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Spatial transcriptomics for assessing the diabetic kidney
No full textThe human kidneys are a vital organ for proper systemic function in the body by maintaining blood chemical composition. However, the ability to properly filter blood decreases as individuals age, which is characterized at a cellular level in a phenomenon deemed senescence, occurring when cells do not divide, nor die. Such cells have unique inflammatory and secretory profiles that are still being studied. In order to relate the cellular level of transcriptomic data with higher level tissue-level structure and patterns, Xenium data can be leveraged for discovery about aging and senescence in the kidneys, as genetic data can be mapped back to a spatially-relevant context. We characterized the genetic profiles of Xenium 5K kidney images and discovered insights into the aging kidney structures crucial for function and affecting disease onset
Not a hair out of place: Polarizing and orienting sensory hair cells.
No full textHair cells (HCs) are specialized sensory receptors in auditory, vestibular, and lateral-line organs that convert mechanical stimuli into neural signals. Auditory HCs transduce sound vibrations, vestibular HCs detect head movements for balance, and lateral-line HCs in aquatic vertebrates sense water currents, providing environmental awareness. A key feature of all HCs is their directional sensitivity, determined by the graded height architecture of their hair bundle. This arrangement ensures optimal HC activation when the hair bundle is deflected towards its tallest side. Within sensory organs, HCs and their hair bundles are precisely aligned within the epithelium plane, another key feature which produces coherent responses for accurate sensory representation. HC alignment is governed by planar cell polarity (PCP) cues relayed between neighboring cells. In some epithelia, such as the mammalian auditory epithelium, HCs are uniformly oriented. In other epithelia, PCP cues can be interpreted differently, and HCs exhibit a normal or reversed orientation creating a mirror-image HC organization. Several mechanisms generate directional sensors with proper alignment. During early development, the apical cytoskeleton breaks central symmetry and produces a staircase-like hair bundle. Over time, the asymmetrical apical cytoskeleton couples with distinct PCP mechanisms and signaling molecules at cell-cell junctions, orienting HCs properly within the sensory epithelium. This chapter highlights our current understanding of the intricate polarization processes that enable HCs to function as directional sensors, providing insights into their critical role in sensory perception and spatial orientation
A consensus guide to preclinical indirect calorimetry experiments.
No full textUnderstanding the complex factors influencing mammalian metabolism and body weight homeostasis is a long-standing challenge requiring knowledge of energy intake, absorption and expenditure. Using measurements of respiratory gas exchange, indirect calorimetry can provide non-invasive estimates of whole-body energy expenditure. However, inconsistent measurement units and flawed data normalization methods have slowed progress in this field. This guide aims to establish consensus standards to unify indirect calorimetry experiments and their analysis for more consistent, meaningful and reproducible results. By establishing community-driven standards, we hope to facilitate data comparison across research datasets. This advance will allow the creation of an in-depth, machine-readable data repository built on shared standards. This overdue initiative stands to markedly improve the accuracy and depth of efforts to interrogate mammalian metabolism. Data sharing according to established best practices will also accelerate the translation of basic findings into clinical applications for metabolic diseases afflicting global populations
Bi-allelic variants in BCAT1 impair mitochondrial function and are associated with a candidate neurometabolic disorder.
No full textBranched-chain amino acid transaminase-1 (BCAT1) initiates the catabolism of branched-chain amino acids (BCAAs), which are essential for neurologic function. However, the role of BCAT1 in neurodevelopment is largely unknown. Here, we identify compound heterozygous BCAT1 variants in a patient with a severe progressive neurodevelopmental syndrome. To investigate the functional consequences, we established patient variant (BCAT1: c.792T\u3eA p.Phe264Leu; c.1042G\u3eA p.Glu348Lys) and BCAT1 knockout hiPSC models. Both disease models show profound defects in cortical neuron differentiation and neurite outgrowth. Furthermore, metabolic analysis revealed evidence of mitochondrial dysfunction associated with increased levels of tricarboxylic acid (TCA) cycle intermediates, glutamate, and glutamine. This increase is linked to altered oxygen consumption rates, superoxide production, and upregulation of UCP2 in BCAT1 disease neurons, suggesting a downstream impact on electron transport chain homeostasis. These findings establish a regulatory role for BCAT1 in mitochondrial function and further define a role for genomic variants in BCAT1 in neurometabolic disorders
Oncopacket: integration of cancer research data using GA4GH phenopackets.
No full textSUMMARY: Lack of data integration remains a significant impediment to cancer research, and many analyses still require customized software to transform and prepare cancer data. We describe a software package to harmonize genetic and clinical cancer data into the GA4GH Phenopacket schema, an ISO standard for representing clinical case data. We integrated demographic, mutation, morphology, diagnosis, intervention, and survival data using case data from the National Cancer Institute for 12 cancer types. The Phenopacket standard provides a foundation for downstream use, including sophisticated statistical and AI/ML analyses. We demonstrate fitness for purpose by using the integrated data to recapitulate a known association between mutations in the gene encoding isocitrate dehydrogenase 1 and survival time in brain cancer patients.
AVAILABILITY AND IMPLEMENTATION: Source code is freely available at: https://github.com/monarch-initiative/oncopacket (archived at 10.5281/zenodo.15353125)
Characterization and automated classification of sentences in the biomedical literature: a case study for biocuration of gene expression and protein kinase activity.
No full textBiological knowledgebases are essential resources for biomedical researchers, providing ready access to gene function and genomic data. Professional, manual curation of knowledgebases, however, is labour-intensive and thus high-performing machine learning (ML) methods that improve biocuration efficiency are needed. Here, we report on sentence-level classification to identify biocuration-relevant sentences in the full text of published references for two gene function data types: gene expression and protein kinase activity. We performed a detailed characterization of sentences from references in the WormBase bibliography and used this characterization to define three tasks for classifying sentences as either (i) fully curatable, (ii) fully and partially curatable, or (iii) all language-related. We evaluated various ML models applied to these tasks and found that GPT and BioBERT achieve the highest average performance, resulting in F1 performance scores ranging from 0.89 to 0.99 depending upon the task. Moreover, our inter-annotator agreement analyses and curator timing exercises demonstrated that curators readily converged on classification of high-quality training sentences that take a relatively short period of time to collect, making expansion of this approach to other data types a realistic addition to existing biocuration workflows. Our findings demonstrate the feasibility of extracting biocuration-relevant sentences from full text. Integrating these models into professional biocuration workflows, such as those used by the Alliance of Genome Resources and the ACKnowledge community curation platform, might well facilitate efficient and accurate annotation of the biomedical literature
MKK4 and MKK7 control degeneration of retinal ganglion cell somas and axons after glaucoma-relevant injury.
No full textRetinal ganglion cell (RGC) death is a critical component of glaucoma pathology. The degenerative signaling pathways that lead to RGC death in glaucoma are incompletely defined. Recently, the transcription factors JUN and DDIT3 were identified as critical hubs regulating RGC somal loss after mechanical axonal injury. However, their position within the degenerative cascade remains unclear. One possibility is that JUN and DDIT3 activity in the soma initiates signaling events that trigger axonal degeneration. Alternatively, JUN and DDIT3 may function downstream of the primary insult, acting specifically to mediate somal degeneration without influencing axonal pathology. Disentangling these possibilities is critical for understanding the compartment-specific mechanisms of RGC degeneration in glaucoma. The MAP2Ks MKK4 and MKK7 control JNK and JUN activity and can indirectly activate DDIT3. Furthermore, MKK4 and MKK7 have been shown to drive RGC axonal degeneration after mechanical axonal injury. The present work investigated whether JUN and DDIT3, or their upstream activators MKK4 and MKK7, control degeneration of RGC axons and somas after glaucoma-relevant injuries; including ocular hypertension in aged DBA/2J mice and after mechanical axonal injury (controlled optic nerve crush, CONC) in C57BL/6J mice. Ddit3 and Jun deletion did not prevent RGC axonal degeneration in DBA/2J mice but prevented nearly all somal loss. Despite robust somal survival, Ddit3 and Jun deletion did not prevent RGC somal shrinkage or pattern electroretinography (PERG) amplitude decline in DBA/2J mice or after CONC in C57BL/6J mice. In contrast, Mkk4 and Mkk7 deletion from C57BL/6J mice significantly lessened RGC soma and axon degeneration while preserving PERG amplitude and soma size after CONC. In summary, activation of MKK4 and MKK7 may be an inciting mechanism governing RGC somal and axonal degeneration after glaucoma-relevant axonal injury
AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome.
No full textMyalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic illness with a multifactorial etiology and heterogeneous symptomatology, posing major challenges for diagnosis and treatment. Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data and detailed clinical symptoms. By simultaneously modeling these diverse data types to predict clinical severity, BioMapAI identifies disease- and symptom-specific biomarkers and classifies ME/CFS in both held-out and independent external cohorts. Using an explainable AI approach, we construct a unique connectivity map spanning the microbiome, immune system and plasma metabolome in health and ME/CFS adjusted for age, gender and additional clinical factors. This map uncovers altered associations between microbial metabolism (for example, short-chain fatty acids, branched-chain amino acids, tryptophan, benzoate), plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA. Overall, BioMapAI provides unprecedented systems-level insights into ME/CFS, refining existing hypotheses and hypothesizing unique mechanisms-specifically, how multi-omics dynamics are associated to the disease\u27s heterogeneous symptoms
Emerging AI approaches for cancer spatial omics.
No full textTechnological breakthroughs in spatial omics and artificial intelligence (AI) have the potential to transform the understanding of cancer cells and the tumor microenvironment. Here we review the role of AI in spatial omics, discussing the current state-of-the-art and further needs to decipher cancer biology from large-scale spatial tissue data. An overarching challenge is the development of interpretable spatial AI models, an activity that demands not only improved data integration but also new conceptual frameworks. We discuss emerging paradigms-in particular, data-driven spatial AI, constraint-based spatial AI, and mechanistic spatial modeling-as well as the importance of integrating AI with hypothesis-driven strategies and model systems to realize the value of cancer spatial information
Exploring the transformative effects of calorie restriction on the lacrimal gland in adult mice.
No full textAdvanced age is one of the most recognizable risk factors for dry eye. Dry eye disease affects millions worldwide and can result from age-related lacrimal gland dysfunction, which correlates with a decline in lacrimal gland secretory cell function and chronic inflammation. This study investigated the potential of calorie restriction to maintain lacrimal gland and ocular surface health. Adult female C57BL/6 J mice were subjected to a 40% calorie restriction for 4 months, starting at 6-7 months and continuing until 10-11 months. These mice were compared to controls fed ad libitum. Bulk RNA sequencing of lacrimal glands, conjunctiva, and cornea subjected to calorie restriction compared to ad libitum revealed significant differentially expressed genes (DEGs). Pathways enriched in the upregulated DEGs indicate enhanced circadian rhythm, secretory functions, and lipid metabolism. These findings were confirmed using individual qRT-PCR and western blotting. In contrast, pathways enriched in the downregulated DEGs were associated with immune cell activation, adaptive immune responses, extracellular matrix remodeling, and metalloproteinase activity. Histological sections of calorie-restricted lacrimal glands revealed reduced mononuclear cell infiltration and fewer positive cells for CD4, CD19, and MHC II than in ad libitum lacrimal glands. Calorie restriction also prevented age-related corneal barrier dysfunction and mitigated age-related conjunctival goblet cell loss, hallmarks of dry eye disease. These findings suggest that calorie restriction supports lacrimal gland and ocular surface health by reducing inflammation and extracellular matrix remodeling and by enhancing the lacrimal gland\u27s secretory function