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Journal of the American Chemical Society May 2022Carbon dioxide (CO) impacts every aspect of life, and numerous sensing technologies have been established to detect and monitor this ubiquitous molecule. However, its...
Carbon dioxide (CO) impacts every aspect of life, and numerous sensing technologies have been established to detect and monitor this ubiquitous molecule. However, its selective sensing at the molecular level remains an unmet challenge, despite the tremendous potential of such an approach for understanding this molecule's role in complex environments. In this work, we introduce a unique class of selective fluorescent carbon dioxide molecular sensors (CarboSen) that addresses these existing challenges through an activity-based approach. Besides the design, synthesis, and evaluation of these small molecules as CO sensors, we demonstrate their utility by tailoring their reactivity and optical properties, allowing their use in a broad spectrum of multidisciplinary applications, including atmospheric sensing, chemical reaction monitoring, enzymology, and live-cell imaging. Collectively, these results showcase the potential of CarboSen sensors as broadly applicable tools to monitor and visualize carbon dioxide across multiple disciplines.
Topics: Carbon Dioxide
PubMed: 35503368
DOI: 10.1021/jacs.2c02361 -
International Journal of Molecular... Sep 2023Periodontitis is one of the primary causes of tooth loss, and is also related to various systemic diseases. Early detection of this condition is crucial when it comes to... (Meta-Analysis)
Meta-Analysis Review
Periodontitis is one of the primary causes of tooth loss, and is also related to various systemic diseases. Early detection of this condition is crucial when it comes to preventing further oral damage and the associated health complications. This study offers a systematic review of the literature published up to April 2023, and aims to clearly explain the role of proteomics in identifying salivary biomarkers for periodontitis. Comprehensive searches were conducted on PubMed and Web of Science to shortlist pertinent studies. The inclusion criterion was those that reported on mass spectrometry-driven proteomic analyses of saliva samples from periodontitis cohorts, while those on gingivitis or other oral diseases were excluded. An assessment for risk of bias was carried out using the Newcastle-Ottawa Scale and Quality Assessment of Diagnostic Accuracy Studies or the NIH quality assessment tool, and a meta-analysis was performed for replicable candidate biomarkers, i.e., consistently reported candidate biomarkers (in specific saliva samples, and periodontitis subgroups, reported in ≥2 independent cohorts/reports) were identified. A Gene Ontology enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resources, which consistently expressed candidate biomarkers, to explore the predominant pathway wherein salivary biomarkers consistently manifested. Of the 15 studies included, 13 were case-control studies targeting diagnostic biomarkers for periodontitis participants (periodontally healthy/diseased, = 342/432), while two focused on biomarkers responsive to periodontal treatment ( = 26 participants). The case-control studies were considered to have a low risk of bias, while the periodontitis treatment studies were deemed fair. Summary estimate and confidence/credible interval, etc. determination for the identified putative salivary biomarkers could not be ascertained due to the low number of studies in each case. The results from the included case-control studies identified nine consistently expressed candidate biomarkers (from nine studies with 230/297 periodontally healthy/diseased participants): (i) those that were upregulated: alpha-amylase, serum albumin, complement C3, neutrophil defensin, profilin-1, and S100-P; and (ii) those that were downregulated: carbonic anhydrase 6, immunoglobulin J chain, and lactoferrin. All putative biomarkers exhibited consistent regulation patterns. The implications of the current putative marker proteins identified were reviewed, with a focus on their potential roles in periodontitis diagnosis and pathogenesis, and as putative therapeutic targets. Although in its early stages, mass spectrometry-based salivary periodontal disease biomarker proteomics detection appeared promising. More mass spectrometry-based proteomics studies, with or without the aid of already available clinical biochemical approaches, are warranted to aid the discovery, identification, and validation of periodontal health/disease indicator molecule(s). Protocol registration number: CRD42023447722; supported by RD-02-202410 and GRF17119917.
Topics: Humans; Proteomics; Periodontitis; Mass Spectrometry; Biomarkers; Proteins; Periodontal Diseases; Saliva
PubMed: 37834046
DOI: 10.3390/ijms241914599 -
Frontiers in Pharmacology 2022The human microbiota produces molecules that are evolved to interact with the diverse cellular machinery of both the host and microbes, mediating health and diseases.... (Review)
Review
The human microbiota produces molecules that are evolved to interact with the diverse cellular machinery of both the host and microbes, mediating health and diseases. One of the most puzzling microbiome molecules is colibactin, a genotoxin encoded in some commensal and extraintestinal microbes and is implicated in initiating colorectal cancer. The colibactin cluster was discovered more than 15 years ago, and most of the research studies have been focused on revealing the biosynthesis and precise structure of the cryptic encoded molecule(s) and the mechanism of carcinogenesis. In 2022, the Balskus group revealed that colibactin not only hits targets in the eukaryotic cell machinery but also in the prokaryotic cell. To that end, colibactin crosslinks the DNA resulting in activation of the SOS signaling pathway, leading to prophage induction from bacterial lysogens and modulation of virulence genes in pathogenic species. These unique activities of colibactin highlight its ecological role in shaping gut microbial communities and further consequences that impact human health. This review dives in-depth into the molecular mechanisms underpinning colibactin cellular targets in eukaryotic and prokaryotic cells, aiming to understand the fine details of the role of secreted microbiome chemistry in mediating host-microbe and microbe-microbe interactions. This understanding translates into a better realization of microbiome potential and how this could be advanced to future microbiome-based therapeutics or diagnostic biomarkers.
PubMed: 36172175
DOI: 10.3389/fphar.2022.958012 -
The FEBS Journal May 2023Drugs interact with their target of interest to bring about the desired phenotypic outcome that results in disease alleviation. Traditionally, most lead optimization... (Review)
Review
Drugs interact with their target of interest to bring about the desired phenotypic outcome that results in disease alleviation. Traditionally, most lead optimization exercises were driven by affinity measures (like IC ) to inform structure-activity relationship (SAR)-guided medicinal chemistry. However, an IC value is a thermodynamic estimate measured under equilibrium conditions that can vary as a function of substrate concentration and/or time (the latter especially for nonequilibrium modalities). Further, like other thermodynamic estimates, it is a state-function that is indifferent to the path traversed from the initial state to the final state. This can be a cause for concern in drug discovery given the predominance of nonequilibrium interactions and the open thermodynamic nature of the human system. Under such situations, employing rates along with equilibrium constants (or IC values) would be far more relevant to capture the time evolution of the small molecule's interaction with the target of interest. These rates are generally typified by the rate of association, rate of dissociation and the residence time of the small molecule on the target (target occupancy). These parameters, when combined with the concept of target vulnerability, therapeutic window, pharmacokinetic profile of the small molecule, estimates of endogenous ligand and target turnover, will shed critical insights into the kinetics and dynamics of a small molecule's interaction with the protein, and allow realistic modelling of the system to enable optimizations and dosing decisions. With that aim, this guide will attempt to introduce the traditional role of mechanistic enzymology within drug discovery and emphasize the importance of kinetics in guiding SAR-based optimizations. It will also present initial ideas on how kinetic investigation should be positioned relative to the temporal span of a drug-discovery pipeline to leverage maximal utility from the investment in time and effort.
Topics: Humans; Kinetics; Structure-Activity Relationship; Proteins; Physics; Drug Discovery
PubMed: 35175693
DOI: 10.1111/febs.16404 -
Cell Proliferation Jun 2024Osteoarthritis (OA) is the most prevalent disorder of synovial joint affecting multiple joints. In the past decade, we have witnessed conceptual switch of OA... (Review)
Review
Osteoarthritis (OA) is the most prevalent disorder of synovial joint affecting multiple joints. In the past decade, we have witnessed conceptual switch of OA pathogenesis from a 'wear and tear' disease to a disease affecting entire joint. Extensive studies have been conducted to understand the underlying mechanisms of OA using genetic mouse models and ex vivo joint tissues derived from individuals with OA. These studies revealed that multiple signalling pathways are involved in OA development, including the canonical Wnt/β-catenin signalling and its interaction with other signalling pathways, such as transforming growth factor β (TGF-β), bone morphogenic protein (BMP), Indian Hedgehog (Ihh), nuclear factor κB (NF-κB), fibroblast growth factor (FGF), and Notch. The identification of signalling interaction and underlying mechanisms are currently underway and the specific molecule(s) and key signalling pathway(s) playing a decisive role in OA development need to be evaluated. This review will focus on recent progresses in understanding of the critical role of Wnt/β-catenin signalling in OA pathogenesis and interaction of β-catenin with other pathways, such as TGF-β, BMP, Notch, Ihh, NF-κB, and FGF. Understanding of these novel insights into the interaction of β-catenin with other pathways and its integration into a complex gene regulatory network during OA development will help us identify the key signalling pathway of OA pathogenesis leading to the discovery of novel therapeutic strategies for OA intervention.
Topics: Humans; Osteoarthritis; Animals; beta Catenin; Signal Transduction; Wnt Signaling Pathway; NF-kappa B; Hedgehog Proteins; Bone Morphogenetic Proteins; Transforming Growth Factor beta
PubMed: 38199244
DOI: 10.1111/cpr.13600 -
Journal of Chemical Information and... Sep 2022The quantitative description between chemical reaction rates and nucleophilicity parameters plays a crucial role in organic chemistry. In this regard, the formula...
The quantitative description between chemical reaction rates and nucleophilicity parameters plays a crucial role in organic chemistry. In this regard, the formula proposed by Mayr et al. and the constructed reactivity database are important representatives. However, the determination of Mayr's nucleophilicity parameter often requires time-consuming experiments with reference electrophiles in the solvent. Several machine learning (ML)-based models have been proposed to realize the data-driven prediction of in recent years. However, in addition to DFT-calculated electronic descriptors, most of them also use a set of artificially predefined structural descriptors as input, which may result in a biased representation of the nucleophile's structural information depending on descriptors' definition preference. Compared with traditional ML algorithms, graph neural networks (GNNs) can naturally take the molecule's structural information into account by applying the message passing technique. We herein proposed a SchNet-based GNN model that only takes the molecular conformation and solvent type as input. The model achieves a comparable performance to the previous benchmark study on 10-fold cross-validation of 894 data points ( = 0.91, RMSE = 2.25). To enhance the model's ability to capture the molecule's electronic information, some DFT-calculated parameters are then incorporated into the model via graph global features, and substantial improvement is achieved in the prediction precision ( = 0.95, RMSE = 1.63). These results demonstrate that both structural and electronic information are important for the prediction of , and GNN can integrate these two kinds of information more effectively.
Topics: Algorithms; Machine Learning; Neural Networks, Computer; Solvents
PubMed: 36097394
DOI: 10.1021/acs.jcim.2c00696 -
ACS Applied Bio Materials Jan 2023Since the onset of the SARS-CoV-2 pandemic, the world has witnessed over 617 million confirmed cases and more than 6.54 million confirmed deaths, but the actual totals...
Since the onset of the SARS-CoV-2 pandemic, the world has witnessed over 617 million confirmed cases and more than 6.54 million confirmed deaths, but the actual totals are likely much higher. The virus has mutated at a significantly faster rate than initially projected, and positive cases continue to surge with the emergence of ever more transmissible variants. According to the CDC, and at the time of this manuscript submission, more than 77% of all current US cases are a result of the B.5 (omicron). The continued emergence of highly transmissible variants makes clear the need for more effective methods of mitigating disease spread. Herein, we have developed an antimicrobial fabric capable of destroying a myriad of microbes including betacoronaviruses. We have demonstrated the capability of this highly porous and nontoxic metal organic framework (MOF), γ-CD-MOF-1, to serve as a host for varied-length benzalkonium chlorides (BACs; active ingredient in Lysol). Molecular docking simulations predicted a binding affinity of up to -4.12 kcal·mol, which is comparable to that of other reported guest molecules for this MOF. Similar Raman spectra and powder X-ray diffraction patterns between the unloaded and loaded MOFs, accompanied by a decrease in the Brunauer-Emmett-Teller surface area from 616.20 and 155.55 m g respectively, corroborate the suggested potential for pore occupation with BAC. The MOF was grown on polypropylene fabric, exposed to a BAC-loading bath, washed to remove excess BAC from the external surface, and evaluated for its microbicidal activity against various bacterial and viral classes. Significant antimicrobial character was observed against , , , bacteriophage, and betacoronavirus. This study shows that a common mask material (polypropylene) can be coated with BAC-loaded γ-CD-MOF-1 while maintaining the guest molecule's antimicrobial effects.
Topics: Humans; Metal-Organic Frameworks; Molecular Docking Simulation; Surface-Active Agents; Polypropylenes; COVID-19; SARS-CoV-2; Anti-Infective Agents
PubMed: 36595712
DOI: 10.1021/acsabm.2c00860 -
Proceedings of SPIE--the International... Aug 2022Advances in nanotechnology enable the detection of trace molecules from the enhanced Raman signal generated at the surface of plasmonic nanoparticles. We have developed...
Advances in nanotechnology enable the detection of trace molecules from the enhanced Raman signal generated at the surface of plasmonic nanoparticles. We have developed technology to enable super-resolution imaging of plasmonic nanoparticles, where the fluctuations in the surface enhanced Raman scattering (SERS) signal can be analyzed with localization microscopy techniques to provide nanometer spatial resolution of the emitting molecule's location. Additional work now enables the super-resolved SERS image and the corresponding spectrum to be acquired simultaneously. Here we will discuss how this approach can be applied to provide new insights into biological cells.
PubMed: 37431396
DOI: 10.1117/12.2632824 -
IEEE Transactions on Biomedical... Feb 2020DNA measurement machines are undergoing an orders-of-magnitude size and power reduction. As a result, the analysis of genetic molecules is increasingly appropriate for...
DNA measurement machines are undergoing an orders-of-magnitude size and power reduction. As a result, the analysis of genetic molecules is increasingly appropriate for mobile platforms. However, sequencing these measurements (converting to the molecule's A-C-G-T text equivalent) requires intense computing resources, a problem for potential realizations as mobile devices. This paper proposes a step towards addressing this issue, the design and implementation of a low-power real-time FPGA hardware accelerator for the basecalling task of nanopore-based DNA measurements. Key basecalling computations are identified and ported to a custom FPGA which operates in tandem with a CPU across a high-speed serial link and a simple API. A measured speed-up over CPU-only basecalling in excess of 100X is realized with an energy efficiency improvement of three orders of magnitude.
Topics: Algorithms; Computational Biology; DNA; Nanopores; Sequence Analysis, DNA
PubMed: 31825872
DOI: 10.1109/TBCAS.2019.2958049