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Understanding and implementing family-centered care becomes easier as nurses are exposed to both the concept and examples of the concept in practice. An annotated bibliography of articles, books, films, training materials, and newsletters will be useful to individual nurses, nurse-educators, and nurse administrators.
SBASE 3.0 is the third release of SBASE, a collection of annotated protein domain sequences. SBASE entries represent various structural, functional, ligand-binding and topogenic segments of proteins as defined by their publishing authors. SBASE can be used for establishing domain homologies using different database-search tools such as FASTA [Lipman and Pearson (1985) Science, 227, 1436-1441], and BLAST3 [Altschul and Lipman (1990) Proc. Natl. Acad. Sci. USA, 87, 5509-5513] which is especially useful in the case of loosely defined domain types for which efficient consensus patterns can not be established. The present release contains 41,749 entries provided with standardized names and cross-referenced to the major protein and nucleic acid databanks as well as to the PROSITE catalogue of protein sequence patterns. The entries are clustered into 2285 groups using the BLAST algorithm for computing similarity measures. SBASE 3.0 is freely available on request to the authors or by anonymous 'ftp' file transfer from < ftp.icgeb.trieste.it >. Individual records can be retrieved with the gopher server at < icgeb.trieste.it > and with a www-server at < http:@www.icgeb.trieste.it >. Automated searching of SBASE by BLAST can be carried out with the electronic mail server < sbase@icgeb.trieste.it >. Another mail server < domain@hubi.abc.hu > assigns SBASE domain homologies on the basis of SWISS-PROT searches. A comparison of pertinent search strategies is presented.
To facilitate future research efforts, an annotated bibliography summarizing the existing pediatric human immunodeficiency virus and acquired immunodeficiency syndrome psychosocial literature was developed. This guide for researchers should be useful in developing studies in this area. Three strategies were used to identify articles that were classified by topic and categorized as data based or non-data based. The article concludes with an examination of the methodologic issues relevant to pediatric human immunodeficiency virus and acquired immunodeficiency syndrome psychosocial research.
The present study is an annotated list of the marine crustaceans (Decapoda and Stomatopoda) from Golfo Dulce, Costa Rica, collected during the RV Victor Hensen Cruise 1993-1994, at depths ranging from 20 to 260 m. Stomatopoda was represented by one family and two species. Decapoda was represented by 12 families and 21 species. Two new records for Costa Rica, Cancer johngarthi and Lysmata californica are reported. This increases the reported marine crustaceans of Golfo Dulce to three species of Stomatopoda and sixty-six of Decapoda (a complete checklist in included). A list of species reported in the literature from the gulf is also included.
Useful clinical strategies are adaptive, specifying the sequence of treatments that are alternatives, what it means for the treatment to "work," the rules for abandoning a treatment, and the subsequent treatments. Because combinatorial complexity precludes comparison of every possible whole strategy, current experiment-based methods rely on comparisons among a few options at particularly crucial decision points, and strategies are pieced together from scraps of information. Nonexperimental methods for strategy development offer a seductive alternative, but their advantages may be illusory. Clinical investigators deploy a wide range of study designs to compare treatment strategies in mental health. This article organizes the types of designs by their purpose and annotates this list with comments on the strengths and weaknesses of each type. We conclude with some general comments on the overall process of development of treatment strategies.
Next-Generation Sequencing (NGS), also known as high-throughput sequencing technologies, has enabled rapid and efficient sequencing of large amounts of DNA and RNA. These technologies have revolutionized the field of genomics, transcriptomics, and proteomics and have been widely used in cancer research, leading to advances in clinical diagnosis and treatment. Improvements in the NGS technologies enabled millions of fragments to be sequenced simultaneously in a time- and cost-effective manner and resulted in large amount of genomic data which require efficient analysis methods. Analysis of the genomic data requires both efficient computer resources and bioinformatics approaches. This chapter details a comprehensive computational approach and analysis steps for genomic data analysis.
PURPOSE: Identifying the pathogenic variant in a patient with rare disease (RD) is the first step in ending their diagnostic odyssey. De novo (Dn) variants affecting protein-coding DNA are a well-established cause of Mendelian disorders in patients with RD. Constrained coding regions (CCRs) are specific segments of coding DNA that are devoid of functional variants in healthy individuals. METHODS: We evaluated the diagnostic utility of incorporating combined Dn/CCR status into the variant prioritization cascade for patients with RD that have undergone genomic sequencing. Using the Genomics England 100,000 Genomes Project v12, we selected 3090 trios that have undergone diagnostic evaluation and been analyzed with an advanced Dn identification pipeline. RESULTS: Our analysis shows that the diagnostic rate increased from 71% in the full cohort to 87% for Dn/CCR variants. Of note, manual evaluation of the Dn/CCR variants from undiagnosed patients with clinical follow-up revealed a diagnosis for 13 further patients. This outcome increases the diagnostic rate for Dn/CCR variants to 91% and suggests that the application of this metric can prioritize diagnostic variants in undiagnosed patients. CONCLUSION: We demonstrate the potential clinical utility of performing bespoke Dn analyses of patients with RD and for incorporating CCR information into the filtering cascade to prioritize pathogenic variants.
MOTIVATION: Rare diseases collectively affect 5% of the population. However, fewer than 50% of rare disease patients receive a molecular diagnosis after whole genome sequencing. Supervised machine learning is a valuable approach for the pathogenicity scoring of human genetic variants. However, existing methods are often trained on curated but limited central repositories, resulting in poor accuracy when tested on external cohorts. Yet, large collections of variants generated at hospitals and research institutions remain inaccessible to machine-learning purposes because of privacy and legal constraints. Federated learning (FL) algorithms have been recently developed enabling institutions to collaboratively train models without sharing their local datasets. RESULTS: Here, we present a proof-of-concept study evaluating the effectiveness of FL for the clinical classification of genetic variants. A comprehensive array of diverse FL strategies was assessed for coding and non-coding Single Nucleotide Variants as well as Copy Number Variants. Our results showed that federated models generally achieved comparable or superior performance to traditional centralized learning. In addition, federated models reached a robust generalization to independent sets with smaller data fractions as compared to their centralized model counterparts. Our findings support the adoption of FL to establish secure multi-institutional collaborations in human variant interpretation. AVAILABILITY AND IMPLEMENTATION: All source code required to reproduce the results presented in this article, implemented in Python, is available under the GNU General Public License v3 at https://github.com/RausellLab/FedLearnVar.
Hemileia vastatrix is the fungal pathogen responsible for coffee leaf rust (CLR), the most economically important disease of Coffea arabica worldwide. Recently, the nuclear genome of this fungus was completely deciphered. However, the mitochondrial genome of H. vastatrix has remained undercharacterized. Here, we present the complete, circularized mitochondrial genome of H. vastatrix Race I (isolate HvRI), assembled using a hybrid approach combining PacBio HiFi long reads and BGIseq short reads. The genome is 173,525 bp in length with a GC content of 33.1% and encodes 41 functional genes, including 15 protein-coding genes, 2 rRNAs, and 24 tRNAs. The assembly reveals significant structural complexity, driven by intron expansion in the cox1 and cob genes. Notably, the atp8 gene contains a group II intron, rare for this locus, whose internal open reading frame displays evidence of pseudogenization via internal stop codons.. We also characterized a putative replication initiation zone (~1.2 kb) defined by a poly-G homopolymer and conserved regulatory motifs. The mitogenome of the HvRI isolate does not contain cob mutations that lead to amino acid substitutions G143A and F129L associated with the quinone outside inhibitor (QoI) fungicide resistance. This high-quality mitogenome is an important resource for comparative mitogenomics, population diversity studies, and the molecular surveillance of QoI fungicide resistance.
For several years the Research Diagnostic Criteria (RDC) have been used widely by investigators to select and describe research subjects. These criteria were used as the initial basis for the specified diagnostic criteria for the major diagnostic categories of DSM-III. With the availability of DSM-III in early 1980, research investigators involved in ongoing studies using the RDC and those planning future studies need to understand the relationship between these two systems so that they can make an informed decision about the use of these systems in their work. We compared each of the RDC categories with the corresponding DSM-III categories and determined major differences in the way the systems define many of the categories and the reasons form these differences. We delineated some of the issues that need to be considered when making decisions about which sets of criteria to use in research studies.
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Genuine anorexia nervosa starting in the elderly is thought relatively uncommon. Some previously reported cases may have been elderly depressives with loss of appetite rather than true eating disorder. The condition also has to be distinguished from "late onset" anorexia in mature but younger women. Two illustrative patients are briefly reported. Some possible psychological mechanisms in this syndrome are discussed in the context of the relatively small total number of previously reported single cases.
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A method (three-dimensional position-specific scoring matrix, 3D-PSSM) to recognise remote protein sequence homologues is described. The method combines the power of multiple sequence profiles with knowledge of protein structure to provide enhanced recognition and thus functional assignment of newly sequenced genomes. The method uses structural alignments of homologous proteins of similar three-dimensional structure in the structural classification of proteins (SCOP) database to obtain a structural equivalence of residues. These equivalences are used to extend multiply aligned sequences obtained by standard sequence searches. The resulting large superfamily-based multiple alignment is converted into a PSSM. Combined with secondary structure matching and solvation potentials, 3D-PSSM can recognise structural and functional relationships beyond state-of-the-art sequence methods. In a cross-validated benchmark on 136 homologous relationships unambiguously undetectable by position-specific iterated basic local alignment search tool (PSI-Blast), 3D-PSSM can confidently assign 18 %. The method was applied to the remaining unassigned regions of the Mycoplasma genitalium genome and an additional 13 regions were assigned with 95 % confidence. 3D-PSSM is available to the community as a web server: http://www.bmm.icnet.uk/servers/3dpssm
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