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Emotional intelligence (EI), or knowledge of how emotions function in self and others, is a popular construct in both scientific and professional communities. Current theoretical models suggest that EI is a combination of dynamic skills that can be learned and enhanced through participation in targeted intervention programs. Although popular, few if any of the aforementioned interventions have been subjected to empirical scrutiny. Consistent with calls for efficacy studies of intervention programs, the purpose of this exploratory study was to examine the effect of an adventure-based intervention on the EI of employees of a multisite dental practice. Fifteen individuals completed the Mayer-Salovey-Caruso Emotional Intelligence Test before and after participation in a day-long intervention. Results suggest that the intervention had a small but positive effect on the participants' EI and that improvements in the 4 branches of EI varied within employee subgroups. Implications for future research and practical considerations for the health care environment are discussed. [ABSTRACT FROM AUTHOR]

Perioperative haemodynamic optimisation of high-risk surgical patients has long been documented to improve both short-term and long-term outcomes, as well as to reduce the rate of postoperative complications. Based on the evidence, cardiac output monitoring and fluid resuscitation, combined with the use of inotropes, would seem to be the gold standard of care for these difficult surgical cases. However, clinicians do not universally apply these techniques and principles in their everyday practice. By exploring the reasons why this is so, perhaps we could move forward in the standardisation of care and the application of evidence-based practice. [ABSTRACT FROM AUTHOR]

Marine cyanobacteria have gained momentum in recent years as a source of novel bioactive small molecules. This paper describes the structure elucidation and pharmacological evaluation of two new (veraguamide O ( 1 ) and veraguamide P ( 2 )) and one known (veraguamide C ( 3 )) analogs isolated from a cyanobacterial collection made in the Las Perlas Archipelago of Panama. We hypothesized that these compounds would be cytotoxic in cancer cell lines. The compounds were screened against HEK-293, estrogen receptor positive (MCF-7), and triple-negative breast cancer (MDA-MB-231) cells as well as against a broad panel of membrane-bound receptors. The planar structures were determined based on NMR and MS data along with a comparison to previously isolated veraguamide analogs. Phylogenetic analysis of the collection suggests it to be an Okeania sp., a similar species to the cyanobacterium reported to produce other veraguamides. Veraguamide O shows no cytotoxicity (greater than 100 μM) against ER-positive cells (MCF-7) with 13 μM IC 50 against MDA-MB-231 TNBC cells. Interestingly, these compounds show affinity for the sigma2/TMEM-97 receptor, making them potential leads for the development of non-toxic sigma 2 targeting ligands.

Single cell transcriptomics (SCT) has revolutionized our understanding of cellular heterogeneity, yet the emergence of single cell proteomics (SCP) promises a more functional view of cellular dynamics. A challenge is that not all mass spectrometry facilities can perform SCP, and not all laboratories have access to cell sorting equipment required for SCP, which together motivate an interest in sending bulk cell samples through the mail for sorting and SCP analysis. Shipping requires cell storage, which has an unknown effect on SCP results. This study investigates the impact of cell storage conditions on the proteomic landscape at the single cell level, utilizing Data-Independent Acquisition (DIA) coupled with Parallel Accumulation Serial Fragmentation (diaPASEF). Three storage conditions were compared in 293T cells: (1) 37 °C (control), (2) 4 °C overnight, and (3) -196 °C storage followed by liquid nitrogen preservation. Both cold and frozen storage induced significant alterations in the cell diameter, elongation, and proteome composition. By elucidating how cell storage conditions alter cellular morphology and proteome profiles, this study contributes foundational technical information about SCP sample preparation and data quality.

Objectives: We applied three electronic triggers to study frequency and contributory factors of missed opportunities for improving diagnosis (MOIDs) in pediatric emergency departments (EDs): return visits within 10 days resulting in admission (Trigger 1), care escalation within 24 h of ED presentation (Trigger 2), and death within 24 h of ED visit (Trigger 3)., Methods: We created an electronic query and reporting template for the triggers and applied them to electronic health record systems of five pediatric EDs for visits from 2019. Clinician reviewers manually screened identified charts and initially categorized them as "unlikely for MOIDs" or "unable to rule out MOIDs" without a detailed chart review. For the latter category, reviewers performed a detailed chart review using the Revised Safer Dx Instrument to determine the presence of a MOID., Results: A total of 2937 ED records met trigger criteria (Trigger 1 1996 [68%], Trigger 2 829 [28%], Trigger 3 112 [4%]), of which 2786 (95%) were categorized as unlikely for MOIDs. The Revised Safer Dx Instrument was applied to 151 (5%) records and 76 (50%) had MOIDs. The overall frequency of MOIDs was 2.6% for the entire cohort, 3.0% for Trigger 1, 1.9% for Trigger 2, and 0% for Trigger 3. Brain lesions, infections, or hemorrhage; pneumonias and lung abscess; and appendicitis were the top three missed diagnoses. The majority (54%) of MOIDs cases resulted in patient harm. Contributory factors were related to patient-provider (52.6%), followed by patient factors (21.1%), system factors (13.2%), and provider factors (10.5%)., Conclusions: Using electronic triggers with selective record review is an effective process to screen for harmful diagnostic errors in EDs: detailed review of 5% of charts revealed MOIDs in half, of which half were harmful to the patient. With further refining, triggers can be used as effective patient safety tools to monitor diagnostic quality., (© 2025 The Author(s). Academic Emergency Medicine published by Wiley Periodicals LLC on behalf of Society for Academic Emergency Medicine.)

Background: Systemic sclerosis (SSc) is a rare connective tissue disease, frequently affecting the skin, lungs, and pulmonary vasculature. Approximately 30-50% of SSc patients develop interstitial lung disease (SSc-ILD), with 30-35% of related deaths attributed to it. Even though men are less likely to develop systemic sclerosis, they have a higher incidence of SSc-ILD than women, and they tend to develop it at a younger age with a higher mortality rate. Sex differences in protein expression in the blood of patients with SSc-ILD have not been reported to date. We aimed to identify sex differences in serum protein expression between men and women with SSc-ILD., Methods: Serum specimens of patients with SSc-ILD underwent dual mass spectrometry (LC-MS/MS) analysis. The association between protein biomarkers and sex was assessed through logistic regression. Time to event analysis was performed to determine any differences in the time to FVC decline of > 5% and the proportion of subjects who experienced FVC decline of > 5% by sex over the total period of observation. The association between biomarkers and sex was assessed through logistic regression. For proteins that were dichotomized, chi-squared testing was used. Multivariable regression models adjusting for meaningful clinical variables were also performed., Results: The cohort consisted of 211 subjects, 162 women and 47 men with a median follow-up of 3.52 years. No significant sex differences were found in the time to FVC decline of > 5% or > 10%. Among the 704 proteins identified, forty differed significantly between sexes. After adjusting for multiple testing, Autotaxin remained significantly higher in women. Autotaxin, known to activate lysophosphatidic acid and promote fibrosis, suggests a potential role in modulating fibrotic processes in SSc-ILD., Conclusions: This study is the first to report sex-specific serum protein differences in patients with SSc-ILD, with Autotaxin remaining significantly different after adjusting for multiple testing. These proteins could influence disease progression and treatment response and underscore the importance of personalized therapeutic strategies and further research into sex-related molecular pathways in SSc-ILD., Clinical Trial Number: Not applicable., Competing Interests: Declarations. Ethical approval: this study was approved by the Internal Review Board of the University of California San Francisco. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Metastatic pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with limited efficacious therapeutic options. Recent investigations have provided proof of concept that circulating tumor cells (CTCs) are reduced by purification of PDAC patient blood samples through ExThera Seraph100™ adsorption filters. Whether additional tumorigenic factors are also removed remains inadequately studied. Here, matched whole blood and purified blood samples from seven PDAC patients were analyzed for microparticle and soluble protein content. For microparticle analysis, patient samples were stratified by abundance. Filters markedly reduced ∼200-nm particles when in high abundance. Exosomes, or vesicles ranging from ∼50 to 150-nm were not significantly affected by the purification process. Proteomic analysis of plasma from the whole and purified blood revealed only a limited number of differentially expressed proteins. The complement C1Q proteins were reduced by the purification process, likely due to their heparin binding affinity. In contrast, there was an elevation in cytoplasmic proteins after purification, which may be due to cell destruction. Taken together, this study shows the selective removal of a subfraction of larger (>200 nm) microvesicles and C1Q during blood purification by the Seraph100™. The clinical significance of these findings requires further study., (Copyright © 2025. Published by Elsevier B.V.)

The prevalence of cardiovascular disease varies with sex, and the impact of intrinsic sex-based differences on vasculature is not well understood. Animal models can provide important insights into some aspects of human biology; however, not all discoveries in animal systems translate well to humans. To explore the impact of chromosomal sex on proteomic phenotypes, we used iPSC-derived vascular smooth muscle cells from healthy donors of both sexes to identify sex-based proteomic differences and their possible effects on cardiovascular pathophysiology. Our analysis confirmed that differentiated cells have a proteomic profile more similar to healthy primary aortic smooth muscle cells than iPSCs. We also identified sex-based differences in iPSC-derived vascular smooth muscle cells in pathways related to ATP binding, glycogen metabolic process, and cadherin binding as well as multiple proteins relevant to cardiovascular pathophysiology and disease. Additionally, we explored the role of autosomal and sex chromosomes in protein regulation, identifying that proteins on autosomal chromosomes also show sex-based regulation that may affect the protein expression of proteins from autosomal chromosomes. This work supports the biological relevance of iPSC-derived vascular smooth muscle cells as a model for disease, and further exploration of the pathways identified here can lead to the discovery of sex-specific pharmacological targets for cardiovascular disease.

Lysine metabolism converges at α-aminoadipic semialdehyde dehydrogenase (ALDH7A1). Rare loss-of-function mutations in ALDH7A1 cause a toxic accumulation of lysine catabolites, including piperideine-6-carboxylate (P6C), that are thought to cause fatal seizures in children unless strictly managed with dietary lysine reduction. In this study, we perform metabolomics and expression analysis of tissues from Aldh7a1-deficient mice, which reveal tissue-specific differences in lysine metabolism and other metabolic pathways. We also develop a fluorescent biosensor to characterize lysine transporter activity and identify competitive substrates that reduce the accumulation of lysine catabolites in ALDH7A1-deficient HEK293 cells. Lastly, we show that intravenous administration of lysine α-oxidase from Trichoderma viride reduces lysine and P6C levels by >80% in mice. Our results improve our understanding of lysine metabolism and make inroads toward improving therapeutic strategies for lysine catabolic disorders., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Myocardial infarctions locally deprive myocardium of oxygenated blood and cause immediate cardiac myocyte necrosis. Irreparable myocardium is then replaced with a scar through a dynamic repair process that is an interplay between hypoxic cells of the infarct zone and normoxic cells of adjacent healthy myocardium. In many cases, unresolved inflammation or fibrosis occurs for reasons that are incompletely understood, increasing the risk of heart failure. Crosstalk between hypoxic and normoxic cardiac cells is hypothesized to regulate mechanisms of repair after a myocardial infarction. To test this hypothesis, microfluidic devices are fabricated on 3D printed templates for co-culturing hypoxic and normoxic cardiac cells. This system demonstrates that hypoxia drives human cardiac fibroblasts toward glycolysis and a pro-fibrotic phenotype, similar to the anti-inflammatory phase of wound healing. Co-culture with normoxic fibroblasts uniquely upregulates pro-inflammatory signaling in hypoxic fibroblasts, including increased secretion of tumor necrosis factor alpha (TNF-α). In co-culture with hypoxic fibroblasts, normoxic human induced pluripotent stem cell (hiPSC)-derived cardiac myocytes also increase pro-inflammatory signaling, including upregulation of interleukin 6 (IL-6) family signaling pathway and increased expression of IL-6 receptor. Together, these data suggest that crosstalk between hypoxic fibroblasts and normoxic cardiac cells uniquely activates phenotypes that resemble the initial pro-inflammatory phase of post-infarct wound healing., (© 2024 Wiley‐VCH GmbH.)

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease characterized by complex metabolic rewiring that enables growth in changing nutrient availability and oxygen conditions. Transcriptome-based prognostic PDAC tumor subtypes, known as 'basal-like' and 'classical' subtypes are associated with differences in metabolic gene expression including genes involved in glycolysis. Tumor subtype-specific metabolism phenotypes may provide new targets for treatment development in PDAC, but their functional relevance has not been fully elucidated. We aimed to investigate differences in metabolic profiles and transcriptomes in tumor models derived from patients with basal-like and classical tumors., Methods: Patient-derived organoids (PDOs) were established from tumor biopsies collected from patients with metastatic PDAC, including three PDOs from basal-like and five PDOs from classical tumors. Metabolic analyses included assessment of differences in metabolic activity using Seahorse Glycolysis and Mito Stress tests and 13 C-glucose metabolites tracing analysis. In order to investigate the influence of mitochondrial pyruvate transport on metabolic differences, PDOs were treated with the mitochondrial pyruvate carrier 1 (MPC1) inhibitor UK-5099. Prognostic relevance of MPC1 was determined using a tumor tissue microarray (TMA) in resectable, and proteomics profiling in metastatic PDAC datasets. Whole genome and transcriptome sequencing, differential gene expression and gene set enrichment analyses were performed in PDOs., Results: Metastatic PDAC PDOs showed subtype-specific differences in glycolysis and oxidative phosphorylation (OXPHOS). Basal-like tumor-derived PDOs had a lower baseline extracellular acidification rate, but higher glycolytic reserves and oxygen consumption rate (OCR) than classical tumor-derived PDOs. OCR difference was eliminated following treatment with UK-5099. In the 13 C-glucose metabolites tracing experiment, a basal-like tumor PDO showed lower fractions of some M + 2 metabolites but higher sensitivity to UK-5099 mediated reduction in M + 2 metabolites than a classical tumor PDO. Protein level analyses revealed lower MPC1 protein levels in basal-like PDAC cases and association of low MPC1 levels with clinicopathologic parameters of tumor aggressiveness in PDAC. PDO differential gene expression analyses identified additional subtype-specific cellular pathways and potential disease outcome biomarkers., Conclusions: Our findings point to distinct metabolic profiles in PDAC subtypes with basal-like tumor PDOs showing higher OXPHOS and sensitivity to MPC1 inhibition. Subtypes-specific metabolic vulnerabilities may be exploited for selective therapeutic targeting., (© 2024. The Author(s).)

Myocardial infarction (MI) causes hypoxic injury to downstream myocardial tissue, which initiates a wound healing response that replaces injured myocardial tissue with a scar. Wound healing is a complex process that consists of multiple phases, in which many different stimuli induce cardiac fibroblasts to differentiate into myofibroblasts and deposit new matrix. While this process is necessary to replace necrotic tissue, excessive and unresolved fibrosis is common post-MI and correlated with heart failure. Therefore, defining how cardiac fibroblast phenotypes are distinctly regulated by stimuli that are prevalent in the post-MI microenvironment, such as hypoxia and transforming growth factor-beta (TGF-β), is essential for understanding and ultimately mitigating pathological fibrosis. In this study, we acutely treated primary human adult cardiac fibroblasts with TGF-β1 or hypoxia and then characterized their phenotype through immunofluorescence, quantitative RT-PCR, and proteomic analysis. We found that fibroblasts responded to low oxygen with increased localization of hypoxia inducible factor 1 (HIF-1) to the nuclei after 4h, which was followed by increased gene expression of vascular endothelial growth factor A (VEGFA), a known target of HIF-1, by 24h. Both TGF-β1 and hypoxia inhibited proliferation after 24h. TGF-β1 treatment also upregulated various fibrotic pathways. In contrast, hypoxia caused a reduction in several protein synthesis pathways, including collagen biosynthesis. Collectively, these data suggest that TGF-β1, but not acute hypoxia, robustly induces the differentiation of human cardiac fibroblasts into myofibroblasts. Discerning the overlapping and distinctive outcomes of TGF-β1 and hypoxia treatment is important for elucidating their roles in fibrotic remodeling post-MI and provides insight into potential therapeutic targets.

The prevalence of cardiovascular disease varies with sex, and the impact of intrinsic sex-based differences on vasculature is not well understood. Animal models can provide important insight into some aspects of human biology, however not all discoveries in animal systems translate well to humans. To explore the impact of chromosomal sex on proteomic phenotypes, we used iPSC-derived vascular smooth muscle cells from healthy donors of both sexes to identify sex-based proteomic differences and their possible effects on cardiovascular pathophysiology. Our analysis confirmed that differentiated cells have a proteomic profile more similar to healthy primary aortic smooth muscle than iPSCs. We also identified sex-based differences in iPSC- derived vascular smooth muscle in pathways related to ATP binding, glycogen metabolic process, and cadherin binding as well as multiple proteins relevant to cardiovascular pathophysiology and disease. Additionally, we explored the role of autosomal and sex chromosomes in protein regulation, identifying that proteins on autosomal chromosomes also show sex-based regulation that may affect the protein expression of proteins from autosomal chromosomes. This work supports the biological relevance of iPSC-derived vascular smooth muscle cells as a model for disease, and further exploration of the pathways identified here can lead to the discovery of sex-specific pharmacological targets for cardiovascular disease., Significance: In this work, we have differentiated 4 male and 4 female iPSC lines into vascular smooth muscle cells, giving us the ability to identify statistically-significant sex-specific proteomic markers that are relevant to cardiovascular disease risk (such as PCK2, MTOR, IGFBP2, PTGR2, and SULTE1).

Background: Few studies have described the insights of frontline health care providers and patients on how the diagnostic process can be improved in the emergency department (ED), a setting at high risk for diagnostic errors. The authors aimed to identify the perspectives of providers and patients on the diagnostic process and identify potential interventions to improve diagnostic safety., Methods: Semistructured interviews were conducted with 10 ED physicians, 15 ED nurses, and 9 patients/caregivers at two separate health systems. Interview questions were guided by the ED-Adapted National Academies of Sciences, Engineering, and Medicine Diagnostic Process Framework and explored participant perspectives on the ED diagnostic process, identified vulnerabilities, and solicited interventions to improve diagnostic safety. The authors performed qualitative thematic analysis on transcribed interviews., Results: The research team categorized vulnerabilities in the diagnostic process and intervention opportunities based on the ED-Adapted Framework into five domains: (1) team dynamics and communication (for example, suboptimal communication between referring physicians and the ED team); (2) information gathering related to patient presentation (for example, obtaining the history from the patients or their caregivers; (3) ED organization, system, and processes (for example, staff schedules and handoffs); (4) patient education and self-management (for example, patient education at discharge from the ED); and (5) electronic health record and patient portal use (for example, automatic release of test results into the patient portal). The authors identified 33 potential interventions, of which 17 were provider focused and 16 were patient focused., Conclusion: Frontline providers and patients identified several vulnerabilities and potential interventions to improve ED diagnostic safety. Refining, implementing, and evaluating the efficacy of these interventions are required., (Copyright © 2024 The Joint Commission. Published by Elsevier Inc. All rights reserved.)

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups., Competing Interests: Competing interests The authors declare no competing interests.

There is an unmet need to improve the efficacy of platinum-based cancer chemotherapy, which is used in primary and metastatic settings in many cancer types. In bladder cancer, platinum-based chemotherapy leads to better outcomes in a subset of patients when used in the neoadjuvant setting or in combination with immunotherapy for advanced disease. Despite such promising results, extending the benefits of platinum drugs to a greater number of patients is highly desirable. Using the multiomic assessment of cisplatin-responsive and -resistant human bladder cancer cell lines and whole-genome CRISPR screens, we identified puromycin-sensitive aminopeptidase (NPEPPS) as a driver of cisplatin resistance. NPEPPS depletion sensitized resistant bladder cancer cells to cisplatin in vitro and in vivo. Conversely, overexpression of NPEPPS in sensitive cells increased cisplatin resistance. NPEPPS affected treatment response by regulating intracellular cisplatin concentrations. Patient-derived organoids (PDO) generated from bladder cancer samples before and after cisplatin-based treatment, and from patients who did not receive cisplatin, were evaluated for sensitivity to cisplatin, which was concordant with clinical response. In the PDOs, depletion or pharmacologic inhibition of NPEPPS increased cisplatin sensitivity, while NPEPPS overexpression conferred resistance. Our data present NPEPPS as a druggable driver of cisplatin resistance by regulating intracellular cisplatin concentrations., Significance: Targeting NPEPPS, which induces cisplatin resistance by controlling intracellular drug concentrations, is a potential strategy to improve patient responses to platinum-based therapies and lower treatment-associated toxicities., (©2024 The Authors; Published by the American Association for Cancer Research.)

Background: Emergency departments (EDs) are susceptible to diagnostic error. Suboptimal communication between the patient and the interdisciplinary care team increases risk to diagnostic safety. The role of communication remains underrepresented in existing diagnostic decision-making conceptual models., Methods: The authors used eDelphi methodology, whereby data are collected electronically, to achieve consensus among an expert panel of 18 clinicians, patients, family members, and other participants on a refined ED-based diagnostic decision-making framework that integrates several potential opportunities for communication to enhance diagnostic quality. This study examined the entire diagnostic process in the ED, from prehospital to discharge or transfer to inpatient care, and identified where communication breakdowns could occur. After four iterative rounds of the eDelphi process, including a final validation round by all participants, the project's a priori consensus threshold of 80% agreement was reached., Results: The authors developed a final framework that positions communication more prominently in the diagnostic process in the ED and enhances the original National Academies of Sciences, Engineering, and Medicine (NASEM) and ED-adapted NASEM frameworks. Specific points in the ED journey were identified where more attention to communication might be helpful. Two specific types of communication-information exchange and shared understanding-were identified as high priority for optimal outcomes. Ideas for communication-focused interventions to prevent diagnostic error in the ED fell into three categories: patient-facing, clinician-facing, and system-facing interventions., Conclusion: This project's refinement of the NASEM framework adapted to the ED can be used to develop communications-focused interventions to reduce diagnostic error in this highly complex and error-prone setting., (Copyright © 2024 The Joint Commission. All rights reserved.)

Motivation: Complex tissues are dynamic ecosystems consisting of molecularly distinct yet interacting cell types. Computational deconvolution aims to dissect bulk tissue data into cell type compositions and cell-specific expressions. With few exceptions, most existing deconvolution tools exploit supervised approaches requiring various types of references that may be unreliable or even unavailable for specific tissue microenvironments., Results: We previously developed a fully unsupervised deconvolution method-Convex Analysis of Mixtures (CAM), that enables estimation of cell type composition and expression from bulk tissues. We now introduce CAM3.0 tool that improves this framework with three new and highly efficient algorithms, namely, radius-fixed clustering to identify reliable markers, linear programming to detect an initial scatter simplex, and a smart floating search for the optimum latent variable model. The comparative experimental results obtained from both realistic simulations and case studies show that the CAM3.0 tool can help biologists more accurately identify known or novel cell markers, determine cell proportions, and estimate cell-specific expressions, complementing the existing tools particularly when study- or datatype-specific references are unreliable or unavailable., Availability and Implementation: The open-source R Scripts of CAM3.0 is freely available at https://github.com/ChiungTingWu/CAM3/(https://github.com/Bioconductor/Contributions/issues/3205). A user's guide and a vignette are provided., (© The Author(s) 2024. Published by Oxford University Press.)

Amino acid transporters (AATs) facilitate nutrient uptake and nutrient exchange between cancer and stromal cells. The posttranslational modification (PTM) of transporters is an important mechanism that tumor-associated cells use to dynamically regulate their function and stability in response to microenvironmental cues. In this review, we summarize recent findings that demonstrate the significance of N-glycosylation, phosphorylation, and ubiquitylation for the function of AATs. We also highlight powerful approaches that hijack the PTM machinery that could be used as therapeutics or tools to modulate transporter activity., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Pancreatic ductal adenocarcinoma (PDAC) cells use glutamine (Gln) to support proliferation and redox balance. Early attempts to inhibit Gln metabolism using glutaminase inhibitors resulted in rapid metabolic reprogramming and therapeutic resistance. Here, we demonstrated that treating PDAC cells with a Gln antagonist, 6-diazo-5-oxo-L-norleucine (DON), led to a metabolic crisis in vitro. In addition, we observed a profound decrease in tumor growth in several in vivo models using sirpiglenastat (DRP-104), a pro-drug version of DON that was designed to circumvent DON-associated toxicity. We found that extracellular signal-regulated kinase (ERK) signaling is increased as a compensatory mechanism. Combinatorial treatment with DRP-104 and trametinib led to a significant increase in survival in a syngeneic model of PDAC. These proof-of-concept studies suggested that broadly targeting Gln metabolism could provide a therapeutic avenue for PDAC. The combination with an ERK signaling pathway inhibitor could further improve the therapeutic outcome., (© 2023. The Author(s).)

The ability of tumor cells to alter their metabolism to support survival and growth presents a challenge to effectively treat cancers. Carbonic anhydrase IX (CAIX) is a hypoxia-induced, metabolic enzyme that plays a crucial role in pH regulation in tumor cells. Recently, through a synthetic lethal screen, we identified CAIX to play an important role in redox homeostasis. In this study, we show that CAIX interacts with the glutamine (Gln) transporter, solute carrier family 1 member 5 (SLC1A5), and coordinately functions to maintain redox homeostasis through the glutathione/glutathione peroxidase 4 (GSH/GPX4) axis. Inhibition of CAIX increases Gln uptake by SLC1A5 and concomitantly increases GSH levels. The combined inhibition of CAIX activity and Gln metabolism or the GSH/GPX4 axis results in an increase in lipid peroxidation and induces ferroptosis, both in vitro and in vivo. Thus, this study demonstrates cotargeting of CAIX and Gln metabolism as a potential strategy to induce ferroptosis in tumor cells., (©2023 The Authors; Published by the American Association for Cancer Research.)

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious, requiring 2 h of mass spectrometry time per single muscle fiber; 50 fibers would take approximately 4 days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 min total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 h. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Ninety-four proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, oxidative phosphorylation, and muscle structure and contractile function. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.

The vascular endothelium constitutes the inner lining of the blood vessel, and malfunction and injuries of the endothelium can cause cardiovascular diseases as well as other diseases including stroke, tumor growth, and chronic kidney failure. Generation of effective sources to replace injured endothelial cells (ECs) could have significant clinical impact, and somatic cell sources like peripheral or cord blood cannot credibly supply enough endothelial cell progenitors for multitude of treatments. Pluripotent stem cells are a promising source for a reliable EC supply, which have the potential to restore tissue function and treat vascular diseases. We have developed methods to differentiate induced pluripotent stem cells (iPSCs) efficiently and robustly across multiple iPSC lines into nontissue-specific pan vascular ECs (iECs) with high purity. These iECs present with canonical endothelial cell markers and exhibit measures of endothelial cell functionality with the uptake of Dil fluorescent dye-labeled acetylated low-density lipoprotein (Dil-Ac-LDL) and tube formation. Using proteomic analysis, we revealed that the iECs are more proteomically similar to established human umbilical vein ECs (HUVECs) than to iPSCs. Posttranslational modifications (PTMs) were most shared between HUVECs and iECs, and potential targets for increasing the proteomic similarity of iECs to HUVECs were identified. Here we demonstrate an efficient robust method to differentiate iPSCs into functional ECs, and for the first time provide a comprehensive protein expression profile of iECs, which indicates their similarities with a widely used immortalized HUVECs, allowing for further mechanistic studies of EC development, signaling, and metabolism for future regenerative applications. NEW & NOTEWORTHY We have developed methods to differentiate induced pluripotent stem cells (iPSCs) across multiple iPSC lines into nontissue-specific pan vascular ECs (iECs) and demonstrated the proteomic similarity of these cells to a widely used endothelial cell line (HUVECs). We also identified posttranslational modifications and targets for increasing the proteomic similarity of iECs to HUVECs. In the future, iECs can be used to study EC development, signaling, and metabolism for future regenerative applications.

Membrane proteins play critical roles at the cell surface and their misfunction is a hallmark of many human diseases. A precise evaluation of the plasma membrane proteome is therefore essential for cell biology and for discovering novel biomarkers and therapeutic targets. However, the low abundance of this proteome relative to soluble proteins makes it difficult to characterize, even with the most advanced proteomics technologies. Here, we apply the peptidisc membrane mimetic to purify the cell membrane proteome. Using the HeLa cell line as a reference, we capture 500 different integral membrane proteins, with half annotated to the plasma membrane. Notably, the peptidisc library is enriched with several ABC, SLC, GPCR, CD, and cell adhesion molecules that generally exist at low to very low copy numbers in the cell. We extend the method to compare two pancreatic cell lines, Panc-1 and hPSC. Here we observe a striking difference in the relative abundance of the cell surface cancer markers L1CAM, ANPEP, ITGB4, and CD70. We also identify two novel SLC transporters, SLC30A1 and SLC12A7, that are highly present in the Panc-1 cell only. The peptidisc library thus emerges as an effective way to survey and compare the membrane proteome of mammalian cells. Furthermore, since the method stabilizes membrane proteins in a water-soluble state, members of the library, here SLC12A7, can be specifically isolated., Competing Interests: Conflict of interest Franck Duong is the scientific founder of Peptidisc Biotech. All other authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Motivation: Analytics tools are essential to identify informative molecular features about different phenotypic groups. Among the most fundamental tasks are missing value imputation, signature gene detection, and expression pattern visualization. However, most commonly used analytics tools may be problematic for characterizing biologically diverse samples when either signature genes possess uneven missing rates across different groups yet involving complex missing mechanisms, or multiple biological groups are simultaneously compared and visualized., Results: We develop ABDS tool suite tailored specifically to analyzing biologically diverse samples. Mechanism-integrated group-wise imputation is developed to recruit signature genes involving informative missingness, cosine-based one-sample test is extended to detect enumerated signature genes, and unified heatmap is designed to comparably display complex expression patterns. We discuss the methodological principles and demonstrate the conceptual advantages of the three software tools. We also showcase the biomedical applications of these individual tools. Implemented in open-source R scripts, ABDS tool suite complements rather than replaces the existing tools and will allow biologists to more accurately detect interpretable molecular signals among diverse phenotypic samples., Availability and Implementation: The R Scripts of ABDS tool suite is freely available at https://github.com/niccolodpdu/ABDS., Competing Interests: COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests.

Systemic sclerosis is a rare connective tissue disease; and interstitial lung disease (SSc-ILD) is associated with significant morbidity and mortality. There are no clinical, radiologic features, nor biomarkers that identify the specific time when patients are at risk for progression at which the benefits from treatment outweigh the risks. Our study aimed to identify blood protein biomarkers associated with progression of interstitial lung disease in patients with SSc-ILD using an unbiased, high-throughput approach. We classified SSc-ILD as progressive or stable based on change in forced vital capacity over 12 months or less. We profiled serum proteins by quantitative mass spectrometry and analyzed the association between protein levels and progression of SSc-ILD via logistic regression. The proteins associated with at a p value of < 0.1 were queried in the ingenuity pathway analysis (IPA) software to identify interaction networks, signaling, and metabolic pathways. Through principal component analysis, the relationship between the top 10 principal components and progression was evaluated. Unsupervised hierarchical clustering with heatmapping was done to define unique groups. The cohort consisted of 72 patients, 32 with progressive SSc-ILD and 40 with stable disease with similar baseline characteristics. Of a total of 794 proteins, 29 were associated with disease progression. After adjusting for multiple testing, these associations did not remain significant. IPA identified five upstream regulators that targeted proteins associated with progression, as well as a canonical pathway with a higher signal in the progression group. Principal component analysis showed that the ten components with the highest Eigenvalues represented 41% of the variability of the sample. Unsupervised clustering analysis revealed no significant heterogeneity between the subjects. We identified 29 proteins associated with progressive SSc-ILD. While these associations did not remain significant after accounting for multiple testing, some of these proteins are part of pathways relevant to autoimmunity and fibrogenesis. Limitations included a small sample size and a proportion of immunosuppressant use in the cohort, which could have altered the expression of inflammatory and immunologic proteins. Future directions include a targeted evaluation of these proteins in another SSc-ILD cohort or application of this study design to a treatment naïve population., (© 2023. The Author(s).)

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious requiring two hours of mass spectrometry time per single muscle fiber; 50 fibers would take approximately four days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 minutes total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 hours. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Sixty-five proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, muscle structure and regulation. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.