Search

Objective. Computed tomography (CT) is a crucial medical imaging technique which uses x-ray radiation to identify cancer tissues. Since radiation poses a significant health risk, low dose acquisition procedures need to be adopted. However, low-dose CT (LDCT) can cause higher noise and artifacts which massively degrade the diagnosis. Approach. To denoise LDCT images more effectively, this paper proposes a deep learning method based on U-Net with multiple lightweight attention-based modules and residual reinforcement (MLAR-UNet). We integrate a U-Net architecture with several advanced modules, including Convolutional Block Attention Module (CBAM), Cross Residual Module (CR), Attention Cross Reinforcement Module (ACRM), and Convolution and Transformer Cross Attention Module (CTCAM). Among these modules, CBAM applies channel and spatial attention mechanisms to enhance local feature representation. However, serious detail loss caused by incorrect embedding of CBAM for LDCT denoising is verified in this study. To relieve this, we introduce CR to reduce information loss in deeper layers, preserving features more effectively. To address the excessive local attention of CBAM, we design ACRM, which incorporates Transformer to adjust the attention weights. Furthermore, we design CTCAM, which leverages a complex combination of Transformer and convolution to capture multi-scale information and compute more accurate attention weights. Results. Experiments verify the embedding rationality and validity of each module and show that the proposed MLAR-UNet denoises LDCT images more effectively and preserves more details than many state-of-the-art methods on clinical chest and abdominal CT datasets. Significance. The proposed MLAR-UNet not only demonstrates superior LDCT image denoising capability but also highlights the strong detail comprehension and negligible overheads of our designed ACRM and CTCAM. These findings provide a novel approach to integrating Transformer more efficiently in image processing., (© 2025 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

The KRAS gene plays a pivotal role in numerous cancers by encoding a GTPase that upon association with the plasma membrane activates the MAPK pathway, promoting cellular proliferation. In our study, we investigated small molecules that disrupt KRAS's membrane interaction, hypothesizing that such disruption could in turn inhibit mutant RAS signaling. Native mass spectrometry screening of KRAS-FMe identified compounds with a preference for interacting with the hypervariable region (HVR), and surface plasmon resonance (SPR) further refined our selection to graveoline as a compound exhibiting preferential HVR binding. Subsequent nuclear magnetic resonance (NMR) analysis showed that graveoline's interaction with KRAS depends on C-terminal O-methylation. Moreover, our findings revealed multiple interaction sites, suggesting weak engagement with the KRAS G domain. Using nanodiscs as a membrane mimetic, further characterization through NMR and Förster resonance energy transfer (FRET) studies demonstrated graveoline's ability to perturb KRAS membrane interaction in a biochemical setting. Our biophysical approach sheds light on the intricate molecular mechanisms underlying KRAS-ligand interactions, providing valuable insights into understanding the KRAS-associated pathophysiology. These findings contribute to the translational aspect of our study, offering potential avenues for further research targeting KRAS membrane association with the potential to lead to a new class of RAS therapeutics., Competing Interests: The authors declare no competing financial interest., (© 2024 American Chemical Society.)

Medical image fusion can provide doctors with more detailed data and thus improve the accuracy of disease diagnosis. In recent years, deep learning has been widely used in the field of medical image fusion. The traditional method of medical image fusion is to operate by superimposing and other methods of pixels. The introduction of deep learning methods has improved the effectiveness of medical image fusion. However, these methods still have problems such as edge blurring and information redundancy. In this paper, we propose a deep learning network model based on Transformer and an improved DenseNet network module integration that can be applied to medical images and solve the above problems. At the same time, the method can be moved to natural images. The use of Transformer and dense concatenation enhances the feature extraction capability of the method by limiting the feature loss which reduces the risk of edge blurring. We compared several representative traditional methods and more advanced deep learning methods with this method. The experimental results show that the Transformer and the improved DenseNet network module have a strong capability of feature extraction. The method yields good results both in terms of visual quality and objective image evaluation metrics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The oncogene RAS, extensively studied for decades, presents persistent gaps in understanding, hindering the development of effective therapeutic strategies due to a lack of precise details on how RAS initiates MAPK signaling with RAF effector proteins at the plasma membrane. Recent advances in X-ray crystallography, cryo-EM, and super-resolution fluorescence microscopy offer structural and spatial insights, yet the molecular mechanisms involving protein-protein and protein-lipid interactions in RAS-mediated signaling require further characterization. This study utilizes single-molecule experimental techniques, nuclear magnetic resonance spectroscopy, and the computational Machine-Learned Modeling Infrastructure (MuMMI) to examine KRAS4b and RAF1 on a biologically relevant lipid bilayer. MuMMI captures long-timescale events while preserving detailed atomic descriptions, providing testable models for experimental validation. Both in vitro and computational studies reveal that RBDCRD binding alters KRAS lateral diffusion on the lipid bilayer, increasing cluster size and decreasing diffusion. RAS and membrane binding cause hydrophobic residues in the CRD region to penetrate the bilayer, stabilizing complexes through β-strand elongation. These cooperative interactions among lipids, KRAS4b, and RAF1 are proposed as essential for forming nanoclusters, potentially a critical step in MAP kinase signal activation., (© 2024. The Author(s).)

Abstract: Ca2+/calmodulin-dependent protein kinase II γ (CAMKIIγ) has been identified as a potential target for treating cancer. Based on our previous study of berbamine (BBM) as a CAMKIIγ inhibitor, we have synthesized a new BBM derivative termed PA4. Compared with BBM, PA4 showed improved potency and specificity and was more cytotoxic against lymphoma and leukemia than against other types of cancer. In addition to indirectly targeting c-Myc protein stability, we demonstrated that its cytotoxic effects were also mediated via increased reactive oxygen species production in lymphoma cells. PA4 significantly impeded tumor growth in vivo in a xenograft T-cell lymphoma mouse model. Pharmacokinetics studies demonstrated quick absorption into plasma after oral administration, with a maximum concentration of 1680 ± 479 ng/mL at 5.33 ± 2.31 hours. The calculated oral absolute bioavailability was 34.1%. Toxicity assessment of PA4 showed that the therapeutic window used in our experiments was safe for future development. Given its efficacy, safety, and favorable pharmacokinetic profile, PA4 is a potential lead candidate for treating lymphoma., (© 2024 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Aims: The purpose of this study is to establish a novel diagnosis system in early acute coronary syndrome (ACS) using probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning (ML) and to validate the diagnostic accuracy. Methods: A total of 32 serum samples derived from 16 ACS patients and 16 control patients were analyzed by PESI-MS. The acquired mass spectrum dataset was subsequently analyzed by partial least squares (PLS) regression to find the relationship between the two groups. A support vector machine, an ML method, was applied to the dataset to construct the diagnostic algorithm. Results: Control and ACS groups were separated into the two clusters in the PLS plot, indicating ACS patients differed from the control in the profile of serum composition obtained by PESI-MS. The sensitivity, specificity, and accuracy of our diagnostic system were all 93.8%, and the area under the receiver operating characteristic curve showed 0.965 (95% CI: 0.84-1). Conclusion: The PESI-MS and ML-based diagnosis system are likely an optimal solution to assist physicians in ACS diagnosis with its remarkably predictive accuracy., Competing Interests: The authors declare no conflict of interest for this article., (Copyright ©2024 Que N. N. Tran, Takeshi Moriguchi, Masateru Ueno, Tomohiko Iwano, and Kentaro Yoshimura.)

Protein-membrane interactions (PMIs) are ubiquitous in cellular signaling. Initial steps of signal transduction cascades often rely on transient and dynamic interactions with the inner plasma membrane leaflet to populate and regulate signaling hotspots. Methods to target and modulate these interactions could yield attractive tool compounds and drug candidates. Here, we demonstrate that the conjugation of a medium-chain lipid tail to the covalent K-Ras(G12C) binder MRTX849 at a solvent-exposed site enables such direct modulation of PMIs. The conjugated lipid tail interacts with the tethered membrane and changes the relative membrane orientation and conformation of K-Ras(G12C), as shown by molecular dynamics (MD) simulation-supported NMR studies. In cells, this PMI modulation restricts the lateral mobility of K-Ras(G12C) and disrupts nanoclusters. The described strategy could be broadly applicable to selectively modulate transient PMIs.

Background: Stratify new lung cancer patients based on the risk of in-hospital mortality rate after diagnosis. Methods: 522,941 lung cancer cases with available data on the Surveillance, Epidemiology, and End Results (SEER) were analyzed for the predicted probability based on six fundamental variables including age, gender, tumor size, T, N, and AJCC stages. The patients were randomly assigned to the training ( n = 115,145) and validation datasets ( n = 13,017). The remaining cohort with missing values ( n = 394,779) was then combined with the primary lung tumour datasets ( n = 1018) from The Cancer Genome Atlas, Lung Adenocarcinoma and Lung Squamous Cell Carcinoma projects (TCGA-LUAD & TCGA-LUSC) for external validation and sensitivity analysis. Results: Receiver Operating Characteristic (ROC) analyses showed high discriminatory power in the training and internal validation cohorts (Area under the curve [AUC] of 0.78 (95%CI = 0.78-0.79) and 0.78 (95%CI = 0.77-0.79), respectively), whereas that of the model on external validation data was 0.759 (95%CI = 0.757-0.761). We developed a static nomogram, a web app, and a risk table based on a logistic regression model using algorithm-selected variables. Conclusions: Our model can stratify lung cancer patients into high- and low-risk of in-hospital mortality to assist clinical further planning.

Interdependence across time and length scales is common in biology, where atomic interactions can impact larger-scale phenomenon. Such dependence is especially true for a well-known cancer signaling pathway, where the membrane-bound RAS protein binds an effector protein called RAF. To capture the driving forces that bring RAS and RAF (represented as two domains, RBD and CRD) together on the plasma membrane, simulations with the ability to calculate atomic detail while having long time and large length- scales are needed. The Multiscale Machine-Learned Modeling Infrastructure (MuMMI) is able to resolve RAS/RAF protein-membrane interactions that identify specific lipid-protein fingerprints that enhance protein orientations viable for effector binding. MuMMI is a fully automated, ensemble-based multiscale approach connecting three resolution scales: (1) the coarsest scale is a continuum model able to simulate milliseconds of time for a 1 μm 2 membrane, (2) the middle scale is a coarse-grained (CG) Martini bead model to explore protein-lipid interactions, and (3) the finest scale is an all-atom (AA) model capturing specific interactions between lipids and proteins. MuMMI dynamically couples adjacent scales in a pairwise manner using machine learning (ML). The dynamic coupling allows for better sampling of the refined scale from the adjacent coarse scale (forward) and on-the-fly feedback to improve the fidelity of the coarser scale from the adjacent refined scale (backward). MuMMI operates efficiently at any scale, from a few compute nodes to the largest supercomputers in the world, and is generalizable to simulate different systems. As computing resources continue to increase and multiscale methods continue to advance, fully automated multiscale simulations (like MuMMI) will be commonly used to address complex science questions.

Objective: Kinesio taping (KT) and vibration treatment (VT) can alleviate delayed-onset muscle soreness (DOMS) to some extent. However, the literature reports on the difference between the two treatments, and whether a joint intervention (JI) works better than single treatments remains unknown. This study compares the effects of KT, VT and JI on DOMS in college students. Methods: A total of 88 college students were randomly divided into the KT (KTG, n = 21), VT (VTG, n = 22), JI (JIG, n = 23) and control (CG, n = 22) groups. All subjects underwent DOMS moulding. The baseline; immediate and 24, 48 and 72 h visual analogue scale (VAS) scores and knee extensor maximum isometric voluntary contraction (MIVC) were determined. Results: The intergroup comparison showed the following results. 1) The VAS scores of the four groups peaked at 24 h and gradually decreased. The immediate, 24 h and 48 h VAS scores followed the order: JIG > KTG and VTG > CG. The 72 h VAS score followed the order: KTG < VTG < JIG < CG. 2) The knee extension MIVC in the four groups was lowest at 24 h and then gradually increased. JIG had larger immediate MIVC than CG. KTG, VTG and JIG had larger 24 h MIVC than CG. JIG had larger 48 h MIVC than KTG and CG. Conclusion: KT and VT can reduce muscle pain and strength loss caused by DOMS to varying degrees. VT is better than KT in improving pain. The combined intervention worked better than single interventions., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Que.)

During the activation of mitogen-activated protein kinase (MAPK) signaling, the RAS-binding domain (RBD) and cysteine-rich domain (CRD) of RAF bind to active RAS at the plasma membrane. The orientation of RAS at the membrane may be critical for formation of the RAS-RBDCRD complex and subsequent signaling. To explore how RAS membrane orientation relates to the protein dynamics within the RAS-RBDCRD complex, we perform multiscale coarse-grained and all-atom molecular dynamics (MD) simulations of KRAS4b bound to the RBD and CRD domains of RAF-1, both in solution and anchored to a model plasma membrane. Solution MD simulations describe dynamic KRAS4b-CRD conformations, suggesting that the CRD has sufficient flexibility in this environment to substantially change its binding interface with KRAS4b. In contrast, when the ternary complex is anchored to the membrane, the mobility of the CRD relative to KRAS4b is restricted, resulting in fewer distinct KRAS4b-CRD conformations. These simulations implicate membrane orientations of the ternary complex that are consistent with NMR measurements. While a crystal structure-like conformation is observed in both solution and membrane simulations, a particular intermolecular rearrangement of the ternary complex is observed only when it is anchored to the membrane. This configuration emerges when the CRD hydrophobic loops are inserted into the membrane and helices α3-5 of KRAS4b are solvent exposed. This membrane-specific configuration is stabilized by KRAS4b-CRD contacts that are not observed in the crystal structure. These results suggest modulatory interplay between the CRD and plasma membrane that correlate with RAS/RAF complex structure and dynamics, and potentially influence subsequent steps in the activation of MAPK signaling., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Biophysical Society. All rights reserved.)

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.

RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-atomistic detail at macroscopic temporal and spatial scales, which is not possible with conventional computational or experimental techniques. We demonstrate here a multiscale simulation infrastructure that uses machine learning to create a scale-bridging ensemble of over 100,000 simulations of active wild-type KRAS on a complex, asymmetric membrane. Initialized and validated with experimental data (including a new structure of active wild-type KRAS), these simulations represent a substantial advance in the ability to characterize RAS-membrane biology. We report distinctive patterns of local lipid composition that correlate with interfacially promiscuous RAS multimerization. These lipid fingerprints are coupled to RAS dynamics, predicted to influence effector binding, and therefore may be a mechanism for regulating cell signaling cascades., (Copyright © 2021 the Author(s). Published by PNAS.)

KRAS4B is a membrane-anchored signaling protein and a primary target in cancer research. Predictions from molecular dynamics simulations that have previously shaped our mechanistic understanding of KRAS signaling disagree with recent experimental results from neutron reflectometry, NMR, and thermodynamic binding studies. To gain insight into these discrepancies, we compare this body of biophysical data to back-calculated experimental results from a series of molecular simulations that implement different subsets of molecular interactions. Our results show that KRAS4B approximates an entropic ensemble of configurations at model membranes containing 30% phosphatidylserine lipids, which is not significantly shaped by interactions between the globular G-domain of KRAS4B and the lipid membrane. These findings revise our understanding of KRAS signaling and promote a model in which the protein samples the accessible conformational space in a near-uniform manner while being available to bind to effector proteins., (Copyright © 2021 Biophysical Society. All rights reserved.)

Small GTPase proteins are ubiquitous and responsible for regulating several processes related to cell growth and differentiation. Mutations that stabilize their active state can lead to uncontrolled cell proliferation and cancer. Although these proteins are well characterized at the cellular scale, the molecular mechanisms governing their functions are still poorly understood. In addition, there is limited information about the regulatory function of the cell membrane which supports their activity. Thus, we have studied the dynamics and conformations of the farnesylated KRAS4b in various membrane model systems, ranging from binary fluid mixtures to heterogeneous raft mimics. Our approach combines long time-scale coarse-grained (CG) simulations and Markov state models to dissect the membrane-supported dynamics of KRAS4b. Our simulations reveal that protein dynamics is mainly modulated by the presence of anionic lipids and to some extent by the nucleotide state (activation) of the protein. In addition, our results suggest that both the farnesyl and the polybasic hypervariable region (HVR) are responsible for its preferential partitioning within the liquid-disordered (Ld) domains in membranes, potentially enhancing the formation of membrane-driven signaling platforms.

RAS proteins are mutated in approximately 20% of all cancers and are generally associated with poor clinical outcomes. RAS proteins are localized to the plasma membrane and function as molecular switches, turned on by partners that receive extracellular mitogenic signals. In the on-state, they activate intracellular signal transduction cascades. Membrane-bound RAS molecules segregate into multimers, known as nanoclusters. These nanoclusters, held together through weak protein-protein and protein-lipid associations, are highly dynamic and respond to cellular input signals and fluctuations in the local lipid environment. Disruption of RAS nanoclusters results in downregulation of RAS-mediated mitogenic signaling. In this review, we discuss the propensity of RAS proteins to display clustering behavior and the interfaces that are associated with these assemblies. Strategies to therapeutically disrupt nanocluster formation or the stabilization of signaling incompetent RAS complexes are discussed.

The small GTPase KRAS is localized at the plasma membrane where it functions as a molecular switch, coupling extracellular growth factor stimulation to intracellular signaling networks. In this process, KRAS recruits effectors, such as RAF kinase, to the plasma membrane where they are activated by a series of complex molecular steps. Defining the membrane-bound state of KRAS is fundamental to understanding the activation of RAF kinase and in evaluating novel therapeutic opportunities for the inhibition of oncogenic KRAS-mediated signaling. We combined multiple biophysical measurements and computational methodologies to generate a consensus model for authentically processed, membrane-anchored KRAS. In contrast to the two membrane-proximal conformations previously reported, we identify a third significantly populated state using a combination of neutron reflectivity, fast photochemical oxidation of proteins (FPOP), and NMR. In this highly populated state, which we refer to as "membrane-distal" and estimate to comprise ∼90% of the ensemble, the G-domain does not directly contact the membrane but is tethered via its C-terminal hypervariable region and carboxymethylated farnesyl moiety, as shown by FPOP. Subsequent interaction of the RAF1 RAS binding domain with KRAS does not significantly change G-domain configurations on the membrane but affects their relative populations. Overall, our results are consistent with a directional fly-casting mechanism for KRAS, in which the membrane-distal state of the G-domain can effectively recruit RAF kinase from the cytoplasm for activation at the membrane., Competing Interests: Competing interest statement: F.M. is a consultant for the following companies: Aduro Biotech, Amgen, Daiichi Ltd, Ideaya Biosciences, Kura Oncology, Leidos Biomedical Research, Inc., PellePharm, Pfizer Inc., PMV Pharma, Portola Pharmaceuticals, and Quanta Therapeutics. F.M. has received research grants from Daiichi Ltd, and Gilead Sciences and is a consultant and cofounder for the following companies (with ownership interest including stock options): BridgeBio, DNAtrix Inc., Olema Pharmaceuticals, Inc., and Quartz. F.M. is Scientific Director of the National Cancer Institute RAS Initiative at Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc.

Second harmonic generation (SHG) is an emergent biophysical method that sensitively measures real-time conformational change of biomolecules in the presence of biological ligands and small molecules. This study describes the successful implementation of SHG as a primary screening platform to identify fragment ligands to oncogenic Kirsten rat sarcoma (KRas). KRas is the most frequently mutated driver of pancreatic, colon, and lung cancers; however, there are few well-characterized small molecule ligands due to a lack of deep binding pockets. Using SHG, we identified a fragment binder to KRas G12D and used 1 H 15 N transverse relaxation optimized spectroscopy (TROSY) heteronuclear single-quantum coherence (HSQC) NMR to characterize its binding site as a pocket adjacent to the switch 2 region. The unique sensitivity of SHG furthered our study by revealing distinct conformations induced by our hit fragment compared with 4,6-dichloro-2-methyl-3-aminoethyl-indole (DCAI), a Ras ligand previously described to bind the same pocket. This study highlights SHG as a high-throughput screening platform that reveals structural insights in addition to ligand binding., Competing Interests: Conflict of interest statement: E.D. and G.M. were previously employed at Biodesy, Inc. S.K. is an employee of Biodesy, Inc. A.D.M. is cofounder and Chief Scientific Officer of SilcsBio LLC. B.M. is an employee of Biodesy, Inc. and has equity grants in the company. J. Salafsky is the founder of Biodesy, Inc., where the research was performed. F.M. is a consultant for the following companies: Aduro Biotech; Amgen; Daiichi Ltd; Ideaya Biosciences; Kura Oncology; Leidos Biomedical Research, Inc.; PellePharm; Pfizer Inc.; PMV Pharma; Portola Pharmaceuticals; and Quanta Therapeutics. F.M. has received research grants from Daiichi Ltd and is a recipient of funded research from Gilead Sciences. F.M. is a consultant and cofounder for the following companies (with ownership interest, including stock options): BridgeBio; DNAtrix Inc.; Olema Pharmaceuticals, Inc.; and Quartz. F.M. is Scientific Director of the National Cancer Institute Ras Initiative at Frederick National Laboratory for Cancer Research/Leidos Biomedical Research, Inc.

Activation of RAF kinase involves the association of its RAS-binding domain (RBD) and cysteine-rich domain (CRD) with membrane-anchored RAS. However, the overall architecture of the RAS/RBD/CRD ternary complex and the orientations of its constituent domains at the membrane remain unclear. Here, we have combined all-atom and coarse-grained molecular dynamics (MD) simulations with experimental data to construct and validate a model of membrane-anchored CRD, and used this as a basis to explore models of membrane-anchored RAS/RBD/CRD complex. First, simulations of the CRD revealed that it anchors to the membrane via insertion of its two hydrophobic loops, which is consistent with our NMR measurements of CRD bound to nanodiscs. Simulations of the CRD in the context of membrane-anchored RAS/RBD then show how CRD association with either RAS or RBD could play an unexpected role in guiding the membrane orientations of RAS/RBD. This finding has implications for the formation of RAS-RAS dimers, as different membrane orientations of RAS expose distinct putative dimerization interfaces.

The development and progression of many human diseases often result in changes in gene expression and protein and metabolite concentrations. Changes at the protein and metabolite level often are detectable in biological fluids and tissues before the appearance of clinical symptoms, rendering them useful diagnostic and prognostic biomarkers. As with many conditions, the discovery of a sensitive and specific urinary biomarker for bladder cancer would save lives and reduce the suffering due to this condition. A number of potential urinary protein biomarkers for bladder cancer have been identified, but they lack the sensitivity and specificity required to replace cystoscopy and histopathology. We discuss the use of mass spectrometry and nuclear magnetic resonance spectroscopy for the detection of metabolites in biological samples, comment on their advantages and limitations, and discuss recently published work in urine metabolic profiling for bladder cancer detection.

Demand for the experimental antineoplastic agent schweinfurthin A, for developmental testing, prompted a re-collection of leaf material of Macaranga schweinfurthii from the original collection site in Cameroon. During chromatographic purification of the organic solvent extract, analytical UPLC-PDA-TOFMS of stilbene-enriched fractions revealed the presence of six known schweinfurthins and two previously unknown stilbenes. The structures of these new compounds, schweinfurthins I and J (1 and 2), were elucidated by 1D- and 2D-NMR techniques.

Metabolomics, the global profiling of metabolites in different living systems, has experienced a rekindling of interest partially due to the improved detection capabilities of the instrumental techniques currently being used in this area of biomedical research. The analytical methods of choice for the analysis of metabolites in search of disease biomarkers in biological specimens, and for the study of various low molecular weight metabolic pathways include NMR spectroscopy, GC/MS, CE/MS, and HPLC/MS. Global metabolite analysis and profiling of two different sets of data results in a plethora of data that is difficult to manage or interpret manually because of their subtle differences. Multivariate statistical methods and pattern-recognition programs were developed to handle the acquired data and to search for the discriminating features between data acquired from two sample sets, healthy and diseased. Metabolomics have been used in toxicology, plant physiology, and biomedical research. In this paper, we discuss various aspects of metabolomic research including sample collection, handling, storage, requirements for sample analysis, peak alignment, data interpretation using statistical approaches, metabolite identification, and finally recommendations for successful analysis.

Metabolic profiling using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) is integral to the rapidly expanding field of metabolomics, which is making progress in toxicology, plant science and various diseases, including cancer. In the area of oncology and metabolic phenotyping, researchers have probed the known changes in malignant cellular pathways using new experimental techniques to gain more insights, and others are exploiting these same cellular pathways for therapeutic drug targets and for novel cancer biomarkers, with the ultimate goal of translation to the clinic. Here, we discuss the challenges and opportunities in metabolic phenotyping for discovering novel cancer biomarkers, and we assess the clinical applicability of MS and NMR.

High-resolution, liquid state nuclear magnetic resonance (NMR) spectroscopy is a popular platform for metabolic profiling because the technique is nondestructive, quantitative, reproducible, and the spectra contain a wealth of biochemical information. Because of the large dynamic range of metabolite concentrations in biofluids, statistical analyses of one-dimensional (1D) proton NMR data tend to be biased toward selecting changes in more abundant metabolites. Although two-dimensional (2D) proton-proton experiments can alleviate spectral crowding, they have been mainly used for structural determination. In this study, 2D total correlation spectroscopy NMR was used to compare the global metabolic profiles of urine obtained from wild-type and Abcc6-knockout mice. The 2D data were compared to an improved 1D experiment in which signal contributions from macromolecules and the urea peak have been spectroscopically removed for more accurate quantitation of low-abundance metabolites. Although statistical models from both 1D and 2D data could differentiate samples acquired from the two groups of mice, only the 2D spectra allowed the characterization of statistically relevant changes in the low-abundance metabolites. While acquisition of the 2D data require more time, the data obtained resulted in a more meaningful and comprehensive metabolic profile, aided in metabolite identifications, and minimized ambiguities in peak assignments.

Two new chondropsin-type macrolide lactams, poecillastrins B (1) and C (2), were isolated from aqueous extracts of the marine sponge Poecillastra sp. These trace metabolites were isolated in low yield (400-600 microg), and their structures were determined primarily by analysis of NMR data acquired using a cyrogenically cooled probe. High-quality 1D and 2D NMR data sets allowed complete assignment of the spectroscopic data and defined the new structures as 35-membered ring analogues of poecillastrin A (3). Compounds 1 and 2 showed potent cytotoxic activity against a human melanoma tumor cell line (LOX) with an IC50 value of less than 1 microg/mL.

The biophysical properties of oligodeoxyribonucleotides (ODNs) selectively modified with conformationally 'locked' bicyclo[3.1.0]hexane pseudosugars (Maier,M.A., Choi,Y., Gaus,H., Barchi,J.J. Jr, Marquez,V.E., Manoharan,M. (2004) Synthesis and characterization of oligonucleotides containing conformationally constrained bicyclo[3.1.0]hexane pseudosugar analogs Nucleic Acids Res., 32, 3642-3650) have been studied by various techniques. Six separate synthetic ODNs based on the Dickerson Drew dodecamer sequence (CGCGAAT*T*CGCG) were examined where each one (or both) of the thymidines (T*) were substituted with a bicyclic pseudosugar locked in either a North (2'-exo) or South (3'-exo) ring pucker. Circular dichroism spectroscopy, differential scanning calorimetry and (1)H NMR spectroscopy were used to examine the duplex stability and conformational properties of the ODNs. Replacement of one or both thymidines with North-locked sugars (RNA-like) into the dodecamer did not greatly affect duplex formation or melt temperatures but distinct differences in thermodynamic parameters were observed. In contrast, incorporation of South-locked sugar derivatives that were predicted to stabilize this standard B-DNA, had the unexpected effect of causing a conformational equilibrium between different duplex forms at specific strand and salt concentrations. Our data and those of others suggest that although DNA can tolerate modifications with RNA-like (North) nucleotides, a more complicated spectrum of changes emerges with modifications restricted to South (DNA-like) puckers.

4'-C-ethynyl-2'-deoxynucleosides belong to a novel class of nucleoside analogues endowed with potent activity against a wide spectrum of HIV viruses, including a variety of resistant clones. Although favorable selectivity indices were reported for several of these analogues, some concern still exists regarding the 3'-OH group and its role in cellular toxicity. To address this problem, we removed the 3'-OH group from 4'-C-ethynyl-2'-deoxycytidine (1a). This compound was chosen because of its combined high potency and low selectivity index. The removal of the 3'-OH was not straightforward; it required a different synthetic approach from the one used to synthesize the parent compound. Starting with glycidyl-4-methoxyphenyl ether, the target 4'-C-ethynyl-2',3'-dideoxycytidine analogue (rac-1h) was obtained after 13 steps. In a cellular assay, rac-1h was completely inactive (0.001-10 microM) against HIV(LAI), demonstrating the critical importance of the 3'-OH for antiviral activity. To determine whether the role of the 3'-OH was essential for the phosphorylation of the compound by cellular kinases or for inhibition of DNA polymerization, we synthesized and tested the 5'-triphosphate (rac-1h-TP) for its ability to inhibit HIV reverse transcriptase (RT). rac-1h-TP was slightly more potent than AZT-5'-triphosphate against wild-type HIV RT, suggesting that the role of the 3'-OH is crucial only for the activation of the drug by cellular kinases. The lipase-catalyzed resolution of rac-1h into ent-1h (beta-D-dideoxyribo) and ent-14 (beta-L-dideoxyribo) and the synthesis of the corresponding 5'-triphosphates established the stereochemical assignment based on HIV RT's preference for the beta-D-enantiomer, which was confirmed by assaying against the M184V variant, an RT mutant with a marked preference for incorporating nucleosides in the D-configuration.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool capable of providing a comprehensive metabolic profile of biofluids such as urine, plasma, and serum. Unfortunately, when measuring serum and plasma, the high protein concentration can obscure the signals originating from low molecular weight metabolites. We evaluated the use of different parameters within the Carr-Purcell-Meiboom-Gill (CPMG) pulse train of fast spin-echoes to remove the macromolecular signal contribution in one-dimensional proton (1H) NMR spectra. Experimental parameters such as the refocusing delay in the CPMG pulse train, pulse miscalibration, and recycle time were examined to assess the ability to remove the protein signals from the spectrum without causing a deleterious effect on the signals originating from free, low molecular weight metabolites. The 1H-NMR spectra of a variety of serum samples spiked with 2'-deoxyadenosine were acquired using various acquisition parameters. Our results show that the delay used in the CPMG spin-echo and the combination of the acquisition pulse flip angle and recycle time are the two major factors affecting the observed metabolite signal amplitudes in the resulting 1H-NMR spectrum.

The advent of systems biology approaches that have stemmed from the sequencing of the human genome has led to the search for new methods to diagnose diseases. While much effort has been focused on the identification of disease-specific biomarkers, recent efforts are underway toward the use of proteomic and metabonomic patterns to indicate disease. We have developed and contrasted the use of both proteomic and metabonomic patterns in urine for the detection of interstitial cystitis (IC). The methodology relies on advanced bioinformatics to scrutinize information contained within mass spectrometry (MS) and high-resolution proton nuclear magnetic resonance (1H-NMR) spectral patterns to distinguish IC-affected from non-affected individuals as well as those suffering from bacterial cystitis (BC). We have applied a novel pattern recognition tool that employs an unsupervised system (self-organizing-type cluster mapping) as a fitness test for a supervised system (a genetic algorithm). With this approach, a training set comprised of mass spectra and 1H-NMR spectra from urine derived from either unaffected individuals or patients with IC is employed so that the most fit combination of relative, normalized intensity features defined at precise m/z or chemical shift values plotted in n-space can reliably distinguish the cohorts used in training. Using this bioinformatic approach, we were able to discriminate spectral patterns associated with IC-affected, BC-affected, and unaffected patients with a success rate of approximately 84%.

Poecillastrin A (1), a new polyketide-derived macrolide lactam, was isolated from a deep-water collection of the marine sponge Poecillastra species. The structure of poecillastrin A (1) was assigned using NMR data acquired at 500 MHz with an inverse-detection cryogenic probe and at 800 MHz with a room-temperature probe.

The chemical structures of six lipid A species (A, B, C, D-1, D-2, and E) purified from Rhizobium etli CE3 were investigated by one- and two-dimensional NMR spectroscopy. The R. etli lipid A subtypes each contain an unusual acyloxyacyl residue at position 2' as part of a conserved distal glucosamine moiety but differ in their proximal units. All R. etli lipid A species lack phosphate groups. However, they are derivatized with an alpha-linked galacturonic acid group at position 4', as shown by nuclear Overhauser effect spectroscopy. Component B, which had been not been reported in previous studies, features a beta, 1'-6 linked disaccharide of glucosamine acylated at positions 2, 3, 2', and 3' in a pattern that is typical of lipid A found in other Gram-negative bacteria. D-1 contains an acylated aminogluconate unit in place of the proximal glucosamine residue of B. C and E lack ester-linked beta-hydroxyacyl chains at position 3, as judged by their H-3 chemical shifts, and may be synthesized from B and D-1, respectively, by the R. etli 3-O-deacylase. D-2 is an isomer of D-1 that forms nonenzymatically by acyl chain migration. A may be an elimination product derived from D-1 during hydrolysis at 100 degrees C (pH 4.5), a step needed to release lipid A from lipopolysaccharide. Based on these findings, we propose a biosynthetic scheme for R. etli lipid A in which B is generated first by a variation of the E. coli pathway. The aminogluconate unit of D-1 could then be made from B by enzymatic oxidation of the proximal glucosamine. As predicted by our hypothesis, enzyme(s) can be demonstrated in extracts of R. etli that convert (14)C-labeled B to D-1.

Lipid A of Rhizobium etli CE3 differs dramatically from that of other Gram-negative bacteria. Key features include the presence of an unusual C28 acyl chain, a galacturonic acid moiety at position 4', and an acylated aminogluconate unit in place of the proximal glucosamine. In addition, R. etli lipid A is reported to lack phosphate and acyloxyacyl residues. Most of these remarkable structural claims are consistent with our recent enzymatic studies. However, the proposed R. etli lipid A structure is inconsistent with the ability of the precursor (3-deoxy-D-manno-octulosonic acid)(2)-4'-(32)P-lipid IV(A) to accept a C28 chain in vitro (Brozek, K. A., Carlson, R. W., and Raetz, C. R. H. (1996) J. Biol. Chem. 271, 32126-32136). To re-evaluate the structure, CE3 lipid A was isolated by new chromatographic procedures. CE3 lipid A is now resolved into six related components. Aminogluconate is present in D-1, D-2, and E, whereas B and C contain the typical glucosamine disaccharide seen in lipid A of most other bacteria. All the components possess a peculiar acyloxyacyl moiety at position 2', which includes the ester-linked C28 chain. As judged by mass spectrometry, the distal glucosamine units of A through E are the same, but the proximal units are variable. As described in the accompanying article (Que, N. L. S., Ribeiro, A. A., and Raetz, C. R. H. (2000) J. Biol. Chem. 275, 28017-28027), the discovery of component B suggests a plausible enzymatic pathway for the biosynthesis of the aminogluconate residue found in species D-1, D-2, and E of R. etli lipid A. We suggest that the unusual lipid A species of R. etli might be essential during symbiosis with leguminous host plants.

Lipid A from the nitrogen-fixing bacterium Rhizobium leguminosarum displays many structural differences compared with lipid A of Escherichia coli. R. leguminosarum lipid A lacks the usual 1- and 4'-phosphate groups but is derivatized with a galacturonic acid substituent at position 4'. R. leguminosarum lipid A often contains an aminogluconic acid moiety in place of the proximal glucosamine 1-phosphate unit. Striking differences also exist in the secondary acyl chains attached to E. coli versus R. leguminosarum lipid A, specifically the presence of 27-hydroxyoctacosanoate and the absence of laurate and myristate in R. leguminosarum. Recently, we have found that lipid A isolated by pH 4.5 hydrolysis of R. leguminosarum cells is more heterogeneous than previously reported (Que, N. L. S., Basu, S. S., White, K. A., and Raetz, C. R. H. (1998) FASEB J. 12, A1284 (abstr.)). Lipid A species lacking the 3-O-linked beta-hydroxymyristoyl residue on the proximal unit contribute to this heterogeneity. We now describe a membrane-bound deacylase from R. leguminosarum that removes a single ester-linked beta-hydroxymyristoyl moiety from some lipid A precursors, including lipid X, lipid IVA, and (3-deoxy-D-manno-octulosonic acid)2-lipid IVA. The enzyme does not cleave E. coli lipid A or lipid A precursors containing an acyloxyacyl moiety on the distal glucosamine unit. The enzyme is not present in extracts of E. coli or Rhizobium meliloti, but it is readily demonstrable in membranes of Pseudomonas aeruginosa, which also contains a significant proportion of 3-O-deacylated lipid A species. Optimal reaction rates are seen between pH 5.5 and 6.5. The enzyme requires a nonionic detergent and divalent metal ions for activity. It cleaves the monosaccharide lipid X at about 5% the rate of lipid IVA and (3-deoxy-D-manno-octulosonic acid)2-lipid IVA. 1H NMR spectroscopy of the deacylase reaction product, generated with lipid IVA as the substrate, confirms unequivocally that the enzyme cleaves only the ester-linked beta-hydroxymyristoyl residue at the 3-position of the glucosamine disaccharide.

The lpxK gene has been proposed to encode the lipid A 4'-kinase in Escherichia coli (Garrett, T. A., Kadrmas, J. L., and Raetz, C. R. H. (1997) J. Biol. Chem. 272, 21855-21864). In cell extracts, the kinase phosphorylates the 4'-position of a tetraacyldisaccharide 1-phosphate precursor (DS-1-P) of lipid A, but the enzyme has not yet been purified because of instability. lpxK is co-transcribed with an essential upstream gene, msbA, with strong homology to mammalian Mdr proteins and ABC transporters. msbA may be involved in the transport of newly made lipid A from the inner surface of the inner membrane to the outer membrane. Insertion of an Omega-chloramphenicol cassette into msbA also halts transcription of lpxK. We have now constructed a strain in which only the lpxK gene is inactivated by inserting a kanamycin cassette into the chromosomal copy of lpxK. This mutation is complemented at 30 degreesC by a hybrid plasmid with a temperature-sensitive origin of replication carrying lpxK+. When this strain (designated TG1/pTAG1) is grown at 44 degreesC, the plasmid bearing the lpxK+ is lost, and the phenotype of an lpxK knock-out mutation is unmasked. The growth of TG1/pTAG1 was inhibited after several hours at 44 degreesC, consistent with lpxK being an essential gene. Furthermore, 4'-kinase activity in extracts made from these cells was barely detectable. In accordance with the proposed biosynthetic pathway for lipid A, DS-1-P (the 4'-kinase substrate) accumulated in TG1/pTAG1 cells grown at 44 degreesC. The DS-1-P from TG1/pTAG1 was isolated, and its structure was verified by 1H NMR spectroscopy. DS-1-P had not been isolated previously from bacterial cells. Its accumulation in TG1/pTAG1 provides additional support for the pathway of lipid A biosynthesis in E. coli. Homologs of lpxK are present in the genomes of other Gram-negative bacteria.

The 3,6-dideoxyhexoses can be found in the cell wall lipopolysaccharide of Gram-negative bacteria, where they have been shown to be the dominant antigenic determinants. All naturally occurring 3,6-dideoxyhexoses, with colitose as the only exception, are biosynthesized via a complex pathway that begins with CDP-d-glucose. Included in this pathway is CDP-paratose synthase, an essential enzyme in the formation of the 3,6-dideoxy sugars, CDP-paratose and CDP-tyvelose. Recently, the gene encoding CDP-paratose synthase in Salmonella typhi, rfbS, has been identified and sequenced [Verma, N., and Reeves, P. (1989) J. Bacteriol. 171, 5694-5701]. On the basis of this information, we have amplified the rfbS gene by polymerase chain reaction (PCR) from S. typhi and cloned this gene into a pET-24(+) vector. Expression and purification of CDP-paratose synthase have allowed us to fully characterize the catalytic properties of this enzyme, which is a homodimeric protein with a preference for NADPH over NADH. It catalyzes the stereospecific hydride transfer of the pro-S hydrogen from the C-4' position of the reduced coenzyme to C-4 of the substrate, CDP-3,6-dideoxy-D-glycero-D-glycero-4-hexulose. The overall equilibrium of this catalysis greatly favors the formation of the reduced sugar product and the oxidized coenzyme. Interestingly, this enzyme also exhibits a high affinity for NADPH with a much smaller dissociation constant (Kia) of 0.005 +/- 0.002 microM compared to the Km of 26 +/- 8 microM for NADPH. While this unusual property complicated the interpretation of the kinetic data, the kinetic mechanism of CDP-paratose synthase as explored by the combination of bisubstrate kinetic analysis, product inhibition studies, and dead-end competitive inhibition studies is most consistent with a Theorell-Chance mechanism. The present study on CDP-paratose synthase, a likely new member of the short-chain dehydrogenase family, represents the first detailed characterization of this type of ketohexose reductase, many of which may share similar properties with CDP-paratose synthase.

The effect of maleate on the Na+-dependent transport of glucose, phenylalanine and phosphate in the renal brush border membranes (BBM) was studied. It was found that maleate as such had no effect on the isolated BBM vesicles. In BBM isolated from kidney cortex slices which were incubated with maleate, as well as in BBM isolated from the kidneys of maleate-treated rats, an inhibition of the Na+-dependent glucose and phenylalanine transport was observed, whereas the Na+-dependent phosphate transport was stimulated. In kidney slices these effects were prevented by the simultaneous addition of acetoacetate to the incubation medium. The permeability to Na+ ions was increased in the brush border membranes isolated from maleate-treated renal tissue. Cyclic AMP level was decreased nearly by half in the kidneys of maleate-treated rats. It is concluded that the formation of maleyl-CoA, which is prevented by acetoacetate, is a prerequisite for the effects of maleate on the BBM. The data suggest that the inhibition of Na+-dependent glucose and phenylalanine transport results from the uncoupling of Na+ and solute transport, due to increased permeability of the BBM to Na+. The stimulation of the phosphate transport system results probably from a decrease of cell cyclic AMP level. It is suggested that the uncoupling of Na+ and solute transport in the BBM is responsible for the generalized impairment by maleate of solute reabsorption in the renal proximal tubules.