Sorghum bicolor (Sorghum) is a drought and heat tolerant C4 grass crop used to produce grain, forage, biofuels, and other bioproducts. Genetic improvement of sorghum hybrid crops is aided by a large and diverse germplasm, sorghum's diploid inbreeding genetics, and a relatively small genome that has facilitated genomic research. Over the past 20 years, the sorghum research community characterized the cytogenetic and recombinant landscapes of sorghum's 10 chromosomes, sequenced and annotated the sorghum genome, and used that information to identify genes/alleles that modulate flowering time, plant height, seed shattering, and other important traits. More recently, >1000 RNA-seq transcriptome profiles were collected from 15 sorghum genotypes to help understand the genetic basis of variation in growth and development of sorghum stems, tillers, roots, and leaves, and the regulation of biosynthetic pathways that produce epicuticular wax, dhurrin, and RFOs, compounds that contribute to sorghum's resilience. Transcriptome studies were designed to identify differentially expressed genes that are co-expressed during development or in response to a treatment to enable construction of gene regulatory networks. Co-expression and network analysis identified transcription factors and their cognate binding sites in target gene promoters and signaling pathways that modulate gene regulatory networks providing gene editing targets for further trait optimization. RNA-seq data from >20 experiments targeting sorghum organs, tissues, cell types, developmental stages, and responses to environmental conditions (i.e., diel, day-length, shading, water-deficit, temperature) has been compiled in a sorghum transcriptome compendium. The goal of this resource paper is to describe compendium content, accessibility, and a compendium data analysis pipeline and to illustrate the types of information that can be derived from the compendium with a focus on the elucidation of gene regulatory networks useful for guiding the improvement of sorghum traits through gene editing.
The diversity of healthcare systems across Europe has predictably resulted in significant variations in point-of-care ultrasound (PoCUS) training and practice for emergency medicine (EM). To encourage a more synchronized approach and address these inconsistencies, the European Society of Emergency Medicine (EUSEM) chartered its ultrasound section to develop a comprehensive curriculum compendium that should serve as a foundational guide for European Emergency Medicine PoCUS clinical and educational guidelines and policies. Under the leadership of a dedicated task force, the EUSEM ultrasound section developed this compendium to provide a structured, tiered framework designed to meet the needs of physicians at every skill level, from novice to advanced users. The compendium emphasizes applications that are currently practiced in different and diverse emergency departments in Europe, including a broad range of topics. An important goal was allowing flexibility to accommodate the unique resources and challenges of different healthcare environments, so that EM physicians can achieve PoCUS competencies matching their local circumstances and needs. To achieve this goal, good educational and clinical stewardship throughout this process is a key part to the success of advancing PoCUS in European EM. This compendium is intended as a resource for creating standardized yet adaptable training pathways. It represents a major step toward harmonizing and advancing PoCUS practice in European EM. Die Vielfalt der verschiedenen Gesundheitssysteme in Europa hat dazu geführt, dass grosse Unterschiede in der Ausbildung und Anwendung des Point-of-Care-Ultraschalls (PoCUS) in der Notfallmedizin bestehen. Um einen stärker synchronisierten Ansatz zu fördern und diesen Unterschieden zu begegnen, hat die Europäische Gesellschaft für Notfallmedizin (EUSEM) ihre Ultraschallsektion damit beauftragt, ein umfassendes Curriculum-Kompendium zu entwickeln. Dieses soll als ein Leitfaden für Europäische Richtlinien und Standards für PoCUS in der klinischen Ausbildung in der Notfallmedizin dienen. Unter der Leitung einer Task Force hat die Ultraschallsektion der EUSEM dieses Kompendium erarbeitet, um Rahmenbedingungen zu schaffen, die den Bedürfnissen von Ärztinnen und Ärzten auf jedem Kompetenzniveau - vom Einsteiger bis zum fortgeschrittenen Anwender - gerecht werden. Das Kompendium beinhaltet Ultraschallanwendungen, die in derzeit sehr diversen Notfallstationen in ganz Europa praktiziert werden, und deckt daher ein breites Spektrum PoCUS-Anwendungen in der Notfallmedizin ab. Ein zentrales Ziel dieser Arbeit war es, Flexibilität zu ermöglichen, um die spezifischen Merkmale wie auch Ressourcen der jeweiligen Gesundheitssysteme zu berücksichtigen, sodass Notfallmediziner:innen PoCUS-Kompetenzen erwerben können, die ihren lokalen Gegebenheiten und Anforderungen entsprechen. Um das Ziel der Weiterentwicklung von PoCUS in der europäischen Notfallmedizin zu erreichen, ist ein entscheidender Erfolgsfaktor eine gute Begleitung sowohl in der klinischen Anwendung, wie auch in der Ausbildung. Dieses Kompendium soll als Grundlage zur Entwicklung standardisierter, zugleich aber anpassungsfähiger Ausbildungspfade dienen. Es stellt einen wichtigen Schritt zur Harmonisierung und Weiterentwicklung des PoCUS in der europäischen Notfallmedizin dar.
High-quality and transparent reporting is fundamental to the credibility, reproducibility, and impact of health research. While widely endorsed reporting guidelines such as CONSORT and PRISMA have improved reporting across many fields, traditional, complementary, and integrative medicine (TCIM) research presents distinctive conceptual, methodological, and contextual challenges that are not always adequately addressed by general frameworks. In response, a growing number of TCIM-specific reporting guidelines have been developed over the past two decades. This manuscript provides a structured compendium of all 30 reporting guidelines listed on the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network under the clinical area labelled "Complementary and Alternative Medicine" as of March 2026. The compendium summarizes each reporting guideline's scope, study design focus, TCIM modality, relationship to established parent reporting guidelines where applicable, and methodological strengths and weaknesses. The identified reporting guidelines span a wide range of research domains, including randomized trials, protocols, systematic reviews, case reports, case series, clinical practice guidelines, and basic research, and encompass modalities such as acupuncture, herbal medicine, homeopathy, massage, moxibustion, cupping, biofield therapies, and reflexology. By consolidating these resources in a single, accessible overview, this compendium aims to support researchers, journal editors, and peer reviewers in identifying and applying appropriate TCIM-specific reporting guidance, thereby strengthening the transparency, consistency, and overall quality of TCIM research.
NTRK gene fusions are oncogenic drivers for a variety of adult and pediatric tumors, making them a target for tumor-agnostic precision medicine. Tropomyosin receptor kinase (TRK) inhibitors are approved by the US Food and Drug Administration for cancers driven by TRK fusions. However, NTRK genes can fuse with many different partner genes, leading to diverse TRK fusion proteins, highlighting the importance of identifying the specific fusion partner with optimal pan-cancer diagnostics. This analysis aims to provide an updated descriptive compendium of NTRK gene fusions. NTRK gene fusions were identified via literature searches (PubMed), a search of a clinical trials database (larotrectinib), and searches of two genomic databases (Memorial Sloan Kettering and Children's Hospital of Philadelphia). In total, 358 distinct NTRK gene fusion-tumor pairings were identified across 25 tumor types. Primary CNS tumors were observed to harbor 86 distinct NTRK gene fusions, followed by sarcomas (n = 73). Overall, 229 different fusion partners were identified across tumor types (regardless of NTRK gene). Twenty-three fusion partners were found to fuse with >1 NTRK gene across tumor types, while 183 fusion partners were associated with only a single NTRK gene in one tumor type. ETV6::NTRK3 was found in the highest number of different tumor types. This analysis illustrates the diversity of NTRK gene fusion partners across various tumor types and highlights the importance of selecting a pan-tumor fusion-partner agnostic test that can identify both known and novel fusion partners to identify patients who may benefit from treatment with TRK inhibitors.
Natural variations in cochlear anatomy have substantial implications for both clinical care and research in the fields of otology, neurotology, and audiology. While precise anatomic characterization is essential for a multitude of applications, comprehensive reference dimensions of both osseous and membranous cochlear structure obtained from a large and morphologically heterogeneous sample set do not currently exist. In this study, one hundred healthy human cadaveric temporal bone samples, without historical or visible pathology, underwent high-resolution three-dimensional synchrotron radiation phase-contrast imaging (SR-PCI) to develop a morphometric compendium of the human cochlea. Measurements of both bone and soft tissue in the cochlea were obtained, including basal turn diameter and width, cochlear height, and cochlear length along multiple anatomic paths (lateral wall, basilar membrane, and modiolar wall). The hook region, scalar geometry (diameter, area, tilt, width, and volume), and round window dimensions were also comprehensively characterized. Normative tonotopic frequency distributions of the basilar membrane and spiral ganglion were derived using cochlear length measurements and Greenwood's frequency-position function. These anatomic benchmarks establish invaluable reference data which may be used for anatomically informed, precision medicine approaches, including patient-specific surgical planning, intracochlear pharmaceutical delivery optimization, the development of automated image analysis algorithms, and the investigation of cochlear structure-function relationships in pathological conditions.
Translating universal health coverage (UHC) commitments into explicit, evidence-informed benefits packages remains a challenge for many resource-constrained health systems. This paper describes the methods and findings of a full-system benefits package revision applying the WHO Universal Health Coverage Compendium (UHCC) within an evidence-informed deliberative process (EDP) to redesign the State-Guaranteed Benefits Programme in Kyrgyzstan. The revision was carried out using the UHCC, following an EDP. The UHCC provided standardised service definitions and resource requirements for analysis. An assessment and appraisal process incorporated technical analysis and governance oversight through the Health Policy Council. The costing methodology estimated input costs per service and multiple financing scenarios were developed with decision-makers to explore coverage-cost trade-offs. The revision was conducted over 2023-2025, with the Health Policy Council endorsing key methodological decisions. Technical evidence on cost, impact and equity was generated for all services. Through deliberative appraisal, 182 services were prioritised as essential. With an available fiscal space of US$19 per capita, only 66 essential services could be financed under fully public funding. A mixed public-private financing scenario maintained comprehensive essential service coverage while reducing public costs. Kyrgyzstan's experience demonstrates that comprehensive, evidence-informed revision of benefits package is feasible in resource-constrained settings when supported by political commitment, strong governance, global tools, structured deliberation and integrated costing. Use of the WHO UHCC enabled standardised service definitions. The approach offers practical lessons for countries seeking to institutionalise priority setting and strengthen progress towards UHC.
The Lyme disease agent Borrelia burgdorferi belongs to a class of metabolically compromised bacteria that cannot survive without host-derived lipids. Survival of the agent in tick and vertebrate hosts requires substantial nutrient acquisition and potential cell envelope remodeling. While prior studies identified cholesterol, cholesterol glycolipids, and phosphatidylcholines as membrane lipids in B. burgdorferi, the identity of many other membrane lipids, their origin, and their physiological relevance remain unknown. Here, we used a suite of untargeted and targeted high-resolution mass spectrometry methods to reveal a complex lipid profile of the pathogen and to identify the origin of its lipids. The analysis detected more than 500 lipids in B. burgdorferi, the majority of which are sourced from the environment. However, the bacterium selectively accumulates certain lipids while excluding others, suggesting discriminatory uptake. These include cholesteryl esters and triglycerides that are organized in foci within the pathogen. Intriguingly, the pathogen also synthesizes predominantly eukaryotic lipids such as the lysosomal bis(monoacylglycerol)phosphate and the plant glycolipid sulfoquinovosyl diacylglycerol (SQDG). The biosynthesis of the latter is carried out by enzymes that exhibit structural homology to plant oxidoreductases and galactosyltransferases, yet their closest orthologs are found in bacteria. This hints that the capability of SQDG synthesis is more widespread in spirochaetes and other bacteria. Together, the comprehensive lipid profiling we report here uncovers novel aspects of the physiology of the metabolically challenged B. burgdorferi and highlights lipid acquisition and synthesis pathways as potentially critical for pathogen survival.
Traditional, knowledge-driven pathway annotations and bulk transcriptomic analyses often fail to capture the cellular specificity and mechanistic heterogeneity of immune responses. We present scImmuneCo, a comprehensive resource of immune cell-specific co-expression modules derived from single-cell RNA sequencing across 17 immunological conditions and 1.78 million cells. Using a modified graph-based framework, we constructed 873 robust modules spanning 7 major immune cell types, providing stable, cell-type-specific interaction networks for functional inference. scImmuneCo resolves complex biology at cellular resolution. We identify 20 interferon-related modules that reveal both conserved and cell-type-specific regulatory programs, clarifying disease-dependent differences that are invisible to pathway tools treating interferon signaling as a unitary process. We also uncover age-associated CD8+ T cell programs, capturing state transitions from naive to effector/memory cells and exposing a progressive imbalance in translation and cytotoxicity with age. Together, these results demonstrate the power of high-resolution, data-driven functional inference to link gene groups to biological roles and disease processes. To support broad application, we provide an R package (https://github.com/FrankQYW/scImmuneCo_R) for module-based analysis of both single-cell and bulk transcriptomic data, along with an interactive web portal (http://www.scimmuneco.site/) for visualization and gene-module exploration. scImmuneCo offers a scalable and interpretable framework for dissecting immune mechanisms and identifying disease-relevant transcriptional programs with cellular resolution.
With more eukaryotic genomes available for study researchers have been able to identify a growing number of horizontal gene transfer (HGT) candidates. We compiled 9,495 protein coding genes that were identified as horizontally transferred to metazoan hosts in the published literature. This dataset contains gene transfers from bacteria, fungi, archaea and protists to metazoans. We assigned a confidence score to each gene based on the methods used in the scientific paper reporting HGT. All the coding sequences and protein sequences for the HGT genes are stored in a fig share repository. This dataset can be used to identify trends in genome and protein evolution and provide a foundation for creating a centralized HGT database for eukaryotes.
The Asian bush mosquito, Aedes japonicus (Theobald, 1901), is an invasive species and a competent vector for several arboviruses, including chikungunya virus, dengue virus, Japanese encephalitis virus, West Nile virus, and Zika virus. Field studies have also detected La Crosse virus in wild populations, further supporting its potential role in arbovirus transmission. To address the fragmented and incomplete state of knowledge regarding its spread, we have assembled a global dataset of documented presences from 1950 to 2025. This data descriptor presents a curated database of geolocated records, formatted as points, derived primarily from peer-reviewed literature and supplemented with validated national survey data and selectively integrated records from the Global Biodiversity Information Facility (GBIF) following rigorous quality control. We detail the methodology for data acquisition, coordinate assignment, and the rigorous validation steps applied. This first comprehensive repository specifically for Ae. japonicus, containing 4618 validated records, provides a critical resource for spatial mapping and risk assessment of this vector and its associated pathogens.
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Heterozygous FOXL2 (non)coding sequence and structural variants (SVs) lead to blepharophimosis, ptosis and epicanthus inversus syndrome (BPES), a rare, autosomal dominant developmental disorder characterized by a completely penetrant eyelid malformation and incompletely penetrant primary ovarian insufficiency (POI). We collected variants from our in-house database, generated via clinical genetic testing and downstream research testing in the Center for Medical Genetics Ghent, Belgium (2001-2024) and via literature and other resources in the same period. All retrieved variants were categorized using ACMG/AMP classifications to increase the knowledge of pathogenicity. We collected 413 unique genetic defects of the FOXL2 region, including 76 novel variants, in 864 index patients. Of these, 87% of patients were identified with a coding FOXL2 sequence variant. The polyalanine tract is a known mutational hotspot of FOXL2, illustrated here by the high percentage of pathogenic polyalanine expansions (24%). Furthermore, the molecular spectrum in typical BPES index patients is characterized by 8% coding deletions and 3% deletions located up- and downstream of FOXL2. The remaining 2% carry translocations along with chromosomal rearrangements of 3q23. This uniform and structured reclassification, incorporating the largest dataset of variants implicated in FOXL2-associated disease so far, will improve both the diagnosis as well as genetic counselling for individuals with BPES.
Shared decision making (SDM) can be conceptualized as observable communication behaviors that foster collaborative decision making. We aimed to develop a compendium of patient-reported SDM instruments and characterize the communication behaviors assessed by them. We then used the identified behaviors to develop a contemporary integrative model of the SDM process. PubMed, Embase, Cochrane Library, and CINAHL were systematically searched through July 2024. Published reviews of SDM instruments were eligible if they included instruments without context restrictions and were available as full text in English, supplemented by a primary search since the last review for potential instruments not included in reviews. Instruments were eligible if they were patient-reported and included at least one item assessing a SDM communication behavior. All items from the included instruments were extracted verbatim and directed content analysis was used to code for SDM communication behaviors. Of 1049 records, 14 reviews underwent full-text assessment, and 9 were included (2007-2021), collectively identifying 98 unique instruments. Twenty-one patient-reported instruments met inclusion criteria, comprising 283 items. Nineteen instruments measured information exchange communication behaviors, including creating choice awareness (n = 8), sharing information and discussing options (n = 12), eliciting and integrating patient preferences (n = 19), and discussing choice enactment (n = 8). Eighteen instruments measured relationship building communication behaviors separately from information exchange, including partnership building (n = 17) and rapport building (n = 6). Sixteen spanned both informational and relational domains, and none contained at least one item measuring all six domains. This review provides a compendium of patient-reported SDM process instruments to support selection of measures aligned with specific conceptual, practice, and research needs. Drawing from the communication behaviors represented in existing instruments, we propose a contemporary integrative model of the SDM process. To comprehensively conceptualize and measure the SDM process, measurement instruments need to consider both information exchange and relationship building communication behaviors.
Accounting for only 8% of Earth's land cover, freshwater wetlands remain the foremost contributors to global methane emissions. Yet the microorganisms and processes underlying methane emissions from wetland soils remain poorly understood. Over a five-year period, we surveyed the microbial membership and in situ methane measurements from over 700 samples in one of the most prolific methane-emitting wetlands in the United States. We constructed a catalog of 2,502 metagenome-assembled genomes (MAGs), with more than half of the 70 bacterial and archaeal phyla sampled containing novel lineages. Integration of these data with 133 soil metatranscriptomes provided a genome-resolved view of the biogeochemical specialization and versatility expressed over wetland soil spatial and temporal gradients. Centimeter-scale depth differences best explained patterns of microbial community structure and transcribed functionalities, even more than land cover or temporal information. Moreover, while extended flooding restructured soil redox, this perturbation failed to reconfigure the transcriptional profiles of methane-cycling microorganisms, contrasting with theoretically expected responses to hydrological perturbations. Co-expression analyses, coupled with depth-resolved methane measurements, revealed the metabolisms and trophic structures most predictive of methane hotspots. Mapping the spatiotemporal transcriptional patterns on this compendium of biogeochemically classified soil-derived genomes begins to untangle the microbial carbon, energy, and nutrient processing contributing to wetland methane production.IMPORTANCESoil microbial ecology is increasingly recognized as essential to climate mitigation, but realizing its full potential requires shifting from static genome inventories to dynamic assessments of microbial activity. This study shows that methane-cycling microbes exhibit stable, depth-stratified expression patterns, even in response to major redox and flooding shifts, undermining assumptions that water-table manipulations common in wetland management can alone reduce methanogenesis. Instead, methane cycling is shaped by spatially organized, transcriptionally active networks involving not only methanogens but also methanotrophs, fermenters, and iron reducers. These findings expose the limitations of genome-only models and highlight the need for soil diagnostics that capture in situ activity. Together, we provide a foundation for developing activity-based microbiome tools, embedding microbial functions into Earth system models, and designing interventions that move beyond "single-lever" strategies and instead work with the structure and dynamics of microbial communities as complex, layered systems.
Programa Criança Feliz (PCF) is Brazil's home visitation program aimed at enhancing early childhood development. Evaluations of the program have found significant program challenges and implementation barriers, including the lack of a structured curriculum, insufficient training, and little supervisory support. This study tests the revised content of the home visits and new implementation strategies aimed at addressing these barriers and enhancing the quality of PCF home visits. The implementation strategies were piloted across 8 diverse municipalities in an implementation feasibility trial. The strategy bundle included a 40-hour initial training for home visitors using demonstration and simulation-based methods (based on the Reach Up methodology), an 8-hour supervision-focused training module for supervisors, and standardized home visit guidelines and an activities compendium. The new strategies were assessed using a one group pre-post analysis along with mixed methods to assess the extent to which they were acceptable, feasible, and associated with a change in home visit quality. A paired t-test and an independent t-test analysis were used to assess the change in home visit quality. The implementation outcomes were assessed with qualitative analysis and the Framework Method approach. The proposed home visitation guidelines, material, training, and supervision process were determined to be highly acceptable, feasible, and associated with improved quality of home visits. The home visit quality scores significantly increased by 14.68 points (SD = 14.89, CI 95%: 7.27-22.08, p = 0.0006), according to the paired t-test. The study participants provide insightful suggestions for adaptations that can occur before testing the strategies more broadly. Key suggested adaptations included adjusting activity difficulty to individual developmental levels rather than age alone, shortening training duration to improve staff access, and incorporating guidance for culturally diverse and traditional communities. The findings suggest three transferable design principles for home visitation and paraprofessional-delivered public health programs: reducing excessive discretion through structured, age-appropriate visit guidance; externalizing quality through experiential training methods such as demonstration and role-play; and embedding feedback loops through structured supervision and monitoring. These principles may generalize to programs facing heterogeneous staff preparation, high turnover, and limited supervisory capacity.
Protein-protein interactions underlie core brain functions, including neurotransmitter release, receptor activation, and intracellular signaling. Here, we present a compendium of protein-protein interactions conserved across vertebrate brains, spanning over 300 million years of evolution. From 2,197 biochemical fractions across five vertebrate species, we identify over 81,000 high-confidence interactions among 6,108 conserved proteins. This interaction map (VerteBrain) reveals both regulatory and structural complexes, including extensive synaptonemal protein associations likely involved in inter-neuronal coordination. Conservation across species underscores essential roles in neuronal and glial function, as well as in additional tissues for more widely expressed complexes. The VerteBrain dataset uncovers candidate disease mechanisms, including roles for ARHGEF1 in short stature syndromes, synaptic vesicle trafficking complexes in epilepsy, and RELCH (Rab11-binding and LisH domain, coiled-coil and HEAT repeat-containing) in congenital deafness. VerteBrain provides a resource for investigating brain protein interactions and their relevance to human neurological disorders.
Density functional theory (DFT) has emerged as the most significant methodology in computational chemistry. However, the ever-growing number of density functional approximations (DFAs) has been a source of confusion to both users and developers. Particularly confusing is the extended "family" of DFAs based on B97, where many approaches have similar names but often differ in their underlying functional form. This review aims to be a succinct compendium of the family of B97-based DFAs and addresses both general and specialised audiences. 57 B97-based DFAs are comprehensively reviewed with a particular focus on the functional form and dispersion-corrected variants. Ambiguously named methods and common aliases are clarified. The general performance of B97-based methods in large-scale benchmarking studies on ground and excited state problems is summarised with the conclusion that B97M-V, ωB97M-V, and ωB97X-V (including other dispersion-corrected forms of these functionals) as well as ωB97M(2) are some of the currently most accurate DFT methods. It is our hope that this review clarifies the current state of the B97 family which is of relevance for DFT users and developers alike, particularly as development for this DFA family is ongoing.
The management of metastatic breast cancer (mBC) relies on tissue-based immunohistochemical subtypes. However, biopsies are invasive, may not capture metastatic heterogeneity, and subtypes can change over time under treatment pressure. Here, we developed cell-free DNA (cfDNA) methylation signatures for minimally invasive BC detection, distinction, and estrogen receptor (ER) status classification. Peripheral blood plasma methylomes were analyzed from 79 patients with mBC spanning ER+/HER2- (n=45), HER2+ (n=13), and triple-negative BC (TNBC; n=21). To derive tissue-informed BC and ER-specific features, public 450K methylation array data (n=9730) were leveraged, and features were selected using generalized linear models via elastic net regularization (GLMnet) with cross-validation. The tissue-informed features were translated to cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq), and the final signatures were validated across a compendium of cfMeDIP-seq profiles (n=713) spanning over ten cancer types. Across training, validation, and external test cohorts, the signatures demonstrated high accuracy for BC detection versus controls, distinction from multiple other malignancies, and ER status classification. Performance generalized across independent cfMeDIP-seq cohorts and reflected tumor fraction. The sensitivity was reduced in samples with low tumor fractions and bone-only disease, while remaining informative for typical tumor fractions observed in the metastatic setting. Promoter-proximal signature regions provided biological insight into tumor phenotypes. This tissue-anchored, platform-translatable framework demonstrates the feasibility of accurate, reproducible cfDNA methylation-based molecular classification in mBC.
Cannabinoids comprise a chemically diverse group of meroterpenoids whose extensive isomerism, variable side-chain length, and frequent oxidative or rearranged derivatives lead to strongly overlapping yet characteristic MS/MS fragmentation patterns. In untargeted LC-MS/MS datasets, this combination of structural diversity and spectral similarity complicates annotation, particularly when reference spectra are sparse or unavailable. Library-based approaches, therefore, recover only a limited fraction of the cannabinoid-related chemical space that is routinely observed in experimental data. In this work, we apply MassQL to encode established cannabinoid fragmentation chemistry into rule-based queries. The resulting compendium covers major cannabinoid subclasses, including neutral and acidic cannabinoids, varinic analogs (C3 side-chain cannabinoids), and structurally modified derivatives, using combinations of diagnostic fragment ions, neutral loss patterns, adducts, and fragment co-occurrence logic. Importantly, class-level retrieval does not depend on complete or unambiguous precursor m/z information and can be driven solely by MS/MS evidence. Application of this framework to a publicly available untargeted LC-MS/MS dataset demonstrates that rule-based querying can recover known cannabinoids while highlighting additional features that share consistent cannabinoid-like fragmentation patterns. These features include putative analogs, transformation products, and derivatized forms that are not represented in current spectral libraries. At the same time, certain known features, such as in-source dehydrated ions, may be under-recovered depending on query design, illustrating current methodological limitations. This study demonstrates the feasibility and interpretability of chemically informed, rule-based MS/MS querying for cannabinoid discovery. Rather than replacing spectral library matching, MassQL-based class-level retrieval provides complementary hypothesis-generating evidence capable of expanding detectable cannabinoid chemical space beyond currently available reference spectra. The results also highlight the importance of polarity-aware fragmentation curation for reliable query-driven metabolomics workflows. MassQL class-level matches should be viewed as chemically informed hypotheses that complement, rather than replace, spectral library identification, while providing a basis for future systematic validation and benchmarking.
Cardiac amyloidosis (CA) has transitioned from a rare, frequently fatal disease to an increasingly recognized cause of heart failure, driven by heightened awareness, noninvasive diagnostic strategies, and the advent of disease-modifying therapies. As a result, molecular imaging has become central to contemporary management by providing signals that reflect underlying disease biology. Transthyretin CA predominantly involves progressive extracellular fibril accumulation causing myocardial stiffening, whereas light-chain CA is characterized by early myocardial dysfunction mediated by direct proteotoxic effects of circulating light chains in addition to extracellular fibril accumulation. These divergent mechanisms may underlie different behaviors of diagnostic imaging such as bone-avid scintigraphy and β-sheet-binding positron emission tomography tracers. In this compendium review, we integrate pathophysiological insights across major and rarer amyloid subtypes with nuclear imaging and contextualize these mechanisms through clinical phenotypes, red flags, and risk stratification tools.