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Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

IntroductionBreast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes.MethodsHere, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects.ResultsWe identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity.DiscussionOur findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.

A multi-phased study was conducted in Cambodia from 2005-2011 to measure the impact of larviciding with the bacterial larvicide, Bacillus thuringiensis israelensis (Bti), a water dispersible granule (WG) formulation on the vector, Aedes aegypti (L.) and the epidemiology. In our studies, all in-use containers were treated at 8 g/1000 L, including smaller containers and animal feeders which were found to contribute 23% of Ae aegypti pupae. The treated waters were subjected to routine water exchange activities. Pupal production was suppressed by an average 91% for 8 weeks. Pupal numbers continued to remain significantly lower than the untreated commune (UTC) for 13 weeks post treatment in the peak dengue vector season (p50% of the household in the UTC harbored ≥11 mosquitoes per home. The adult population continued to remain at significantly much lower numbers in the Bti treated commune than in the UTC for 10-12 weeks post treatment (p

Malignant pleural mesothelioma (MPM) is an almost invariably fatal, asbestos-related malignancy arising from the mesothelial membrane lining the thoracic cavities. Despite some improvements in treatment, therapy is not considered curative and median survival following diagnosis is less than 1 year. Although still classed as a rare cancer, the incidence of MPM is increasing, and the limited progress in treating the disease makes the identification of new therapies a priority. As there is evidence for expression of the integrins αvβ3 and αvβ5 in MPM, there is a rationale for investigating the effects on MPM of cilengitide, a synthetic peptide inhibitor of integrin αv heterodimer with high specificity for αvβ3 and αvβ5. In mesothelial cells (MC) and 7 MPM cell lines, growth inhibition by cilengitide was associated with the expression level of its target integrins. Furthermore, cilengitide caused cell detachment and subsequent death of anoikis-sensitive cells. It also suppressed invasion of MPM cells in monolayer and three-dimensional cultures. Gene knockdown experiments indicated that these effects of cilengitide were, at least partly, due to antagonism of αvβ3 and αvβ5.

Abstract Background The average annual reported dengue incidence in Cambodia is 3.3/1,000 among children < 15 years of age (2002–2007). To estimate the economic burden of dengue, accurate cost-of-illness data are essential. We conducted a prospective, community-based, matched case-control study to assess the cost and impact of an episode of dengue fever and other febrile illness on households in rural Cambodia. Methods In 2006, active fever surveillance was conducted among a cohort of 6,694 children aged ≤ 15 years in 16 villages in Kampong Cham province, Cambodia. Subsequently, a case-control study was performed by individually assigning one non-dengue febrile control from the cohort to each laboratory-confirmed dengue case. Parents of cases and controls were interviewed using a standardized questionnaire to determine household-level, illness-related expenditures for medical and non-medical costs, and estimated income loss (see Additional file 1). The household socio-economic status was determined and its possible association with health seeking behaviour and the ability to pay for the costs of a febrile illness. Additional File 1 2006 cost study survey questionnaire, Cambodia. the questionnaire represents the data collection instrument that was developed and used during the present study. Click here for file Results Between September and November 2006, a total of 60 household heads were interviewed: 30 with dengue-positive and 30 with dengue-negative febrile children. Mean total dengue-related costs did not differ from those of other febrile illnesses (31.5 vs. 27.2 US$, p = 0.44). Hospitalization almost tripled the costs of dengue (from 14.3 to 40.1 US$) and doubled the costs of other febrile illnesses (from 17.0 to 36.2 US$). To finance the cost of a febrile illness, 67% of households incurred an average debt of 23.5 US$ and higher debt was associated with hospitalization compared to outpatient treatment (US$ 23.1 vs. US$ 4.5, p < 0.001). These costs compared to an average one-week expenditure on food of US$ 9.5 per household (range 2.5–21.3). In multivariate analysis, higher socio-economic status (odds ratio [OR] 4.4; 95% confidence interval [CI] 1.4–13.2), duration of fever (OR 2.1; 95%CI 1.3–3.5), and age (OR 0.8; 95%CI 0.7–0.9) were independently associated with hospitalization. Conclusion In Cambodia, dengue and other febrile illnesses pose a financial burden to households. A possible reason for a lower rate of hospitalization among children from poor households could be the burden of higher illness-related costs and debts.

Purpose: To devise a mathematical model for estimating the intraoperative lowest instrumented vertebra (LIV) tilt angle using preoperative supine left side-bending (LSB) radiographs in adolescent idiopathic scoliosis (AIS) patients with Lenke type 1 and 2 (non-AR curves), and to review its clinical and radiological outcomes., Methods: The mathematical model for the adjusted LSB LIV tilt angle (α) measured preoperatively, was expressed as the sum of preoperative LSB LIV tilt angle (x) and LIV displacement angle (y) (α = x + y). This model was validated through inter-rater and intra-rater analysis in Part I of the study. The α angle derived was applied to estimate the intraoperative LIV tilt angle. In part II of the study, clinical and radiological outcomes of 50 Lenke type 1 and 2 (non-AR curves) AIS patients operated using the α angle were reviewed. The difference between the intraoperative LIV tilt angle achieved (β) and the preoperative α angle was determined (∆LIV tilt angle = β-α)., Results: The α angle had excellent inter-rater and intra-rater intraclass correlation coefficients (0.982; 0.907). 42 patients had positive ∆LIV tilt angles whereas 8 patients had negative ∆LIV tilt angles. The overall incidence of distal adding-on (AO) was 10.0% (n = 5/50). Patients with negative ∆LIV tilt angles had a higher incidence of distal AO (n = 4/8, 50.0%) than patients with positive ∆LIV tilt angles (n = 1/42, 2.4%) (p = 0.001)., Conclusion: Achieving an intraoperative LIV tilt angle (β) greater than or equal to the preoperative α angle derived (β ≥ α) may help avoid the distal AO phenomenon., Competing Interests: Conflict of interest: The authors have no relevant financial or non-financial interests to disclose., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: The clinical implication of intrarenal venous flow patterns in decompensated heart failure with worsening renal function is unknown. We aimed to study the relationship between intrarenal venous flow patterns, inferior vena cava volume status, caval index, clinical degree of congestion and the renal outcome in patients with decompensated heart failure and worsening renal function. Secondary objectives were to study the combined endpoint of readmission and mortality rate within 30 days (after the last scan) among intrarenal venous flow patterns and the effect of congestion status on the renal outcome., Methods: Twenty-three patients admitted for decompensated heart failure (ejection fraction ⩽40%) with worsening renal function (absolute increase in serum creatinine of 26.5 µmol/L or ⩾1.5-fold increment from baseline) were enrolled in this study. A total of 64 scans were performed. Patients were visited on day 0, 2, 4 and 7 (or earlier if discharged). Patients were called 30 days after discharge to evaluate readmission or mortality. Intrarenal venous flow patterns were ranked from continuous, interrupted, biphasic, to monophasic. Clinical congestion was scored from 0 to 7., Results: Intrarenal venous flow patterns had statistically significant positive correlations with inferior vena cava volume status (Spearman's ρ, 0.51; p  < 0.01) and congestion score ( ρ , 0.65; p  < 0.01) and a significant negative correlation with caval index ( ρ , -0.53; p  < 0.01). Intrarenal venous flow patterns were not significant in predicting estimated glomerular filtration rate improvement or the combined endpoint. Reduced congestion significantly predicted an estimated glomerular filtration rate improvement on the following scan day ( p  = 0.04, odds ratio = 4.3, 95% confidence interval = 1.1-17.2)., Conclusion: Although intrarenal venous flow patterns correlate with other congestive parameters, clinical congestion status rather than intrarenal venous flow patterns predicted the renal outcome., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article., (© The Author(s) 2022.)

Purpose: There was limited study available on successful intervention for central-line-associated bloodstream infection (CLABSI) done at nonintensive care unit (ICU) and resources-limited setting. The objective of this study was to design, implement and evaluate a strategy to reduce CLABSI rate in non-ICU settings at general medical wards of Hospital Tuanku Ja'afar Seremban., Design/methodology/approach: Preinterventional study was conducted in one-month period of January 2019, followed by intervention period from February to March 2019. Postintervention study was conducted from April to July 2019. The CLABSI rates were compared between pre and postintervention periods. A multifaceted intervention bundle was implemented, which comprised (1) educational program for healthcare workers, (2) weekly audit and feedback and (3) implementation of central line bundle of care., Findings: There was a significant overall reduction of CLABSI rate between preintervention and postintervention period [incidence rate ratio (IRR) of 0.06 (95 percent CI, 0.01-0.33; P  = 0.001)]., Practical Implications: CLABSI rates were reduced by a multifaceted intervention bundle, even in non-ICU and resource-limited setting. This includes a preinterventional study to identify the risk factors followed by a local adaption of the recommended care bundles. This study recommends resources-limited hospitals to design a strategy that is suitable for their own local setting to reduce CLABSI., Originality/value: This study demonstrated the feasibility of a multifaceted intervention bundle that was locally adapted with an evidence-based approach to reduce CLABSI rate in non-ICU and resource-limited setting., (© Emerald Publishing Limited.)

Peptide-mediated interactions, in which a short linear motif binds to a globular domain, play major roles in cellular regulation. An accurate structural model of this type of interaction is an excellent starting point for the characterization of the binding specificity of a given peptide-binding domain. A number of different protocols have recently been proposed for the accurate modeling of peptide-protein complex structures, given the structure of the protein receptor and the binding site on its surface. When no information about the peptide binding site(s) is a priori available, there is a need for new approaches to locate peptide-binding sites on the protein surface. While several approaches have been proposed for the general identification of ligand binding sites, peptides show very specific binding characteristics, and therefore, there is a need for robust and accurate approaches that are optimized for the prediction of peptide-binding sites. Here, we present PeptiMap, a protocol for the accurate mapping of peptide binding sites on protein structures. Our method is based on experimental evidence that peptide-binding sites also bind small organic molecules of various shapes and polarity. Using an adaptation of ab initio ligand binding site prediction based on fragment mapping (FTmap), we optimize a protocol that specifically takes into account peptide binding site characteristics. In a high-quality curated set of peptide-protein complex structures PeptiMap identifies for most the accurate site of peptide binding among the top ranked predictions. We anticipate that this protocol will significantly increase the number of accurate structural models of peptide-mediated interactions., (Copyright © 2013 Wiley Periodicals, Inc.)

Formaldehyde has long been recognized as a hazardous environmental agent highly reactive with DNA. Recently, it has been realized that due to the activity of histone demethylation enzymes within the cell nucleus, formaldehyde is produced endogenously, in direct vicinity of genomic DNA. Should it lead to extensive DNA damage? We address this question with the aid of a computational mapping method, analogous to X-ray and nuclear magnetic resonance techniques for observing weakly specific interactions of small organic compounds with a macromolecule in order to establish important functional sites. We concentrate on the leading reaction of formaldehyde with free bases: hydroxymethylation of cytosine amino groups. Our results show that in B-DNA, cytosine amino groups are totally inaccessible for the formaldehyde attack. Then, we explore the effect of recently discovered transient flipping of Watson-Crick (WC) pairs into Hoogsteen (HG) pairs (HG breathing). Our results show that the HG base pair formation dramatically affects the accessibility for formaldehyde of cytosine amino nitrogens within WC base pairs adjacent to HG base pairs. The extensive literature on DNA interaction with formaldehyde is analyzed in light of the new findings. The obtained data emphasize the significance of DNA HG breathing.

Binding hot spots, protein sites with high-binding affinity, can be identified using X-ray crystallography or NMR by screening libraries of small organic molecules that tend to cluster at such regions. FTMAP, a direct computational analog of the experimental screening approaches, globally samples the surface of a target protein using small organic molecules as probes, finds favorable positions, clusters the conformations and ranks the clusters on the basis of the average energy. The regions that bind several probe clusters predict the binding hot spots, in good agreement with experimental results. Small molecules discovered by fragment-based approaches to drug design also bind at the hot spot regions. To identify such molecules and their most likely bound positions, we extend the functionality of FTMAP (http://ftmap.bu.edu/param) to accept any small molecule as an additional probe. In its updated form, FTMAP identifies the hot spots based on a standard set of probes, and for each additional probe shows representative structures of nearby low energy clusters. This approach helps to predict bound poses of the user-selected molecules, detects if a compound is not likely to bind in the hot spot region, and provides input for the design of larger ligands.

Fragment-based drug design (FBDD) starts with finding fragment-sized compounds that are highly ligand efficient and can serve as a core moiety for developing high-affinity leads. Although the core-bound structure of a protein facilitates the construction of leads, effective design is far from straightforward. We show that protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements the fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. The method places small molecular probes, the size of organic solvents, on a dense grid around the protein and identifies the hot spots as consensus clusters formed by clusters of several probes. The hot spots are ranked based on the number of probe clusters, which predicts the binding propensity of the subsites and hence their importance for drug design. Accordingly, with a single exception the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency.

Motivation: Binding site identification is a classical problem that is important for a range of applications, including the structure-based prediction of function, the elucidation of functional relationships among proteins, protein engineering and drug design. We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods., Availability: FTSite is freely available as a web-based server at http://ftsite.bu.edu.

Binding hot spots, protein regions with high binding affinity, can be identified by using X-ray crystallography or NMR spectroscopy to screen libraries of small organic molecules that tend to cluster at such hot spots. FTMap, a direct computational analogue of the experimental screening approaches, uses 16 different probe molecules for global sampling of the surface of a target protein on a dense grid and evaluates the energy of interaction using an empirical energy function that includes a continuum electrostatic term. Energy evaluation is based on the fast Fourier transform correlation approach, which allows for the sampling of billions of probe positions. The grid sampling is followed by off-grid minimization that uses a more detailed energy expression with a continuum electrostatics term. FTMap identifies the hot spots as consensus clusters formed by overlapping clusters of several probes. The hot spots are ranked on the basis of the number of probe clusters, which predicts their binding propensity. We applied FTMap to nine structures of hen egg-white lysozyme (HEWL), whose hot spots have been extensively studied by both experimental and computational methods. FTMap found the primary hot spot in site C of all nine structures, in spite of conformational differences. In addition, secondary hot spots in sites B and D that are known to be important for the binding of polysaccharide substrates were found. The predicted probe-protein interactions agree well with those seen in the complexes of HEWL with various ligands and also agree with an NMR-based study of HEWL in aqueous solutions of eight organic solvents. We argue that FTMap provides more complete information on the HEWL binding site than previous computational methods and yields fewer false-positive binding locations than the X-ray structures of HEWL from crystals soaked in organic solvents., (© 2011 American Chemical Society)

The aim of this article is to analyze conformational changes by comparing 10 different structures of Pseudomonas aeruginosa phosphomannomutase/phosphoglucomutase (PMM/PGM), a four-domain enzyme in which both substrate binding and catalysis require substantial movement of the C-terminal domain. We focus on changes in interdomain and active site crevices using a method called computational solvent mapping rather than superimposing the structures. The method places molecular probes (i.e., small organic molecules containing various functional groups) around the protein to find hot spots. One of the most important hot spots is in the active site, consistent with the ability of the enzyme to bind both glucose and mannose phosphosugar substrates. The protein has eight additional hot spots at domain-domain interfaces and hinge regions. The locations and nature of six of these hot spots vary between the open, half-open, and closed conformers of the enzyme, in good agreement with the ligand-induced conformational changes. In the closed structures the number of probe clusters at the hinge region significantly depends on the position of the phosphorylated oxygen in the substrate (e.g., glucose 1-phosphate versus glucose 6-phosphate), but the protein remains almost unchanged in terms of the overall RMSD, indicating that computational solvent mapping is a more sensitive approach to detect changes in binding sites and interdomain crevices. Focusing on multidomain proteins we show that the subresolution conformational differences revealed by the mapping are in fact significant, and present a general statistical method of analysis to determine the significance of rigid body domain movements in X-ray structures., (Copyright © 2010 The Protein Society.)

The steroid and xenobiotic-responsive human pregnane X receptor (PXR) binds a broad range of structurally diverse compounds. The structures of the apo and ligand-bound forms of PXR are very similar, in contrast to most promiscuous proteins that generally adapt their shape to different ligands. We investigated the structural origins of PXR's recognition promiscuity using computational solvent mapping, a technique developed for the identification and characterization of hot spots, i.e., regions of the protein surface that are major contributors to the binding free energy. Results reveal that the smooth and nearly spherical binding site of PXR has a well-defined hot spot structure, with four hot spots located on four different sides of the pocket and a fifth close to its center. Three of these hot spots are already present in the ligand-free protein. The most important hot spot is defined by three structurally and sequentially conserved residues, W299, F288, and Y306. This largely hydrophobic site is not very specific and interacts with all known PXR ligands. Depending on their sizes and shapes, individual PXR ligands extend into two, three, or four more hot spot regions. The large number of potential arrangements within the binding site explains why PXR is able to accommodate a large variety of compounds. All five hot spots include at least one important residue, which is conserved in all mammalian PXRs, suggesting that the hot spot locations have remained largely invariant during mammalian evolution. The same side chains also show a high level of structural conservation across hPXR structures. However, each of the hPXR hot spots also includes residues with moveable side chains, further increasing the size variation in ligands that PXR can bind. Results also suggest a unique signal transduction mechanism between the PXR homodimerization interface and its coactivator binding site.

The influenza virus subtype H5N1 has raised concerns of a possible human pandemic threat because of its high virulence and mutation rate. Although several approved anti-influenza drugs effectively target the neuraminidase, some strains have already acquired resistance to the currently available anti-influenza drugs. In this study, we present the synergistic application of extended explicit solvent molecular dynamics (MD) and computational solvent mapping (CS-Map) to identify putative 'hot spots' within flexible binding regions of N1 neuraminidase. Using representative conformations of the N1 binding region extracted from a clustering analysis of four concatenated 40-ns MD simulations, CS-Map was utilized to assess the ability of small, solvent-sized molecules to bind within close proximity to the sialic acid binding region. Mapping analyses of the dominant MD conformations reveal the presence of additional hot spot regions in the 150- and 430-loop regions. Our hot spot analysis provides further support for the feasibility of developing high-affinity inhibitors capable of binding these regions, which appear to be unique to the N1 strain.