and accurate diagnostic assays for clinical samples are crucial. We developed a novel, rapid recombinase-aided amplification (RAA) assay targeting the 18S rRNA, ITS1, 5.8S rRNA, ITS2, and 28S rRNA genes for C. auris identification. This assay can rapidly amplify DNA at 39 °C in 20 min. The analytical sensitivity and specificity were evaluated. From 241 clinical samples collected from pediatric inpatients, none were detected as C. auris-positive. We then prepared simulated clinical samples by adding 10-fold serial dilutions of C. auris into the samples to test the RAA assay's efficacy and compared it with that of real-time PCR. The assay demonstrated an analytical sensitivity of 10 copies/µL and an analytical specificity of 100%. The lower detection limit of the RAA assay for simulated clinical samples was 101 CFU/mL, which was better than that of real-time PCR (102-103 CFU/mL), demonstrating that the RAA assay may have a better detection efficacy for clinical samples. In summary, the RAA assay has high sensitivity, specificity, and detection efficacy. This assay is a potential new method for detecting C. auris, with simple reaction condition requirements, thus helping to manage C. auris epidemics.

Allogeneic CAR-T cells with of HLA-A/B and TRAC disruption exhibit promising antitumor capacity against B cell malignancies.

BACKGROUND: Although chimeric antigen receptor T (CAR-T) cells have been proven to be an effective way of treating B cell malignancies, a lot of patients could not benefit from it because of failure in CAR-T cell manufacturing, disease progression, and unaffordable price. The study aimed to explore universal CAR-T cell products to extend the clinical accessibility. METHODS: The antitumor activity of CRISPR/Cas9-edited allogeneic anti-CD19 CAR-T (CAR-T19) cells was assessed in vitro, in animal models, and in patients with relapsed/refractory (R/R) acute B cell lymphoblastic leukemia (B-ALL) or diffuse large B cell lymphoma. RESULTS: B2M-/TRAC- universal CAR-T19 (U-CAR-T19) cells exhibited powerful anti-leukemia abilities both in vitro and in animal models, as did primary CD19+ leukemia cells from leukemia patients. However, expansion, antitumor efficacy, or graft-versus-host-disease (GvHD) was not observed in six patients with R/R B cell malignancies after U-CAR-T19 cell infusion. Accordingly, significant activation of natural killer (NK) cells by U-CAR-T19 cells was proven both clinically and in vitro. HLA-A-/B-/TRAC- novel CAR-T19 (nU-CAR-T19) cells were constructed with similar tumoricidal capacity but resistance to NK cells in vitro. Surprisingly, robust expansion of nU-CAR-T19 cells, along with rapid eradication of CD19+ abnormal B cells, was observed in the peripheral blood and bone marrow of another three patients with R/R B-ALL. The patients achieved complete remission with no detectable minimal residual disease 14 days after the infusion of nU-CAR-T19 cells. Two of the three patients had grade 2 cytokine release syndrome, which were managed using an IL-6 receptor blocker. Most importantly, GvHD was not observed in any patient, suggesting the safety of TRAC-disrupted CAR-T cells generated using the CRISPR/Cas9 method for clinical application. CONCLUSIONS: The nU-CAR-T19 cells showed a strong response in R/R B-ALL. nU-CAR-T19 cells have the potential to be a promising new approach for treating R/R B cell malignancies.

Myelin oligodendrocyte glycoprotein antibody and N-methyl-d-aspartate receptor antibody overlapping syndrome: insights from the recent case reports.

The overlapping of two or more types of neural autoantibodies in one patient has increasingly been documented in recent years. The coexistence of myelin oligodendrocyte glycoprotein (MOG) and N-methyl-d-aspartate receptor (NMDAR) antibodies is most common, which leads to a unique condition known as the MOG antibody and NMDAR antibody overlapping syndrome (MNOS). Here, we have reviewed the pathogenesis, clinical manifestations, paraclinical features, and treatment of MNOS. Forty-nine patients with MNOS were included in this study. They were young males with a median onset age of 23 years. No tumors were observed in the patients, and 24 of them reported prodromal symptoms. The most common clinical presentations were psychiatric symptoms (35/49) and seizures (25/49). Abnormalities on magnetic resonance imaging involved the brainstem (11/49), cerebellum (9/49), and parietal lobe (9/49). Most patients mostly responded to immunotherapy and had a good long-term prognosis. However, the overall recurrence rate of MNOS was higher than that of mono antibody-positive diseases. The existence of concurrent NMDAR antibodies should be suspected in patients with MOG antibody-associated disease having psychiatric symptoms, seizures, movement disorders, or autonomic dysfunction. Similarly, serum MOG antibody testing should be performed when patients with anti-NMDAR encephalitis present with atypical clinical manifestations, such as visual impairment and limb weakness, and neuroradiological findings, such as optic nerve, spinal cord, or infratentorial involvement or meningeal enhancement. Early detection of the syndrome and prompt treatment can be beneficial for these patients, and maintenance immunosuppressive therapy is recommended due to the high overall recurrence rate of the syndrome.

CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning.

MOTIVATION: Metabolic stability plays a crucial role in the early stages of drug discovery and development. Accurately modeling and predicting molecular metabolic stability has great potential for the efficient screening of drug candidates as well as the optimization of lead compounds. Considering wet-lab experiment is time-consuming, laborious, and expensive, in silico prediction of metabolic stability is an alternative choice. However, few computational methods have been developed to address this task. In addition, it remains a significant challenge to explain key functional groups determining metabolic stability. RESULTS: To address these issues, we develop a novel cross-modality graph contrastive learning model named CMMS-GCL for predicting the metabolic stability of drug candidates. In our framework, we design deep learning methods to extract features for molecules from two modality data, i.e. SMILES sequence and molecule graph. In particular, for the sequence data, we design a multihead attention BiGRU-based encoder to preserve the context of symbols to learn sequence representations of molecules. For the graph data, we propose a graph contrastive learning-based encoder to learn structure representations by effectively capturing the consistencies between local and global structures. We further exploit fully connected neural networks to combine the sequence and structure representations for model training. Extensive experimental results on two datasets demonstrate that our CMMS-GCL consistently outperforms seven state-of-the-art methods. Furthermore, a collection of case studies on sequence data and statistical analyses of the graph structure module strengthens the validation of the interpretability of crucial functional groups recognized by CMMS-GCL. Overall, CMMS-GCL can serve as an effective and interpretable tool for predicting metabolic stability, identifying critical functional groups, and thus facilitating the drug discovery process and lead compound optimization. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/dubingxue/CMMS-GCL.

Multiple factors trigger the formation and resuscitation of the VBNC state in alcohol-producing Klebsiella pneumoniae.

Klebsiella pneumoniae can enter a viable but nonculturable (VBNC) state to survive in unfavorable environments. Our research found that high-, medium-, and low-alcohol-producing K. pneumoniae strains are associated with nonalcoholic fatty liver disease. However, the presence of the three Kpn strains has not been reported in the VBNC state or during resuscitation. In this study, the effects of different strains, salt concentrations, oxygen concentrations, temperatures, and nutrients in K. pneumoniae VBNC state were evaluated. The results showed that high-alcohol-producing K. pneumoniae induced a slower VBNC state than medium-alcohol-producing K. pneumoniae, and low-alcohol-producing K. pneumoniae. A high-salt concentration and micro-oxygen environment accelerated the loss of culturability. Simultaneously, both real-time quantitative PCR and droplet digital PCR were developed to compare the quantitative comparison of three Kpn strain VBNC states by counting single-copy gene numbers. At 22°C or 37°C, the number of culturable cells decreased significantly from about 108 to 105-106 CFU/mL. In addition, imipenem, ciprofloxacin, polymyxin, and phiW14 inhibited cell resuscitation but could not kill VBNC-state cells. These results revealed that the different environments evaluated play different roles in the VBNC induction process, and new effective strategies for eliminating VBNC-state cells need to be further studied. These findings provide a better understanding of VBNC-state occurrence, maintenance, detection, and absolute quantification, as well as metabolic studies of resuscitation resistance and ethanol production.IMPORTANCEBacteria may enter VBNC state under different harsh environments. Pathogenic VBNC bacteria cells in clinical and environmental samples pose a potential threat to public health because cells cannot be found by routine culture. The alcohol-producing Kpn VBNC state was not reported, and the influencing factors were unknown. The formation and recovery of VBNC state is a complete bacterial escape process. We evaluated the influence of multiple induction conditions on the formation of VBNC state and recovery from antibiotic and bacteriophage inhibition, and established a sensitive molecular method to enumerate the VBNC cells single-copy gene. The method can improve the sensitivity of pathogen detection in clinical, food, and environmental contamination monitoring, and outbreak warning. The study of the formation and recovery of VBNC-state cells under different stress environments will also promote the microbiological research on the development, adaptation, and resuscitation in VBNC-state ecology.

Development and validation of a new multiplex panel using SNaPshot-based DIP-TriSNP markers for forensic DNA mixtures.

Short tandem repeat analysis is challenging when dealing with unbalanced mixtures in forensic cases due to the presence of stutter peaks and large amplicons. In this research, we propose a novel genetic marker called DIP-TriSNP, which combines deletion/insertion polymorphism (DIP) with tri-allelic single nucleotide polymorphism in less than 230 bp length of human genome. Based on multiplex PCR and SNaPShot, a panel, including 14 autosomal DIP-TriSNPs and one Y chromosomal DIP-SNP, had been developed and applied to genotyping 102 unrelated Han Chinese individuals in Sichuan of China and simulated a mixture study. The panel sensitivity can reach as low as 0.1 ng DNA template, and the minor contributor of DNA can be detected with the highest ratio of 19:1, as indicated by the obtained results. In the Sichuan Han population, the cumulative probability of informative genotypes reached 0.997092, with a combined power of discrimination of 0.999999998801. The panel was estimated to detect more than two alleles in at least one locus in 99.69% of mixtures of the Sichuan Han population. In conclusion, DIP-TriSNPs have shown promising as an innovative DNA marker for identifying the minor contributor in unbalanced DNA mixtures, offering advantages such as short amplifications, increased polymorphism, and heightened sensitivity.

LIGHT/TNFSF14 promotes CAR-T cell trafficking and cytotoxicity through reversing immunosuppressive tumor microenvironment.

Tertiary lymphoid structures (TLSs) in tumor tissues facilitate immune cell trafficking and cytotoxicity, which benefits survival and favorable responses in immune therapy. Here, we observed a high correlation of tumor necrosis factor superfamily member 14 (LIGHT) expression with TLS signature genes, which are all markers for immune cell accumulation and better prognosis, through retrieving RNA sequencing (RNA-seq) data from patients with cancer, suggesting the potential of LIGHT in reconstituting a high immune-infiltrated tumor microenvironment. Accordingly, LIGHT co-expressed chimeric antigen receptor T (LIGHT CAR-T) cells not only showed enhanced cytotoxicity and cytokine production but also improved CCL19 and CCL21 expression by surrounding cells. And the supernatant of LIGHT CAR-T cells promoted T cell migration in a paracrine manner. Furthermore, LIGHT CAR-T cells showed superior anti-tumor efficacy and improved infiltration in comparison with conventional CAR-T cells in immunodeficient NSG mice. Accordingly, murine LIGHT-OT-1 T cells normalized tumor blood vessels and enforced intratumoral lymphoid structures in C57BL/6 syngeneic tumor mouse models, implying the potential of LIGHT CAR-T in clinical application. Taken together, our data revealed a straightforward strategy to optimize trafficking and cytotoxicity of CAR-T cells by redirecting TLSs through LIGHT expression, which has great potential to expand and optimize the application of CAR-T therapy in solid tumors.

Detecting and quantifying Veillonella by real-time quantitative PCR and droplet digital PCR.

Veillonella spp. are Gram-negative opportunistic pathogens present in the respiratory, digestive, and reproductive tracts of mammals. An abnormal increase in Veillonella relative abundance in the body is closely associated with periodontitis, inflammatory bowel disease, urinary tract infections, and many other diseases. We designed a pair of primers and a probe based on the 16S rRNA gene sequences of Veillonella and conducted real-time quantitative PCR (qPCR) and droplet digital PCR (ddPCR) to quantify the abundance of Veillonella in fecal samples. These two methods were tested for specificity and sensitivity using simulated clinical samples. The sensitivity of qPCR was 100 copies/µL, allowing for the accurate detection of a wide range of Veillonella concentrations from 103 to 108 CFU/mL. The sensitivity of ddPCR was 11.3 copies/µL, only allowing for the accurate detection of Veillonella concentrations from 101 to 104 CFU/mL because of the limited number of droplets generated by ddPCR. ddPCR is therefore more suitable for the detection of low-abundance Veillonella samples. To characterize the validity of the assay system, clinical samples from children with inflammatory bowel disease were collected and analyzed, and the results were verified using isolation methods. We conclude that molecular assays targeting the 16S rRNA gene provides an important tool for the rapid diagnosis of chronic and infectious diseases caused by Veillonella and also supports the isolation and identification of Veillonella for research purposes. KEY POINTS: • With suitable primer sets, the qPCR has a wider detection range than ddPCR. • ddPCR is suitable for the detection of low-abundance samples. • Methods successfully guided the isolation of Veillonella in clinical sample.

High-density lipoprotein mimetic nano-therapeutics targeting monocytes and macrophages for improved cardiovascular care: a comprehensive review.

The prevalence of cardiovascular diseases continues to be a challenge for global health, necessitating innovative solutions. The potential of high-density lipoprotein (HDL) mimetic nanotherapeutics in the context of cardiovascular disease and the intricate mechanisms underlying the interactions between monocyte-derived cells and HDL mimetic showing their impact on inflammation, cellular lipid metabolism, and the progression of atherosclerotic plaque. Preclinical studies have demonstrated that HDL mimetic nanotherapeutics can regulate monocyte recruitment and macrophage polarization towards an anti-inflammatory phenotype, suggesting their potential to impede the progression of atherosclerosis. The challenges and opportunities associated with the clinical application of HDL mimetic nanotherapeutics, emphasize the need for additional research to gain a better understanding of the precise molecular pathways and long-term effects of these nanotherapeutics on monocytes and macrophages to maximize their therapeutic efficacy. Furthermore, the use of nanotechnology in the treatment of cardiovascular diseases highlights the potential of nanoparticles for targeted treatments. Moreover, the concept of theranostics combines therapy and diagnosis to create a selective platform for the conversion of traditional therapeutic medications into specialized and customized treatments. The multifaceted contributions of HDL to cardiovascular and metabolic health via highlight its potential to improve plaque stability and avert atherosclerosis-related problems. There is a need for further research to maximize the therapeutic efficacy of HDL mimetic nanotherapeutics and to develop targeted treatment approaches to prevent atherosclerosis. This review provides a comprehensive overview of the potential of nanotherapeutics in the treatment of cardiovascular diseases, emphasizing the need for innovative solutions to address the challenges posed by cardiovascular diseases.

Porcupine quills keratin peptides induces G0/G1 cell cycle arrest and apoptosis via p53/p21 pathway and caspase cascade reaction in MCF-7 breast cancer cells.

BACKGROUND: Porcupine quills, a by-product of porcupine pork, are rich in keratin, which is an excellent source of bioactive peptides. The objective of this study was to investigate the underlying mechanism of anti-proliferation effect of porcupine quills keratin peptides (PQKPs) on MCF-7 cells. RESULTS: Results showed that PQKPs induced MCF-7 cells apoptosis by significantly decreasing the secretion level of anti-apoptosis protein Bcl-2 and increasing the secretion levels of pro-apoptosis proteins Bax, cytochrome c, caspase 9, caspase 3 and PARP. PQKPs also arrested the cell cycle at G0/G1 phase via remarkably reducing the protein levels of CDK4 and enhancing the protein levels of p53 and p21. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis identified nine peptides with molecular weights less than 1000 Da in PQKPs. Molecular docking results showed that TPGPPT and KGPAC identified from PQKPs could bind with p53 mutant and Bcl-2 protein by conventional hydrogen bonds, carbon hydrogen bonds and van der Waals force. Furthermore, the anti-proliferation impact of synthesized peptides (TPGPPT and KGPAC) was shown in MCF-7 cells. CONCLUSION: These findings indicated that PQKPs suppressed the proliferation of MCF-7 breast cancer cells by triggering apoptosis and G0/G1 cell cycle arrest. Moreover, the outcome of this study will bring fresh insights into the production and application of animal byproducts. © 2023 Society of Chemical Industry.

Covalent conjugation of Inca peanut albumin and polyphenols with different phenolic hydroxyl numbers through laccase catalysis to improve functional properties.

BACKGROUND: Enzymatic crosslinking is a method that can be used to modify Inca peanut albumin (IPA) using polyphenols, and provides desirable functionalities; however, the effect of polyphenol structures on conjugate properties is unclear. In this study, we selected four polyphenols with different numbers of phenolic hydroxyl groups [para-hydroxybenzoic acid (HBA), protocatechuic acid (PCA), gallic acid (GA), and epigallocatechin gallate (EGCG)] for covalent modification of IPA by enzymatic crosslinking, and explored the structure-function changes of the IPA-polyphenol conjugates. RESULTS: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) analysis showed that laccase successfully promoted covalent crosslinking of IPA with polyphenols, with the order of degree of conjugation as EGCG > GA > PCA > HBA, the IPA-EGCG conjugate showed the highest polyphenol binding equivalents (98.35 g kg-1 protein), and a significant reduction in the content of free amino, sulfhydryl, and tyrosine group. The oxidation of polyphenols by laccase forms quinone or semiquinone radicals that are covalently crosslinked to the reactive groups of IPA, leading to significant changes in the secondary and tertiary structures of IPA, with spherical structures transforming into dense lamellar structures. The 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability and emulsification stability of IPA-EGCG conjugates improved by almost 6-fold and 2.7-fold, respectively, compared with those of unmodified IPA. CONCLUSION: These data suggest that the higher the number of polyphenol hydroxyl groups, the higher the degree of IPA-polyphenol conjugation; additionally, enzymatic crosslinking can significantly improve the functional properties of IPA. © 2024 Society of Chemical Industry.

A Bibliometric and Visual Analysis of the Current Status and Trends of Forensic Mixed Stain Research.

OBJECTIVES: To explore the context and hotspot changes of forensic mixed stain research through bibliometric approach. METHODS: The literature of forensic mixed stain included in the core collection of Web of Science database from 2011 to 2022 were collected as the study object, and the annual publication number, countrie (region), institution, journal, keywords, etc. were bibliometrically and visually analyzed using the R-based Bibliometrix 1.1.6 package and VOSviewer 1.6.18 software. RESULTS: A total of 732 articles on forensic mixed stain were included from 2011 to 2022, with the annual number of articles published and the annual citation frequency showing a steady increase year by year. Among the 59 countries (regions) with the most published articles, the United States ranked first with 246 articles, followed by China with 153 articles. The literature came from 104 journals, and the total number of articles published in the top 10 journals was 633. FORENSIC SCI INT GENET ranked first with 307 articles. Visual analysis using VOSviewer software showed that keywords could be divided into four research clusters, namely the genetic marker development group (blue), the mixed stain typing analysis theory group (red), the sequencing analysis group (yellow), and the case sample research group (green). It can be divided into four development stages in terms of different time periods: early development (2011-2013), middle development (2014-2016), rapid development (2017-2020) and latest development (2021-2022). CONCLUSIONS: The number of publications by domestic and foreign scholars in the study of mixed stain in forensic science is showing a relatively stable trend. Machine learning, next generation sequencing and other research have been the hottest topics that have attracted the most attention in recent years, which is expected to further develop the theory of mixed stain typing and sequencing analysis in forensic mixed stain research.

High Density Single Fe Atoms on Mesoporous N-Doped Carbons: Noble Metal-Free Electrocatalysts for Oxygen Reduction Reaction in Acidic and Alkaline Media.

It remains a challenge to develop efficient noble metal-free electrocatalysts for the oxygen reduction reaction (ORR) in various renewable energy systems. Single atom catalysts have recently drawn great attention as promising candidates both due to their high activity and their utmost atom utilization for electrocatalytic ORR. Herein, the synthesis of an efficient ORR electrocatalyst that is composed of N-doped mesoporous carbon and a high density (4.05 wt%) of single Fe atoms via pyrolysis Fe-conjugated polymer is reported. Benefiting from the abundant atomic Fe-N4 sites on its conductive, mesoporous carbon structures, this material exhibits an excellent electrocatalytic activity for ORR, with positive onset potentials of 0.93 and 0.98 V in acidic and alkaline media, respectively. Its electrocatalytic performance for ORR is also comparable to that of Pt/C (20 wt%) in both media. Furthermore, it electrocatalyzes the reaction almost fully to H2 O (or barely to H2 O2 ). Additionally, it is durable and tolerates the methanol crossover reaction well. Furthermore, a proton exchange membrane fuel cell and a zinc-air battery assembled using it on their cathode deliver high maximum power densities (320 and 91 mW cm-2 , respectively). Density functional theory calculation reveals that the material's decent electrocatalytic performance for ORR is due to its atomically dispersed Fe-N4 sites.

MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction.

MOTIVATION: During lead compound optimization, it is crucial to identify pathways where a drug-like compound is metabolized. Recently, machine learning-based methods have achieved inspiring progress to predict potential metabolic pathways for drug-like compounds. However, they neglect the knowledge that metabolic pathways are dependent on each other. Moreover, they are inadequate to elucidate why compounds participate in specific pathways. RESULTS: To address these issues, we propose a novel Multi-Label Graph Learning framework of Metabolic Pathway prediction boosted by pathway interdependence, called MLGL-MP, which contains a compound encoder, a pathway encoder and a multi-label predictor. The compound encoder learns compound embedding representations by graph neural networks. After constructing a pathway dependence graph by re-trained word embeddings and pathway co-occurrences, the pathway encoder learns pathway embeddings by graph convolutional networks. Moreover, after adapting the compound embedding space into the pathway embedding space, the multi-label predictor measures the proximity of two spaces to discriminate which pathways a compound participates in. The comparison with state-of-the-art methods on KEGG pathways demonstrates the superiority of our MLGL-MP. Also, the ablation studies reveal how its three components contribute to the model, including the pathway dependence, the adapter between compound embeddings and pathway embeddings, as well as the pre-training strategy. Furthermore, a case study illustrates the interpretability of MLGL-MP by indicating crucial substructures in a compound, which are significantly associated with the attending metabolic pathways. It is anticipated that this work can boost metabolic pathway predictions in drug discovery. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/dubingxue/MLGL-MP.

Research on synthesis and property of nano-textured Sc2O3-MgO efficient antibacterial agents.

In order to obtain the inorganic efficient antibacterial agents, the means of ion doping and morphology construction in this research are used to enhance the antibacterial property of nano-MgO, which is according to the "oxidative damage mechanism" and "contact mechanism". In this work, the nano-textured Sc2O3-MgO are synthesized by doping Sc3+ in nano-MgO lattice through calcining at 600 °C. When the Sc3+ content reaches 10%, the nanotextures on the powders surface are pretty clearly visible and uniform, and the specific surface area and the oxygen vacancy are ideal, so that the 10% Sc3+-doped powders (SM-10) has the excellent antibacterial property against E. coli and S. aureus (MBC = 0.03 mg/mL). The efficient antibacterial agents in this research have a better antibacterial effect than the 0% Sc3+-doped powders (SM-0, MBC = 0.20 mg/mL) and the commercial nano-MgO (CM, MBC = 0.40 mg/mL), which have application prospects in the field of antibacterial.

A novel phage carrying capsule depolymerase effectively relieves pneumonia caused by multidrug-resistant Klebsiella aerogenes.

BACKGROUND: Klebsiella aerogenes can cause ventilator-associated pneumonia by forming biofilms, and it is frequently associated with multidrug resistance. Phages are good antibiotic alternatives with unique advantages. There has been a lack of phage therapeutic explorations, kinetic studies, and interaction mechanism research targeting K. aerogenes. METHODS: Plaque assay, transmission electron microscopy and whole-genome sequencing were used to determine the biology, morphology, and genomic characteristics of the phage. A mouse pneumonia model was constructed by intratracheal/endobronchial delivery of K. aerogenes to assess the therapeutic effect of phage in vivo. Bioinformatics analysis and a prokaryotic protein expression system were used to predict and identify a novel capsule depolymerase. Confocal laser scanning microscopy, Galleria mellonella larvae infection models and other experiments were performed to clarify the function of the capsule depolymerase. RESULTS: A novel lytic phage (pK4-26) was isolated from hospital sewage. It was typical of the Podoviridae family and exhibited serotype specificity, high lytic activity, and high environmental adaptability. The whole genome is 40,234 bp in length and contains 49 coding domain sequences. Genomic data show that the phage does not carry antibiotic resistance, virulence, or lysogenic genes. The phage effectively lysed K. aerogenes in vivo, reducing mortality and alleviating pneumonia without promoting obvious side effects. A novel phage-derived depolymerase was predicted and proven to be able to digest the capsule, remove biofilms, reduce bacterial virulence, and sensitize the bacteria to serum killing. CONCLUSIONS: The phage pK4-26 is a good antibiotic alternative and can effectively relieve pneumonia caused by multidrug-resistant K. aerogenes. It carries a depolymerase that removes biofilms, reduces virulence, and improves intrinsic immune sensitivity.