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A method of data collection and analysis is proposed for identifying environmental indicators significant to community health. The methods were applied to a study of child mortality in the city of Cali, Colombia. Pridit analysis (principal component analysis of ridits) is described. The methods have potential usefulness for monitoring and health care planning.
A simple form of pattern recognition is successfully used to classify a set of structurally diverse therapeutic agents. By using only organic structural information, the major pharmacological classes present were correctly identified and the pharmacologically unrelated compounds were separated out. One technique of factor analysis--principal component analysis--is shown to be readily adaptable in preprocessing the data. Simple graphical representation of the results enables their direct interpretation.
AIM: The primary duties of emergency healthcare professionals (EHPs) are to provide emergency patient care to acutely ill and injured individuals. Due to the nature of their work, EHPs operate under constant stress, often requiring rapid decision-making, swift action, and the delivery of necessary medical care in life-or-death situations, sometimes under inadequately safe conditions. Therefore, the aim of this study is to determine the validity and reliability of the Emergency Healthcare Professional Stress Factors and Symptoms (SEHP:SFMS) Scale in Turkish for identifying stress factors and symptoms in emergency medical care professionals providing emergency patient care services. DESIGN: A methodological study design was used in this study. METHODS: The study was conducted with the participation of 211 EHPs from employees working in emergency care institutions affiliated with the Muğla Provincial Health Directorate between November 2023 and June 2024. Data were collected via a face-to-face survey. Data were analysed using Lawshe content validity ratio, Kaiser-Meyer-Olkin coefficient, Bartlett test, exploratory factor analysis, principal component analysis, Varimax factor rotation method, confirmatory factor analysis, Cronbach's α internal consistency coefficient, convergent validity, discriminant validity, test-retest, and Spearman correlation coefficient tests. RESULTS: The linguistic translation and cultural adaptation of the SEHP:SFMS showed strong performance. The scope validity index of the scale is 0.83. The item-total correlation values of the scale were found to be between 0.486 and 0.794, and the factor loadings were between 0.474 and 0.816. Confirmatory factor analysis fit indices: χ2 = 248.727; df = 101; n = 211; p = 0.000; χ2/df = 2.463; RMSEA = 0.083; CFI = 0.914, SRMR = 0.052, which was found to be compatible and acceptable with the proposed 3-factor model. The Cronbach's α reliability coefficient of the scale was 0.931, and the total variance was 61.97%. CONCLUSIONS: SEHP:SFMS is a valid and reliable tool to assess stress factors and symptoms of Turkish emergency healthcare professionals. Its use improves the quality of emergency care. PATIENT OR PUBLIC CONTRIBUTION: These study findings have been used to create a tool with Turkish validity and reliability that allows for the examination of stress factors among healthcare professionals working in emergency and critical services. Identifying and reducing stress factors among healthcare professionals is crucial for the delivery of quality healthcare services. It can also be used to develop targeted interventions and ongoing strategies to facilitate improved clinical supervision and mentoring. IMPLICATION FOR NURSING PRACTICE: Nurses in emergency departments, which are among the most stressful, dynamic, intense, life-saving, and critical environments in healthcare institutions, and where life-saving treatment is administered, are at high risk of experiencing psychological trauma. Trauma experienced in the work environment is a significant problem for nursing. The consequences of trauma negatively affect nurses and institutions. Studies show that post-traumatic stress, anxiety, depression, and burnout are commonly observed in emergency department nurses. In this sense, understanding the stress and stress factors experienced by nurses can guide future interventions. The results of this study are considered important in making visible the stress and stress factors experienced by nurses in the emergency department, and also in guiding managers and nurses working in this field in terms of preventive and protective measures.
In order to get information about the premorbid personality of patients with endogenous psychosis, we examined the adjective check list of von Zerssen with regard to form and content on a sample of 126 schizophrenic and 31 affective-psychotic patients. The data gathering occured through retrospective evaluation by a close relative of each patient. One aim of the study was the development of a psychometric instrument in order to construct clinically relevant scales, which would allow us to objectify characterizations of the premorbid personality of patients with psychic illness. Another aim was to test the validity of this instrument by investigating the coherence between the obtained test results and the corresponding clinical psychiatric judgments of experts in the form of diagnoses. Finally, we sought to determine if typical premorbid characteristic features give a predisposition for specific aspects of psychotic diseases, in order to be able to differentiate between diverse psychiatric groups of diagnoses. By means of factor analysis (principal component analysis) with Varimax rotation we came to five easily distinguishable clinical-psychological well interpretable factors, from which we derived five scales. These scales seem to be appropriate for the characterization of premorbid personality traits. They represent the following clinical concepts: (1) cyclothymia, (2) sthenia, (3) anancasm, (4) hostility, (5) schizothymia. Formal examination of the factor-analytical proved scales according to criteria of classic test-theory (item-test correlation, reliability, distribution, intercorrelation) showed that we were able to measure rather independent dimensions of premorbid personality by our five scales with sufficient accuracy. To get evidence for the empirical validity of our scales we compared our test results (1) with three groups of different diagnoses concerning premorbid personality and (2) with the two diagnostic groups of schizophrenia and affective psychoses. We also tried to work out differential aspects within the diagnostic group of schizophrenia for four subgroups. As criteria for validity we sued clinical judgments of psychiatrists both for the premorbid personality and for the diagnosis of the present disease. On the whole our adjective check list turned out be as useful instrument to get a discriminating description of premorbid characteristic features which is better than a global evaluation in form of a single diagnosis. First First indications of the practical importance of our scales are discussed.
Kazakhstan's sheep portfolio underpins much of the country's mutton and wool production, yet several of its principal breeds remain genomically uncharacterised. The aim of this study was to characterise the genomic diversity, population structure, and global phylogenetic placement of three economically important Kazakh breeds and to determine whether they constitute separate gene pools requiring independent management. We present the first genome-wide SNP characterisation to include the Degeres (DE), the Etti Merino (EM), and the Kazakh fat-tailed coarse-wool (KKG) breeds simultaneously. A total of 1497 animals (DE = 354, EM = 642, KKG = 501) sampled across seven production households were genotyped and, after quality control, analysed at 42,279 SNPs, of which 22,766 LD-pruned markers were used for principal component analysis and AMOVA. We applied principal component analysis (PCA), pairwise FST, analysis of molecular variance (AMOVA), neighbour-joining phylogenetics, model-based ancestry estimation (ADMIXTURE), and Hill-number diversity profiling, and projected the breeds against the global Ovine SNP50 HapMap panel (74 reference breeds, 2819 animals; 37,685 shared SNPs). All three breeds retained uniformly high within-breed diversity (expected heterozygosity 0.413-0.417) with fixation indices at or near zero. AMOVA partitioned 94.03% of variance within breeds (ΦST = 0.060, p < 0.001). PCA, phylogeny, and ADMIXTURE concordantly resolved three breed-specific clusters at K = 3, with a maximum interbreed FST of 0.038 within the study dataset. Against the global panel, EM was genetically closest to Merino and Merino-derived reference breeds (pooled FST = 0.017) and substantially more distant from Southwest Asian sheep (FST = 0.045), whereas DE and KKG showed the reciprocal pattern (FST = 0.027 and 0.020 to Southwest Asia, 0.052 to the Merino group). DE additionally displayed the heterozygote excess and partial admixture expected of an incompletely consolidated composite. These results delineate three distinct gene pools and carry direct implications for breed management and the conservation of genomic diversity in Kazakhstani sheep.
SUMMARY: We developed slideimp, an R package that extends and optimizes K-nearest neighbor (K-NN) and Principal Component Analysis (PCA) imputation with grouped and sliding-window modes for accurate and efficient imputation of microarray and whole-genome DNA methylation (DNAm) data, respectively. Under a realistic scenario, slideimp achieved ≈12-28× faster runtime and ≈3-6× peak memory usage reduction for DNAm microarray imputation (GSE286313, EPICv2, N = 72) and achieved high imputation accuracy in a whole-genome DNAm dataset (N = 41). AVAILABILITY AND IMPLEMENTATION: The code used in this study is available at https://github.com/hhp94/slideimp_paper. The R package slideimp is available on CRAN (DOI: 10.32614/CRAN.package.slideimp). Version 1.0.0 of slideimp, which was used in this study, is archived on Zenodo (DOI: 10.5281/zenodo.20029382).
The antagonism of various components of maximal Metrazol-seizures (MMS) (i.e. tonic hindpaw extension, tonic backward extension of the forepaws, generalized clonic seizures and tremors), ataxia and loss of righting reflex-activity have been studied in a standardized procedure comparing 41 antiepileptics and related compounds. Appropriate analyses (Cluster Analysis and Principal Component Analysis) resulted in the distinction of seven clusters which could be considered along two continua. A first continuum is characterized by a progressive strengthening of loss of righting reflex-inducing properties, a decreasing dissociation of ataxia and loss of righting reflex and the disappearance of a selective anticonvulsant effect. The second continuum is characterized by an increasing relative potency of ataxia-inducing properties, an increasing dissociation of ataxia and loss of righting reflex and a decreasing antagonism of tremors. Three main types of anticonvulsants could be defined: drugs with a complete anti-MMS effect antagonizing both clonic and tonic seizures; drugs selectively abolishing tonic seizures, i.e., tonic extension of hind- and forepaws; and drugs exclusively blocking tonic hind-paw extension. The neurological and clinical significance of these different types of anticonvulsant activity has been discussed. Finally, the described modification of the maximal Metrazol-seizures test is proposed for routine screening purposes.
Correlations between mass spectra and pharmacological activities were surveyed by means of computerized learning machine and cluster analysis. The principal component analysis and the nonlinear mapping techniques were used for the feature selection of the data set.
UNLABELLED: Klebsiella pneumoniae is one of the most frequently reported healthcare-associated pathogens. The current gold standard approach to perform the epidemiological typing of these bacteria is Whole Genome Sequencing (WGS), which is an expensive and challenging procedure. IR Biotyper (Bruker Daltonics, GmbH) is a new equipment based on Fourier transform infrared spectroscopy, which allows a rapid, low-cost, and user-friendly method to type bacterial isolates. However, there is a need for studies that evaluate the efficacy of the IR Biotyper. The aim of this study was to evaluate the capability of IR Biotyper to type K. pneumoniae according to sequence type (ST) and capsular type-using K locus (KL)-as well as to develop a classifier using machine learning. Seventy-three isolates of K. pneumoniae previously characterized by WGS were selected for IR Biotyper analysis using principal component analysis for dimensionality reduction, Euclidean, and unweighted pair group method with arithmetic mean (UPGMA) for clustering method, and spectra were analyzed in the 1,300-800 cm⁻¹ wavenumber range. Among these, 54 isolates were used to create a classifier, and 19 were used to validate the classifier. When considering the ST, ST307 was grouped in the same cluster as ST11. When KL was considered for the analysis, the clusters were 100% correctly grouped according to their KL type. Furthermore, the classifier developed was able to classify the isolates according to KL with a high concordance. This study showed that KL correlates well with KL for typing K. pneumoniae isolates using the IR Biotyper. Additionally, IR Biotyper demonstrated to be a cost-effective method and a promising tool to classify isolates within minutes. IMPORTANCE: Klebsiella pneumoniae is a major cause of severe hospital infections, and controlling its spread requires quick identification and comparison of bacterial strains. WGS is accurate but expensive, slow, and technically demanding. In this study, we evaluated the IR Biotyper, a device that uses infrared light to analyze bacteria and group them by capsule type-a key feature linked to their spread. The IR Biotyper matched WGS results with high accuracy, delivering results in minutes instead of days. This fast, affordable method can help hospitals detect outbreaks earlier and respond more effectively. Our findings suggest that the IR Biotyper is a valuable tool for routine use in microbiology laboratories, supporting epidemiological surveillance and outbreak control.
INTRODUCTION: In animal taxa and jellyfish, the same genome encodes for the different phenotypes that characterize life stages that follow each other during ontogeny. This situation underscores the existence of profound regulation of genomic information at the epigenetic level. MicroRNAs are fundamental epigenetic regulators. The aim of this study is to evaluate the role of microRNA regulation during jellyfish metamorphosis and to explore the existence of evolutionarily conserved microRNAs. METHODS: Specimens belonging to the 4-metamorphosis stages of A. aurita (polyps, ephyra, young, and adult jellyfish) were bred and collected. The expression of 2,549 miRNAs for each stage was tested using microarray technology. The comparison of microRNA expression for each phase was performed using line plot analysis and Principal Component Analysis of variance (PCA), while the identification of microRNA clusters was performed via volcano plot analysis. RESULTS: A remarkable number of A. aurita miRNAs specifically hybridize with a human miRNA library. Each metamorphosis stage is characterized by a different level of expression of miRNAs: 1) Polyp vs. Ephyra stage: 128 upregulated, 2 downregulated; 2) Ephyra vs. Young stage: 2 upregulated, 135 downregulated; 3) Young vs. Adult stage: 69 upregulated, 6 downregulated. Specific functions inferred from known activities of corresponding miRNAs in higher animals (PubMed database) appear to be coherent with the correlated experimental model. DISCUSSION: Present results reveal that microRNAs with human homologs undergo specific expression changes throughout Aurelia aurita metamorphosis. This observation reinforces the hypothesis of a shared evolutionary origin of certain miRNA families between Cnidaria and Bilateria. The dynamic and stage-specific regulation pattern observed suggests that miRNAs play a key role in orchestrating the complex transitions involved in jellyfish development. These findings point to a broader conservation of epigenetic mechanisms, such as miRNA-mediated gene silencing, which may have emerged early in metazoan evolution and contributed to the regulation of cell differentiation and phenotype modulation. CONCLUSION: The present study highlights the importance of Aurelia aurita as a model for investigating miRNA-driven epigenetic regulation in non-bilaterian animals. The identification of human-homologous miRNAs provides novel insights into the evolutionary stability of the epigenetic machinery and suggests conserved regulatory functions across distant taxa. Although limited by the use of a human-based microarray platform, the data presented here lay a solid foundation for future studies employing sequencing and functional assays to further explore the role of miRNAs in cnidarian development and evolution.
Evodia rutaecarpa is a valuable medicinal plant, yet its non-medicinal tissues remain largely underexplored. Here, we integrated ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)-based widely targeted metabolomics and RNA sequencing (RNA-seq) transcriptomics to systematically profile the metabolic and transcriptional landscapes of roots, stems, leaves, and flowers of Evodia rutaecarpa (Juss.) Benth. Our aim was to characterize tissue-specific metabolic differentiation and its underlying transcriptional regulatory mechanisms. Metabolomic analysis, employing principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) with robust model parameters (R2Y > 0.9, Q2 > 0.5), identified 3090 differential metabolite features (variable importance in projection, VIP > 1.0; p < 0.05) across the four tissues, which exhibited distinct tissue-specific clustering patterns. Integrated Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and weighted gene co-expression network analysis (WGCNA) revealed that roots specifically accumulated quinolone alkaloids and flavonoid glycosides, accompanied by the coordinated upregulation of genes involved in flavonoid and phenylpropanoid biosynthetic pathways. In contrast, stems, leaves, and flowers were enriched in indole alkaloids (evodiamine and rutaecarpine) and volatile oil precursors, with concurrent upregulation of genes involved in tryptophan metabolism and indole alkaloid biosynthesis (e.g., tryptophan decarboxylase, TDC; s N-methyltransferase, NMT). Notably, leaves and flowers displayed particularly high accumulation levels of these bioactive alkaloids, suggesting their potential as alternative sources for industrial and pharmaceutical applications. WGCNA further identified multiple transcription factors and structural gene modules tightly correlated with evodiamine accumulation, offering promising candidate regulators for future biosynthetic pathway engineering. Collectively, this multi-omics integration study systematically elucidates the tissue-partitioned secondary metabolism of Evodia rutaecarpa (Juss.) Benth. and provides a solid scientific foundation for full-plant resource utilization, targeted development of non-medicinal tissues, and future metabolic engineering of indole alkaloid production.
The blast pathogen, Magnaporthe oryzae, is one of the most destructive fungal pathogens of rice worldwide, yet its morphological features, genetic diversity and population structure in Northeast India remain poorly understood. In this study, twenty‒two M. oryzae isolates collected from eight states of Northeast India were characterized using morphological, molecular, and population genetic analyses. Morphological characterization revealed whitish to greyish‒white mycelia with sparse sporulation and colony diameters ranged from 36 to 90 mm, classifying the isolates into 14 fast and 8 slow‒growing groups. Whole genome sequencing was performed to enable both ITS‒based identification and SSR locus mining from the assembled genomes. Molecular identification using ITS rDNA sequences confirmed all isolates as M. oryzae, with 95.5-100% similarity. Phylogenetic analysis grouped the isolates into two major clades and identified seven ITS sequence types (GenBank Accessions: PX273287-PX273293). Genetic diversity assessed using 30 SSR markers revealed substantial polymorphism, with 1-7 alleles per locus and polymorphism information content (PIC) values ranging from 0.00 to 0.81. Heatmap clustering, dendrogram analysis, and distance metrics consistently identified two major genetic groups, with some isolates forming nearly identical clusters and others showing moderate divergence. Principal Component Analysis (PCA) and Principal Coordinates Analysis (PCoA) accounted for 87.8% of the total variance (PC1 and PC2 accounted for 54.4% and 33.4% respectively of the total variance) and revealed distinct outliers. Analysis of Molecular Variance (AMOVA) attributed 80% of the total genetic variation to differences among populations while only 20% was attributed to within population differences highlighting significant inter‒population divergence and clonal population structure. The study revealed substantial morphological and genetic diversity among M. oryzae populations in Northeast India, underscoring the need for region‒specific disease management strategies.
A nonspecific opsonin function has been ascribed to human alpha 2 HS glycoprotein. Its serum level has been shown to be decreased in trauma patients. Recent studies from this laboratory revealed a heterogeneity among the products obtained in the course of the preparation of the protein. To date, no definitive agreement existed with regard to a molecular homogeneous entity of alpha 2 HS glycoprotein (Ba-alpha 2 glycoproteins). The purpose of the current work was to study the variations in serum level of alpha 2 HS in patients suffering from an acute inflammatory process of bacterial etiology and to determine whether a decrease in alpha 2 HS was accompanied by the appearance of fragments of this protein in the serum. A method of preparing alpha 2 HS was thus developed, using an immune absorbent as a final purification step. In an intermediary step of the preparation, alpha 2 HS was found to bind zinc when metal chelate affinity chromatography was employed. Immunologically and physico-chemically pure alpha 2 HS was obtained. The protein consists of a unique polypeptide chain of about 50,000 daltons and has a unique amino-terminal residue, alanine. However, the protein maintained its molecular integrity with difficulty, and spontaneous fragments ranging from 30,000 to less than 10,000 daltons were produced in some of the preparations. No major modification in the molecular structure of the protein was noted in the sera of subjects suffering from an acute inflammatory process. Serum level of alpha 2 HS and alpha 1 antitrypsin (AT)was determined in 23 patients. When the acute-phase (AP-)reactant alpha 1 AT was increased (difference with normal mean greater than +2 or +3 SD), the sera showed a large decrease in alpha 2 HS (difference with normal mean less than -2 or -3 SD). The serum level of alpha 2 HS, albumin, alpha 2 macroglobulin, and of positive AP-reactants, orosomucoidinal study of seven patients. The results were submitted to a principal components analysis. Alpha 2 HS showed a negative correlation with the AP-reactants alpha 1 AT, orosomucoid, and haptoglobin (P less than 0.05) and a positive correlation with albumin (P less than 0.05); these findings indicate that alpha 2 HS is a negative AP-reactant. In addition, analysis of the principal components confirms thestrong analogy between alpha 2 HS and albumin and indicates that serum level behavior of the AP-reactants during the course of the disease closely depends on the protein studied.
A prospective study of 102 patients with chronic lymphocytic leukaemia (CLL) on 30 parameters subdivided into 77 variables was analyzed by correspondence analysis, a variant of principal component analysis, which allows simultaneous graphical representation of patients and variables. This statistical method clearly defined three principal clinical features recognized at the time of diagnosis: lymph node proliferation, lymphoid infiltration and cytopenia. Cytopenia was clearly subdivided into peripheral and central types. Each of these clinical features were derived from clinical and laboratory observations which agreed with each other. Simple examination permitted an evaluation of these three syndromes. They seemed to be independent of each other except for a relationship between central cytopenia and lymphoid infiltration. Thus clinical staging at the moment of diagnosis must record three scales of severity corresponding to the three independant clinical features. Prognosis was essentially related to cytopenia, whatever the mechanism. In a further analysis of the subsequent progress of the disease, a "common path" for patients was found terminating in a region of the graph where marked splenomegaly and cytopenia were plotted. We conclude that it is necessary to consider the three clinical features independently in a clinical staging. This study emphasizes the poor prognosis of cytopenia and splenomegaly and indicates that follow up and treatment should take this feature into account.
INTRODUCTION: Pulmonary sarcoidosis exhibits heterogeneous clinical trajectories ranging from self-limited disease resolution to chronic progressive fibrosis, yet reliable biomarkers capable of distinguishing these disease patterns remain lacking. Whether longitudinal CT-defined sarcoidosis phenotypes are associated with distinct circulating molecular signatures remains unknown. METHODS: We performed high-throughput plasma proteomics (SomaScan 11K) in participants with pulmonary sarcoidosis classified into longitudinal chest CT-defined progressive fibrosis, progressive nodular inflammatory disease, or resolving disease trajectories, along with healthy controls. CT phenotypes were assigned based on predefined longitudinal changes in reticulation, traction bronchiectasis, nodular involvement, and mediastinal lymphadenopathy across serial CT scans. One plasma sample per participant was selected from the study visit corresponding to the CT time point at which criteria for the assigned longitudinal phenotype were met. Principal component analysis, hierarchical clustering, pathway enrichment, and correlation-based analyses linking protein expression to quantitative CT features were used to evaluate whether distinct longitudinal CT phenotypes were associated with divergent proteomic signatures. RESULTS: Principal component analysis and hierarchical clustering suggested partial segregation by CT-defined phenotype. Longitudinal CT phenotypes were associated with distinct pathway-level proteomic signatures, with progressive fibrosis enriched for epithelial-mesenchymal transition signaling, and progressive nodular inflammatory disease enriched for mTORC1, MYC, oxidative phosphorylation, adipogenesis, and fatty acid metabolism pathways. Correlation analyses showed coordinated protein-expression patterns associated with fibrotic CT features and mediastinal lymph node enlargement. DISCUSSION: These findings suggest that longitudinal CT-defined fibrotic and inflammatory sarcoidosis phenotypes are associated with distinct pathway-level proteomic signatures. This pilot study provides preliminary proof-of-concept evidence that integrating longitudinal CT imaging phenotypes with plasma proteomics may serve as a framework for future mechanistic studies and biomarker discovery in pulmonary sarcoidosis.
Skinfold measurements (triceps, subscapular, suprailiac and medial calf) in four samples (376 boys, 352 girs, 338 men and 380 women from rural Colombia) were subjected to principal components analysis to identify components of obesity and relative fat patterning. Three components emerged which were similar in the four samples: a first component of fatness explaining 70-80% of the variance and two fat pattern components each explaining 10-15% of the variance: trunk-extremity and upper-lower body. Fatness and the trunk-extremity pattern components changed with age in children (7-12 years), but none of the components changed with age in adults (25-60+). The fatter tended to be more patterned in both age groups. Canonical correlation analysis revealed that socioeconomic status was more related to fatness than to patterning. With the exception of brothers, all first degree relatives (sib, parent-off-spring) and spouses were correlated in fatness. Some of the correlations between relatives--usually sibs, but not spouses--were also significant for the pattern components, suggesting a genetic basis for the known stability of this characteristic (Garn, '55a). Principal components analysis is a useful multivariate alternative for quantitative studies of anthropometric patterning.
This study aimed to integrate multiple datasets for the identification of atrial fibrillation (AF)-related differentially expressed genes (DEGs), analyze their underlying mechanisms through functional enrichment and machine learning, construct diagnostic models, and explore immune-metabolic interactions to provide novel biomarkers and theoretical foundations. Gene expression datasets were integrated and normalized, with batch effects removed using principal component analysis. Differential expression analysis, functional enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways), and machine learning-based feature gene selection and model construction were performed. Shapley additive explanations analysis was utilized to interpret the constructed models, while gene set enrichment analysis, gene set variation analysis, and immune cell infiltration analysis were conducted to investigate the associations between feature genes and immune infiltration. After integrating and normalizing gene expression data and eliminating batch effects via principal component analysis, 6 DEGs were identified, including 4 upregulated and 2 down-regulated ones. Functional enrichment analysis showed these DEGs were significantly enriched in neuro-related biological processes and pathways, indicating their key roles in AF pathogenesis. Five key feature genes were selected using LASSO, random forest, and support vector machine-recursive feature elimination algorithms. They had significant expression differences between the AF and control groups (P < .001) and were located on distinct chromosomes. The constructed random forest and support vector machine models performed excellently (area under the curve ≥ 0.85). Shapley additive explanations analysis revealed TNNI1 contributed most to model prediction, with its expression significantly positively correlated with immune cell infiltration. Gene set enrichment analysis and gene set variation analysis analyses further showed feature genes participated in AF pathogenesis by regulating immune modulation, metabolic pathways, and autophagy. Immune cell infiltration analysis found altered proportions of T-cell subsets and M0 macrophages in the AF group, along with complex links between feature gene expression and immune cell function. This study systematically elucidated the unique gene expression patterns and key regulatory pathways associated with AF, clarifying the crucial roles of feature genes in immune regulation, metabolic imbalance, and cellular dysfunction. These findings provide a theoretical basis and potential therapeutic targets for understanding AF pathogenesis and developing targeted treatment strategies.
PURPOSE: Primary mitochondrial diseases (PMD) arise from variants in the mitochondrial or nuclear genomes. Phenotype-based recognition of specific PMD genotypes remains difficult, prolonging the diagnostic odyssey. We expanded the MitoPhen database to characterize phenotypic variation across PMD more systematically. METHODS: Individual-level data on mitochondrial DNA disorders, nuclear-encoded mitochondrial diseases, and single large-scale mitochondrial DNA deletions were manually curated with Human Phenotype Ontology (HPO) terms to produce MitoPhen v2. Principal-component analysis summarized system-level abnormalities; HPO-level enrichment and mean phenotype-similarity scores were then used to distinguish common PMD genotypes. RESULTS: MitoPhen v2 adds 3940 individuals to the original release, now encompassing 1597 publications, 10,626 individuals, and 117 genotypes. Among 7586 affected cases, 72,861 HPO terms were recorded. Principal-component analysis revealed 6 phenotype dimensions capturing most system-level variance. At the HPO level, we observed genotype-specific enrichments and identified 111 gene-phenotype links absent from the current HPO database. Using MT-TL1, single large-scale mitochondrial DNA deletions, and POLG as exemplars, phenotype-similarity scores reliably separated individuals with these genotypes from those without. CONCLUSION: MitoPhen v2 enabled systematic, genotype-aware analysis of heterogeneous PMD phenotypes and highlighted the diagnostic value of structured, individual-level data. Phenotype-similarity metrics from such data sets can refine variant interpretation in large rare-disease cohorts and provide a transferable framework for other phenotypically complex genetic disorders.