Roughness of Molecular Property Landscapes and Its Impact on Modellability.

In molecular discovery and drug design, structure-property relationships and activity landscapes are often qualitatively or quantitatively analyzed to guide the navigation of chemical space. The roughness (or smoothness) of these molecular property landscapes is one of their most studied geometric attributes, as it can characterize the presence of activity cliffs, with rougher landscapes generally expected to pose tougher optimization challenges. Here, we introduce a general, quantitative measure for describing the roughness of molecular property landscapes. The proposed roughness index (ROGI) is loosely inspired by the concept of fractal dimension and strongly correlates with the out-of-sample error achieved by machine learning models on numerous regression tasks.

Self-Focusing Virtual Screening with Active Design Space Pruning.

High-throughput virtual screening is an indispensable technique utilized in the discovery of small molecules. In cases where the library of molecules is exceedingly large, the cost of an exhaustive virtual screen may be prohibitive. Model-guided optimization has been employed to lower these costs through dramatic increases in sample efficiency compared to random selection. However, these techniques introduce new costs to the workflow through the surrogate model training and inference steps. In this study, we propose an extension to the framework of model-guided optimization that mitigates inference costs using a technique we refer to as design space pruning (DSP), which irreversibly removes poor-performing candidates from consideration. We study the application of DSP to a variety of optimization tasks and observe significant reductions in overhead costs while exhibiting similar performance to the baseline optimization. DSP represents an attractive extension of model-guided optimization that can limit overhead costs in optimization settings where these costs are non-negligible relative to objective costs, such as docking.

K-mer clustering algorithm using a MapReduce framework: application to the parallelization of the Inchworm module of Trinity.

BACKGROUND: De novo transcriptome assembly is an important technique for understanding gene expression in non-model organisms. Many de novo assemblers using the de Bruijn graph of a set of the RNA sequences rely on in-memory representation of this graph. However, current methods analyse the complete set of read-derived k-mer sequence at once, resulting in the need for computer hardware with large shared memory. RESULTS: We introduce a novel approach that clusters k-mers as the first step. The clusters correspond to small sets of gene products, which can be processed quickly to give candidate transcripts. We implement the clustering step using the MapReduce approach for parallelising the analysis of large datasets, which enables the use of compute clusters. The computational task is distributed across the compute system using the industry-standard MPI protocol, and no specialised hardware is required. Using this approach, we have re-implemented the Inchworm module from the widely used Trinity pipeline, and tested the method in the context of the full Trinity pipeline. Validation tests on a range of real datasets show large reductions in the runtime and per-node memory requirements, when making use of a compute cluster. CONCLUSIONS: Our study shows that MapReduce-based clustering has great potential for distributing challenging sequencing problems, without loss of accuracy. Although we have focussed on the Trinity package, we propose that such clustering is a useful initial step for other assembly pipelines.

Topological "Shape" in Micellar Dynamics.

For micelles, "shape" is prominent in rheological computations of fluid flow, but this "shape" is often expressed too informally to be useful for rigorous analyses. We formalize topological "shape equivalence" of micelles, both globally and locally, to enable visualization of computational fluid dynamics. Although topological methods in visualization provide significant insights into fluid flows, this opportunity has been limited by the known difficulties in creating representative geometry. We present an agile geometric algorithm to represent the micellar shape for input into fluid flow visualizations. We show that worm-like and cylindrical micelles have formally equivalent shapes, but that visualization accentuates unexplored differences. This global-local paradigm is extensible beyond micelles.

Clinical and radiological septic joint analysis of spontaneous sternoclavicular joint infections: achieving the best outcomes-a systems engineering approach.

OBJECTIVES: Spontaneous sternoclavicular joint infection (SSCJI) is a rare and poorly understood disease process. This study aims to identify factors guiding effective management strategies for SSCJI by using data mining. METHODS: An Institutional Review Board-approved retrospective review of patients from 2 large hospitals (2010-2022) was conducted. SSCJI is defined as a joint infection without direct trauma or radiation, direct instrumentation or contiguous spread. An interdisciplinary team consisting of thoracic surgeons, radiologists, infectious disease specialists, orthopaedic surgeons, hospital information experts and systems engineers selected relevant variables. Small set data mining algorithms, utilizing systems engineering, were employed to assess the impact of variables on patient outcomes. RESULTS: A total of 73 variables were chosen and 54 analysed against 11 different outcomes. Forty-seven patients [mean age 51 (22-82); 77% male] met criteria. Among them, 34 underwent early joint surgical resection (<14 days), 5 patients received delayed surgical intervention (>14 days) and 8 had antibiotic-only management. The antibiotic-only group had comparable outcomes. Indicators of poor outcomes were soft tissue fluid >4.5 cm, previous SSCJI, moderate/significant bony fragments, HgbA1c >13.9% and moderate/significant bony sclerosis. CONCLUSIONS: This study suggests that targeted antibiotic-only therapy should be considered initially for SSCJI cases while concurrently managing comorbidities. Patients displaying indicators of poor outcomes or no symptomatic improvement after antibiotic-only therapy should be considered for surgical joint resection.

A computational model for overcoming drug resistance using selective dual-inhibitors for aurora kinase A and its T217D variant.

The human Aurora kinase-A (AK-A) is an essential mitotic regulator that is frequently overexpressed in several cancers. The recent development of several novel AK-A inhibitors has been driven by the well-established association of this target with cancer development and progression. However, resistance and cross-reactivity with similar kinases demands an improvement in our understanding of key molecular interactions between the Aurora kinase-A substrate binding pocket and potential inhibitors. Here, we describe the implementation of state-of-the-art virtual screening techniques to discover a novel set of Aurora kinase-A ligands that are predicted to strongly bind not only to the wild type protein, but also to the T217D mutation that exhibits resistance to existing inhibitors. Furthermore, a subset of these computationally screened ligands was shown to be more selective toward the mutant variant over the wild type protein. The description of these selective subsets of ligands provides a unique pharmacological tool for the design of new drug regimens aimed at overcoming both kinase cross-reactivity and drug resistance associated with the Aurora kinase-A T217D mutation.

"Mega" Cisterna Chyli: A Case Report and Review of the Literature.

Enlarged cisterna chyli is an infrequently encountered entity and is most often an asymptomatic, incidental finding on imaging for other reasons. The pathogenesis of cisterna chyli enlargement is not well elucidated and includes infectious, inflammatory, and idiopathic causes. In this report, we present the rare case of an asymptomatic, markedly dilated "mega" cisterna chyli in a 60-year-old female.

Efficient Algorithm for the Topological Characterization of Worm-like and Branched Micelle Structures from Simulations.

Many surfactant-based formulations are utilized in industry as they produce desirable viscoelastic properties at low concentrations. These properties are due to the presence of worm-like micelles (WLMs), and as a result, understanding the processes that lead to WLM formation is of significant interest. Various experimental techniques have been applied with some success to this problem but can encounter issues probing key microscopic characteristics or the specific regimes of interest. The complementary use of computer simulations could provide an alternate route to accessing their structural and dynamic behavior. However, few computational methods exist for measuring key characteristics of WLMs formed in particle simulations. Further, their mathematical formulations are challenged by WLMs with sharp curvature profiles or density fluctuations along the backbone. Here, we present a new topological algorithm for identifying and characterizing WLMs in particle simulations, which has desirable mathematical properties that address shortcomings in previous techniques. We apply the algorithm to the case of sodium dodecyl sulfate micelles to demonstrate how it can be used to construct a comprehensive topological characterization of the observed structures.

Imaging infection.

Diagnostic imaging of the thorax is routinely used among both immunocompetent and immunosuppressed patients to detect infection, identify its complications, and aid in differentiating infectious from noninfectious intrathoracic disease. Imaging is more effective in suggesting specific types of infection in immunocompromised hosts where imaging findings can be combined with information on the patient's immune status, which in some cases allows treatment to be initiated without a pathologic diagnosis. CT imaging is particularly useful in immunosuppressed hosts with symptoms and minimally abnormal radiographs, such as those patients afflicted with bacterial airway infections.

Pulmonary vasculitis: diagnosis and endovascular therapy.

Pulmonary vasculitides are caused by a heterogeneous group of diseases with different clinical features and etiologies. Radiologic manifestations depend on the predominant type of vessel involved, which are grouped into large, medium, or small-sized vessels. Diagnosing pulmonary vasculitides is a challenging task, and radiologists play an important role in their management by providing supportive evidence for diagnosis and opportunities for minimally invasive therapy. This paper aims to present a practical approach for understanding the vasculitides that can affect the pulmonary vessels and lungs. We will describe and illustrate the main radiologic findings, discussing opportunities for minimally invasive treatment.

Cross-sectional imaging of sinus of Valsalva aneurysms: lessons learned.

Sinus of Valsalva aneurysm, dilatation of one or more of the aortic sinuses, is a rare but important aortic root defect, which can be a cause of some serious cardiac sequels. The purpose of this article is to review the etiopathogenesis, relevant anatomy, clinical manifestations, potential complications, multimodality imaging features, and management of this rare but important entity of sinus of Valsalva.

Toward a Standard Protocol for Micelle Simulation.

In this paper, we present protocols for simulating micelles using dissipative particle dynamics (and in principle molecular dynamics) that we expect to be appropriate for computing micelle properties for a wide range of surfactant molecules. The protocols address challenges in equilibrating and sampling, specifically when kinetics can be very different with changes in surfactant concentration, and with minor changes in molecular size and structure, even using the same force field parameters. We demonstrate that detection of equilibrium can be automated and is robust, for the molecules in this study and others we have considered. In order to quantify the degree of sampling obtained during simulations, metrics to assess the degree of molecular exchange among micellar material are presented, and the use of correlation times are prescribed to assess sampling and for statistical uncertainty estimates on the relevant simulation observables. We show that the computational challenges facing the measurement of the critical micelle concentration (CMC) are somewhat different for high and low CMC materials. While a specific choice is not recommended here, we demonstrate that various methods give values that are consistent in terms of trends, even if not numerically equivalent.

Imaging infection.

Thoracic imaging is widely used to detect lower respiratory tract infections, identify their complications, and aid in differentiating infectious from noninfectious thoracic disease. Less commonly, the combination of imaging findings and a clinical setting can favor infection with a specific organism. This confluence can occur in cases of bronchiectatic nontuberculous mycobacterial infections in immune-competent hosts, invasive fungal disease among neutropenic patients, Pneumocystis jiroveci pneumonia in patients with AIDS, and in cytomegalovirus infections in patients with recent hematopoietic cell transplantation. These specific diagnoses often depend on computed tomography scanning rather than chest radiography alone.

Quantification of regional interstitial lung disease from CT-derived fractional tissue volume: a lung tissue research consortium study.

RATIONALE AND OBJECTIVES: Evaluation of chest computed tomography (CT) is usually qualitative or semiquantitative, resulting in subjective descriptions often by different observers over time and imprecise determinations of disease severity within distorted lobes. There is a need for standardized imaging biomarkers to quantify regional disease, maximize diagnostic yield, and facilitate multicenter comparisons. We applied lobe-based voxelwise image analysis to derive regional air (Vair) and tissue (Vtissue) volumes and fractional tissue volume (FTV = tissue/[tissue+air] volume) as internally standardized parameter for assessing interstitial lung disease (ILD). MATERIALS AND METHODS: High-resolution CT was obtained at supine and prone end-inspiration and supine end-expiration in 29 patients with ILD and 20 normal subjects. Lobar Vair, Vtissue, and FTV were expressed along standard coordinate axes. RESULTS: In normal subjects from end-inspiration to end-expiration, total Vair declined ~43%, FTV increased ~80%, but Vtissue remained unchanged. With increasing ILD, Vair declined and Vtissue rose in all lobes; FTV increased with a peripheral-to-central progression inversely correlated to spirometry and lung diffusing capacity (r(2) = 0.57-0.75, prone end-inspiration). Inter- and intralobar coefficients of variation of FTV increased 84-148% in mild-to-moderate ILD, indicating greater spatial heterogeneity, then normalized in severe ILD. Analysis of discontinuous images incurs <3% error compared to consecutive images. CONCLUSIONS: These regional attenuation-based biomarkers could quantify heterogeneous parenchymal disease in distorted lobes, detect mild ILD involvement in all lobes and describe the pattern of disease progression. The next step would be to study a larger series, examine reproducibility and follow longitudinal changes in correlation with clinical and functional indices.