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Are transversion mutations better? A Mutagenesis Assistant Program analysis on P450 BM-3 heme domain.

Directed evolution represents a versatile tool to tailor enzyme properties to needs in industrial applications and to understand structure-function relationships. Genetic diversity is commonly generated using error-prone PCR. Exploration of sequence space by random mutagenesis strongly favors transitions when enzyme-based mutagenesis methods are employed (Wong, T. S., Zhurina, D., Schwaneberg, U., Comb. Chem. High Throughput Screen. 2006, 9, 271-288). The genetic code has been organized in a manner that limits chemical diversity when a single transition mutation occurs in a codon (Wong, T. S., Roccatano, D., Schwaneberg, U., Biocatal. Biotransformation 2006, in press). Are transitions more beneficial than transversions for adapting biocatalysts to non-natural process conditions? In a statistical analysis performed with the Mutagenesis Assistant Program (MAP), we compared the consequences of transition and transversion bias on amino acid substitution patterns of the P450 BM-3 heme domain. For the analysis, we used a recently introduced benchmarking system consisting of a protein structure indicator, an amino acid diversity indicator with a codon diversity coefficient, and a chemical diversity indicator. A detailed analysis for the P450 BM-3 heme domain showed that an ideal transversion bias generates more diverse amino acid substitution patterns with a significantly different chemical composition than an ideal transition bias. Emphasis is given on the theoretical analysis with a brief discussion on potential implication of transition and transversion bias in directed evolution experiments.

Algorithms↗

High performance computing for the human genome project.

Human Genome Analysis and Image Processing are part of the 'Grand Challenges' in High Performance Computing. The traditional mainframe has become insufficient for these applications in Biocomputing. New scalable parallel processor systems enter the marketplace with superior price/performance. The evaluation process of such a system by an application-oriented benchmark test suite is described. The system is integrated in the client/server structure of the Deutsches Krebsforschungszentrum where 'rightsizing' will eliminate the mainframe completely in the near future.

Computer Systems↗

Development of a cell-based nanoluciferase reporter system for high-throughput screening of HBV cccDNA inhibitors.

Hepatitis B virus (HBV) persistence is sustained by the viral covalently closed circular DNA (cccDNA) minichromosome, which remains a major barrier to curative antiviral therapies. The lack of reliable quantitative cccDNA detection methods and surrogate markers has hindered efforts to target cccDNA in antiviral high-throughput screening (HTS). Here, we established a novel inducible cccDNA-dependent nanoluciferase (NLuc) reporter cell line, designated HepBLE12, by inserting an in-frame 11-amino acid split-NLuc HiBiT tag into the precore (pC) coding region of an HBV transgene. The resulting 1.3-kDa HiBiT tag on pC serves as the detection module of the split NLuc system, generating quantitative luminescence upon high-affinity complementation with the cognate 18-kDa LgBiT subunit in cell lysates. Notably, the HiBiT assay enables direct detection of intracellular HiBiT-pC protein rather than secreted HBeAg, providing a reporter signal more closely linked to cccDNA activity. HepBLE12&#x202f;cells exhibited inducible and robust viral DNA replication, and the cccDNA-dependent HiBiT signal was validated under diverse experimental conditions that modulate cccDNA formation or transcription. We further miniaturized the assay to a 384-well format and optimized key parameters following standard HTS assay development practices. The assay was successfully automated and demonstrated excellent performance in a multi-day variability study and a pilot screen, with signal-to-background (S/B)&#x202f;&#x2248;&#x202f;9, coefficient of variance (CV)&#x202f;<&#x202f;10%, and average Z-factor value of 0.74, exceeding canonical HTS quality benchmarks. Together, the HepBLE12 cell-based HTS platform provides a robust and practical tool for identifying inhibitors targeting HBV cccDNA.

Hepatitis B virus↗

Improved spatial characterization of the epileptic brain by focusing on nonlinearity.

An advanced characterization of the complicated dynamical system brain is one of science's biggest challenges. Nonlinear time series analysis allows characterizing nonlinear dynamical systems in which low-dimensional nonlinearity gives rise to complex and irregular behavior. While several studies indicate that nonlinear methods can extract valuable information from neuronal dynamics, others doubt their necessity and conjecture that the same information can be obtained using classical linear techniques. To address this issue, we compared these two concepts, but included furthermore a combination of nonlinear measures with surrogates, an approach that has been designed to specifically focus on nonlinearity. As a benchmark we used the discriminative power to detect the seizure-generating hemisphere in medically intractable mesial temporal lobe epilepsy. We analyzed intracranial electroencephalographic recordings from the seizure-free interval of 29 patients. While the performance of both linear and nonlinear measures was weak, if not insignificant, a very high performance was obtained by the use of surrogate-corrected measures. Focusing on nonlinearity by using a combination of nonlinear measures with surrogates appears as the key to a successful characterization of the spatial distribution of the epileptic process.

Electroencephalography↗

A proposed method to estimate premorbid intelligence utilizing group achievement measures from school records.

Estimating premorbid cognitive functioning is an important part of any neuropsychological evaluation. This estimate is the benchmark against which current cognitive functioning is compared to establish the existence, degree, and rate of cognitive decline. Typically methods used to estimate premorbid cognitive functioning are based on; (1) demographic information, (2) combined current test performance with demographics, and (3) current reading (word recognition) ability. These approaches each have drawbacks including difficulty estimating premorbid abilities of people close to the extremes of intellectual functioning (i.e., estimating the premorbid ability of individuals in the gifted or borderline intellectual ranges). The current study reviewed the existing data comparing commonly used group administered achievement and college board tests with the Wechsler IQ tests. It is proposed that clinicians may predict premorbid cognitive functioning by applying the well-known predicted-difference method to estimate IQ from group administered achievement test scores. The correlations between group administered achievement and college board tests with the Wechsler IQ tests are reviewed and the descriptive statistics of selected group administered achievement and college board tests are presented.

Adolescent↗

Developments in vascular surgery at Epworth Hospital.

Epworth Hospital has been a leading centre for vascular surgery in Melbourne for over 30 years with a strong focus on vascular reconstruction by open surgical methods. Epworth pioneered the hybrid suite, which combined state-of-the-art imaging, and operating theatre standard suite. This development has become the benchmark for other vascular centres when designing their own vascular suites. Epworth Hospital has become a leading centre in the southern hemisphere for endografting for both abdominal aortic aneurysm and thoracic aneurysm with 76 endografts being performed in the calendar year 2000, 125 in the year 2001 and 106 in the year 2002. We look forward to Epworth Vascular Unit continuing to practice world-best standards in peripheral arterial reconstruction, to continue its role in mentoring surgical trainees and other vascular surgeons learning endovascular skills and to promote the development of innovations in vascular surgery.

Journal Article↗

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data.

MOTIVATION: Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods. RESULTS: We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets. AVAILABILITY AND IMPLEMENTATION: Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

Proteomics↗

Transhiatal esophagectomy: clinical experience and refinements.

OBJECTIVE: To review the authors' clinical experience with transhiatal esophagectomy (THE) and the refinements in this procedure that have evolved. BACKGROUND: Increased use of THE during the past two decades has generated controversy about the merits and safety of this approach compared with transthoracic esophageal resection. The authors' large THE experience provides a valuable basis for benchmarking data regarding the procedure. METHODS: The results of THE were analyzed retrospectively using the authors' prospectively established esophageal resection database and follow-up information on these patients. RESULTS: From 1976 to 1998, THE was performed in 1085 patients, 26% with benign disease and 74% with cancer. The procedure was possible in 98.6% of cases. Stomach was the esophageal substitute in 96%. The hospital mortality rate was 4%. Blood loss averaged 689 cc. Major complications were anastomotic leak (13%), atelectasis/pneumonia (2%), intrathoracic hemorrhage, recurrent laryngeal nerve paralysis, chylothorax, and tracheal laceration (<1% each). Actuarial survival of patients with carcinoma equaled or exceeded that reported after transthoracic esophagectomy. Late functional results were good or excellent in 70%. With preoperative pulmonary and physical conditioning, a side-to-side stapled cervical esophagogastric anastomosis (<3% incidence of leak), and postoperative epidural anesthesia, the need for an intensive care unit stay has been eliminated and the length of stay reduced to 7 days. CONCLUSION: THE is possible in most patients requiring esophageal resection and can be performed with greater safety and fewer complications than the traditional transthoracic approaches.

Adolescent↗

Predicting the sub-cellular location of proteins from text using support vector machines.

We present an automatic method to classify the sub-cellular location of proteins based on the text of relevant medline abstracts. For each protein, a vector of terms is generated from medline abstracts in which the protein/gene's name or synonym occurs. A Support Vector Machine (SVM) is used to automatically partition the term space and to thus discriminate the textual features that define sub-cellular location. The method is benchmarked on a set of proteins of known sub-cellular location from S. cerevisiae. No prior knowledge of the problem domain nor any natural language processing is used at any stage. The method out-performs support vector machines trained on amino acid composition and has comparable performance to rule-based text classifiers. Combining text with protein amino-acid composition improves recall for some sub-cellular locations. We discuss the generality of the method and its potential application to a variety of biological classification problems.

Automation↗

Generating correlated data for omics simulation.

Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.

Computer Simulation↗

A MAGIBU-based model for pediatric and juvenile CNS tumors: an in-house epigenetic decision-support framework compared with online DNA methylation classifiers.

Background: DNA methylation profiling is a tool that provides key support for central nervous system (CNS) tumor classification. However, diagnostically ambiguous pediatric cases may result in discordant outputs across classifiers. We developed MAGIBU, a cross-platform, projection-based framework that embeds individual methylomes into a fixed CNS reference landscape, ranking diagnostic entities by local epigenetic proximity to support clinician-led integrative diagnosis. Methods: As a proof-of-concept, we evaluated MAGIBU in eight morphologically challenging pediatric/juvenile CNS tumors with unresolved diagnoses after institutional and central pathology review. To establish a benchmark in the absence of a definitive histopathological ground truth, a consensus epigenetic reference was defined a priori for cases showing concordant results between the Heidelberg CNS Tumor Methylation Classifier and Methylscape Analysis. Comparisons were also performed with Epigenomic Digital Pathology (EpiDiP). To validate MAGIBU beyond this discovery cohort, performance was assessed at the family level across the CNS methylation spectrum (n = 678, 28 methylation families), on non-array platforms (whole-genome bisulfite sequencing and Oxford Nanopore), and in a focused analysis of the low-grade glioma and diffuse midline glioma compartment across four independent cohorts (n = 670). Results: In the discovery cohort, MAGIBU achieved high concordance with the consensus reference (Cohen's &#x3ba; = 0.855), outperforming EpiDiP (&#x3ba; = 0.278), which frequently placed low-grade tumors in proximity to higher-grade reference regions. Conclusions: MAGIBU provides a stable, quantitative differential diagnosis framework that mitigates the limitations of rigid categorical assignments. By leveraging a distance-based proximity metric, it offers a transparent decision-support tool that integrates effectively with clinical, radiological, and molecular data. While performance is inherently dependent on reference atlas composition, MAGIBU represents a robust complementary approach for the diagnostic workup of ambiguous CNS tumors.

Brain↗

Promoting physician productivity through a variable compensation system.

Integrated delivery systems must find ways to achieve optimal physician productivity and accountability, while fostering an entrepreneurial attitude among physicians. Lovelace Health Systems, Albuquerque, New Mexico, has implemented a variable compensation system designed for this purpose. An assessment of Lovelace's physician productivity had indicated performance well below national medians. To offer physicians a strong incentive to increase productivity, Lovelace developed a variable compensation system based on the resource-based relative value scale and relative value units. Lovelace also developed benchmark productivity targets.

Delivery of Health Care, Integrated↗

Supercomputing in cancer research.

Human Genome Analysis and Image Processing are part of the 'Grand Challenges' in High Performance Computing. The traditional mainframe has become insufficient for these applications in Biocomputing. Scalable parallel processor systems have entered the marketplace with superior price/performance. The evaluation process of such a system by an application-oriented benchmark test suite is described. Meanwhile a large system is integrated in the client/server structure of the Deutsches Krebsforschungszentrum where the traditional mainframe is completely replaced by scalable systems.

Benchmarking↗

Comparative performance assessment in managed care: data envelopment analysis for health care managers.

In health care markets increasingly dominated by managed care, health care managers need sophisticated yet understandable comparative performance assessment methods. Ideally, these methods should provide targets for the managers to improve program or organization performance. This article reviews three comparative performance methodologies with a comprehensive explanation of data envelopment analysis (DEA). DEA is a form of linear programming that allows for the inclusion of multiple input and output/outcome performance variables from a virtually unlimited number of organizations, facilitating meaningful health service provider comparative assessments.

Administrative Personnel↗

Strategies for Medicare health plans serving racial and ethnic minorities.

The Medicare Managed Care (MMC) Consumer Assessment of Health Plans Study (CAHPS) survey offers an opportunity to examine differences in health plan experiences and patterns of use of services of racial and ethnic minority beneficiaries enrolled in health plans. Analysis of the survey data and review of prior literature indicate significant health disparities and different patterns of health care use by racial and ethnic minorities. Improved measurement of health plan performance in serving minority enrollees, and development of performance improvement strategies, could have the potential to reduce the observed health disparities.

Aged↗

Motor perseveration in geriatric medical patients.

Perseveration has long been considered as a pathognomonic sign of neurological disease, yet, surprisingly, little research exists regarding the accuracy of this assumption. This study matched 56 geriatric medical inpatients with 56 inpatients with recent cerebrovascular accidents. Participants were given one of two measures of general cognition and four Lurian tasks of motor coordination. The results suggest that both motor incoordination and across-tasks perseveration were associated with decreased cognitive status. After controlling for cognitive status, individuals with a neurological history evidenced greater dyscoordination and increased perseveration when compared to age-equivalent general medical patients. Perseveration in participants with recent strokes appeared more related to the amount of neural system disruption as opposed to specific lesion sites. Overall, the results suggest that motor incoordination and "stuck-in-set" perseveration are more indicative of global than localizable brain dysfunction. Possible nonneurologic factors associated with this behavior are also proposed as benchmarks for future research.

Aged↗

Usefulness of the serum ferritin concentration in the detection of iron deficiency in a general hospital.

The efficacy of measuring the transferrin saturation and the serum ferritin concentration to detect iron deficiency was determined under routine conditions in a general hospital. The tests were performed on 100 adult patients who consecutively underwent bone marrow aspiration for the appraisal of a wide range of clinical conditions. The absence of stainable reticuloendothelial iron in smears of the aspirate was used as the benchmark of iron deficiency. Of the 86 patients who were anemic 19 lacked hemosiderin in the bone marrow. The percentage of patients with iron deficiency who were correctly classified by the tests (i.e., the tests' sensitivity) was 84% for the transferrin saturation and 79% for the serum ferritin concentration, and the percentage of patients free of iron deficiency who were correctly classified by the tests (i.e., the tests' specificity) was 63% and 96% respectively. The predictive value of an abnormal (positive) result for the detection of iron deficiency was 39% for the transferrin saturation and 83% for the serum ferritin concentration, whereas the predictive value of a normal or high (negative) result for the exclusion of iron deficiency was 93% and 94% respectively. Measurement of the serum ferritin concentration was superior to measurement of the transferrin saturation only in its specificity. The former is of particular value in clinical settings where the prevalence of iron deficiency is low and conditions that increase the serum ferritin concentration out of proportion to the size of the body iron stores are infrequent.

Adult↗

Improved learning algorithms for mixture of experts in multiclass classification.

Mixture of experts (ME) is a modular neural network architecture for supervised learning. A double-loop Expectation-Maximization (EM) algorithm has been introduced to the ME architecture for adjusting the parameters and the iteratively reweighted least squares (IRLS) algorithm is used to perform maximization in the inner loop [Jordan, M.I., Jacobs, R.A. (1994). Hierarchical mixture of experts and the EM algorithm, Neural Computation, 6(2), 181-214]. However, it is reported in literature that the IRLS algorithm is of instability and the ME architecture trained by the EM algorithm, where IRLS algorithm is used in the inner loop, often produces the poor performance in multiclass classification. In this paper, the reason of this instability is explored. We find out that due to an implicitly imposed incorrect assumption on parameter independence in multiclass classification, an incomplete Hessian matrix is used in that IRLS algorithm. Based on this finding, we apply the Newton-Raphson method to the inner loop of the EM algorithm in the case of multiclass classification, where the exact Hessian matrix is adopted. To tackle the expensive computation of the Hessian matrix and its inverse, we propose an approximation to the Newton-Raphson algorithm based on a so-called generalized Bernoulli density. The Newton-Raphson algorithm and its approximation have been applied to synthetic data, benchmark, and real-world multiclass classification tasks. For comparison, the IRLS algorithm and a quasi-Newton algorithm called BFGS have also been applied to the same tasks. Simulation results have shown that the use of the proposed learning algorithms avoids the instability problem and makes the ME architecture produce good performance in multiclass classification. In particular, our approximation algorithm leads to fast learning. In addition, the limitation of our approximation algorithm is also empirically investigated in this paper.

Journal Article↗