[Human science. Awareness (1). Behavior and awareness - definition of awareness].
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Awareness↗
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CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov-Arnold network.
MOTIVATION: The mapping from codon to amino acid is surjective due to codon degeneracy, suggesting that codon space might harbor higher information content. Embeddings from the codon language model have recently demonstrated success in various protein downstream tasks. However, predictive models for residue-level tasks such as phosphorylation sites, arguably the most studied Post-Translational Modification (PTM), and PTM sites prediction in general, have predominantly relied on representations in amino acid space. RESULTS: We introduce a novel approach for predicting phosphorylation sites by utilizing codon-level information through embeddings from the codon adaptation language model (CaLM), trained on protein-coding DNA sequences. Protein sequences are first reverse-translated into reliable coding sequences by mapping UniProt sequences to their corresponding NCBI reference sequences and extracting the exact coding sequences from their GenBank format using a dynamic programming-based global pairwise alignment. The resulting coding sequences are encoded using the CaLM encoder to generate codon-aware embeddings, which are subsequently integrated with amino acid-aware embeddings obtained from a protein language model, through an early fusion strategy. Next, a window-level representation of the site of interest, retaining the full sequence context, is constructed from the fused embeddings. A ConvBiGRU network extracts feature maps that capture spatiotemporal correlations between proximal residues within the window. This is followed by a prediction head based on a Kolmogorov-Arnold network (KAN) using the derivative of gaussian wavelet transform to generate the inference for the site. The overall model, dubbed CaLMPhosKAN, performs better than the existing approaches across multiple datasets. AVAILABILITY AND IMPLEMENTATION: CaLMPhosKAN is publicly available at https://github.com/KCLabMTU/CaLMPhosKAN.
Codon↗
[Human science. Awareness (2). Awareness and psychophysiological problems].
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Awareness↗
[Human science. Self-awareness. (3). Awareness of the ego].
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Ego↗
Awareness in Gestalt sex therapy.
Awareness is conceived to be selective, curative, a method, a prescription for ideal living, and a ground for human existence. In this paper the following gestalt awareness methods are described: continuum of awareness, awareness questions, biobehavioral feedback, directed awareness, concentration, present-centering, taking responsibilty, and shuttles in awareness. The use of these methods is illustrated in a gestalt therapy dialogue. The application of awareness as concept and method to sensate focus and to the treatment of the prematurely ejaculating male is discussed. Shuttles in awareness and the shared continua of awareness are introduced as promising new methods in the treatment of sexual dysfunction and as enhancing sexual pleasure and communion.
Awareness↗
From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.
PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.
Humans↗
Primary ACL Repair and Reconstruction in Isolated ACL Ruptures: Forgotten Joint Scores and the Association Between Residual Laxity and Joint Awareness.
BACKGROUND: Primary anterior cruciate ligament (ACL) repair has recently reemerged as a treatment option for carefully selected proximal ACL tears. However, evidence regarding patient-reported joint awareness and the relationship between postoperative laxity and joint awareness remains limited. PURPOSE: To compare joint awareness, clinical outcomes, and postoperative laxity between primary ACL repair and hamstring tendon autograft reconstruction in carefully selected patients with isolated ACL rupture, and to explore the association between residual laxity and postoperative joint awareness. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: This retrospective cohort study included 85 patients with isolated ACL rupture treated with either primary ACL repair (n = 26) or hamstring autograft reconstruction (n = 59), with a minimum follow-up of 24 months. Clinical outcomes, including visual analog scale score, Lysholm score, International Knee Documentation Committee (IKDC) score, Tegner activity scale score, postoperative knee laxity, return to sport, and rerupture rates, were evaluated. The authors also used the Forgotten Joint Score-12 (FJS-12), a measure of joint awareness, to evaluate patients. A higher score reflects lower joint awareness, suggesting function more similar to a native knee. Multivariable regression analyses were performed to evaluate variables associated with postoperative FJS-12 values. RESULTS: No differences were observed between groups in postoperative Lysholm, IKDC, and Tegner activity scale scores; Lachman- and pivot-shift-assessed postoperative laxity; and return-to-sport rates. However, postoperative FJS-12 values were significantly higher in the repair group compared with the reconstruction group (87.0 ± 15.0 vs 77.5 ± 14.2; mean difference, 9.5 points [95% CI, 2.8-16.3]; P = .006), corresponding to a moderate effect size (Cohen d = 0.66). Secondary exploratory regression analyses demonstrated that residual postoperative laxity was associated with lower postoperative FJS-12 values in both Lachman- and pivot-shift-based models (R2 = 0.649 and 0.680, respectively; P < .001 for both). CONCLUSION: In carefully selected patients with proximal ACL tears and adequate tissue quality, no significant between-group differences were detected in conventional clinical outcomes, postoperative laxity, return-to-sport rates, or rerupture rates between primary ACL repair and reconstruction. Primary ACL repair was associated with higher postoperative FJS-12 values at short- to midterm follow-up, suggesting function more similar to that of a native knee. Residual postoperative laxity was associated with lower FJS-12 values in secondary exploratory analyses.
Humans↗
Self-awareness and transgression in children: two field studies.
Two field studies explored the relationship between self-awareness and transgressive behavior. In the first study, 363 Halloween trick-or-treaters were instructed to only take one candy. Self-awareness induced by the presence of a mirror placed behind the candy bowl decreased transgression rates for children who had been individuated by asking them their name and address, but did not affect the behavior of children left anonymous. Self-awareness influenced older but not younger children. Naturally occurring standards instituted by the behavior of the first child to approach the candy bowl in each group were shown to interact with the experimenter's verbally stated standard. The behavior of 349 subjects in the second study replicated the findings in the first study. Additionally, when no standard was stated by the experimenter, children took more candy when not self-aware than when self-aware.
Awareness↗
Body awareness and personality.
The relation between personality characteristics and body awareness, defined as the attention paid to different body zones and measured by means of the Fisher Body Focus Questionnaire, is examined in two ways in groups of medical and dental students: (1) Our results replicate fairly well the relation, reported by Fisher, between back and head awareness and anal characteristics. (2) Exploration of the relations between body awareness and descriptive personality characteristics (neuroticism, extraversion, etc.) reveals differences between sexes: in women back awareness correlates positively with neuroticism and negatively with extraversion; in men higher awareness of the right side of the body is related to lower neuroticism but also to higher scores for test-taking attitude and social desirability. Some implications for our understanding of the position of the body and for psychosomatic research are briefly discussed.
Adult↗
Awareness and disengagement in cancer patients.
The authors found that cancer patients (N = 44) did not differ from patients with other chronic illnesses (N = 27) with respect to awareness of their condition or ratings on an unobtrusive, nonverbal measure of disengagement. Cancer patients who were aware were more engaged than those who were not, but this was equally true for the noncancer patients. Awareness, for the cancer patients, was not associated with frequency of visiting or with living for a longer or shorter period than expected. There was a significant interaction, however, in that patients who were aware lived longer if they were engaged, whereas patients who were unaware lived longer if they were disengaged. Caution and judgment should be exercised in sharing information with terminally ill patients because awareness may be beneficial for some but not for all.
Aged↗
PheBee: A Graph-Aware System for Scalable, Traceable, and Semantic Phenotyping.
OBJECTIVES: Phenotype-driven workflows in clinical and translational research require standardized ontology-based representation, ontology-aware cohort discovery, and provenance inspection for each assertion. Existing approaches optimize either for semantic traversal or scalable batch analytics, but not both. We describe PheBee, a hybrid system that links semantic assertions to scalable evidence storage via a deterministic identifier, preserving provenance while supporting ontology-aware discovery at cohort scale. MATERIALS AND METHODS: PheBee represents phenotype assertions in a knowledge graph as ontology-linked nodes with clinical modifier context (e.g., negated, family history), and stores supporting evidence records in a scalable row-oriented evidence table for cohort-scale access. The two layers are connected by a deterministic identifier enabling stable joins across repeated ingestions without duplicating high-volume evidence in the graph. We evaluated PheBee using synthetic datasets designed to exercise end-to-end ingestion and query workflows. RESULTS: Functional evaluation validated hierarchical term expansion, qualifier-aware retrieval, duplicate-free assertion handling under re-ingestion, and privacy-conscious management of subjects shared across multiple research projects. At scale (10,000 subjects producing 12M evidence records) PheBee completed ingestion in ~30 minutes and responded to interactive queries within 6 seconds under concurrent load. DISCUSSION: PheBee exposes a unified API for ontology-aware cohort discovery with hierarchical term expansion, subject-centric retrieval of phenotypes and clinical modifiers, and evidence and provenance queries. Its data model aligns with GA4GH Phenopackets, facilitating interoperability with phenotype exchange standards. CONCLUSION: By combining ontology-aware semantics with scalable, provenance-bearing evidence storage, PheBee provides a practical open-source foundation for phenotype-driven research workflows that demand both semantic precision and cohort-scale traceability.
cohort studies↗
A leakage-aware genomic prediction pipeline for meropenem resistance in Klebsiella pneumoniae using transformer-based resistome representation learning.
MOTIVATION: Antimicrobial resistance (AMR) in Klebsiella pneumoniae, particularly to carbapenems such as meropenem, is a major global health problem. Machine learning is increasingly used to predict resistance from genomic markers; however, many models fail to capture high-level gene-gene interactions and may exhibit inflated performance due to lineage-biased prediction. Existing genomic prediction models largely rely on flat feature representations that fail to capture epistatic gene interactions, and commonly suffer from inflated performance estimates due to phylogenetic data leakage. To address these limitations simultaneously, a leakage-aware hybrid TabTransformer-CatBoost pipeline was developed, combining self-attention-based resistome representation learning with gradient boosting classification under clade-aware data partitioning. A self-attention encoder converts sparse gene presence-absence profiles into contextualized latent embeddings, which are subsequently classified using gradient boosting to capture lineage-aware AMR patterns. RESULTS: The proposed architecture outperformed classical baselines including Logistic Regression, Random Forest, XGBoost, and optimized CatBoost models. Internal accuracy reached 92.59% for the Chained Hybrid configuration (area under the receiver operating characteristic curve, AUROC = 0.8670, F1 = 0.8537). Performance gains primarily originated from the embedding stage, as confirmed by ablation analysis. External validation across independent multinational cohorts (n = 305) demonstrated generalizability (AUROC = 0.8105; F1 = 0.7552). Permutation testing produced near-zero Matthews Correlation Coefficient (MCC) = 0.0091, indicating predictions reflect genuine biological signal rather than noise. These results establish attention-based genomic embedding with gradient boosting as a scalable, interpretable, and leakage-aware framework for clinical AMR prediction. AVAILABILITY AND IMPLEMENTATION: The source code for the TabTransformer-CatBoost framework, including preprocessing pipelines and pre-trained embeddings, is available at https://github.com/SibelKervanci/kp-meropenem-tabtransformer.
Journal Article↗
Awareness, muscle relaxants and balanced anaesthesia.
The incidence of awareness during insufficient anaesthesia is reported to be one per cent. It is usually due to the use of muscle relaxants, a balanced technique and the lightest possible depth of anaesthesia. Increased incidences were noted in open-heart surgery, during intubation-endoscopy procedures and in caesarean delivery patients. Experiences of awareness are disturbing to patients, who are usually benefited by a sympathetic and forthright explanation of the event. Fourteen representative cases of the problem are reported. Since no adequate sign or test exists for detection of awareness during very light anaesthesia or with associated paralysis, more meticulous attention is required in using relaxants or the balanced technique. Greater anaesthetic supplementation and reduction in the use of relaxants are recommended to halt the recurrence of this most serious anaesthetic problem.
Adult↗
Autonomic classical conditioning as a function of awareness of stimulus contingencies.
Two groups of 32 college students were presented compound CSs (lights and tones presented simultaneously) during a classical conditioning paradigm. By means of a masking task and verbal instructions, a partially informed group was made aware of only the visual CS's contingency with the UCS, while a fully informed group was made aware of both the visual and auditory contingencies. Autonomic indices of conditioning (electrodermal responses, heart rate, and digital pulse volume) were later measured to the individual component CSs and to various compound CSs. It was found that: (1) the partially informed group exhibited conditioning exclusively to the visual CS+ and to compounds which included the visual CS+, while (2) the fully informed group exhibited conditioning to both visual and auditory CS+s. The results confirm the importance of awareness in human autonomic discrimination classical conditioning. It is suggested that human autonomic conditioning may be usefully conceptualized as an information processing task with the autonomic indices of conditioning reflecting central cognitive processes.
Acoustic Stimulation↗
SeqQC-former: A sequence-quality fusion framework for QC-aware review prioritization of candidate somatic SNVs in cancer genomics.
The accurate prioritization of candidate somatic single-nucleotide variants (SNVs) remains a challenge due to the substantial variability in sequencing quality across genomic loci. SeqQC-Former is a sequence-quality fusion framework that integrates the local nucleotide context with read-level quality-control (QC) covariates derived from matched tumor-normal sequencing data. This integration generates QC-aware prioritization scores for the downstream review of candidate variants. Unlike conventional variant callers, SeqQC-Former is designed not to infer biological truth but to support post-calling review and prioritization under heterogeneous sequencing conditions. The framework was trained and evaluated on a SEQC2-derived dataset comprising 89,447 candidate loci, including 1378 positive and 88,069 negative loci. In chromosome-held-out validation, which aims to reduce potential genomic-position leakage, SeqQC-Former demonstrated strong discrimination (AUROC = 0.9479; AUPRC = 0.9448), indicating good generalization to previously unseen chromosomes. Given that the SEQC2-derived labels contain QC-associated information; these results should be interpreted as an evaluation of QC-aware prioritization capability rather than an independent validation of biological variant correctness. Ablation analyses revealed that structured QC covariates provided the dominant predictive signal under the current SEQC2-derived labeling regime. SeqQC-Former achieved a significantly higher AUROC than classical machine-learning baselines, as determined by DeLong's test (p < 0.01). Application to 53,164 glioblastoma variants demonstrated that external predictions were sensitive to QC scaling and threshold selection, underscoring that model outputs should be interpreted as QC-dependent prioritization scores rather than calibrated probabilities or definitive biological classifications. Overall, SeqQC-Former offers a reproducible post-calling QC-aware prioritization framework for large-scale somatic SNV review and underscores the importance of explicitly modeling sequencing-quality information when interpreting structured cancer genomics datasets.
Humans↗
Bladder cancer in rubber workers. Do screening and doctors' awareness distort the statistics?
The use of recognised carcinogens in the rubber industry before 1950 led to the introduction of screening progammes offering urinary cytology to workers who had been exposed. Publicity given to the introduction of these programmes and to individual claims for compensation have increased medical practitioners' awareness of a relationship between work and the industry and the subsequent development of bladder cancer. In this study 27 rubber workers and 88 controls registered in 1966 and 1967 with bladder cancer have been followed. A comparison of their death-rates and of the relative frequency of bladder cancer recorded on the death certificates should indicate whether cytological screening or doctors' awareness might explain a recent rise in the bladder-cancer death-rate in this industry. Since the proportions of rubber workers and controls who died before 1976 were similar (74% and 73% respectively) and bladder cancer was mentioned with similar frequence on their death certificates (80% and 83% respectively) neither screening nor doctor's awareness would appear to have an important influence.
Adenocarcinoma↗
A modular class-aware workflow for small RNA sequencing analysis using mouse sperm as a case study.
BACKGROUND: Small RNA sequencing analysis is challenging because RNA classes differ in biogenesis, sequence redundancy, genomic organization, and annotation reliability. Integrated workflows accommodating these constraints remain limited, particularly for fragment-level and cluster-level analysis. METHODS: We present a reproducible, containerized, class-aware workflow for small RNA sequencing analysis, using mouse sperm as a case study. The workflow combines standardized preprocessing with complementary annotation and quantification strategies for microRNAs (miRNAs), transfer RNA-derived small RNAs (tsRNAs), ribosomal RNA-derived small RNAs (rsRNAs), and PIWI-interacting RNA (piRNA)-enriched genomic clusters. Using sperm small RNA data from offspring of lipopolysaccharide (LPS)-exposed male mice, we compared integrated-reference mapping, multi-class annotation, fragment-level tsRNA profiling, and genome-based piRNA cluster analysis, with custom modules for locus-aware harmonization and condition-specific cluster analysis. RESULTS: Integrated-reference mapping aligned 88.17% of reads and retained 690 features after filtering. It identified 11 differentially expressed miRNAs between LPS and controls, while other classes showed limited signal. Fragment-level profiling improved tsRNA resolution. piRNA cluster analysis identified 958 control and 940 LPS clusters, with 18 control-specific and no LPS-specific clusters. CONCLUSION: This workflow supports transparent, reproducible, class-aware interpretation of small RNA sequencing data while emphasizing cautious interpretation of piRNA-enriched signals from total small RNA sequencing.
Small non-coding RNA analysis↗
Prevalence and awareness of malocclusion in Swedish men.
Previous orthodontic treatment, the awareness of malocclusion, the demand for orthodontic treatment and the prevalence of malocclusion were studied in 389 Swedish men, aged 21-54 years (mean age 32 years). Nine percent had been treated with an orthodontic appliance and 15% reported that permanent teeth had been extracted on orthodontic indications. Malposition of teeth was found in 75%, with rotation as the most common type of malposition. Crowding was recorded in 43% and spacing in 18%. Fifty-seven percent had some occlusal anomaly. The need for orthodontic treatment was rated on a four-point scale. It was found that 76% were in need of treatment. The need for treatment was only slight in half of the men but moderate to urgent in 25% of the sample. About a quarter of the men were aware of malposition of front teeth, equally often for maxillary and mandibular teeth, but only about 1% were aware of malposition of posterior teeth. Only a few percent thought they were in need of orthodontic treatment. The presence of malocclusion was correlated to age, place of birth and educational level. This might perhaps be a consequence of tooth loss.
Adult↗