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PubMed2025

Realfreq: real-time base modification analysis for nanopore sequencing.

SUMMARY: Nanopore sequencers allow sequencing data to be accessed in real-time. This allows live analysis to be performed, while the sequencing is running, reducing the turnaround time of the results. We introduce realfreq, a framework for obtaining real-time base modification frequencies while a nanopore sequencer is in operation. Realfreq calculates and allows access to the real-time base modification frequency results while the sequencer is running. We demonstrate that the data analysis rate with realfreq on a laptop computer can keep up with the output data rate of a nanopore MinION sequencer, while a desktop computer can keep up with a single PromethION 2 solo flowcell. AVAILABILITY AND IMPLEMENTATION: Realfreq is a free and open-source application implemented in C programming language and shell scripts. The source code and the documentation for realfreq can be found at https://github.com/imsuneth/realfreq. The version used for the manuscript is also available at https://doi.org/10.5281/zenodo.15128668.

Nanopore Sequencing↗
PubMed2026

A novel method for across-chromosome phasing without relative data.

MOTIVATION: Across-chromosome phasing identifies which haplotypes of different chromosomes come from the same parent. This differs from within-chromosome phasing, which uses linkage disequilibrium patterns to determine which alleles were co-inherited within each chromosome but does not match haplotypes across different chromosomes. While across-chromosome phasing can be conducted using genotypes from parents or close relatives, current methods perform poorly for samples of unrelated individuals. Here, we introduce a novel approach for across-chromosome phasing that employs a window-based SNP-similarity metric, eliminating the need for data from close relatives or detection of identical-by-descent haplotypes. RESULTS: Using UK Biobank offspring with both parents genotyped as a gold standard, we evaluated the performance of our method by phasing the offspring without using parental data. In genomic data with no within-chromosome phase errors, our algorithm achieved a mean across-chromosome phasing accuracy of 95%, with 53% of individuals phased perfectly. When data was pre-phased computationally using a standard within-chromosome phasing algorithm, mean accuracy for across-chromosome phasing dropped to 83.1%. Thus, our method is limited primarily by the accuracy of within-chromosome phasing accuracy and can approach near-perfect across-chromosome phasing accuracy as within-chromosome phasing accuracy improves. AVAILABILITY AND IMPLEMENTATION: The implementation was executed within a multi-node computational environment of University of Colorado Boulder Research Computing (Blanca Cluster: https://www.colorado.edu/rc/resources/blanca), employing parallelization techniques in the C programming language. The source code has been made publicly accessible online at https://github.com/emmanuelsapin/AcrossChromosomesPhasing, thereby facilitating reproducibility of the results for researchers with authorized access to the UK Biobank dataset.

Algorithms↗
PubMed2026

An interpretable deep learning framework uncovers features governing CRISPR-Cas9 genome-editing efficiency.

MOTIVATION: CRISPR-Cas9 genome-editing efficiency is strongly influenced by the sequence composition and positional context of single-guide RNAs (sgRNAs). Although numerous deep learning-based models have been developed to predict Cas9 efficiency from sgRNA sequences, most operate as black boxes, offering limited insight into the sequence determinants underlying Cas9 activity. In addition, previous studies often overlook how the positional context of sequence motifs within sgRNAs influences their effects on Cas9 binding or cleavage. RESULTS: We introduce DeepCC9, an interpretable machine learning framework that combines explicit sequence feature extraction with a residual block-based deep architecture to improve interpretability and identify composition- and position-based motifs governing Cas9 genome-editing efficiency. We applied this method to multiple Cas9 variant datasets, achieving superior predictive performance compared with existing methods while enabling direct interpretation of sequence motifs and their positional effects. Our analysis uncovered 74 sequence motifs enriched or depleted at specific positions within sgRNAs and strongly associated with Cas9 efficiency, providing mechanistic insight into sequence features that influence guide performance. Together, these results establish DeepCC9 as a generalizable and interpretable framework for modeling sequence-function relationships and advancing the understanding of the sequence determinants underlying CRISPR-Cas9 genome editing. AVAILABILITY AND IMPLEMENTATION: The authors have implemented their algorithm in the Python programming language (version 3.X), which is accessible using (https://zenodo.org/records/20073890).

Deep Learning↗
PubMed2026

SNPannotator: automated functional annotation of genetic variants and linked proxies.

SUMMARY: Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with complex traits and diseases. However, explaining the mechanisms underlying phenotypic variation remains challenging. Here, we introduce SNPannotator, an automated post-GWAS analysis software package designed to streamline the interpretation of GWAS findings. Our pipeline implements a multi-step process that identifies proxy variants in high linkage disequilibrium (LD) with associated lead variants, then queries comprehensive resources (including Ensembl, the GTEx Portal, the eQTL Catalog, and STRING DB) for genomic position, deleteriousness, regulatory annotations, clinical significance, trait associations, expression (eQTLs) and splicing quantitative trait loci (sQTLs), and functional enrichment analyses and compiles the results into user-friendly reports. This package is implemented in the R programming language and includes auxiliary functions for variant lookup and LD exploration. SNPannotator provides a practical framework for efficiently deriving biologically meaningful insights from GWAS data and for assisting researchers in prioritizing candidate variants for functional validation. AVAILABILITY AND IMPLEMENTATION: The SNPannotator package is available from the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/SNPannotator. The development version and tutorial is available on GitHub (https://github.com/omicslaboratory/SNPannotator). The online version of the package is available at https://omicslab.org/snpannotator.

Software↗
PubMed2025

Accurate detection of tandem repeats exposes ubiquitous reuse of biological sequences.

Tandem repetition is one of the major processes underlying genome evolution and phenotypic diversification. While newly formed tandem repeats are often easy to identify, it is more challenging to detect repeat copies as they diverge over evolutionary timescales. Existing programs for finding tandem repeats return markedly different results, and it is unclear which predictions are more correct and how much room remains for improvement. Here, we introduce DetectRepeats, a new method that uses empirical information about structural repeats to improve the accuracy of repeat detection. We show that DetectRepeats advances the state-of-the-art by finding highly divergent repeats with relatively few false positive detections. We apply DetectRepeats to genomes across the tree of life to discover an enrichment of detectable tandem repeats within different genes, genome regions, and taxa. Furthermore, we use phylogenetic reconciliation to determine that some tandem repeats continue to evolve through intra-repeat unit replacement. In this manner, tandem repeats serve as a renewable genetic resource offering a bountiful source of alternative genetic material. Our work unlocks the confident detection of ancient tandem repeats, opening a doorway to future discoveries. DetectRepeats is part of the DECIPHER package for the R programming language and available via Bioconductor.

Tandem Repeat Sequences↗
PubMed2025

A Systematic Review of Spatial Epidemiological Modeling Approaches Applied During the COVID-19 Pandemic.

BACKGROUND: A wide range of epidemiological modeling approaches have been applied to the SARS-CoV-2 pandemic, which presents an opportunity to assess common approaches applied to specific research questions. Spatial models interrogate how heterogeneities and host movement dynamics influence local and regional patterns of disease, issues that were of great interest for understanding and controlling SARS-CoV-2. OBJECTIVE: Here we present a systematic review of spatial epidemiological modeling approaches of SARS-CoV-2. We describe common themes and highlight unique strategies, providing a foundation for researchers to devise spatial models most appropriate for future pathogens and epidemics. Our review also categorizes the research questions that were addressed with spatial models, highlights parameter estimation techniques, and describes the cyber infrastructure used for model development. METHODS: We conducted a systematic review using Web of Science and a standardized set of keywords, followed by thorough examination of abstracts and full texts to determine which studies met our inclusion criteria. To guide our description and comparisons of models, we developed a Geography, Population, Movement (GPM) framework that conceptualizes the interactions between three distinct subcomponents of any spatial model. The geographic model represents the physical arena in which the model is implemented, the intra-population model describes the transmission and disease processes that occur within distinct spatial units of the geography, and the movement model describes the algorithms that dictate how hosts move among spatial units within the geography. RESULTS: The search identified a total of 193 articles, of which 109 were included in our review. The most abundant intra-population modeling methods were agent-based (47.7%) and compartmental modeling (29.4%) approaches. Movement models ranged in complexity, with the most complex models implementing commuter movement among many points of interest in the geographic arena, which were sometimes parameterized by fine-scale mobility data. Geographic models ranged from describing microcosms, such as single classrooms, all the way up to multi-country models. Of the 63.3% of models studies that specified the programming language used, we detected ten different languages, with Matlab and Python being the most frequent, although only 30.6% of studies provided open-access code for their models. We also described eight specialized software systems that were used to construct agent-based or compartment models of COVID-19. CONCLUSIONS: Our review identified and characterized a variety of spatial modeling strategies and software that were usefully employed to address many relevant epidemiological questions for COVID-19. Future research is needed to quantitatively assess which modeling approaches are most appropriate in specific situations, to answer specific questions, or to apply to certain disease systems. Moreover, future cyberinfrastructure could help to modularize and standardize modeling approaches, which would increase transparency and reproducibility, and which would facilitate a detailed examination of which model attributes relate to model performance in a variety of contexts.

COVID-19↗
PubMed1992

Fuzzy control of mean arterial pressure in postsurgical patients with sodium nitroprusside infusion.

We developed a fuzzy control system to provide closed-loop control of mean arterial pressure (MAP) in postsurgical patients in a cardiac surgical intensive care unit setting by regulating sodium nitroprusside (SNP) infusion. The fuzzy controller, originally expert-system-based, was analytically converted to ten nonfuzzy control algorithms, which reduced execution time dramatically. The core of the control algorithms was a nonlinear proportional-integral (PI) controller whose proportional gain and integral gain adjusted continuously according to error and rate change of error of the process output. The gains became larger when process output was far from desired setpoint and smaller when process output was close to desired setpoint, resulting in more dynamic and stable control performance than the regular PI controller, especially when a linear process with time-delay or a nonlinear process was involved. The control algorithms, encoded in C programming language, were implemented to control MAP in patients. Preliminary clinical results showed that the average percentage of time in which MAP stayed between 90% and 110% of the MAP setpoint was 89.31%, with a standard deviation of 4.96%. These were calculated based on 12 patient trials, with total trial time of 95 and 13 min.

Algorithms↗
PubMed2026

Identification of NR4A2 as a Potential Predictive Biomarker for Atherosclerosis.

INTRODUCTION/OBJECTIVE: Atherosclerosis, a leading cause of death globally, is characterized by the buildup of immune cells and lipids in medium to large-sized arteries. However, its precise mechanism remains unclear. The purpose of this study is to explore innovative and reliable biomarkers as a viable approach for the identification and management of atherosclerosis. METHODS: The atherosclerosis-related datasets GSE100927 and GSE66360 were retrieved from the Gene Expression Omnibus (GEO) database. The Limma package in the R programming language was utilized, applying the criteria of |logFC| > 1 and P < 0.05. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 127 identified DEGs using R. Machine learning techniques were then applied to these data to explore and pinpoint potential biomarkers. The diagnostic potential of these markers was assessed via Receiver Operating Characteristic (ROC) curve analysis. Finally, western blot, real-time quantitative PCR (qRT-PCR), and immunohistochemistry (IHC) were employed to confirm the key biomarkers. RESULTS: Our research indicated that a total of 127 DEGs linked to atherosclerosis were successfully identified. Through the application of machine learning methods, eight critical genes were highlighted. Among these, Nuclear Receptor Subfamily 4 Group A Member-2 (NR4A2) emerged as the most promising marker for further investigation. CIBERSORT analysis revealed that NR4A2 expression levels were significantly correlated with multiple immune cell types, including B cells, plasma cells, and macrophages. Additional validation experiments confirmed that NR4A2 expression was indeed elevated in atherosclerotic plaques, supporting its potential as a biomarker for atherosclerosis. CONCLUSION: Our study identified NR4A2 as a potential immune-related biomarker for the diagnosis and treatment of atherosclerosis.

Atherosclerosis↗
PubMed2026

Weight regain following discontinuation of glucagon-like peptide-1 receptor agonists in adults who are overweight or obese: a systematic review and meta-analysis.

OBJECTIVE: This study aims to explore the effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) on weight changes and the occurrence of adverse reactions in overweight or obese adults after drug withdrawal. METHODS: Computerized searches were conducted in evidence-based databases such as PubMed, Embase, Cochrane Library and Scopus. The search period was from the establishment of the database to December 2025. Collect randomised controlled trials (RCTs) and controlled trials on GLP-1RAs, including tirzepatide, semaglutide, liraglutide, and dulaglutide, for the treatment of overweight or obese adult patients. The risk of bias in the included studies was assessed using the Cochrane Risk of Bias V2.0 tool provided by the Cochrane Collaboration, and meta-analysis was performed using the R programming language. RESULTS: A total of 699 studies were initially retrieved. Eventually, six studies involving 8,993 patients were included in the quantitative analysis, comprising 5,553 patients in the discontinuation group and 3,440 in the continued treatment group. The results of the meta-analysis showed that, compared with the continued treatment group, the weight difference in the discontinuation group was mean difference (MD) = 17.90%, 95% confidence interval (CI) [14.11-21.69], P&#xa0;<&#xa0;0.0001. It can be seen that there was a significant rebound in weight after drug withdrawal, and there was statistical heterogeneity among the studies (P&#xa0;=&#xa0;0.0082). Subgroup analysis further revealed that the weight rebound amplitude after discontinuation of tirzepatide was significantly higher than that of semaglutide. This result suggests that the differences in the mechanism of action of different GLP-1RAs may be the reason for the differences in weight changes after discontinuation. In addition, the percentage difference in body weight between after and before drug withdrawal was MD = 9.11%, 95% CI [7.91-10.30], P&#xa0;<&#xa0;0.0001, further verifying the trend of weight rebound after drug withdrawal. The summary of adverse reaction reports analyzed and studied indicates that after drug withdrawal, the overall adverse reactions of patients decreased, gastrointestinal adverse reactions decreased, and the incidence of cardiovascular events was not affected by drug withdrawal. CONCLUSION: There is a significant weight rebound phenomenon after discontinuation of GLP-1RAs, and the rebound magnitudes vary among different types of drugs. At the same time, there is a risk of adverse reactions during the use of such drugs.

Humans↗
PubMed1979

Quantitative image analysis: applications using sequential transformations.

The theoretical foundations of quantitative image analysis and its implementation in the Leitz T.A.S. have been discussed in the preceeding paper [4]. Especially the Mathematical Morphology and its recent developments have been pointed out. Sequential image transformations are a new approach of morphological analysis. Elementary transform steps, which are hardwired in the device, performed in specific sequences, which are implemented as macroinstructions in the programming language have proven to be a very useful tool in image analysis. A specific sequence of elementary steps will be referred to as morphological function. This new approach will be illustrated by four general examples: analysis of fibers, computing the number of edges for metallic grains, separation of overlapping cells, analysis of minerals which occur free and locked to another one.

Cell Separation↗
PubMedDate not supplied

Mirex kinetics in the rhesus monkey. II. Pharmacokinetic model.

14C-Mirex was given iv and po to female rhesus monkeys (Macaca mulatta) and radioactivity was measured in plasma, urine, and feces at intervals after dosing and in tissues when animals were killed. Graphical analysis of plots of the logarithm of plasma concentration vs. time was used to provide estimates of the values of the first-order rate constants required by the proposed pharmacokinetic models. A BASIC-language program, FITKIN, was used to obtain numerical solutions to the differential equations for each model and to adjust the estimates to obtain a normalized, least squares fit. Of several models postulated, a mammillary, four-compartment, open-system model, providing for the urinary excretion of Mirex from a "central" compartment and for the fecal excretion of Mirex from a "fast" tissue compartment, yielded theoretical data in agreement with observed values. This model predicted that the accumulation of Mirex into fat would be retarded by the presence of a "slow" tissue compartment so that distribution equilibrium would take about half a year. From that time to the end of a 5-year projection, little decline in the quantities of Mirex was predicted for any compartment. Sequestration in fat and a lack of metabolism were responsible for the long biological half-life of Mirex in the rhesus monkey.

Adipose Tissue↗
PubMed1976

The comparison of parameters estimated from several different samples by maximum likelihood.

A system of computer programs has been developed to compare the parameters of several samples taken from populations with arbitrary but known distribution functions. The user indicates which of the parameters are assumed to be equal in all populations under the null hypothesis alone or under both the null and the alternative hypotheses. The programs perform maximum likelihood estimation under the general and the restricted model and also calculate the values needed for a likelihood ratio test. The programming language used was PL/I-FORM AC. An illustrative numerical example is given.

Animals↗
PubMed1977

Behavioral training for parents of retarded children: alternative formats based on instructional manuals.

A series of instructional manuals in behavior modification with retarded children was tested as a self-contained resource and as part of three larger training programs involving different amounts of professional assistance to parents: telephone consultations, training groups, training groups plus home visits. One hundred and sixty families were randomly assigned to the four training conditions or to a delayed-treatment control group. The 20-week treatment period emphasized the programming of self-help skills, but also provided an introduction to programming language skills and managing behavior problems. The manuals-alone format was as effective as the more expensive training formats in producing gains in children's self-help skills and fostering knowledge of behavioral principles in mothers. The two group-training formats produced more efforts at behavior-problem management, greater gains in knowledge of principles by fathers, and higher self-confidence as teachers. Telephone consultation was generally the least effective training format; the manuals-alone condition was surprisingly effective. Some implications of the results for future strategies of family intervention were discussed.

Activities of Daily Living↗
PubMed1978

Maternal speech to normal and Down's syndrome children matched for mean length of utterance.

The study was designed to provide data on the maternal linguistic environments of normal and Down's syndrome children at three levels of language development, as assessed by children's mean length of utterances (MLU). The three MLU levels were 1.00--1.50, 1.75--2.25, and 2.50--3.00, respectively. The subjects were 21 Down's syndrome children and their natural mothers and 21 normal children and their natural mothers. Normal children ranged in chronological age from 20 to 32 months and Down's syndrome children from 3 to 12 years. A one-hour verbal interaction between mother and child was tape recorded at home in a free-play situation. Maternal speech was analyzed using 20 measures related to its output-numerical, lexical, syntactical, semantic-structural, semantic-pragmatic, and language-teaching aspects. Additionally, eight measures of children's speech related to the output-numerical, lexical, syntactical semantic-structural aspects, and to imitativeness of maternal speech were computed as a means of testing the validity of the MLU-matching that forms a basis for this study. Except for the Type-token ratio, which favored Down's syndrome children, normal and Down's syndrome children were not found to differ. In contrast, there were numerous differences between the children in the different aspects of speech considered according to language level. None of the comparisons made of mother's speech to normal and to Down's syndrome children led to differences for any of the three children's language levels studied. It appeared that the maternal linguistic environments of language-learning Down's syndrome and normal children of corresponding MLU were similar in most respects. In contrast, there were numerous differences in mother's speech according to the language level of the children addressed. This confirmed that the expressive language level of the children is a far more powerful factor in influencing maternal speech than whether they are normal or Down's syndrome children. The implications of these findings were related to the delay-difference question in the language development of Down's syndrome children and to various interpretations of the effects of maternal linguistic input for language development and for intervention programs of language enhancement in the Down's syndrome child.

Adult↗
PubMed1976

Mime in language therapy and clinician training.

A speech pathologist developed a program with language goals which included spontaneous communication, focus, attention span, auditory memory, receptive and expressive vocabulary, and concepts such as body image, spatial relationships, and same and different polarities. The services of a professional mime were used to translate these goals into mimetic activities and to perform the activities in group sessions with the children. In addition, the mime taught the speech clinicians some simple mimetic activities. The subjects were five children with mental retardation, language delay, lack of spontaneity, short attention span and very poor visual and auditory memory. The results suggested increase in spontaneity and attention span in all the children and a facility to remember the illusions depicted for them by the mime. The experience with the mime training for clinicians was also positive.

Adolescent↗
PubMed1992

Future trends in language intervention: addressing cultural bias in service delivery.

In this paper the cultural biases in a widely-used language intervention approach--the Hanen Early Language Parent Program--that trains parents to be conversational partners with their language-delayed children, are explored. In many respects this program represents the best of current clinical practice. It is empirically and theoretically grounded in recent research on parent-child interaction; studies have documented its efficacy; and it is a family-centred approach. And yet, in clinical practice, it does not work with all families. Not surprisingly, these families are often from nonmainstream backgrounds. Potential reasons for the lack of effectiveness with some families become apparent as research on patterns of language socialization in a wide variety of cultures is reviewed. This review reveals that all of the basic premises of this program rest on culturally relative beliefs and values. Specifically considered are cultural variation in (1) aspects of social organization related to interaction, (2) the value of talk, (3) how status is handled in interaction, (4) beliefs about intentionality, and (5) beliefs about teaching language to children. Suggestions for incorporating this information into clinical services with nonmainstream families are offered.

Child↗