Ontology based autonomous robot task processing framework.

Introduction: In recent years, the perceptual capabilities of robots have been significantly enhanced. However, the task execution of the robots still lacks adaptive capabilities in unstructured and dynamic environments. Methods: In this paper, we propose an ontology based autonomous robot task processing framework (ARTProF), to improve the robot's adaptability within unstructured and dynamic environments. ARTProF unifies ontological knowledge representation, reasoning, and autonomous task planning and execution into a single framework. The interface between the knowledge base and neural network-based object detection is first introduced in ARTProF to improve the robot's perception capabilities. A knowledge-driven manipulation operator based on Robot Operating System (ROS) is then designed to facilitate the interaction between the knowledge base and the robot's primitive actions. Additionally, an operation similarity model is proposed to endow the robot with the ability to generalize to novel objects. Finally, a dynamic task planning algorithm, leveraging ontological knowledge, equips the robot with adaptability to execute tasks in unstructured and dynamic environments. Results: Experimental results on real-world scenarios and simulations demonstrate the effectiveness and efficiency of the proposed ARTProF framework. Discussion: In future work, we will focus on refining the ARTProF framework by integrating neurosymbolic inference.

Lattice Strain and Mott-Schottky Effect of the Charge-Asymmetry Pd1Fe Single-Atom Alloy Catalyst for Semi-Hydrogenation of Alkynes with High Efficiency.

The ideal interface design between the metal and substrate is crucial in determining the overall performance of the alkyne semihydrogenation reaction. Single-atom alloys (SAAs) with isolated dispersed active centers are ideal media for the study of reaction effects. Herein, a charge-asymmetry "armor" SAA (named Pd1Fe SAA@PC), which consists of a Pd1Fe alloy core and a semiconducting P-doped C (PC) shell, is rationally designed as an ideal catalyst for the selective hydrogenation of alkynes with high efficiency. Multiple spectroscopic analyses and density functional theory calculations have demonstrated that Pd1Fe SAA@PC is dual-regulated by lattice tensile and Schottky effects, which govern the selectivity and activity of hydrogenation, respectively. (1) The PC shell layer applied an external traction force causing a 1.2% tensile strain inside the Pd1Fe alloy to increase the reaction selectivity. (2) P doping into the C-shell layer realized a transition from a p-type semiconductor to an n-type semiconductor, thereby forming a unique Schottky junction for advancing alkyne semihydrogenation activity. The dual regulation of lattice strain and the Schottky effect ensures the excellent performance of Pd1Fe SAA@PC in the semihydrogenation reaction of phenylethylene, achieving a conversion rate of 99.9% and a selectivity of 98.9% at 4 min. These well-defined interface modulation strategies offer a practical approach for the rational design and performance optimization of semihydrogenation catalysts.

Antioxidant and Hepatoprotective Effect of Rosa davurica Pall Seed Oil on CCl4-Induced Acute Liver Injury in Mice.

The liver, being the most metabolically active organ, is highly vulnerable to damage caused by oxidative stress. Rosa davurica Pall. seed oil (RDPO), a novel vegetable oil, and its bioactive components have been extensively researched in the field of antioxidants. In this research, the antioxidant properties and hepatoprotection by RDPO were evaluated. A series of antioxidant evaluation systems and a CCl4-induced acute liver injury model in mice were used to investigate the antioxidant activity and hepatoprotective efficacy of RDPO. The results showed that the extraction rate of RDPO was 11.12% using the optimal extraction process. Three major unsaturated fatty acids of the oil were α-linolenic acid (11.89 ± 0.017%), linoleic acid (18.52 ± 0.072%), and oleic acid (11.54 ± 0.425%). Furthermore, its antioxidant small-molecule compounds were ß-sitosterol (1.429 ± 0.002 µg/g), α-tocopherol (1.273 ± 0.079 µg/g), ß-carotene (0.012 ± 0.001 µg/g), lycopene (0.108 ± 0.002 µg/g), squalene (178.950 ± 0.794 µg/g), total polyphenols (1.114 ± 0.032 µg GAE/mg), and total flavonoids (0.504 ± 0.009 mg RU/g), respectively. In vitro, RDPO significantly inhibited the production of ABTS+•, DPPH•, O2•-, and hydroxyl radicals, as well as Fe3+. In vivo, RDPO significantly reversed the activity of total superoxide-dismutase, catalase, L-glutathione, and the level of malondialdehyde (MDA) in liver tissue. It also obviously inhibited the activity of aspartate transaminase (AST) and the level of MDA in the serum. Therefore, RDPO has demonstrated excellent antioxidant activity and a potential liver protective effect. This effect may be ascribed to its capacity for decreasing AST activity, inhibiting lipid peroxidation, and boosting endogenous antioxidant enzyme activity. Therefore, RDPO has significant application value in the biopharmaceutical industry and as a dietary supplement.

Functional divergence in orthologous transcription factors: insights from AtCBF2/3/1 and OsDREB1C.

Despite traditional beliefs of orthologous genes maintaining similar functions across species, growing evidence points to their potential for functional divergence. C-repeat binding factors/dehydration-responsive element binding protein 1s (CBFs/DREB1s) are critical in cold acclimation, with their overexpression enhancing stress tolerance but often constraining plant growth. In contrast, a recent study unveiled a distinctive role of rice OsDREB1C in elevating nitrogen use efficiency (NUE), photosynthesis, and grain yield, implying functional divergence within the CBF/DREB1 orthologs across species. Here, we delve into divergent molecular mechanisms of OsDREB1C and AtCBF2/3/1 by exploring their evolutionary trajectories across rice and Arabidopsis genomes, regulatomes, and transcriptomes. Evolutionary scrutiny shows discrete clades for OsDREB1C and AtCBF2/3/1, with the Poaceae-specific DREB1C clade mediated by a transposon event. Genome-wide binding profiles highlight OsDREB1C's preference for GCCGAC compared to AtCBF2/3/1's preference for A/GCCGAC, a distinction determined by R12 in the OsDREB1C AP2/ERF domain. Cross-species multi-omic analyses reveal shared gene orthogroups (OGs) and underscore numerous specific OGs uniquely bound and regulated by OsDREB1C, implicated in NUE, photosynthesis, and early flowering, or by AtCBF2/3/1, engaged in hormone and stress responses. This divergence arises from gene gains/losses (∼16.7‒25.6%) and expression reprogramming (∼62.3‒66.2%) of OsDREB1C- and AtCBF2/3/1-regulated OGs during the extensive evolution following the rice-Arabidopsis split. Our findings illustrate the regulatory evolution of OsDREB1C and AtCBF2/3/1 at a genomic scale, providing insights on the functional divergence of orthologous transcription factors following gene duplications across species.

Real-time Trajectory Planning and Tracking Control of Bionic Underwater Robot in Dynamic Environment.

In this article, we study the trajectory planning and tracking control of a bionic underwater robot under multiple dynamic obstacles. We first introduce the design of the bionic leopard cabinet underwater robot developed in our lab. Then, we model the trajectory planning problem of the bionic underwater robot by combining its dynamics and physical constraints. Furthermore, we conduct global trajectory planning for bionic underwater robots based on the temporal-spatial Bezier curves. In addition, based on the improved proximal policy optimization, local dynamic obstacle avoidance trajectory replanning is carried out. In addition, we design the fuzzy proportional-integral-derivative controller for tracking control of the planned trajectory. Finally, the effectiveness of the real-time trajectory planning and tracking control method is verified by comparative simulation in dynamic environment and semiphysical simulation of UWSim. Among them, the real-time trajectory planning method has advantages in trajectory length, trajectory smoothness, and planning time. The error of trajectory tracking control method is controlled around 0.2 m.

Settling velocity of atmospheric particles in seawater: Based on hydrostatic sedimentation method using video imaging techniques.

When atmospheric particles deposit to the ocean, their settling velocities and residence times associated are critical for their effects on oceanic ecosystems. We developed a hydrostatic sedimentation method using video imaging techniques to track particles of 5-20 µm in diameter falling into seawater and determine the particle settling velocities in relation to their diameter, shape, organic matter contained, and seawater salinity. The measured settling velocities varied from 0.025 to 0.41 mm/s. Irregular particle shape and organic matter contained in particles also, however, reduced the values. The settling velocities were decelerated by the dissolution process of particle in seawater. Combined with the experimental results, a formula for calculating the settling velocity formulae for atmospheric particles was estimated. Using this equation, the residence time of particles is estimated to be less than one month in continental shelf sea and more than 100 days in the oceans.

Phyllostachys edulis Argonaute genes function in the shoot architecture.

Argonaute (AGO) proteins are the core components of the RNA-induced silencing complexes (RISC) in the cytoplasm and nucleus, and are necessary for the development of plant shoot meristem, which gives rise to the above-ground plant body. In this study, we identified 23 Phyllostachys edulis AGO genes (PhAGOs) that were distributed unequally on the 14 unmapped scaffolds. Gene collinearity and phylogeny analysis showed that the innovation of PhAGO genes was mainly due to dispersed duplication and whole-genome duplication, which resulted in the enlarged PhAGO family. PhAGO genes were expressed in a temporal-spatial expression pattern, and they encoded proteins differently localized in the cytoplasm and/or nucleus. Overexpression of the PhAGO2 and PhAGO4 genes increased the number of tillers or leaves in Oryza sativa and affected the shoot architecture of Arabidopsis thaliana. These results provided insight into the fact that PhAGO genes play important roles in plant development.

In Situ Self-Assembled Active and Stable Ir@MnOx/La0.7Sr0.3Cr0.9Ir0.1O3-δ Interfaces for CO2 Electrolysis.

Solid oxide electrolysis cells are prospective approaches for CO2 utilization but face significant challenges due to the sluggish reaction kinetics and poor stability of the fuel electrodes. Herein, we strategically addressed the long-standing trade-off phenomenon between enhanced exsolution and improved structural stability via topotactic ion exchange. The surface dynamic reconstruction of the MnOx/La0.7Sr0.3Cr0.9Ir0.1O3-δ (LSCIr) catalyst was visualized at the atomic scale. Compared with the Ir@LSCIr interface, the in situ self-assembled Ir@MnOx/LSCIr interface exhibited greater CO2 activation and easily removable carbonate intermediates, thus reached a 42% improvement in CO2 electrolysis performance at 1.6 V. Furthermore, an improved CO2 electrolysis stability was achieved due to the uniformly wrapped MnOx shell of the Ir@MnOx/LSCIr cathode. Our approach enables a detailed understanding of the dynamic microstructure evolution at active interfaces and provides a roadmap for the rational design and evaluation of efficient metal/oxide catalysts for CO2 electrolysis.

Dextran Macroinitiator for Synthesis of Polysaccharide-b-Polypeptide Block Copolymers via NCA Ring-Opening Polymerization.

Synthesis of polysaccharide-b-polypeptide block copolymers represents an attractive goal because of their promising potential in delivery applications. Inspired by recent breakthroughs in N-carboxyanhydride (NCA) ring-opening polymerization (ROP), we present an efficient approach for preparation of a dextran-based macroinitiator and the subsequent synthesis of dextran-b-polypeptides via NCA ROP. This is an original approach to creating and employing a native polysaccharide macroinitiator for block copolymer synthesis. In this strategy, regioselective (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) oxidation of the sole primary alcohol located at the C-6 position of the monosaccharide at the nonreducing end of linear dextran results in a carboxylic acid. This motif is then transformed into a tetraalkylammonium carboxylate, thereby generating the dextran macroinitiator. This macroinitiator initiates a wide range of NCA monomers and produces dextran-b-polypeptides with a degree of polymerization (DP) of the polypeptide up to 70 in a controlled manner (D < 1.3). This strategy offers several distinct advantages, including preservation of the original dextran backbone structure, relatively rapid polymerization, and moisture tolerance. The dextran-b-polypeptides exhibit interesting self-assembly behavior. Their nanostructures have been investigated by dynamic light scattering (DLS) and transmission electron microscopy (TEM), and adjustment of the structure of block copolymers allows self-assembly of spherical micelles and worm-like micelles with varied diameters and aspect ratios, revealing a range of diameters from 60 to 160 nm. Moreover, these nanostructures exhibit diverse morphologies, including spherical micelles and worm-like micelles, enabling delivery applications.

m1A inhibition fuels oncolytic virus-elicited antitumor immunity via downregulating MYC/PD-L1 signaling.

N1-methyladenosine (m1A) RNA methylation is critical for regulating mRNA translation; however, its role in the development, progression, and immunotherapy response of head and neck squamous cell carcinoma (HNSCC) remains largely unknown. Using Tgfbr1 and Pten conditional knockout (2cKO) mice, we found the neoplastic transformation of oral mucosa was accompanied by increased m1A modification levels. Analysis of m1A-associated genes identified TRMT61A as a key m1A writer linked to cancer progression and poor prognosis. Mechanistically, TRMT61A-mediated tRNA-m1A modification promotes MYC protein synthesis, upregulating programmed death-ligand 1 (PD-L1) expression. Moreover, m1A modification levels were also elevated in tumors treated with oncolytic herpes simplex virus (oHSV), contributing to reactive PD-L1 upregulation. Therapeutic m1A inhibition sustained oHSV-induced antitumor immunity and reduced tumor growth, representing a promising strategy to alleviate resistance. These findings indicate that m1A inhibition can prevent immune escape after oHSV therapy by reducing PD-L1 expression, providing a mutually reinforcing combination immunotherapy approach.

A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data.

BACKGROUND: Survival prediction using high-dimensional molecular data is a hot topic in the field of genomics and precision medicine, especially for cancer studies. Considering that carcinogenesis has a pathway-based pathogenesis, developing models using such group structures is a closer mimic of disease progression and prognosis. Many approaches can be used to integrate group information; however, most of them are single-model methods, which may account for unstable prediction. METHODS: We introduced a novel survival stacking method that modeled using group structure information to improve the robustness of cancer survival prediction in the context of high-dimensional omics data. With a super learner, survival stacking combines the prediction from multiple sub-models that are independently trained using the features in pre-grouped biological pathways. In addition to a non-negative linear combination of sub-models, we extended the super learner to non-negative Bayesian hierarchical generalized linear model and artificial neural network. We compared the proposed modeling strategy with the widely used survival penalized method Lasso Cox and several group penalized methods, e.g., group Lasso Cox, via simulation study and real-world data application. RESULTS: The proposed survival stacking method showed superior and robust performance in terms of discrimination compared with single-model methods in case of high-noise simulated data and real-world data. The non-negative Bayesian stacking method can identify important biological signal pathways and genes that are associated with the prognosis of cancer. CONCLUSIONS: This study proposed a novel survival stacking strategy incorporating biological group information into the cancer prognosis models. Additionally, this study extended the super learner to non-negative Bayesian model and ANN, enriching the combination of sub-models. The proposed Bayesian stacking strategy exhibited favorable properties in the prediction and interpretation of complex survival data, which may aid in discovering cancer targets.

Strain rate-dependent failure mechanics of the intervertebral disc under tension/compression and constitutive analysis.

BACKGROUND: The intervertebral disc exhibits not only strain rate dependence (viscoelasticity), but also significant asymmetry under tensile and compressive loads, which is of great significance for understanding the mechanism of lumbar disc injury under physiological loads. OBJECTIVE: In this study, the strain rate sensitive and tension-compression asymmetry of the intervertebral disc were analyzed by experiments and constitutive equation. METHOD: The Sheep intervertebral disc samples were divided into three groups, in order to test the strain rate sensitive mechanical behavior, and the internal displacement as well as pressure distribution. RESULTS: The tensile stiffness is one order of magnitude smaller than the compression stiffness, and the logarithm of the elastic modulus is approximately linear with the logarithm of the strain rate, showing obvious tension-compression asymmetry and rate-related characteristics. In addition, the sensitivity to the strain rate is the same under these two loading conditions. The stress-strain curves of unloading and loading usually do not coincide, and form a Mullins effect hysteresis loop. The radial displacement distribution is opposite between the anterior and posterior region, which is consistent with the stress distribution. By introducing the damage factor into ZWT constitutive equation, the rate-dependent viscoelastic and weakening behavior of the intervertebral disc can be well described.

The influence of gender-specific factors influencing severe anxiety in psychotic major depression: role of thyroid hormones and depression severity.

BACKGROUND: Psychotic major depression (PMD) is characterized by major depressive disorder (MDD) accompanied by delusions or hallucinations. While the prevalence of PMD and its association with anxiety have been studied, gender-specific differences and the role of thyroid hormones in PMD-related anxiety remain less explored. METHODS: A total of 1718 first-episode and drug-naïve MDD patients was assessed for the presence of PMD and severe anxiety. Clinical assessments, including Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), Positive and Negative Syndrome Scale (PANSS), and Clinical Global Impressions-Severity (CGI-S) scale, were conducted to assess depression, anxiety, psychotic symptoms, and clinical severity, respectively. Blood samples were collected to measure thyroid function parameters. RESULTS: The prevalence of severe anxiety was higher in PMD patients compared to non-psychotic MDD patients (71.3% vs. 5.3%). No significant gender differences were observed in the prevalence of severe anxiety among PMD patients. However, elevated thyroid-stimulating hormone (TSH) levels and increased depression severity (HAMD scores) were identified as independent risk factors for severe anxiety in female PMD patients. In contrast, no significant risk factors were found in male PMD patients. The area under the receiver operating characteristic (AUCROC) analysis revealed that the HAMD score and TSH level showed acceptable discriminatory capacity for distinguishing between female PMD patients with and without severe anxiety. CONCLUSION: This study highlights the heightened prevalence of severe anxiety in PMD patients, with TSH levels and depression severity emerging as gender-specific risk factors for anxiety in females. These findings suggest the importance of thyroid hormone assessment and tailored interventions for managing anxiety in female PMD patients.

Write your paper on the motherland?

'Write your paper on the motherland' is an influential Chinese slogan encouraging researchers to focus on domestic issues and prioritize local applications of their work, though interpretations differ. The 2024 'International Journal Early Warning List' update sparked renewed debate over the slogan's meaning. This letter argues that misinterpreting this slogan as merely promoting domestic journal submissions could lead to a more conservative submission behavior and a more closed academic system. This reflects a common challenge among non-English-speaking countries to balance international reach with local contributions in publications.

Neural processing of speech comprehension in noise predicts individual age using fNIRS-based brain-behavior models.

Speech comprehension in noise depends on complex interactions between peripheral sensory and central cognitive systems. Despite having normal peripheral hearing, older adults show difficulties in speech comprehension. It remains unclear whether the brain's neural responses could indicate aging. The current study examined whether individual brain activation during speech perception in different listening environments could predict age. We applied functional near-infrared spectroscopy to 93 normal-hearing human adults (20 to 70 years old) during a sentence listening task, which contained a quiet condition and 4 different signal-to-noise ratios (SNR = 10, 5, 0, -5 dB) noisy conditions. A data-driven approach, the region-based brain-age predictive modeling was adopted. We observed a significant behavioral decrease with age under the 4 noisy conditions, but not under the quiet condition. Brain activations in SNR = 10 dB listening condition could successfully predict individual's age. Moreover, we found that the bilateral visual sensory cortex, left dorsal speech pathway, left cerebellum, right temporal-parietal junction area, right homolog Wernicke's area, and right middle temporal gyrus contributed most to prediction performance. These results demonstrate that the activations of regions about sensory-motor mapping of sound, especially in noisy conditions, could be sensitive measures for age prediction than external behavior measures.

Atypical neural encoding of faces in individuals with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) experience pervasive difficulties in processing social information from faces. However, the behavioral and neural mechanisms underlying social trait judgments of faces in ASD remain largely unclear. Here, we comprehensively addressed this question by employing functional neuroimaging and parametrically generated faces that vary in facial trustworthiness and dominance. Behaviorally, participants with ASD exhibited reduced specificity but increased inter-rater variability in social trait judgments. Neurally, participants with ASD showed hypo-activation across broad face-processing areas. Multivariate analysis based on trial-by-trial face responses could discriminate participant groups in the majority of the face-processing areas. Encoding social traits in ASD engaged vastly different face-processing areas compared to controls, and encoding different social traits engaged different brain areas. Interestingly, the idiosyncratic brain areas encoding social traits in ASD were still flexible and context-dependent, similar to neurotypicals. Additionally, participants with ASD also showed an altered encoding of facial saliency features in the eyes and mouth. Together, our results provide a comprehensive understanding of the neural mechanisms underlying social trait judgments in ASD.

Long-neglected contribution of nitrification to N2O emissions in the Yellow River.

Rivers play a significant role in the global nitrous oxide (N2O) budget. However, the microbial sources and sinks of N2O in river systems are not well understood or quantified, resulting in the prolonged neglect of nitrification. This study investigated the isotopic signatures of N2O, thereby quantifying the microbial source of N2O production and the degree of N2O reduction in the Yellow River. Although denitrification has long been considered to be the dominant pathway of N2O production in rivers, our findings indicated that denitrification only accounted for 18.3% (8.2%-43.0%) of the total contribution to N2O production in the Yellow River, with 50.2%-80.2% being concurrently reduced. The denitrification contribution to N2O production (R2 = 0.44, p < 0.01) and N2O reduction degree (R2 = 0.70, p < 0.01) were positively related to the dissolved organic carbon (DOC) content. Similar to urban rivers and eutrophic lakes, denitrification was the primary process responsible for N2O production (43.0%) in certain reaches with high organic content (DOC = 5.29 mg/L). Nevertheless, the denitrification activity was generally constrained by the availability of electron donors (average DOC = 2.51 mg/L) throughout the Yellow River basin. Consequently, nitrification emerged as the primary contributor in the well-oxygenated Yellow River. Additionally, our findings further distinguished the respective contribution of ammonia-oxidizing bacteria (AOB) and archaea (AOA) to N2O emissions. Although AOB dominated the N2O production in the Yellow River, the AOA specie abundance (AOA/(AOA + AOB)) contributed up to 32.6%, which resulted in 25.6% of the total nitrifier-produced N2O, suggesting a significant occurrence of AOA in the oligotrophic Yellow River. Overall, this study provided a non-invasive approach for quantifying the microbial sources and sinks to N2O emissions, and demonstrated the substantial role of nitrification in the large oligotrophic rivers.

Polyphenols functionalized MOF encapsulated BPQDs for synergistic photothermal/photodynamic antibacterial properties and multifunctional food preservation.

Active antibacterial materials play an important role in solving food safety problems caused by pathogen contamination. In this study, a composite active antibacterial material with the synergistic antibacterial effectiveness of photothermal, photodynamic and the surface charge of polyphenols was developed, where the multi-porous polyphenol functionalized metal-organic frameworks (ZIF-8-TA) were used as the framework carrier, and black phosphorus quantum dots (BPQDs) were used as the photosensitive source. The resulted ZIF-8-TA/PBQDs possesses excellent photothermal conversion efficiency (27.92%), photodynamic performance and surface charge, and these factors ensure the outstanding broad-spectrum antibacterial performance (100%). Multifunctional characteristics and excellent biocompatibility endow the materials with vast potential for foodstuff packaging. The results showed that the composite antibacterial film produced by doping ZIF-8-TA/PBQDs into chitosan could effectively prolong the shelf life of foodstuff compared with commercial membrane. The successful implementation of this research provides a new idea for controlling microbial contamination and developing multifunctional antibacterial materials.

Fn-OMV potentiates ZBP1-mediated PANoptosis triggered by oncolytic HSV-1 to fuel antitumor immunity.

Oncolytic viruses (OVs) show promise as a cancer treatment by selectively replicating in tumor cells and promoting antitumor immunity. However, the current immunogenicity induced by OVs for tumor treatment is relatively weak, necessitating a thorough investigation of the mechanisms underlying its induction of antitumor immunity. Here, we show that HSV-1-based OVs (oHSVs) trigger ZBP1-mediated PANoptosis (a unique innate immune inflammatory cell death modality), resulting in augmented antitumor immune effects. Mechanistically, oHSV enhances the expression of interferon-stimulated genes, leading to the accumulation of endogenous Z-RNA and subsequent activation of ZBP1. To further enhance the antitumor potential of oHSV, we conduct a screening and identify Fusobacterium nucleatum outer membrane vesicle (Fn-OMV) that can increase the expression of PANoptosis execution proteins. The combination of Fn-OMV and oHSV demonstrates potent antitumor immunogenicity. Taken together, our study provides a deeper understanding of oHSV-induced antitumor immunity, and demonstrates a promising strategy that combines oHSV with Fn-OMV.

Machine Learning Models Identify Inhibitors of New Delhi Metallo-ß-lactamase.

The worldwide spread of the metallo-ß-lactamases (MBL), especially New Delhi metallo-ß-lactamase-1 (NDM-1), is threatening the efficacy of ß-lactams, which are the most potent and prescribed class of antibiotics in the clinic. Currently, FDA-approved MBL inhibitors are lacking in the clinic even though many strategies have been used in inhibitor development, including quantitative high-throughput screening (qHTS), fragment-based drug discovery (FBDD), and molecular docking. Herein, a machine learning-based prediction tool is described, which was generated using results from HTS of a large chemical library and previously published inhibition data. The prediction tool was then used for virtual screening of the NIH Genesis library, which was subsequently screened using qHTS. A novel MBL inhibitor was identified and shown to lower minimum inhibitory concentrations (MICs) of Meropenem for a panel of E. coli and K. pneumoniae clinical isolates expressing NDM-1. The mechanism of inhibition of this novel scaffold was probed utilizing equilibrium dialyses with metal analyses, native state electrospray ionization mass spectrometry, UV-vis spectrophotometry, and molecular docking. The uncovered inhibitor, compound 72922413, was shown to be 9-hydroxy-3-[(5-hydroxy-1-oxa-9-azaspiro[5.5]undec-9-yl)carbonyl]-4H-pyrido[1,2-a]pyrimidin-4-one.