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This is a resource and planning guideline for hospitals and physicians. The status of medical instrumentation in peripheral vascular disease diagnosis is reviewed and the application of examination methods to categories of vascular disease discussed. Resour
This updated and expanded planning guideline describes the optimal environment in which cardiac surgery can be performed effectively and safely and suggests criteria for evaluating existing facilities and for long-range hospital planning. The status of cardiac surgery is reviewed and measures are provided for assessing a hospital's ability to support a cardiac surgical service. Recommendations are given for appropriate case loads, administrative arrangements, and professional staff qualifications and relationships. The emerging role of the nurse is considered and requirements are enumerated for allied clinical supporting services. Special criteria are provided for pediatric cardiac surgical units and detailed specifications are given for the hospital's physical plant and equiptment including a protocol for checking the electrical safety of surgical suites. A data base is suggested for taking regular inventory of community cardiac surgical programs.
MOTIVATION: Biodata resources constitute a critical, large-scale, and globally distributed infrastructure underpinning life science research, yet their organic growth has hindered efforts to quantify key indicators needed to justify sustainable support, including usage, impact, and interdependencies. Here, we present an updated Global Biodata Coalition inventory alongside a Total Resource Usage (TRU) dataset that integrates this inventory with two complementary literature-derived sources: data citations and informal resource name mentions extracted from full-text articles using a fine-tuned machine learning model. A unified database schema enables cross-resource comparisons, dependency network analyses, and evaluation of resource name distinctiveness. RESULTS: The combined dataset captures 11.5 million formal and informal references, revealing that most resources are acknowledged informally within article text. Network analysis indicates a densely interconnected ecosystem in which Global Core Biodata Resources function as key providers and integrators, underscoring their foundational role. While full resource names are generally distinctive, widespread use of acronyms limits detectability through text mining. Together, these findings provide robust empirical evidence of a highly utilized and interconnected biodata infrastructure, highlight limitations of single-metric assessments, and underscore the need for multi-dimensional evaluation frameworks and more consistent data citation practices to support informed decision-making and long-term sustainability. AVAILABILITY AND IMPLEMENTATION: The database and analytical code described here are available on https://github.com/globalbiodata.
BACKGROUND AND OBJECTIVES: Antifungal resistance represents an increasing global threat, driven by the rising burden of fungal disease. Antifungal stewardship (AFS) is a critical component of broader antimicrobial resistance (AMR) efforts, but education in this area remains less established than antibacterial stewardship initiatives. The scope and characteristics of the current landscape of online AFS resources have not yet been systematically described. To identify and evaluate online educational resources focused on fungal disease management and AFS, and assess their accessibility, format, educational design and implementation focus. METHODS: A structured search of internet search engines, distribution platforms and organizational websites was conducted to identify English-language web-based resources related to fungal disease management and stewardship. Resources were evaluated using predefined criteria including access model, format, length, educational design, interactivity and AFS content. An overall educational value score (1-10) was assigned. RESULTS: Twenty-three educational resources were identified. Most were delivered as online unfacilitated courses (11, 48%) and were short (<4 h) (12, 52%). Most focused on guidelines and syndromic management (18, 78%) and targeted doctors and/or nurses/midwives (22, 96%). Limited interactivity was reported in nine (39%) courses. Five courses (22%) had either a substantial or comprehensive focus on AFS. CONCLUSIONS: Online AFS educational resources are available and support awareness and knowledge development. However, they remain relatively few in number. Greater emphasis on implementation-focused learning, behaviour change components and broader global representation may enhance their impact.
MOTIVATION: Building and sustaining High-Performance Computing (HPC) infrastructure for bioinformatics research in resource-limited settings presents significant technical, financial and operational challenges. Institutions in low-and middle-income regions often face constraints such as limited technical expertise, unstable infrastructure and restricted funding which can hinder the deployment of large-scale computational platforms necessary for modern genomics and bioinformatics analyses. RESULTS: We present a scalable and modular HPC framework developed at the Uganda Virus Research Institute (UVRI) to support large-scale genomics and other omics data analyses in resource-limited settings. The framework integrates open-source HPC management tools, infrastructure automation, and reproducible configuration management to enable reliable deployment and maintenance. Optimized storage and networking configurations combined with a phased capacity-building strategy support high-throughput genomic workflows while strengthening local technical expertise. From our implementation experience, we derive ten practical design and operational rules that provide a transferable methodology for establishing and sustaining in-house HPC infrastructure. These rules emphasize strategic investment in human capacity, structured planning, leveraging collaborations, adoption of open-source technologies and service management practices to improve operational resilience and long-term sustainability. AVAILABILITY: The design principles, automation strategies and implementation guidelines described in this work are applicable to institutions seeking to establish sustainable HPC resources for bioinformatics research in resource-constrained environments.
Nine-year-old brain tumor patient Gabriella Miller challenged members of Congress to "stop talking and start doing" when providing federal funding for research into cures for pediatric cancer and congenital anomalies. Though she ultimately lost her life to that cancer, her advocacy efforts resulted in the 2014 Gabriella Miller Kids First Research Act, launching the Gabriella Miller Kids First Pediatric Research Program at the National Institutes of Health (NIH). The overarching goal of the Gabriella Miller Kids First Pediatric Research Program is to help researchers uncover new insights into the biology of childhood cancer and congenital anomalies. Following the signing of the Gabriella Miller Kids First Research Act 2.0 in January 2025, the program has been extended at NIH through 2028 to advance the groundwork laid in the program's first ten years. The Gabriella Miller Kids First Data Resource Center has since honored her legacy by building a comprehensive data resource for genomic research into pediatric conditions. Data from more than 30,000 participants annotated with demographic and clinical information related to their diagnoses have been released for secondary research and analysis using the center's web-based platforms. This paper analyzes the outcomes of the initiative and highlights breakthroughs made by the larger research community resulting from the availability of this data resource. We explore the future expansion of the data resource to include new modalities and tools for supporting life-saving research for children like Gabriella Miller.
AIMS: Nurse-led titration (NLT) models of care assist with delivery of guideline directed medical therapy for patients with heart failure with reduced ejection fraction (HFrEF). Effectiveness of NLT is established but there is limited information of characteristics of models, patient outcomes and healthcare resource utilization. To build upon the existing evidence by providing a systematic narrative review of the literature of NLT of medications for patients with HFrEF. This review syntheses characteristics of NLT models of care, patient outcomes and healthcare resource utilization. METHODS AND RESULTS: A systematic narrative literature review with systematic search strategy, identification of results, thematic analysis and narrative synthesis. A search was conducted from 2012 to 2025 in Medline, Cinahl complete, Embase and Cochrane. Sixteen studies of NLT models of care were identified from 1944 screened records. Characteristics of models of care were participation of nurses, multidisciplinary teams, follow-up and common features of service delivery. Patient outcomes of mortality were favourable for those that received NLT. There is some evidence of changes in healthcare resource utilization; studies in which the NLT groups received more HF nurse visits and greater HF medication use also reported reduced rehospitalizations. CONCLUSION: Findings reinforce the published benefits of NLT. Additional studies examining adverse events and quality-of-life outcomes are needed to strengthen the evidence base. Several studies suggest a shift in resource use with NLT, highlighting the need for an economic evaluation to inform a cost-effective model of care.
Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.
Plant viruses affect production through symptom induction in host plants. These symptoms could partially arise from nutrient deprivation: The resource competition hypothesis posits that massive viral replication deprives hosts of essential nutrients, yet direct evidence for phosphorus (P) competition is lacking. Moreover, it is reported that biotic stresses can lead to alterations on P metabolism. Using a hydroponic system enabling separate analysis of shoots and roots in adult Arabidopsis thaliana plants, we investigated whether Turnip mosaic virus (TuMV) drawed significant P internal pools leading to P competition or altered P metabolism. TuMV genomic RNA represented < 0.3% of the P pool allocated to 18S rRNA, refuting the resource competition hypothesis. Instead, TuMV induced a marked shoot-to-root P redistribution: Shoot/Root Pi and Porg changed from 1.7 to 1.04 to 0.71 and 0.68, respectively. This altered partitioning correlated with organ-specific gene expression changes: high-affinity transporters PHT1; 4 and PHT1; 5 were co-induced in shoots, whereas immunity-related PHT1; 4 was uniquely repressed in roots. The senescence-associated gene SEN1 showed opposite regulation between organs (repressed in shoots, induced in roots), distinguishing virus-induced responses from canonical senescence. Multivariate analysis revealed that shoots and roots only partially share physiological and molecular responses to TuMV. The virus reprograms phosphorus metabolism through organ-specific changes, not through resource depletion, and roots act as a distinct hub integrating infection response, senescence, and nutrient dynamics. This study advances the understanding of growth-defense trade-offs in plant mineral nutrition and identifies new targets for maintaining crop productivity under biotic stress.
BACKGROUND: Sickle cell disease (SCD) is an inherited hemoglobinopathy characterized by hemoglobin S production, in which homozygous individuals (HbSS) develop a broad range of acute and chronic complications. While disease-modifying and curative therapies are increasingly available in high-income settings, red blood cell (RBC) transfusion remains the mainstay of treatment in resource-limited countries and is associated with high rates of alloimmunization. This systematic review and meta-analysis aimed to estimate the prevalence of alloimmunization and identify associated risk factors among patients with SCD living in resource-limited settings. METHODS: Africa Journals Online (AJOL), Embase, PubMed, Scopus, and Web of Science were searched for original studies published from inception to December 15, 2025. Only studies conducted in low- and lower-middle-income countries (LMICs) were included. Eligible studies evaluated the prevalence of alloimmunization in patients with SCD receiving RBC transfusions. A random-effects meta-analysis of proportions was performed to pool quantitative data, while qualitative findings were systematically summarized in tabular form. Statistical heterogeneity was assessed using the I² statistic and further explored using Baujat plots, leave-one-out analyses, and meta-regression. RESULTS: Our analysis included 27 studies conducted in Africa (n = 23) and Asia (n = 4), predominantly from lower-middle-income countries (n = 19) and mainly employing a cross-sectional design (n = 20), comprising 3128 previously transfused patients with SCD. The pooled prevalence of RBC alloimmunization was 8.76% (95% CI: 6.71-11.37%; I² = 75%). Higher alloimmunization rates were observed in West and North Africa, particularly in Côte d'Ivoire, Egypt, and Nigeria, whereas lower rates were reported in Asia and East Africa. The most frequently identified antibodies belonged to the Rh blood group system (n = 153), followed by the Kell system (n = 65). CONCLUSION: In resource-limited settings, RBC alloimmunization is a frequent and clinically significant complication in patients with SCD, contributing to increased morbidity and potential mortality. Targeted and economically viable antigen matching may reduce alloimmunization rates and improve transfusion safety in LMICs.
BACKGROUND: This is part II of a 2-part series examining artificial intelligence in colorectal surgery. Part I established foundational concepts and clinical applications. Implementation, however, requires understanding research methodologies, available resources, and the specific challenges currently limiting widespread adoption. These topics are the focus of part II. OBJECTIVE: To examine artificial intelligence's transformation of surgical research, provide practical implementation resources, address adoption challenges, and explore future directions in colorectal surgery. METHODS: Comprehensive literature review focusing on artificial intelligence research methodology, implementation barriers, educational resources, and emerging technologies relevant to colorectal surgeons. RESULTS: Artificial intelligence streamlines clinical trial design through predictive modeling and natural language processing, reducing enrollment challenges that contribute to failed or inadequate trial accrual. Machine learning enables heterogeneity analysis within clinical trials, identifying treatment-responsive subgroups. Foundation models unlock analysis of unstructured electronic health record data at scale. Professional societies and universities offer specialized artificial intelligence education programs, with open-access data sets facilitating research participation. However, implementation faces multifaceted challenges: technical infrastructure demands, with real-time processing requiring dedicated graphics processing unit clusters; regulatory frameworks struggling with continuously evolving algorithms; undefined liability distribution for artificial intelligence-assisted decisions; algorithmic bias risking health care disparities; and the "black box" problem limiting clinical trust. Economic barriers include substantial initial costs without clear reimbursement pathways. Future directions include multimodal artificial intelligence integrating imaging, genomics, and histopathology; cognitive robotic systems with real-time decision support; digital twin technology for patient-specific surgical simulation; and global surgical artificial intelligence networks enabling distributed learning across institutions. CONCLUSIONS: Although artificial intelligence offers transformative potential for colorectal surgery research and practice, successful implementation requires addressing technical, regulatory, ethical, and economic challenges. The surgeon's evolving role demands both traditional expertise and computational fluency. Future advances in multimodal integration, autonomous systems, and global collaboration will fundamentally reshape surgical practice but will require thoughtful implementation prioritizing patient benefit and clinical value.
Evolutionary maintenance of dioecy is a complex phenomenon and varies by species and underlying pathways. Also, different sexes may exhibit variable resource allocation (RA) patterns among the vegetative and reproductive functions. Such differences are reflected in the extent of sexual dimorphism. Though rarely pursued, investigation on plant species harbouring intermediate sexual phenotypes may reveal useful information on the strategy pertaining to sex-ratios and evolutionary pathways. We studied H. rhamnoides ssp. turkestanica, a subdioecious species with polygamomonoecious (PGM) plants, in western Himalaya. The species naturally inhabits a wide range of habitats ranging from river deltas to hill slopes. These attributes of the species are conducive to test the influence of abiotic factors on sexual dimorphism, and RA strategy among different sexes. The study demonstrates sexual dimorphism in vegetative and reproductive traits. The sexual dimorphism index, aligned the traits like height, number of branches, flower production, and dry-weight of flowers with males while others including fresh-weight of leaves, number of thorns, fruit production were significantly associated with females. The difference in RA pattern is more pronounced in reproductive traits of the male and female plants, while in the PGM plants the traits overlap. In general, habitat conditions did not influence either the extent of sexual dimorphism or RA pattern. However, it seems to influence secondary sex-ratio as females show their significant association with soil moisture. Our findings on sexual dimorphism and RA pattern supports attributes of wind-pollination in the species. The observed extent of sexual dimorphism in the species reiterates limited genomic differences among the sexes and the ongoing evolution of dioecy via monoecy in the species. The dynamics of RA in the species appears to be independent of resource availability in the habitats as the species grows in a resource-limited and extreme environment.
Wheat production is challenged by biotic and abiotic stresses. Alien gene transfer is an effective approach to tackle such challenges. We previously showed that sea wheatgrass (SWG; Thinopyrum junceiforme (2n = 2x = 28; J1J2) is an untapped resource possessing resistance to an array of pests and abiotic stress. However, the transfer of these important traits has been hindered by the lack of genomic resources and a clear picture of its genome constitution. Using multi-color genomic in situ hybridization, we distinguished the SWG sub-genomes and corroborated that the J1 sub-genome is closely related to the E genome of Th. elongatum and the J genome of Th. bessarabicum and the J2 sub-genome to the V genome of Dasypyrum villosum. Meanwhile, we developed a draft SWG genome assembly and 127 SWG-specific DNA markers covering the 14 SWG chromosomes. Screening a population of 466 BC2F1 and BC2F2 individuals, derived from backcrosses of wheat-SWG amphiploid to wheat, by the SWG-specific markers led to selection of 72 plants putatively carrying one or two SWG chromosomes. The genome painting analysis of the 72 plants eventually identified a set of 37 wheat-SWG chromosome addition lines covering all the 14 pairs of SWG chromosomes and two compensating Robertsonian translocations (RobTs). While the wheat-SWG chromosome addition lines and RobTs are invaluable genetic resources for wheat improvement via chromosome engineering, our results showed the power of genome-specific markers in combination with genome painting in dissection of a polyploid genome and implicated the origin of a group of important polyploid grasses.
A public private cooperative mating design between elite maize inbred lines and diversity donors shows that genomic prediction holds great promise to improve the use of genetic resources. Genetic diversity is essential for plant breeding, enabling long-term gains and adaptation to climate change and new agronomical practices. Breeders can access diverse genetic resources to enhance elite germplasm and introduce new favorable variations. The limited performance of genetic resources may hamper their use. To overcome this, a bridging population can be implemented to evaluate and select progenies from crosses between diversity donors and elite lines before their introduction in breeding programs. The choice of such crosses can be dealt with the usefulness criterion (UC), which determines its ability to produce transgressive individuals. This paper investigates the use of genome-wide marker effects to predict (i) the performance of individuals derived from crosses between donors and elite lines and (ii) the UC of crosses not observed yet. It also compares donor introduction strategies based on the UC or the H criterion, which considers the genome-wide donor-elite complementarity. We used a flint maize collaborative multi-parental BC1-S2 population, consisting in materials from six breeding companies and one public institute crossed to different donors. The 20 crosses had contrasted means and genetic variances, and most of them presented transgressive individuals above the elite parent. Results emphasize the importance of half-siblings derived from the elite line parent of the predicted cross to efficiently predict progeny performances or the UC. They also showed that using the H criterion appears promising to select iteratively donors that best complement initial elite materials. The paper concludes with guidelines for implementing a bridging population using genome-wide marker-based predictions.
PURPOSE: Pharmacogenomics (PGx) is a critical component of precision health care that aims to improve drug efficacy and reduce adverse events. Terminologies and standards have not always aligned between PGx and broader genomic medicine communities, which is a barrier to PGx implementation. An updated assessment of community barriers, needs, and perspectives is critical to enable more standardized terminologies and interpretation frameworks. METHODS: The Clinical Genome Resource's PGx Interpretation Committee (PGxIC, formerly referred to as the PGx Working Group, PGxWG) conducted 2 surveys targeting the PGx and genomic medicine communities (n = 508) to evaluate perspectives on PGx clinical validity and actionability frameworks, as well as other barriers to PGx implementation. Surveys were tailored toward self-reported familiarity with PGx. Data primarily consisted of free text, which were analyzed using qualitative content analysis methods. RESULTS: Survey responses indicated conflation of terminology across disciplines, including confusion around differing definitions of terms in PGx and non-PGx contexts. Data also indicated broad support for leveraging existing PGx guidelines and framework structures alongside the standardization of approaches and centralization of resources. CONCLUSION: These novel survey results demonstrate broad consensus on the importance of integrating PGx into clinical practice, including support for development of gene-drug response clinical validity and actionability frameworks aligned with Clinical Genome Resource's frameworks for gene-disease relationships.
BACKGROUND: Dapsone is a drug used to treat leprosy. Dapsone causes a highly morbid and potentially fatal severe drug hypersensitivity reaction (DHS) in 1-3% of leprosy cases. The allele HLA-B*13:01 is a known genetic risk factor for DHS. However, resource-intensive genotyping methods preclude its testing in resource-limited settings. This study aimed to develop an endpoint PCR assay to detect the presence of HLA-B*13:01. RESEARCH DESIGN AND METHODS: DNA was extracted from blood samples of leprosy patients at Anandaban Hospital, Nepal (2022-24). A duplex endpoint PCR was optimized and validated against a previously validated commercial qPCR method and NGS (next‑generation sequencing). RESULTS: In 113 samples, duplex PCR showed 100% (95% CI: 79.4-100%) sensitivity and 100% specificity (95% CI: 96.2-100%) compared to the validated qPCR method. The same accuracy was confirmed in 58 NGS-typed samples (concordance 98.3%, 95% CI: 90.7-99.9%). The assay reliably differentiated HLA-B*13:01 from closely related allele. Analytical sensitivity reached a lower detection limit of 100 genome equivalents (0.67 ng DNA/reaction). CONCLUSION: The developed duplex endpoint PCR offers a simple and affordable method for detecting HLA-B*13:01, suitable in low-resource settings. Its use may significantly reduce the risk of DHS by guiding safer drug choices prior to MDT initiation.
MOTIVATION: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. RESULTS: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. AVAILABILITY AND IMPLEMENTATION: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.
BACKGROUND: The genus Barringtonia (Lecythidaceae) is a vital component of tropical coastal forests and mangrove ecosystems. Among its members, B. racemosa and B. fusicarpa are classified as Endangered and Vulnerable, respectively, due to habitat degradation and anthropogenic pressures, underscoring the urgent need for genetic studies to guide conservation. Chloroplast (cp.) genomes serve as essential resources for phylogenetic reconstruction and conservation genetics. However, the scarcity of cp. genome data for Barringtonia has limited comprehensive evolutionary and conservation-oriented investigations. RESULTS: We assembled and annotated the first complete cp. genomes of B. racemosa, B. fusicarpa, and B. acutangula. All three genomes exhibit the typical quadripartite structure, ranging from 158,959 bp (B. racemosa) to 159,837 bp (B. acutangula), and contain 132 genes (87 protein-coding, 37 tRNA, 8 rRNA) with a GC content of 36.68%-36.86%. Collinearity and IR boundary analyses revealed high structural conservation without large-scale rearrangements. Interspecific sequence-level variations were detected in simple sequence repeats (SSRs) and long repeats. Nucleotide diversity (π) analysis identified highly polymorphic regions, including rpl20 (π = 0.080), rpoA (π = 0.064), rps3 (π = 0.063), and ndhF (π = 0.060), which represent promising molecular markers for population genetics within the genus. Codon-based selection analyses (Ka/Ks) showed that all protein-coding genes are under strong purifying selection (mean Ka/Ks 0.32-0.37), with no evidence of positive selection. Pairwise genetic distances (p-distances) among Barringtonia species are extremely low (mean 0.0046), while distances to the related genus Bertholletia are ~ 6-fold higher, supporting their generic distinction. CONCLUSIONS: Phylogenetic analysis robustly supports Barringtonia as a monophyletic clade (bootstrap = 100%), with B. racemosa and B. fusicarpa forming a sister lineage to B. acutangula. This study provides the first high-quality cp. genome resources for the two threatened Barringtonia species, revealing strong structural and sequence conservation but no direct chloroplast genomic correlates of endangerment. The identified polymorphic regions and repeat markers lay a foundation for future population genetics, phylogeographic studies, and conservation-oriented genetic management of these ecologically important coastal plants.