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At least 325 records · Page 18

Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus‐associated oropharyngeal squamous cell carcinoma

Background Understanding biological differences between different racial groups of human papillomavirus (HPV)‐associated oropharyngeal squamous cell carcinoma (OPSCC) patients, who have differences in terms of incidence, survival, and tumor morphology, can facilitate accurate prognostic biomarkers, which can help develop personalized treatment strategies. Methods This study evaluated whether there were morphologic differences between HPV‐associated tumors from Black and White patients in terms of multinucleation index (MuNI), an image analysis‐derived metric that measures density of multinucleated tumor cells within epithelial regions on hematoxylin–eosin images and previously has been prognostic in HPV‐associated OPSCC patients. In this study, the authors specifically evaluated whether the same MuNI cutoff that was prognostic of overall survival (OS) and disease‐free survival in their previous study, T TR , is valid for Black and White patients, separately. We also evaluated population‐specific cutoffs, T B for Blacks and T W for Whites, for risk stratification. Results MuNI was statistically significantly different between Black (mean, 3.88e–4; median, 3.67e–04) and White patients (mean, 3.36e–04; median, 2.99e–04), with p = .0078. Using T TR , MuNI was prognostic of OS in the entire population with hazard ratio (HR) of 1.71 ( p = .002; 95% confidence interval [CI], 1.21–2.43) and in White patients with HR of 1.72 ( p = .005; 95% CI, 1.18–2.51). Population‐specific cutoff, T W , yielded improved HR of 1.77 ( p = .003; 95% CI, 1.21–2.58) for White patients, whereas T B did not improve risk‐stratification in Black patients with HR of 0.6 ( p = .3; HR, 0.6; 95% CI, 0.2–1.80). Conclusions Histological difference between White and Black patient tumors in terms of multinucleated tumor cells suggests the need for considering population‐specific prognostic biomarkers for personalized risk stratification strategies for HPV‐associated OPSCC patients.

Koyuncu, Can F.↗

Engineering highly stable variants of Corynactis californica green fluorescent proteins

Fluorescent proteins (FPs) are versatile biomarkers that facilitate effective detection and tracking of macromolecules of interest in real time. Engineered FPs such as superfolder green fluorescent protein (sfGFP) and superfolder Cherry (sfCherry) have exceptional refolding capability capable of delivering fluorescent readout in harsh environments where most proteins lose their native functions. Our recent work on the development of a split FP from a species of strawberry anemone, Corynactis californica, delivered pairs of fragments with up to threefold faster complementation than split GFP. We present the biophysical, biochemical, and structural characteristics of five full-length variants derived from these split C. californica GFP (ccGFP). These ccGFP variants are more tolerant under chemical denaturation with up to 8 kcal/mol lower unfolding free energy than that of the sfGFP. It is likely that some of these ccGFP variants could be suitable as biomarkers under more adverse environments where sfGFP fails to survive. A structural analysis suggests explanations of the variations in stabilities among the ccGFP variants.

59 BASIC BIOLOGICAL SCIENCES↗

A machine learning approach for identifying variables associated with risk of developing neutralizing antidrug antibodies to factor VIII

A key unmet need in the management of hemophilia A (HA) is the lack of clinically validated markers that are associated with the development of neutralizing antibodies to Factor VIII (FVIII) (commonly referred to as inhibitors). This study aimed to identify relevant biomarkers for FVIII inhibition using Machine Learning (ML) and Explainable AI (XAI) using the My Life Our Future (MLOF) research repository. The dataset includes biologically relevant variables such as age, race, sex, ethnicity, and the variants in the F8 gene. In addition, we previously carried out Human Leukocyte Antigen Class II (HLA-II) typing on samples obtained from the MLOF repository. Using this information, we derived other patient-specific biologically and genetically important variables. These included identifying the number of foreign FVIII derived peptides, based on the alignment of the endogenous FVIII and infused drug sequences, and the foreign-peptide HLA-II molecule binding affinity calculated using NetMHCIIpan. The data were processed and trained with multiple ML classification models to identify the top performing models. The top performing model was then chosen to apply XAI via SHAP, (SHapley Additive exPlanations) to identify the variables critical for the prediction of FVIII inhibitor development in a hemophilia A patient. Using XAI we provide a robust and ranked identification of variables that could be predictive for developing inhibitors to FVIII drugs in hemophilia A patients. These variables could be validated as biomarkers and used in making clinical decisions and during drug development. The top five variables for predicting inhibitor development based on SHAP values are: (i) the baseline activity of the FVIII protein, (ii) mean affinity of all foreign peptides for HLA DRB 3, 4, & 5 alleles, (iii) mean affinity of all foreign peptides for HLA DRB1 alleles), (iv) the minimum affinity among all foreign peptides for HLA DRB1 alleles, and (v) F8 mutation type.

60 APPLIED LIFE SCIENCES↗

Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic ß-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity – is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through diagnosis. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D are complement deficient relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

59 BASIC BIOLOGICAL SCIENCES↗

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomics measures the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of significant changes in subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot precisely infer the abundance changes of intact proteins, which are presented as proteoforms. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantification directly on thin tissue sections. The spatial TDP platform consisted of a nanoPOTS (nanodroplet Processing in One pot for Trace Samples)-based sample preparation system and an LCM (laser capture microdissection)-based cell isolation system. We improved the nanoPOTS sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ~200 cultured cells as model samples, the improved approach increased proteoform identifications from 493 to 700; newly identified proteoforms primarily corresponded to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed LCM-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 426 proteoforms by combining identifications from TopPIC and TDPortal with the quantitation from ProMex. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential PTM-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

59 BASIC BIOLOGICAL SCIENCES↗

Overexpression and surface localization of HPRT in prostate cancer provides a potential target for cancer specific antibody mediated cellular cytotoxicity

Highlights: • HPRT is heterogeneously expressed in prostate cancer cells, with surface HPRT being expressed in a p53-dependent fashion. • HPRT is localized to the surface of DU145 prostate cancer cells and is targeted specifically to induce anti-tumor efficacy. • Reductions in p53 expression correspond to reductions in HPRT internal and surface expression within mutant p53 cell lines. We chose to evaluate Hypoxanthine Guanine Phosphoribosyltransferase (HPRT) as a possible biomarker for prostate cancer due to its involvement in nucleotide synthesis and cell cycle progression. We utilized two prostate cancer cell lines (PC3 and DU145) along with patient tissue and knockdowns to evaluate overall HPRT expression. The surface localization of HPRT was determined utilizing flow cytometry, confocal microscopy, and scanning electron microscopy followed by ADCC to evaluate targeting potential. We found significant upregulation of HPRT within malignant samples with approximately 47% of patients had elevated levels of HPRT compared to normal controls. We also observed a significant association between HPRT and the plasma membrane of DU145 cells (p = 0.0004), but found no presence on PC3 cells (p = 0.14). This was confirmed with scanning electron microscopy and confocal microscopy. ADCC experiments were performed to determine whether HPRT could be used as a target antigen for selective cell-mediated killing. We found that DU145 cells treated with HPRT antibodies had a significantly higher incidence of cell death than both isotype treated samples and PC3 cells treated with the same concentrations of HPRT antibody. Finally, we determined that p53 had a significant impact on HPRT expression both internally and on the surface of cancer cells. These results suggest HPRT as a possible biomarker target for the treatment of patients with prostate cancer.

60 APPLIED LIFE SCIENCES↗

Endothelial surface translocation of mitochondrial PDCE2 involves the non-canonical secretory autophagy pathway: Putative molecular target for radiation-guided drug delivery

Highlights: • Radiation induces ectopic endothelial surface exposure of mitochondrial PDCE2. • PDCE2 translocation is associated with late-stage inhibition of autophagic flux. • Radiation damage overloads the degradative lysosomal pathway of autophagy. • PDCE2 trafficking occurs via autophagosomes and non-canonical secretory autophagy. • Surface PDCE2 provides a novel target for radiation-guided vascular drug delivery. Radiation has been proposed as a priming agent to induce discriminatory luminal biomarkers for vascular targeting and drug delivery in disorders such as brain arteriovenous malformations and cancers. We previously observed ectopic expression of intracellular proteins such as mitochondrial PDCE2 on irradiated endothelium in animal models. In this study we examined the mechanism of PDCE2 trafficking in human endothelial cells to better understand its suitability as a vascular target. Ionizing radiation induced PDCE2 surface localization in association with accumulation of autophagosome markers (L3CB and p62) indicative of late-stage inhibition of autophagic flux. This effect was abolished in the presence of Rapamycin, an autophagy-inducer, but replicated in the presence of Bafilomycin A, an autophagy blocker. PDCE2 co-localized with lysosomal markers of the canonical degradative autophagy pathway in response to radiation but also with recycling endosomes and SNARE proteins responsible for autophagosome-plasma membrane fusion. These findings demonstrate that radiation-induced blockade of autophagic flux stimulates redirection of intracellular molecules such as PDCE2 to the cell surface via a non-canonical secretory autophagy pathway. Intracellular membrane proteins trafficked in this way could provide a unique pool of radiation biomarkers for therapeutic drug delivery.

60 APPLIED LIFE SCIENCES↗

RAN and YBX1 are required for cell proliferation and IL-4 expression and linked to poor prognosis in oral squamous cell carcinoma

Highlights: • RAN and YBX1 are co-expressed and required for cell proliferation in OSCC cells. • RAN and YBX1 are positively associated with the immune infiltrates of CD4{sup +} Th2 cells. • RAN and YBX1 can promote IL-4 expression. • RAN is a direct target of YBX1. • RAN and YBX1 can serve as potential co-biomarkers for poor prognosis in OSCC. Oral squamous cell carcinoma (OSCC) is one of the most common malignancies in the world, with a high mortality rate. RAN is a member of the Ras GTPase family and is overexpressed in a range of cancers, however, the relationship between RAN and OSCC is rarely reported. In this study, we found that RAN is overexpressed in OSCC tissues. RAN inhibition retarded OSCC cell proliferation and led to apoptosis and cell cycle arrest. Knockdown of RAN inhibited tumor growth in vivo. Strikingly, we found that RAN and oncogene Y-box binding protein-1 (YBX1) are positively associated with the immune infiltrates of CD4{sup +} Th2 cells in multiple types of cancer, and can promote IL-4 expression. IL-4 treatment can partially rescue RAN knockdown-induced cell apoptosis in OSCC cells. Moreover, overexpression of RAN could rescue cell growth inhibition caused by knockdown of YBX1. Furthermore, patients with low expression of both RAN and YBX1 had better overall survival than others. Collectively, these findings indicate that RAN is a target of YBX1. RAN and YBX1 are required for cell proliferation and IL-4 expression. RAN and YBX1 are co-expressed and can serve as potential co-biomarkers for poor prognosis in OSCC.

60 APPLIED LIFE SCIENCES↗

Comprehensive analysis of differentially expressed mRNA and circRNA in Ankylosing spondylitis patients’ platelets

Highlights: • 4996 mRNAs and 2942 circRNAs were identified differentially expressed in platelets of AS patients. • Several platelet-derived immune mediators were upregulated to regulate the interaction between platelets and immune cells. • Two downregulated circRNA were identified, and the corresponding circRNA-miRNA-mRNA regulatory network was constructed. • mRNAs and circRNAs found herein could be used as diagnostic biomarkers or new therapeutic targets. Ankylosing spondylitis (AS) is a chronic inflammatory disease significantly decreasing the quality of life. Platelets play an important and active role in the development of AS. Accumulating evidence demonstrated platelets contain diverse RNA repository inherited from megakaryocytes or microvesicles. Platelet RNAs are dynamically affected by pathological conditions and could be used as diagnostic or prognostic biomarkers. However, the role of the platelet RNAs in AS is elusive. In this study, we compared mRNA and circRNA profiles in platelets between AS patients and healthy controls using RNA sequencing and bioinformatic analysis, and found 4996 mRNAs and 2942 circRNAs were differently expressed. The significantly over-expressed mRNAs in AS patients are involved in platelet activity, gap junction, focal adhesion, rap1 and toll and Imd signaling pathway. The previous identified platelet-derived immune mediators such as P2Y1, P2Y12, PF4, GPIbα, CD40L, ICAM2, CCL5 (RANTES), TGF-β (TGF-β1 and TGF-β2) and PDGF (PDGFB and PDGFA) are also included in these over expressed mRNAs, implying these factors may trigger inflammatory cascades and promote the development of AS. Additionally, we found two down-regulated circRNA (circPTPN22 and circFCHSD2) from the intersection analyses of platelets and spinal ligament tissues of AS patients. The circRNA-miRNA-mRNA regulatory network of these two circRNAs was constructed, and the target mRNAs were enriched in Th17 cell differentiation, inflammatory bowel disease, cell adhesion molecules, cytokine-cytokine receptor interaction, Jak-STAT and Wnt signaling pathway, all these pathways participate in the bone remodeling and pro/anti-inflammatory immune regulation in AS. Then, qRT-PCR was performed to validate the expression of selected key mRNAs and circRNAs and the results demonstrated that the expression levels of P2Y12, GPIbα, circPTPN22 and circFCHSD2 were consistent with the sequencing analysis. In addition, the high expression of five predicted miRNAs interacting with circPTPN22 and circFCHSD2 were also detected in AS by qRT-PCR. Taken together, our study presents a comprehensive overview of mRNAs and circRNAs in platelets in AS patients and offers new insight into the mechanisms of platelet involving in the pathogenesis of AS. The mRNAs and circRNAs identified in this study may serve as candidates for diagnosis and targeted treatment of AS.

60 APPLIED LIFE SCIENCES↗

Development of a Universal Second-Tier Newborn Screening LC–MS/MS Method for Amino Acids, Lysophosphatidylcholines, and Organic Acids

First-tier MS-based newborn screening by flow injection analysis can have high presumptive positive rates, often due to isomeric/isobaric compounds or poor biomarker specificity. These presumptive positive samples can be analyzed by second-tier screening assays employing separations such as liquid chromatography–mass spectrometry (LC–MS/MS), which increases test specificity and drastically reduces false positive referrals. The ability to screen for multiple disorders in a single multiplexed test simplifies workflows and maximizes public health laboratories’ resources. In this study, we developed and validated a highly multiplexed second-tier method for dried blood spots using a hydrophilic interaction liquid chromatography (HILIC) column coupled to an MS/MS system. The LC–MS/MS method was capable of simultaneously detecting second-tier biomarkers for maple syrup urine disease, homocystinuria, methylmalonic acidemia, propionic acidemia, glutaric acidemia type 1, glutaric acidemia type 2, guanidinoacetate methyltransferase deficiency, short-chain acyl-CoA dehydrogenase deficiency, adrenoleukodystrophy, and Pompe disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Highly Active Carbon–Platinum-Based Nanozymes: Synthesis, Characterization, and Immunoassay Application

Nanozymes (nanomaterials with intrinsic enzyme-like characteristics) have gained much attention for diagnostics and therapy due to their excellent enzyme-mimicking capability, great stability in environments, and facile and low-cost production. However, developing nanozymes with a high catalytic constant, K cat , has been challenging. Herein, we report a class of nanozyme-mimicking peroxidases, which are formed by depositing ultrasmall platinum nanoparticles (Pt NPs) 1–2 nm in size on the surface of hydrophilic nitrogen-doped carbon nanoparticles (CN NPs). These nanozymes defined as CN-Pt NPs show a high peroxidase-like activity with K cat values of 1.27 M·mL/s·g for 3,3,5,5′-tetramethylbenzidine (TMB) and 1.97 M·mL/s·g for hydrogen peroxide (H 2 O 2 ), respectively, which are at least one or two orders higher than many other reported carbon–noble metal-based nanozymes. Our developed CN-Pt NPs were further utilized in a colorimetric immunoassay as signal amplifiers for the biomarker detection of Burkholderia pseudomallei, a Gram-negative bacterial pathogen classified as a tier 1 select agent by the US CDC. In conclusion, the assay achieved lower limits of detection of 0.11 ng/mL in phosphate-buffered saline (PBS) and 0.16 ng/mL in human serum, when compared to many other assays in detecting the same biomarker.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhanced Stability and Sensitivity for CA-125 Detection Under Microfluidic Shear Flow Using Polyethylene Glycol-Coated Biosensor

The microfluidic-based point-of-care (POC) diagnostic tool has garnered significant interest in recent years, offering rapid and cost-effective disease detection. There is a growing trend toward integrating microfluidic platforms with biosensors, aligning lab-on-a-chip technologies with POC diagnostic devices. Despite numerous efforts to incorporate biosensors into microfluidic systems, researchers have performed very limited investigations on the stability of biomarker detection when biosensors operate under microfluidic shear flow conditions. Gold nanoparticles (AuNPs) are a widely employed material in capacitive biosensors for antibody immobilization and sensitivity enhancement. However, AuNPs have limitations in providing stable detection of biomarkers within microfluidic shear flow due to their agglomeration nature. This study addresses these limitations by employing 2 kDa polyethylene glycol (PEG) as an intermediate biofunctional layer to immobilize CA-125 antibodies on gold-interdigitated electrodes for the stable and accurate detection of CA-125 antigens. The stabilities and sensitivities of AuNPs and PEG-coated biosensors are evaluated under both static drop and microfluidic shear flow conditions for CA-125 antigen detection. The experimental results demonstrate a capacitive signal response (5660 pF at 10 kHz) 2.2 times higher using the PEG-coated biosensor than the signal (2551 pF at 10 kHz) measured by the AuNP-coated biosensor in the detection of CA-125 antigen–antibody conjugation under static drop conditions, indicating the higher sensitivity of the PEG-coated biosensor. Additionally, the PEG-coated biosensor exhibits better consistency for the CA-125 antigen detection between static drop and microfluidic shear flow conditions (Cp decrease in percentage (ΔCp%↓) = 2.9% at 10 kHz) compared to the electrical signals measured using the AuNP-coated biosensor (ΔCp%↓ = 32.4% at 10 kHz), which suggests that the PEG-coated biosensor demonstrates higher stability for CA-125 antigen detection under microfluidic shear flow conditions. With these significant improvements brought by the PEG-coated biosensor, especially under microfluidic conditions, a substantial hurdle in developing electrical biosensors for POC diagnostic applications has been overcome, expediting further advancements in the field.

36 MATERIALS SCIENCE↗

Highly Stable Fe/Co-TPY-MIL-88(NH 2 ) Metal–Organic Framework (MOF) in Enzymatic Cascade Reactions for Chemiluminescence-Based Detection of Extracellular Vesicles

Metal-Organic Frameworks (MOFs) can deliver many advantages when acting as enzyme mimics to assist with signal amplification in molecular detection: they have abundant active catalytic sites per unit volume of the material; their structures and elemental compositions are highly tunable, and their high specific surface area and porous property can assist with target separation and enrichment. In the present work, we have demonstrated that, by adding the pore partition agent, 2,4,6-tris(4-pyridyl)pyridine (TPY) during synthesis of the bimetallic Fe/Co-MIL-88(NH 2 ) MOF to block the open metal sites, a highly porous MOF of Fe/Co-TPY-MIL-88(NH 2 ) can be produced. This material also exhibits high stability in basic solutions and biofluids and possesses high peroxidase-mimicking activity, which can be utilized to produce long-lasting chemiluminescence (CL) from luminol and H 2 O 2 . Moreover, acting as the peroxidase-mimic, the Fe/Co-TPY-MIL-88(NH 2 ) MOF can form the enzymatic cascade with glucose oxidase (GOx) for biomarker detection. Further, when applied to detect extracellular vesicles (EVs), the MOF material and GOx are brought to the proximity on the EVs through two surface proteins, which triggers the enzyme cascade to produce high CL from glucose and luminol. EVs within the concentration range of 5 × 10 5 - 4 ×10 7 particles/mL can be detected, and the method can be used to analyze EV contents in human serum without sample preparation and EV purification. Overall, our work demonstrates that the high versatility and tunability of the MOF structures could bring in significant benefits to biosensing and enable ultrasensitive detection of biomarkers with judicious material designs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Learning perturbation-inducible cell states from observability analysis of transcriptome dynamics

Abstract A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state referred to as cell state. We construct low-dimensional models of gene expression dynamics and rank genes by their ability to capture the perturbation-specific cell state using a novel observability analysis. Using this ranking, we extract 15 analyte-responsive promoters for the organophosphate malathion in the underutilized host organism Pseudomonas fluorescens SBW25. We develop synthetic genetic reporters from each analyte-responsive promoter and characterize their response to malathion. Furthermore, we enhance malathion reporting through the aggregation of the response of individual reporters with a synthetic consortium approach, and we exemplify the library’s ability to be useful outside the lab by detecting malathion in the environment. The engineered host cell, a living malathion sensor, can be optimized for use in environmental diagnostics while the developed machine learning tool can be applied to discover perturbation-inducible gene expression systems in the compendium of host organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Metabolomics and the pig model reveal aberrant cardiac energy metabolism in metabolic syndrome

Abstract Although metabolic syndrome (MS) is a significant risk of cardiovascular disease (CVD), the cardiac response (MR) to MS remains unclear due to traditional MS models’ narrow scope around a limited number of cell-cycle regulation biomarkers and drawbacks of limited human tissue samples. To date, we developed the most comprehensive platform studying MR to MS in a pig model tightly related to human MS criteria. By incorporating comparative metabolomic, transcriptomic, functional analyses, and unsupervised machine learning (UML), we can discover unknown metabolic pathways connections and links on numerous biomarkers across the MS-associated issues in the heart. For the first time, we show severely diminished availability of glycolytic and citric acid cycle (CAC) pathways metabolites, altered expression, GlcNAcylation, and activity of involved enzymes. A notable exception, however, is the excessive succinate accumulation despite reduced succinate dehydrogenase complex iron-sulfur subunit b (SDHB) expression and decreased content of precursor metabolites. Finally, the expression of metabolites and enzymes from the GABA-glutamate, GABA-putrescine, and the glyoxylate pathways significantly increase, suggesting an alternative cardiac means to replenish succinate and malate in MS. Our platform discovers potential therapeutic targets for MS-associated CVD within pathways that were previously unknown to corelate with the disease.

59 BASIC BIOLOGICAL SCIENCES↗

Disentangling Alzheimer’s disease neurodegeneration from typical brain ageing using machine learning

Abstract Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer’s disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer’s Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T1-weighted MRI scans of 4054 participants (48–95 years) with Alzheimer’s disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer’s disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer’s disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer’s disease continuum group (n = 718; consisting of amyloid-positive Alzheimer’s disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer’s disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer’s disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56–0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer’s disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer’s disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer’s disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer’s disease.

Hwang, Gyujoon↗

Metabolic and transcriptomic study of pennycress natural variation identifies targets for oil improvement

Pennycress (Thlaspi arvense L.), a member of the Brassicaceae family, produces seed oil high in erucic acid, suitable for biodiesel and aviation fuel. Although pennycress, a winter annual, could be grown as a dedicated bioenergy crop, an increase in its seed oil content is required to improve its economic competitiveness. The success of crop improvement relies upon finding the right combination of biomarkers and targets, and the best genetic engineering and/or breeding strategies. In this work, we combined biomass composition with metabolomic and transcriptomic studies of developing embryos from 22 pennycress natural variants to identify targets for oil improvement. The selected accession collection presented diverse levels of fatty acids at maturity ranging from 29% to 41%. Pearson correlation analyses, weighted gene co‐expression network analysis and biomarker identifications were used as complementary approaches to detect associations between metabolite level or gene expression and oil content at maturity. The results indicated that improving seed oil content can lead to a concomitant increase in the proportion of erucic acid without affecting the weight of embryos. Processes, such as carbon partitioning towards the chloroplast, lipid metabolism, photosynthesis, and a tight control of nitrogen availability, were found to be key for oil improvement in pennycress. Besides identifying specific targets, our results also provide guidance regarding the best timing for their modification, early or middle maturation. Thus, this work lays out promising strategies, specific for pennycress, to accelerate the successful development of lines with increased seed oil content for biofuel applications.

59 BASIC BIOLOGICAL SCIENCES↗

Glove-based sensors for multimodal monitoring of natural sweat

Sweat sensors targeting exercise or chemically induced sweat have shown promise for noninvasive health monitoring. Natural thermoregulatory sweat is an attractive alternative as it can be accessed during routine and sedentary activity without impeding user lifestyles and potentially preserves correlations between sweat and blood biomarkers. We present simple glove-based sensors to accumulate natural sweat with minimal evaporation, capitalizing on high sweat gland densities to collect hundreds of microliters in just 30 min without active sweat stimulation. Sensing electrodes are patterned on nitrile gloves and finger cots for in situ detection of diverse biomarkers, including electrolytes and xenobiotics, and multiple gloves or cots are worn in sequence to track overarching analyte dynamics. Direct integration of sensors into gloves represents a simple and low-overhead scheme for natural sweat analysis, enabling sweat-based physiological monitoring to become practical and routine without requiring highly complex or miniaturized components for analyte collection and signal transduction.

42 ENGINEERING↗