Sialic acid blockade inhibits the metastatic spread of prostate cancer to bone.

BACKGROUND: Bone metastasis is a common consequence of advanced prostate cancer. Bisphosphonates can be used to manage symptoms, but there are currently no curative treatments available. Altered tumour cell glycosylation is a hallmark of cancer and is an important driver of a malignant phenotype. In prostate cancer, the sialyltransferase ST6GAL1 is upregulated, and studies show ST6GAL1-mediated aberrant sialylation of N-glycans promotes prostate tumour growth and disease progression. METHODS: Here, we monitor ST6GAL1 in tumour and serum samples from men with aggressive prostate cancer and using in vitro and in vivo models we investigate the role of ST6GAL1 in prostate cancer bone metastasis. FINDINGS: ST6GAL1 is upregulated in patients with prostate cancer with tumours that have spread to the bone and can promote prostate cancer bone metastasis in vivo. The mechanisms involved are multi-faceted and involve modification of the pre-metastatic niche towards bone resorption to promote the vicious cycle, promoting the development of M2 like macrophages, and the regulation of immunosuppressive sialoglycans. Furthermore, using syngeneic mouse models, we show that inhibiting sialylation can block the spread of prostate tumours to bone. INTERPRETATION: Our study identifies an important role for ST6GAL1 and α2-6 sialylated N-glycans in prostate cancer bone metastasis, provides proof-of-concept data to show that inhibiting sialylation can suppress the spread of prostate tumours to bone, and highlights sialic acid blockade as an exciting new strategy to develop new therapies for patients with advanced prostate cancer. FUNDING: Prostate Cancer Research and the Mark Foundation For Cancer Research, the Medical Research Council and Prostate Cancer UK.

Glycosylated Polyhydroxyproline Is a Potent Antifreeze Molecule.

Molecules that inhibit the growth of ice crystals are highly desirable for applications in building materials, foods, and agriculture. Antifreezes are particularly essential in biomedicine for tissue banking, yet molecules currently in use have known toxic effects. Antifreeze glycoproteins have evolved naturally in polar fish species living in subzero climates, but practical issues with collection and purification have limited their commercial use. Here, we present a synthetic strategy using polymerization of amino acid N-carboxyanhydrides to produce polypeptide mimics of these potent natural antifreeze proteins. We investigated a set of mimics with varied structural properties and identified a glycopolypeptide with potent ice recrystallization inhibition properties. We optimized for molecular weight, characterized their conformations, and verified their cytocompatibility in a human cell line. Overall, we present a material that will have broad applications as a biocompatible antifreeze.

Unlocking Health Literacy: The Ultimate Guide to Hypertension Education From ChatGPT Versus Google Gemini.

Background Google Gemini (Google, Mountain View, CA) represents the latest advances in the realm of artificial intelligence (AI) and has garnered attention due to its capabilities similar to the increasingly popular ChatGPT (OpenAI, San Francisco, CA). Accurate dissemination of information on common conditions such as hypertension is critical for patient comprehension and management. Despite the ubiquity of AI, comparisons between ChatGPT and Gemini remain unexplored. Methods ChatGPT and Gemini were asked 52 questions derived from the American College of Cardiology's (ACC) frequently asked questions on hypertension, following a specified prompt. Prompts included: no prompting (Form 1), patient-friendly prompting (Form 2), physician-level prompting (Form 3), and prompting for statistics/references (Form 4). Responses were scored as incorrect, partially correct, or correct. Flesch-Kincaid (FK) grade level and word count were recorded. Results Across all forms, scoring frequencies were as follows: 23 (5.5%) incorrect, 162 (38.9%) partially correct, and 231 (55.5%) correct. ChatGPT showed higher rates of partially correct answers than Gemini (p = 0.0346). Physician-level prompts resulted in a higher word count across both platforms (p < 0.001). ChatGPT showed a higher FK grade level (p = 0.033) in physician-friendly prompting. Gemini exhibited a significantly higher mean word count (p < 0.001); however, ChatGPT had a higher FK grade level across all forms (p > 0.001). Conclusion To our knowledge, this study is the first to compare cardiology-related responses from ChatGPT and Gemini, two of the most popular AI chatbots. The grade level for most responses was collegiate level, which was above average for the National Institutes of Health (NIH) recommendations, but on par with most online medical information. Both chatbots responded with a high degree of accuracy, with inaccuracies being rare. Therefore, it is reasonable that cardiologists suggest either chatbot as a source of supplementary education.

The Global Impact of Diversifying PrEP Options: Results of an International Discrete Choice Experiment of Existing and Potential PrEP Strategies with Gay and Bisexual Men (GBM) and Physicians.

To improve current and future use of existing (oral, injectable) and potential future (implants, douches) PrEP products, we must understand product preferences relative to one another, among gay and bisexual men (GBM), and physicians who prescribe PrEP. We completed an online discrete choice experiment (DCE) with separate groups of GBM and/or physicians from the U.S., South Africa, Spain, and Thailand. Participants were presented information on PrEP products, including daily pills, event-driven pills (2-1-1 regimen), injections, subdermal implants (dissolvable, removable), and rectal douches. Next, they completed a choice exercise in which they were shown ten screens, each presenting three of the aforementioned products at a time with 11 attributes for physicians and 10 attributes for GBM. For the attributes that were not constant, one level was shown per screen for each product. Participants selected the product they preferred most and rated their likelihood to select (GBM) or recommend (physicians) that product. Data were modeled using Hierarchical Bayes estimation; resulting model coefficients were used to develop attribute importance measures and product preferences. For GBM across all countries, if all aforementioned PrEP products were on the market at the same time, over 90% of GBM would use some form of PrEP; 100% of physicians would recommend at least one of the PrEP products. There were variations in product preference by country. GBM in the U.S. and Thailand preferred the injection (21.7%, 22.9%, respectively), while the dissolvable implant was preferred in South Africa and Spain (19.9%, 19.8%, respectively). In the U.S., South Africa, and Spain (where physician data were available), physicians were most likely to recommend the dissolvable implant (37.2%, 40.6%, 38.3%, respectively).

Non-Small Cell Lung Cancer, Version 4.2024.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non-Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of patients with NSCLC, including diagnosis, primary disease management, surveillance for relapse, and subsequent treatment. The panel has updated the list of recommended targeted therapies based on recent FDA approvals and clinical data. This selection from the NCCN Guidelines for NSCLC focuses on treatment recommendations for advanced or metastatic NSCLC with actionable molecular biomarkers.

From signalling to form: the coordination of neural tube patterning.

The development of the vertebrate spinal cord involves the formation of the neural tube and the generation of multiple distinct cell types. The process starts during gastrulation, combining axial elongation with specification of neural cells and the formation of the neuroepithelium. Tissue movements produce the neural tube which is then exposed to signals that provide patterning information to neural progenitors. The intracellular response to these signals, via a gene regulatory network, governs the spatial and temporal differentiation of progenitors into specific cell types, facilitating the assembly of functional neuronal circuits. The interplay between the gene regulatory network, cell movement, and tissue mechanics generates the conserved neural tube pattern observed across species. In this review we offer an overview of the molecular and cellular processes governing the formation and patterning of the neural tube, highlighting how the remarkable complexity and precision of vertebrate nervous system arises. We argue that a multidisciplinary and multiscale understanding of the neural tube development, paired with the study of species-specific strategies, will be crucial to tackle the open questions.

Synthesis, Electronic, and Antibacterial Properties of 3,7-Di(hetero)aryl-substituted Phenothiazinyl N-Propyl Trimethylammonium Salts.

In this study, a library of 3,7-di(hetero)aryl-substituted 10-(3-trimethylammoniumpropyl)10H-phenothiazine salts is prepared. These title compounds and their precursors are reversible redox systems with tunable potentials. The Hammett correlation gives a very good correlation of the first oxidation potentials with σp parameters. Furthermore, the title compounds and their precursors are blue to green-blue emissive. Screening of the salts reveals for some derivatives a distinct inhibition of several pathogenic bacterial strains (Mycobacterium tuberculosis, Staphylococcus aureus, Escherichia coli, Aconetobacter baumannii, and Klebsiella pneumoniae) in the lower micromolar range.

Interactive transcriptome analyses of Northern Wild Rice (Zizania palustris L.) and Bipolaris oryzae show convoluted communications during the early stages of fungal brown spot development.

Fungal diseases, caused mainly by Bipolaris spp., are past and current threats to Northern Wild Rice (NWR) grain production and germplasm preservation in both natural and cultivated settings. Genetic resistance against the pathogen is scarce. Toward expanding our understanding of the global gene communications of NWR and Bipolaris oryzae interaction, we designed an RNA sequencing study encompassing the first 12 h and 48 h of their encounter. NWR activated numerous plant recognition receptors after pathogen infection, followed by active transcriptional reprogramming of signaling mechanisms driven by Ca2+ and its sensors, mitogen-activated protein kinase cascades, activation of an oxidative burst, and phytohormone signaling-bound mechanisms. Several transcription factors associated with plant defense were found to be expressed. Importantly, evidence of diterpenoid phytoalexins, especially phytocassane biosynthesis, among expression of other defense genes was found. In B. oryzae, predicted genes associated with pathogenicity including secreted effectors that could target plant defense mechanisms were expressed. This study uncovered the early molecular communication between the NWR-B. oryzae pathosystem, which could guide selection for allele-specific genes to boost NWR defenses, and overall aid in the development of more efficient selection methods in NWR breeding through the use of the most virulent fungal isolates.

[18F]FDG PET/CT for identifying the causes of fever of unknown origin (FUO).

Fever of unknown origin (FUO) continues to be a challenging diagnosis in clinical medicine. It has more than 200 known causes, including infections, autoimmune diseases, neoplasia, and other miscellaneous disorders. Despite the development of a wide range of diagnostic tools, a specific diagnostic algorithm for FUO is not yet available. However, [18F]FDG PET/CT, which yields information on cellular metabolism, in addition to details of organ anatomy, has been shown to be successful in the FUO investigation. This study highlights the uses of [18F]FDG PET/CT in diagnosing various causes of FUO. [18F]FDG PET/CT has been increasingly used to detect septic infections, sterile inflammatory processes, and malignancies, occupying a significant portion of the known causes of FUO. It has led to a more definitive identification of the etiology of FUO and accurate clinical management. However, more in-depth studies are crucial to understanding if [18F]FDG PET/CT can be used in the work-up of FUO.

Ophiobolin A Covalently Targets Mitochondrial Complex IV Leading to Metabolic Collapse in Cancer Cells.

Ophiobolin A (OPA) is a sesterterpenoid fungal natural product with broad anticancer activity. While OPA possesses multiple electrophilic moieties that can covalently react with nucleophilic amino acids on proteins, the proteome-wide targets and mechanism of OPA remain poorly understood in many contexts. In this study, we used covalent chemoproteomic platforms to map the proteome-wide reactivity of the OPA in a highly sensitive lung cancer cell line. Among several proteins that OPA engaged, we focused on two targets: lysine-72 of cytochrome c oxidase subunit 5A (COX5A) and cysteine-53 of mitochondrial hypoxia induced gene 1 domain family member 2A (HIGD2A). These two subunit proteins are part of complex IV (cytochrome C oxidase) within the electron transport chain and contributed significantly to the antiproliferative activity of OPA. OPA activated mitochondrial respiration in a COX5A- and HIGD2A-dependent manner, leading to an initial spike in mitochondrial ATP and heightened mitochondrial oxidative stress. OPA compromised mitochondrial membrane potential, ultimately leading to ATP depletion. We have used chemoproteomic strategies to discover a unique anticancer mechanism of OPA through activation of complex IV leading to compromised mitochondrial energetics and rapid cell death.

Ultralow Catalytic Loading for Optimised Electrocatalytic Performance of AuPt Nanoparticles to Produce Hydrogen and Ammonia.

The hydrogen evolution and nitrite reduction reactions are key to producing green hydrogen and ammonia. Antenna-reactor nanoparticles hold promise to improve the performances of these transformations under visible-light excitation, by combining plasmonic and catalytic materials. However, current materials involve compromising either on the catalytic activity or the plasmonic enhancement and also lack control of reaction selectivity. Here, we demonstrate that ultralow loadings and non-uniform surface segregation of the catalytic component optimize catalytic activity and selectivity under visible-light irradiation. Taking Pt-Au as an example we find that fine-tuning the Pt content produces a 6-fold increase in the hydrogen evolution compared to commercial Pt/C as well as a 6.5-fold increase in the nitrite reduction and a 2.5-fold increase in the selectivity for producing ammonia under visible light excitation relative to dark conditions. Density functional theory suggests that the catalytic reactions are accelerated by the intimate contact between nanoscale Pt-rich and Au-rich regions at the surface, which facilitates the formation of electron-rich hot-carrier puddles associated with the Pt-based active sites. The results provide exciting opportunities to design new materials with improved photocatalytic performance for demanding sustainable energy applications.

Development of Ln(III) Derivatives as 19F Parashift Probes.

19F parashift probes with paramagnetically shifted reporter nuclei provide attractive platforms to develop molecular imaging probes. These probes enable ratiometric detection of molecular disease markers using a direct detection technique. Here, we describe a series of trivalent lanthanide (Ln(III)) complexes that are structural analogues of the clinically approved MR contrast agent (CA) ProHance to obtain LnL 19F parashift probes. We evaluated trans-gadolinium paramagnetic lanthanides compared to diamagnetic YL for 19F chemical shift and relaxation rate enhancement. The paramagnetic contribution to chemical shift (δPCS) for paramagnetic LnL exhibited either shifts to lower frequency (δPCS < 0 for TbL, DyL, and HoL) or shifts to higher frequency (δPCS > 0 for ErL, TmL, and YbL) compared to YL 19F spectroscopic signal. Zero-echo time pulse sequences achieved 56-fold sensitivity enhancement for DyL over YL, while developing probe-specific pulse sequences with fast delay times and acquisition times achieved 0.6-fold enhancement in limit of detection for DyL. DyL provides an attractive platform to develop 19F parashift probes for ratiometric detection of enzymatic activity.

Propionate prevents loss of the PDIM virulence lipid in Mycobacterium tuberculosis.

Phthiocerol dimycocerosate (PDIM) is an essential virulence lipid of Mycobacterium tuberculosis. In vitro culturing rapidly selects for spontaneous PDIM-negative mutants that have attenuated virulence and increased cell wall permeability, thus impacting the relevance of experimental findings. PDIM loss can also reduce the efficacy of the BCG Pasteur vaccine. Here we show that vancomycin susceptibility can rapidly screen for M. tuberculosis PDIM production. We find that metabolic deficiency of methylmalonyl-CoA impedes the growth of PDIM-producing bacilli, selecting for PDIM-negative variants. Supplementation with odd-chain fatty acids, cholesterol or vitamin B12 restores PDIM-positive bacterial growth. Specifically, we show that propionate supplementation enhances PDIM-producing bacterial growth and selects against PDIM-negative mutants, analogous to in vivo conditions. Our study provides a simple approach to screen for and maintain PDIM production, and reveals how discrepancies between the host and in vitro nutrient environments can attenuate bacterial pathogenicity.

Intricacies of Human-AI Interaction in Dynamic Decision-Making for Precision Oncology: A Case Study in Response-Adaptive Radiotherapy.

Background: Adaptive treatment strategies that can dynamically react to individual cancer progression can provide effective personalized care. Longitudinal multi-omics information, paired with an artificially intelligent clinical decision support system (AI-CDSS) can assist clinicians in determining optimal therapeutic options and treatment adaptations. However, AI-CDSS is not perfectly accurate, as such, clinicians' over/under reliance on AI may lead to unintended consequences, ultimately failing to develop optimal strategies. To investigate such collaborative decision-making process, we conducted a Human-AI interaction case study on response-adaptive radiotherapy (RT). Methods: We designed and conducted a two-phase study for two disease sites and two treatment modalities-adaptive RT for non-small cell lung cancer (NSCLC) and adaptive stereotactic body RT for hepatocellular carcinoma (HCC)-in which clinicians were asked to consider mid-treatment modification of the dose per fraction for a number of retrospective cancer patients without AI-support (Unassisted Phase) and with AI-assistance (AI-assisted Phase). The AI-CDSS graphically presented trade-offs in tumor control and the likelihood of toxicity to organs at risk, provided an optimal recommendation, and associated model uncertainties. In addition, we asked for clinicians' decision confidence level and trust level in individual AI recommendations and encouraged them to provide written remarks. We enrolled 13 evaluators (radiation oncology physicians and residents) from two medical institutions located in two different states, out of which, 4 evaluators volunteered in both NSCLC and HCC studies, resulting in a total of 17 completed evaluations (9 NSCLC, and 8 HCC). To limit the evaluation time to under an hour, we selected 8 treated patients for NSCLC and 9 for HCC, resulting in a total of 144 sets of evaluations (72 from NSCLC and 72 from HCC). Evaluation for each patient consisted of 8 required inputs and 2 optional remarks, resulting in up to a total of 1440 data points. Results: AI-assistance did not homogeneously influence all experts and clinical decisions. From NSCLC cohort, 41 (57%) decisions and from HCC cohort, 34 (47%) decisions were adjusted after AI assistance. Two evaluations (12%) from the NSCLC cohort had zero decision adjustments, while the remaining 15 (88%) evaluations resulted in at least two decision adjustments. Decision adjustment level positively correlated with dissimilarity in decision-making with AI [NSCLC: ρ = 0.53 ( p < 0.001); HCC: ρ = 0.60 ( p < 0.001)] indicating that evaluators adjusted their decision closer towards AI recommendation. Agreement with AI-recommendation positively correlated with AI Trust Level [NSCLC: ρ = 0.59 ( p < 0.001); HCC: ρ = 0.7 ( p < 0.001)] indicating that evaluators followed AI's recommendation if they agreed with that recommendation. The correlation between decision confidence changes and decision adjustment level showed an opposite trend [NSCLC: ρ = -0.24 ( p = 0.045), HCC: ρ = 0.28 ( p = 0.017)] reflecting the difference in behavior due to underlying differences in disease type and treatment modality. Decision confidence positively correlated with the closeness of decisions to the standard of care (NSCLC: 2 Gy/fx; HCC: 10 Gy/fx) indicating that evaluators were generally more confident in prescribing dose fractionations more similar to those used in standard clinical practice. Inter-evaluator agreement increased with AI-assistance indicating that AI-assistance can decrease inter-physician variability. The majority of decisions were adjusted to achieve higher tumor control in NSCLC and lower normal tissue complications in HCC. Analysis of evaluators' remarks indicated concerns for organs at risk and RT outcome estimates as important decision-making factors. Conclusions: Human-AI interaction depends on the complex interrelationship between expert's prior knowledge and preferences, patient's state, disease site, treatment modality, model transparency, and AI's learned behavior and biases. The collaborative decision-making process can be summarized as follows: (i) some clinicians may not believe in an AI system, completely disregarding its recommendation, (ii) some clinicians may believe in the AI system but will critically analyze its recommendations on a case-by-case basis; (iii) when a clinician finds that the AI recommendation indicates the possibility for better outcomes they will adjust their decisions accordingly; and (iv) When a clinician finds that the AI recommendation indicate a worse possible outcome they will disregard it and seek their own alternative approach.

Exposure to autoimmune disorders increases Alzheimer's disease risk in a multi-site electronic health record analysis.

Molecular studies of Alzheimer's disease (AD) implicate potential links between autoimmunity and AD, but the underlying clinical relationships between these conditions remain poorly understood. Electronic health records (EHRs) provide an opportunity to determine the clinical risk relationship between autoimmune disorders and AD and understand whether specific disorders and disorder subtypes affect AD risk at the phenotypic level in human populations. We evaluated relationships between 26 autoimmune disorders and AD across retrospective observational case-control and cohort study designs in the EHR systems at UCSF and Stanford. We quantified overall and sex-specific AD risk effects that these autoimmune disorders confer. We identified significantly increased AD risk in autoimmune disorder patients in both study designs at UCSF and at Stanford. This pattern was driven by specific autoimmunity subtypes including endocrine, gastrointestinal, dermatologic, and musculoskeletal disorders. We also observed increased AD risk from autoimmunity in both women and men, but women with autoimmune disorders continued to have a higher AD prevalence than men, indicating persistent sex-specificity. This study identifies autoimmune disorders as strong risk factors for AD that validate across several study designs and EHR databases. It sets the foundation for exploring how underlying autoimmune mechanisms increase AD risk and contribute to AD pathogenesis.

Identification of the Molecular Components of Enhancer-Mediated Gene Expression Variation in Multiple Tissues Regulating Blood Pressure.

BACKGROUND: Inter-individual variation in blood pressure (BP) arises in part from sequence variants within enhancers modulating the expression of causal genes. We propose that these genes, active in tissues relevant to BP physiology, can be identified from tissue-level epigenomic data and genotypes of BP-phenotyped individuals. METHODS: We used chromatin accessibility data from the heart, adrenal, kidney, and artery to identify cis-regulatory elements (CREs) in these tissues and estimate the impact of common human single-nucleotide variants within these CREs on gene expression, using machine learning methods. To identify causal genes, we performed a gene-wise association test. We conducted analyses in 2 separate large-scale cohorts: 77 822 individuals from the Genetic Epidemiology Research on Adult Health and Aging and 315 270 individuals from the UK Biobank. RESULTS: We identified 309, 259, 331, and 367 genes (false discovery rate <0.05) for diastolic BP and 191, 184, 204, and 204 genes for systolic BP in the artery, kidney, heart, and adrenal, respectively, in Genetic Epidemiology Research on Adult Health and Aging; 50% to 70% of these genes were replicated in the UK Biobank, significantly higher than the 12% to 15% expected by chance (P<0.0001). These results enabled tissue expression prediction of these 988 to 2875 putative BP genes in individuals of both cohorts to construct an expression polygenic score. This score explained ≈27% of the reported single-nucleotide variant heritability, substantially higher than expected from prior studies. CONCLUSIONS: Our work demonstrates the power of tissue-restricted comprehensive CRE analysis, followed by CRE-based expression prediction, for understanding BP regulation in relevant tissues and provides dual-modality supporting evidence, CRE and expression, for the causality genes.

Epidemiology and prevalence of dementia and Alzheimer's disease in American Indians: Data from the Strong Heart Study.

INTRODUCTION: Accurate epidemiologic estimates for dementia are lacking for American Indians, despite substantive social and health disparities. METHODS: The Strong Heart Study, a population-based cohort of 11 American Indian tribes, conducted detailed cognitive testing and examinations over two visits approximately 7 years apart. An expert panel reviewed case materials for consensus adjudication of cognitive status (intact; mild cognitive impairment [MCI]; dementia; other impaired/not MCI) and probable etiology (Alzheimer's disease [AD], vascular bain injury [VBI], traumatic brain injury [TBI], other). RESULTS: American Indians aged 70-95 years had 54% cognitive impairment including 10% dementia. VBI and AD were primary etiology approximately equal proportions (>40%). Apolipoprotein (APO) Eε4 carriers were more common among those with dementia (p = 0.040). Plasma pTau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were higher among those with cognitive impairment, but not amyloid beta (Aß). Cognitive intact had mean 3MSE 92.2 (SD 6.4) and mean Montreal Cognitive Assessment (MoCA) score of 21.3 (SD 3.2). DISCUSSION: This is the first population-based study to estimate the prevalence of vascular and Alzheimer's dementias in a population-based study of American Indians. HIGHLIGHTS: The Strong Heart Study is a population-based cohort of American Indian tribes, conducted over 30+ years and three US geographic regions (Northern Plains, Southern Plains, Southwest). Our teams conducted detailed cognitive testing, neurological examination, and brain imaging over two visits approximately 7 years apart. An expert panel reviewed collected materials for consensus-based adjudication of cognitive status (intact; MCI; dementia; other impaired/not MCI) and probable underlying etiology (AD; VBI; TBI; other). In this cohort of American Indians aged 70-95, 54% were adjudicated with cognitive impairment, including approximately 35% MCI and 10% dementia. These data expand on prior reports from studies using electronic health records, which had suggested prevalence, and incidence of dementia in American Indians to be more comparable to the majority population or non-Hispanic White individuals, perhaps due to latent case undercounts in clinical settings. Vascular and neurodegenerative injuries were approximately equally responsible for cognitive impairment, suggesting that reduction of cardiovascular disease is needed for primary prevention. Traumatic injury was more prevalent than in other populations, and common among those in the "other/not MCI" cognitive impairment category. Mean scores for common dementia screening instruments-even among those adjudicated as unimpaired-were relatively low compared to other populations (mean unimpaired 3MSE 92.2, SD 6.4; mean unimpaired MoCA 21.3, SD 3.2), suggesting the need for cultural and environmental adaptation of common screening and evaluation instruments.

Reconstituting membrane fission using a high content and throughput assay.

Protein-mediated membrane fission has been analyzed both in bulk and at the single event resolution. Studies on membrane fission in vitro using tethers have provided fundamental insights into the process but are low in throughput. In recent years, supported membrane template (SMrT) have emerged as a facile and convenient assay system for membrane fission. SMrTs provide useful information on intermediates in the pathway to fission and are therefore high in content. They are also high in throughput because numerous fission events can be monitored in a single experiment. This review discusses the utility of SMrTs in providing insights into fission pathways and its adaptation to annotate membrane fission functions in proteins.

Right ventricular to pulmonary artery coupling in patients with different types of aortic stenosis undergoing TAVI.

BACKGROUND: Right ventricular (RV) dysfunction in patients undergoing transcatheter aortic valve implantation (TAVI) for aortic stenosis (AS) has long been disregarded. We aimed to assess the predictive value of RV to pulmonary artery coupling (RV/PAc), defined as tricuspid annular plane systolic excursion to systolic pulmonary artery pressure, on mortality in different flow types of AS after TAVI. METHODS: All patients undergoing TAVI for AS at our centre between 2018 and 2020 were assessed; 862 patients were analysed. The cohort was dichotomized using a ROC analysis (cut-off 0.512 mm/mmHg), into 429 patients with preserved and 433 patients with reduced RV/PAc. RESULTS: Reduced RV/PAc was associated with male sex and a higher rate of comorbidities. Short-term VARC-3 endpoints and NYHA classes at follow-up were comparable. Reduced RV/PAc was associated with higher 2-year all-cause mortality (35.0% [30.3-39.3%] vs. 15.4% [11.9-18.7%], hazard ratio 2.5 [1.9-3.4], p < 0.001). Cardiovascular mortality was almost tripled. Results were consistent after statistical adjustment and in a multivariate model. Sub-analyses of AS flow types revealed lower RV/PAc in classical and paradoxical low-flow low-gradient AS, with the majority having reduced RV/PAc (74% and 59%). RV/PAc retained its predictive value in these subgroups. CONCLUSIONS: RV dysfunction defined by low RV/PAc is a strong mortality predictor after TAVI independent of flow group. It should be incorporated in future TAVI risk assessment.