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PubMed1979

An attempted integration of information relevant to schizophrenic subtypes.

The usefulness and validity of traditional subtypes are questionable. The subtypes described in earlier years no longer emerge with the clarity previously described. The four classical subtypes cannot be reliably distinguished and have not been shown to have predictive validity. Subtypes classified along course or prognostic lines may be more clinically useful. Attempts to subdivide schizophrenia along biologic and genetic lines offer promise. Recent efforts to describe new subdivisions of schizophrenia are readily justified, but new descriptive subtypes are likely to prove useful only when validated by biological, genetic, treatment response, and outcome data.

Adult↗
PubMed1975

Integration of information in a clinical judgment task, an empirical comparison of six models.

Six models were compared for their effectiveness in reproducing six clinical psychologists' judgments of 38 patients on intelligence, ability to establish contact, and control of affect and impulses. In two of the models, subjective weights were used in the prediction of a judge's ratings. The judges based their judgments solely on verbal protocols from the Rorschach, a sentence completion test, and the Thematic Apperception test. The stability of the linear aspect of the judgment process was very high but decreased as the depth of interpretation of the rating variable increased. The nonlinear aspect of the judgment process had considerably low stability. In general, a model based on subjective weights was most effective in reproducing the judges' ratings.

Adolescent↗
PubMed1978

Comment on internal feedback as a theory of judgment: a reply to Levin.

Levin's suggestion that internal feedback strategies be employed in judgmental and learning tasks is discussed. The predictions of an internal feedback notion are seen as inconsistent with Veit's ratio and difference task data. Scale-free frameworks and scale-convergence criteria used in previous research are described as useful techniques for separating integration from judgmental processes in information-integration as well as learning-task situations.

Feedback↗
PubMed1978

Testing toxic substances for protection of the environment.

The Toxic Substances Control Act requires pre-production testing of chemicals for potential hazards to human and environmental health. Effective control of chemicals requires evaluations of chemical hazard that go beyond determinations of toxicity to humans to include the effects, transport, and fat of chemicals in the environemnt. Formulation of meaningful hazard evaluations depends on integrating information from tests of chemical effects, transport, and fate or by developing testing tools that integrate these factors during experimentation. Chemical effects may be acute or chronic and they may be observed individual organisms, populations or organisms, or in total ecosystems. Chemical transport through the environment depends on physico-chemical characteristics of the chemical and the medium (soil, water, or air) as well as environmental factors and biotic processes. The ultimate fate of chemicals (persistence, transformation, or degradation) is determined by numerous physical and biological processes occurring in the environment, and must be acknowledged to effectively determine the hazard. Many techniques are available for the separate and routine evaluation of the effects, transport and fate of environmental contaminants. However, separate identification of the importance and magnitude of each of these factors limits their utility in assessments of chemical hazard. The microcosm (model ecosystem) method integrates many of these tests in replicable experimental units, and may provide substantial information on chemical hazard in ecosystem context.

Chemical Phenomena↗
PubMedDate not supplied

Strengthening the public health system.

Although the American public health system has made major contributions to life expectancy for residents of this country over the past century, the system now faces more complex health problems that require comprehensive approaches and increased capacity, particularly in local and State public health agencies. To strengthen the public health system, concerted action is needed to meet these five critical needs: First, the knowledge base of public health workers needs to be supplemented through on-the-job training and continuing education programs. To this end, self-study courses will be expanded, and a network of regional training centers will be established throughout the country. Second, communities need dynamic leadership from public health officials and their agencies. To enhance leadership skills and expand the leadership role of public health agencies, focused personal leadership development activities, including a Public Health Leadership Institute, and national conferences will provide a vision of the future role of public health agencies. Third, local and State public health agencies need access to data on the current health status of the people in their communities and guidance from the nation's public health experts. To improve access to information resources, state-of-the-art technologies will be deployed to create integrated information and communication systems linking all components of the public health system. Fourth, local and State agencies need disease prevention and health promotion plans that target problems and develop strategies and the capacity to address them. To provide communities with structured approaches to this process, planning tools have been developed and distributed, and technical assistance will be provided to local and State health agencies to involve each community in planning,priority setting, and constituency building.Finally, public health agencies need adequate resources to fund prevention programs. To improve the use of existing Federal support and enhance the availability of new community resources, grant programs will be modified, and innovative approaches to local resource enhancement will be developed and shared.Activities in these five key areas are designed to improve the infrastructure of the public health system and its capacity to carry out effectively the core functions of public health assessment, policy development, and assurance of the availability of the benefits of public health. If the nation is to achieve the health objectives for the year 2000, the public health system-the individuals and institutions that, when working effectively together, promote and protect the health of the people-must be strengthened.

Computer Communication Networks↗
PubMed1992

Integrating external clinical information with the ten-step monitoring and evaluation process: from theory to practice.

Traditionally, Sisters of Mercy Health System (SMHS)-St Louis hospitals have had difficulty integrating quality information from external sources into their own monitoring and evaluation activities. This difficulty became apparent at the 14 hospitals of the SMHS when the system headquarters began providing its hospitals with comparative clinical outcome information. Although the hospitals found value in the comparative studies, the information was not fully used in individual hospitals' quality improvement efforts. As a result, SMHS developed a model for integrating external quality information into the local hospitals' ten-step monitoring and evaluation process. This article explains the integration model and shows how it has worked in several clinical scenarios.

Hospital Information Systems↗
PubMed2026

Using the DNA language model, GROVER, to parse effects of sequence, chromatin and regulatory features on genome stability.

MOTIVATION: Genome stability is shaped by DNA sequence and chromatin context, but their relative contributions to double-strand break (DSB) sensitivity remain unclear. RESULTS: We show that the DNA language model, GROVER, can infer DSB location based on sequence. DSB hotspots tend to contain GC-rich sequences that belong to promoters, genes and short interspersed nuclear elements (SINEs). Additionally, we identified several specific short sequences (tokens) that are associated with modulating DSB sensitivity. Another model using chromatin and genome regulatory features outperforms the sequence-only model, highlighting complementary and cell-type specific information. Integrating sequence and genome biological features yields the best performance, demonstrating their synergy. Analyzing this model revealed that, dependent on the sample, genome stability information encoded in H3K36me3 and DNase-seq can be learned from the sequence, but not H3K27ac or H3K9me3. Embedding chromatin data directly into the GROVER architecture enabled cell-type specific modeling with performance matching the full chromatin feature model. Our results suggest that while chromatin and regulatory context provides important information, such as cell-type specificity, much of the information shaping DSB patterns is already encoded in the DNA sequence itself. Our integrative modeling approach not only reveals DSB patterns but also provides a generalizable strategy for tracing predictions in genomic data. AVAILABILITY: Data, models, and a tutorial are available on Zenodo.

Chromatin↗
PubMed1979

[An analysis of moral judgments in impression formation (author's transl)].

This experiment was designed to test the assumption of additive information integration in moral judgment. 35 subjects gave punishment ratings for descriptions that varied in kind of offence, information about previous conviction and personality characteristics. The data, analysed by Anova, show regular deviations from additivity.

Analysis of Variance↗
PubMed2026

Conditional Diffusion Model-Based Method for Annotation of Antibiotic Resistance Gene Properties.

The crisis of bacterial antibiotic resistance, which has led to a decline in the effectiveness of antibiotics originally used to combat bacterial infections, has emerged as an urgent challenge for public health. Antibiotic resistance genes (ARGs) are one of the key reasons for bacteria to develop resistance to antibiotics. Therefore, accurately identifying and annotating the critical properties of ARGs is of great importance for addressing the antibiotic resistance emergency. Although existing deep learning models demonstrate remarkable effectiveness in extracting local features from sequence data, they still face limitations in the capacity to further gain the enriched latent representations within the data. To address the critical challenge of extracting higher-quality representations from ARGs sequence data, we propose a novel ARGs properties annotation method based on the conditional diffusion model which is used to learn latent representations through domain-specific knowledge injection. Specifically, during the conditional information integration phase, we systematically incorporate ARGs' domain knowledge to guide the diffusion process in generating high-quality latent representations. To overcome information redundancy caused by direct concatenation of conditional information and intermediate features, we design a cross-attention mechanism that enables feature fusion between heterogeneous information sources, thereby enhancing further the quality of obtained representations. Experimental results on widely used data sets demonstrate the framework's effectiveness in achieving superior prediction performance compared to existing methods.

Anti-Bacterial Agents↗
PubMed1978

A test of the schizophrenic's ability to process information in one or two sensory modes.

Twenty-three schizophrenics, ten psychiatric controls, and 17 normal controls were used to test the hypothesis that schizophrenics suffer a deficit in their ability to integrate information from different sensory modes. The task involved identifying auditory, visual, or mixed (auditory and visual) patterns which had previously been equated in difficulty for normal subjects. Mean error scores were greatest for schizophrenics and least for normals with psychiatric controls in between. Moreover, the schizophrenics did equally well whether the task was visual, auditory, or mixed. Thus, schizophrenics showed no deficit specific to the synthesis of information from two different sensory modes.

Adolescent↗
PubMed2025

Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review.

Systems biology is a holistic approach to biological sciences that combines experimental and computational strategies, aimed at integrating information from different scales of biological processes to unravel pathophysiological mechanisms and behaviours. In this scenario, high-throughput technologies have been playing a major role in providing huge amounts of omics data, whose integration would offer unprecedented possibilities in gaining insights on diseases and identifying potential biomarkers. In the present review, we focus on strategies that have been applied in literature to integrate genomics, transcriptomics, proteomics, and metabolomics in the year range 2018-2024. Integration approaches were divided into three main categories: statistical-based approaches, multivariate methods, and machine learning/artificial intelligence techniques. Among them, statistical approaches (mainly based on correlation) were the ones with a slightly higher prevalence, followed by multivariate approaches, and machine learning techniques. Integrating multiple biological layers has shown great potential in uncovering molecular mechanisms, identifying putative biomarkers, and aid classification, most of the time resulting in better performances when compared to single omics analyses. However, significant challenges remain. The high-throughput nature of omics platforms introduces issues such as variable data quality, missing values, collinearity, and dimensionality. These challenges further increase when combining multiple omics datasets, as the complexity and heterogeneity of the data increase with integration. We report different strategies that have been found in literature to cope with these challenges, but some open issues still remain and should be addressed to disclose the full potential of omics integration.

Algorithms↗
PubMedDate not supplied

Implementation of a computerized information system in a long-term care facility.

The successful implementation of computerized nursing information systems requires the completion of many tasks and the participation of many persons. In 1989, Pulliam and Boettcher described a six-step process for introducing computerized information systems into long-term care facilities. This article describes the process, particularly the implementation phase, as it actually happened in a 124-bed facility in a mid-Atlantic state. This facility found that successful implementation requires a systems coordinator who is a professional nurse who understands the needs of the patients, can integrate information with the computer system, and can provide on-going support for the users.

Delaware↗
PubMed1979

Oncogenic transformation of rat lung epitheloid cells by SV 40 DNA and restriction enzyme fragments.

Rat epitheloid lung cells were transformed with various preparations of SV40 dna using the Ca2+-precipitation technique. The amount of SV40 genetic information integrated into transformed clones was evaluated by DNA-DNA renaturation kinetics. The growth properties on plastic and in soft-agar were examined, as well as the ability to induce tumors in syngeneic new-born animals or in adult nude mice. One particular transformed line, which had received the Hpa II/BamH I A (59 per cent) fragment, was found to contain about 3 integrated copies of this fragment per cell and no significant amount of the Hpa II/BamH I B (41 per cent) fragment. This line which grew to high saturation densities and efficiently formed clones in low serum on plastic, produced tumors in both syngeneic rats and nude mice. Thus the Hpa II/BamH I A fragment, which mainly includes early viral information, was sufficient to impart these properties to rat epitheloid lung cells.

Animals↗
PubMed2026

KG-Microbe: Building modular and scalable knowledge graphs for microbiome and microbial sciences.

BACKGROUND: The integration of many disparate forms of data is essential for understanding the microbial world and its interaction with the environment and human health. Doing so is particularly challenging in the context of microbe-host and microbe-microbe interactions that contribute to health or environmental outcomes. There are thousands of relevant microbial species, and millions of interactions among those microbes and with their environment or host. Integrated information (e.g., about host and microbial physiology, genetics, and metabolism) facilitates deeper understanding of complex mechanisms and helps interpret correlative results. RESULTS: The KG-Microbe construction framework is a novel approach to harmonizing bacterial and archaeal data in the form of a findable, accessible, interoperable, reusable and AI-ready knowledge graph (KG). Starting from a core KG with organismal traits, environments, and growth preferences and the integration of established ontologies, the framework generates a hierarchy of related KGs targeting specific use cases, including the human microbiome in the context of disease, or environmental microbiomes. The framework supports customizable taxa subsets representing communities or clades of interest. Evaluations of the KG-Microbe KGs through a series of competency questions demonstrate the accuracy and effectiveness of the data harmonization, and the utility of the resulting KGs in studies of inflammatory bowel disease and Parkinson's disease. Finally, the predictive and environmental capabilities of the KGs are demonstrated by predicting growth preferences using graph features. CONCLUSIONS: The KG-Microbe framework unifies microbial contexts in a single resource to support integrative analyses across biomedical, host, and environmental domains. KG-Microbe is a flexible, modular enabling technology for humans and machine learning methods to uncover candidate mechanistic explanations of microbial associations.

Microbiota↗