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Results for “Performance benchmarking”

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PubMed1999

A branch and bound algorithm for protein structure refinement from sparse NMR data sets.

We describe new methods for predicting protein tertiary structures to low resolution given the specification of secondary structure and a limited set of long-range NMR distance constraints. The NMR data sets are derived from a realistic protocol involving completely deuterated 15N and 13C-labeled samples. A global optimization method, based upon a modification of the alphaBB (branch and bound) algorithm of Floudas and co-workers, is employed to minimize an objective function combining the NMR distance restraints with a residue-based protein folding potential containing hydrophobicity, excluded volume, and van der Waals interactions. To assess the efficacy of the new methodology, results are compared with benchmark calculations performed via the X-PLOR program of Brünger and co-workers using standard distance geometry/molecular dynamics (DGMD) calculations. Seven mixed alpha/beta proteins are examined, up to a size of 183 residues, which our methods are able to treat with a relatively modest computational effort, considering the size of the conformational space. In all cases, our new approach provides substantial improvement in root-mean-square deviation from the native structure over the DGMD results; in many cases, the DGMD results are qualitatively in error, whereas the new method uniformly produces high quality low-resolution structures. The DGMD structures, for example, are systematically non-compact, which probably results from the lack of a hydrophobic term in the X-PLOR energy function. These results are highly encouraging as to the possibility of developing computational/NMR protocols for accelerating structure determination in larger proteins, where data sets are often underconstrained.

Algorithms↗
PubMed2026

Towards efficient perturbation for the noncoding genome.

Deciphering the functionality of the noncoding genome, which includes important cis-regulatory elements (CREs) and transcribed noncoding RNA genes, remains technically challenging. Here, using massively parallel genetic screening, we systematically benchmark the performance of five representative loss-of-function perturbation tools, including single-guide RNA (gRNA) mediated SpCas9 cleavage or CRISPR interference, and paired gRNA (pgRNA) involved dual-SpCas9, Big Papi (paired SpCas9 and SaCas9) or dual-enAsCas12a fragment deletion methods, in decoding the roles of the noncoding genome. For targeting CREs such as enhancers, dual-SpCas9 outperforms other methods with superior efficiency in destroying functional genomic regions. For perturbing noncoding RNA genes, in addition to dual-SpCas9, other RNA-targeting methods such as RNA interference are recommended to discriminate transcript-dependent or -independent roles. A deep learning model, DeepDC, with an associated web server, is built to facilitate optimal dual-SpCas9 pgRNA design for efficiently deleting a genomic fragment. Together, our work provides practical guidance on selecting appropriate loss-of-function tools to resolve the functional complexity of the noncoding genome.

CRISPR-Cas Systems↗
PubMed2026

Comprehensive Evaluation and Explainable Interpretation of Peptide-HLA Binding Prediction Tools.

Accurate prediction of peptide binding to human leukocyte antigen class I (HLA-I) molecules is critical for advancing immunological research, particularly in vaccine design and immunotherapy. However, limitations in model performance, interpretability, and dataset quality impede the widespread adoption of existing predictive tools. Here, we present a comprehensive evaluation of 17 HLA-I peptide binding prediction models, utilizing a meticulously curated dataset comprising over 290,000 peptides spanning 44 HLA-I alleles. We assessed model accuracy, robustness, and interpretability, employing explainability techniques such as SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) to elucidate underlying prediction mechanisms. Our results reveal substantial performance disparities, with self-attention-based models, including STMHCpan and BigMHC, exhibiting superior accuracy. Notably, the capsule network model CapsNet-MHC_AN demonstrated robust performance. Models trained on eluted ligand datasets outperformed those relying on binding affinity data, underscoring the critical role of high-quality training data. Ensemble and multi-algorithm approaches further improved prediction reliability. These findings highlight the need for ongoing innovation in model architecture, integration of diverse and high-quality datasets, and incorporation of structural predictors to develop more accurate, interpretable, and clinically applicable HLA-I peptide binding prediction tools.

HLA-I binding↗
PubMed2026

Genome-resolved assessment of archaeal diversity in full-scale anaerobic digesters reveals variability in mcrA primer coverage.

AIMS: Methanogenic archaea are key players in anaerobic digestion, driving methane production in biogas reactors. This study aimed to assess the diversity of methanogenic archaea in full-scale anaerobic digesters using genome-resolved metagenomics and to systematically evaluate the taxonomic coverage of commonly used mcrA-targeted qPCR primer sets against this genomic framework. METHODS AND RESULTS: Methanogenic diversity was assessed using 113 dereplicated archaeal metagenome-assembled genomes (MAGs) recovered from 109 full-scale anaerobic digesters treating diverse substrates. Genome-resolved analyses revealed a diverse archaeal community spanning multiple phyla, dominated by Halobacteriota and Methanobacteriota, with additional representatives from Methanobacteriota_B, Thermoplasmatota, and Thermoproteota. The presence of the mcrA gene was identified in a subset 55 MAGs, which were subsequently used as the genomic framework to evaluate six commonly used mcrA qPCR primer sets in silico. This subset clustered into nine phylogenetic groups and formed the basis for the primer coverage analysis. The evaluation revealed marked differences in taxonomic coverage among primer sets. Most primers preferentially detected Methanobacteriales and Methanosarcinales, while underrepresenting or excluding other methanogenic lineages, including H₂-dependent methylotrophic Methanomassiliicoccaceae. CONCLUSIONS: Commonly used mcrA primer sets differ substantially in their ability to capture methanogenic diversity, with some showing broad representation of reactor-associated methanogens and others exhibiting strong lineage-specific biases. Genome-resolved metagenomics provides an effective framework for benchmarking primer performance and supports the selection and improvement of molecular tools for more accurate monitoring of anaerobic digestion systems.

Archaea↗
PubMed2026

Computed tomography-guided precision biopsy combined with metagenomic next-generation sequencing for etiological diagnosis in patients with blood culture-negative systemic infections.

ObjectiveTo evaluate the diagnostic efficacy of computed tomography-guided percutaneous biopsy combined with metagenomic next-generation sequencing in patients with blood culture-negative systemic infections and to assess the clinical impact of using this combined strategy for etiological confirmation and guidance of targeted antimicrobial therapy.MethodsThis single-center retrospective observational cohort study enrolled 78 patients who met the Sepsis-3 consensus criteria for suspected systemic infection and had negative conventional microbiological work-ups (at least two sets of blood cultures) between April 2022 and March 2025. All patients underwent computed tomography-guided biopsy of radiologically identified infectious foci, with specimens processed concurrently for conventional culture and metagenomic next-generation sequencing. Diagnostic performance was benchmarked against the final comprehensive clinical diagnosis, and the influence of metagenomic next-generation sequencing findings on antimicrobial therapy modification was analyzed. Sample size calculation, based on a prior study estimating an metagenomic next-generation sequencing detection rate of 85% (&#x3b1;&#x2009;=&#x2009;0.05, &#x3b2;&#x2009;=&#x2009;0.2), indicated a minimum of 68 cases; accordingly, 78 patients were enrolled.ResultsComputed tomography-guided biopsy was technically successful in all 78 patients (100%). The pathogen detection rate of metagenomic next-generation sequencing (91.0%, 71/78) was significantly higher than that of conventional culture (55.1%, 43/78; p&#x2009;<&#x2009;0.001). Using the final clinical diagnosis as the reference standard, metagenomic next-generation sequencing achieved a sensitivity of 94.7% (95% confidence interval: 86.9-98.5), specificity of 100.0% (95% confidence interval: 29.2-100.0), positive predictive value of 100.0% (95% confidence interval: 94.9-100.0), and negative predictive value of 42.9% (95% confidence interval: 9.9-81.6). Among the 35 culture-negative specimens, metagenomic next-generation sequencing established a definitive microbiological diagnosis in 28 cases (80.0%) and detected polymicrobial infections in 11 cases (14.1% of the cohort). Antimicrobial therapy was rationally adjusted based on metagenomic next-generation sequencing results in 69.2% (54/78) of the patients.ConclusionsThe integration of computed tomography-guided precision biopsy with metagenomic next-generation sequencing offers a highly effective diagnostic approach for blood culture-negative systemic infections. This synergistic strategy improves etiological diagnosis by providing high-yield target specimens that enable comprehensive, unbiased pathogen screening, facilitates differentiation between infectious and non-infectious etiologies, and supplies critical evidence for guiding precision antimicrobial therapy. These findings highlight the growing role of interventional radiology in the contemporary framework of precision infectious disease management.

Humans↗
PubMed1998

Size characteristics of larger academic human environmental health programs in the United States.

We have performed a benchmark exercise evaluating larger academic programs in human environmental health sciences. These programs are located at schools of public health and at other institutions that have NIEHS Centers of Excellence. The largest programs were those in which there was both an NIEHS center and a public health graduate education program. This suggests that there is synergy between environmental health sciences research and involvement in public and community health.

Data Collection↗
PubMed2026

Optimized Hot Phenol-Based RNA Extraction from Mycobacteria: A Robust Approach for Reliable Gene Expression Analysis.

Mycobacterium tuberculosis (Mtb) remains a major global health threat, underscoring the need for reliable transcriptomic studies to understand its biology and drug resistance mechanisms. Such analyses depend on obtaining high-quality, high-yield RNA. Although several RNA extraction methods are available, many require expensive reagents, large culture volumes, or specialized equipment, limiting their suitability for large-scale studies, particularly in resource-constrained settings. Here, an optimized Hot Phenol based RNA extraction method specifically tailored for mycobacteria is presented. The method uses minimal culture volume and commonly available reagents to consistently yield high-quality RNA suitable for high-throughput transcriptomic applications. RNA quantity and integrity were assessed by gel electrophoresis and RNA integrity analysis (RIN), and its suitability for downstream applications was confirmed by qPCR and Qubit 4. To benchmark the performance of the optimized method, a parallel RNA extraction using TRIzol and RNeasy under identical experimental conditions was carried out, including the same Mycobacterium species, culture volume, growth phase (logarithmic and stationary), and lysis conditions. This allowed a direct comparison of yield, quality, feasibility, and cost. The optimized Hot Phenol method demonstrated comparable or improved RNA yield and quality while significantly reducing reagent cost and dependence on specialized equipment. Owing to its efficiency, reproducibility, and affordability, this protocol provides a practical alternative for large-scale gene expression and transcriptomic studies in Mtb and other mycobacterial species.

RNA, Bacterial↗
PubMed1998

Panel discussion. Data needs in cancer.

A prospective, comprehensive outcomes database was recently initiated by the National Comprehensive Cancer Network (NCCN) after a 2-year study to test data collection methods and systems. It started with data on 400 patients with newly diagnosed breast cancer at five NCCN sites, and over the next 3 years is projected to grow to include more than 12,000 patients with common cancers treated at all eligible NCCN sites. Among the goals of the database are: 1) to establish the capability to select, analyze, and report patterns of care and outcomes; 2) to allow NCCN members to assess their compliance with NCCN clinical practice guidelines and benchmark their performance against the rest of the NCCN; 3) to establish a true databased continuous quality improvement program; 4) to support clinical disease-oriented research and methodologic studies; and 5) to provide the NCCN with a vehicle for forging partnerships with others in the health-care field, such as the pharmaceutical industry, regulatory agencies, and accrediting bodies. Many of those potential partners were represented on this panel. Panelists discussed the data needs of their organizations, what they are doing to meet those needs, and how a comprehensive database will ultimately help improve patient care.

Aged↗
PubMed1993

Benchmarking hospital laboratory financial and operational performance.

The movement toward more integrated delivery systems requires hospital administrators, medical staffs, and health care network organizations to consider strategies that will meet the future challenges facing laboratory services. Many health care experts predict that the number of hospital inpatient days, staffed acute care beds, and length of stay will continue their precipitous decline, and then stabilize during the next four to five years. Hospitals should carefully evaluate how their laboratories might be affected as a result of the decline in inpatient services and the integration of health care services at all levels. Hospital executive management must find a way to manage staffing levels and technical resources in order to maintain quality patient services in the face of declining test volume. This Special Report discusses relevant benchmarks intended to help hospital administrators and laboratory directors identify "best practices" in hospital laboratories so that comparisons of patterns of care and financial operations can be made. Benchmarking the relative financial and operational performance of hospital laboratories allows health care planners to design the most appropriate laboratory services delivery system for future hospital inpatient and outpatient market demands. Factors influencing financial and operation performance will be investigated, including utilization, testing costs, staffing mix, productivity, and organizational structure. This will be followed by a discussion on the future of laboratories and the trend toward regional laboratories owned by hospital consortiums.

Clinical Laboratory Techniques↗
PubMed1999

Why use noise?

Measuring the dependence of visual sensitivity on parameters of the visual stimulus is a mainstay of vision science. However, it is not widely appreciated that visual sensitivity is a product of two factors that are each invariant with respect to many properties of the stimulus and task. By estimating these two factors, one can isolate visual processes more easily than by using sensitivity measures alone. The underlying idea is that noise limits all forms of communication, including vision. As an empirical matter, it is often useful to measure the human observer's threshold with and without a noise background added to the display, to disentangle the observer's ability from the observer's intrinsic noise. And when we know how much noise there is, it is often useful to calculate ideal performance of the task at hand, as a benchmark for human performance. This strips away the intrinsic difficulty of the task to reveal a pure measure of human ability. Here we show how to do the factoring of sensitivity into efficiency and equivalent noise, and we document the invariances of the two factors.

Artifacts↗
PubMed1997

Benchmarking in home care.

Recognizing that continuous quality improvement will be imperative for success in the future, six visiting nurse associations of northwestern Pennsylvania used benchmarking as a tool to improve their respective agencies' performance. The agencies benchmarked three areas: continuity of care, patient rehospitalization, and nosocomial infection rate.

Continuity of Patient Care↗