Metabolomics

Simultaneous quantification of monoglycosphingolipid stereoisomers is required to monitor changes in defective enzymatic pathways linked to diseases such as Gaucher Disease, Parkinson's Disease, and Krabbe Disease. Resolution of beta-glucosyl and beta-galactosyl epimers cannot be achieved by standard liquid chromatography, electrospray ionization, tandem mass spectrometry (LC-ESI-MS/MS). Separation becomes possible when field asymmetric ion mobility spectrometry (FAIMS), also known as differential mobility mass spectrometry (DMS), is added as an orthogonal separation technique to LC. FAIMS/DMS separates epimeric ion clusters in a high versus low electric field (separation voltage, SV) then redirects the target epimeric ions to the mass spectrometer through the application of a direct current (compensation voltage, CoV). Resolving SVs and CoVs must be manually determined for each lipid. Manual derivation is a labour-intensive process that requires pure synthetic standards, limiting the number of stereoisomers a user can include in an assay. To address this problem, we introduce here intelligent DMS (iDMS). iDMS is an in silico supervised neural network model that learns the ion mobility relationships between SV and CoV and the monoglycosphingolipid structural features of sugar headgroup, N-acyl chain length, and N-acyl degree of unsaturation. iDMS predicts the SV and CoV combinations capable of resolving any stereoisomer pair from a training dataset of composed of measured signal intensities across a range of SVs and CoVs of 12 lipids. This machine learning alternative to manual DMS optimization promises to accelerate the deployment of multiple-reaction-monitoring mode (MRM) RPLC-ESI-DMS-MS/MS assays for the routine and rapid quantification of biologically relevant monoglycosphingolipid stereoisomers.

Background: Acute phase response is an early immunometabolic response to brain injuries, primarily coordinated by the liver via the activation of acute phase proteins. These immune responses can be both beneficial, promoting tissue repair, and detrimental, exacerbating neurological deficits, if not properly controlled. Despite the central role of the liver in immunometabolism, how hepatic metabolism dynamically adapts to traumatic brain injury remains under explored, primarily due to limited liver-specific modalities that can assess metabolic pathways in vivo. 13C MRI utilizing hyperpolarized 13C-pyruvate can assess key regulatory enzyme activities in hepatic metabolism. Methods: Rats with controlled cortical impact were studied in vivo using hyperpolarized [1-13C]pyruvate and [2-13C]pyruvate under fed and fasted conditions 3-4 days after injury. Hyperpolarized 13C products, including [13C]bicarbonate from [1-13C]pyruvate and [5-13C]glutamate, [1-13C]acetyl-L-carnitine, and [2-13C]phosphoenolpyruvate from [2-13C]pyruvate, were evaluated to assess mitochondrial and gluconeogenic metabolism. In parallel, liver tissues were collected following [U-13C3]pyruvate injection for NMR isotopomer analysis of phosphoenolpyruvate, glucose, and glutamate. Results: While no metabolic differences were detected under fed condition, [13C]bicarbonate and [2-13C]phosphoenolpyruvate increased after brain injury under fasted condition, indicating an upregulation of the hepatic gluconeogenic pathway after injury. 13C NMR of liver tissue extracts from injured rats showed an elevated [2,3-13C2]glutamate-to-[4,5-13C2]glutamate ratio and increased 13C-labeling in phosphoenolpyruvate than controls, confirming enhanced hepatic gluconeogenic pathway. Conclusion: This study demonstrates that hepatic acute phase response to brain injuries can be monitored in vivo by hyperpolarized pyruvate, which may be further utilized for longitudinal immunometabolic evaluation of the liver during pathogenesis and therapeutic interventions.

Introduction: Parkinson's disease (PD) and aging both disrupt hypothalamic-pituitary-adrenal (HPA) axis function and peripheral immune homeostasis. Whether aging or -synuclein (-syn) pathology alters glucocorticoid (GC) sensitivity of peripheral immune cells has not been investigated. Methods: Using an ex vivo GC sensitivity assay, we assessed the responsiveness of isolated and lipopolysaccharide (LPS)-stimulated splenocytes to the anti-inflammatory effects of increasing doses of corticosterone (CORT) in a wild-type (WT) aging cohort and in a PD -syn transgenic mouse model and respective age-matched controls. Results: Compared with splenocytes from 6-month-old WT mice, splenocytes from 20-month-old WT mice were less sensitive to 0.1 and 0.5 M CORT. Isolated splenocytes from PD vs. control mice were less sensitive to 0.05, 0.1, and 0.5 M CORT specifically at 16 months of age, but not at 6 or 20 months of age. As peripheral immune phenotyping revealed neither differences in HPA axis-related parameters nor in splenic GC receptor expression between PD and age-matched control mice at 6, 16, and 20 months, splenic GC resistance in PD mice at 16 months of age seems to be mediated by downstream GR signaling dysfunction. Conclusion: Together, our results support the hypothesis that -syn pathology accelerates an aging-associated decline in the peripheral sensitivity to anti-inflammatory GCs and may thereby sustain systemic and neuroinflammatory processes in PD.

Pancreatic ductal adenocarcinoma (PDAC) harbors a distinct intratumoral microbiome. Yet rigorous characterization of its composition is hampered by pervasive environmental and procedural contamination. Sources of contamination have not been thoroughly explored, and the methods of decontamination have not been sufficiently evaluated in a benchmarking manner. We systematically collected >300 negative control (NCT) samples comprising paraffin from formalin-fixed paraffin-embedded (FFPE) samples, lysis buffer and sterile water over a period of four years processed by different laboratory persons (LP). All samples were sequenced using full-length 16S rRNA gene sequencing with Oxford-Nanopore Technologies. We benchmarked four decontamination methods (restrictive filtering, decontam, SCRuB, and the Nejman et al.-derived (Nj) pipeline) against fresh-frozen tumor samples (FF) from LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) mice, using the abovementioned contamination assessment to calculate a composite score for the assessment. Further, we validated those methods via technical replicates. Microbial profiles of NCT samples were significantly determined by control type, LP, year and season reflecting complex batch effects. The 15 most abundant contaminants spanned well-characterized environmental taxa and human commensals from the oral cavity. The LP processing samples left a significant microbial trace highly contributing to the batch effect. Decontamination benchmarking demonstrated that the Nj method consistently outperformed alternatives in both composite score and inter-replicate concordance. Application of Nj to fresh frozen PDAC samples substantially reduced contaminant burden while preserving putative tumor-associated signals in FF but not FFPE samples. Our results support the adoption of the Nj decontamination approach for future intratumoral microbiome studies in fresh frozen tumor samples.

Background: Low-dose computed tomography (LDCT) screening reduces lung cancer mortality but is limited by low uptake and associated with high rates of false-positives and indeterminate-nodules. Breath volatile organic compound (VOC) analysis is a non-invasive candidate biomarker approach that could complement LDCT, but prior work has relied on laboratory-based high-resolution mass spectrometry (HRMS), limiting point-of-care deployment. Methods: In this pilot study, breath samples were collected from 40 patients with treatment-naive, pathologically confirmed non-small cell lung cancer (NSCLC) and 25 lung-cancer-screening-eligible healthy controls. Paired samples were analyzed via a compact point-of-care GC-MS platform (CLARION) and a laboratory HRMS reference. Diagnostic classification models were built independently for each platform using elastic net logistic regression with leave-one-out cross-validation, and performance was evaluated by area under the receiver operating characteristic curve (AUC). Results: CLARION identified 103 VOCs across breath specimens, compared to over 900 identified by HRMS. Despite this difference in panel size, CLARION achieved diagnostic performance nearly identical to HRMS for distinguishing NSCLC cases from controls (AUC 0.864 vs. 0.863). Compared to controls, performance statistics were similar for early-stage NSCLC (AUC 0.854 vs. 0.841) and adenocarcinoma (AUC 0.770 vs. 0.787). VOCs of interest include p-cymene, phenol, propylbenzene, tetradecane, {beta}-ocimene, 2,3-dihydro-indole, and 1-methylthio-(Z)-1-propene. Conclusion: A compact, point-of-care breath GC-MS platform achieved diagnostic performance for NSCLC detection comparable to a laboratory HRMS reference despite a substantially smaller detected VOC panel. These findings support continued development of point-of-care breath VOC testing as a non-invasive, field-deployable complement to LDCT-based lung cancer screening.

Objective White smoke inhalation injury (WSI) causes severe acute lung damage with no specific therapy currently available. Sphingolipid metabolism is implicated in pulmonary inflammation, but its transcriptional regulatory landscape in WSI remains unexplored. This study aimed to identify key sphingolipid metabolism related genes and evaluate their regulatory roles and therapeutic potential in WSI. Methods We established a rat model of WSI and performed integrated bulk RNA sequencing, weighted gene coexpression network analysis (WGCNA), and single-cell RNA sequencing (scRNAseq) to screen for differentially expressed sphingolipid metabolism-related genes (DESRGs). Protein-protein interaction (PPI) network with four centrality algorithms was used to prioritize hub genes. In silico gene knockout and molecular docking were conducted to assess regulatory functions and identify potential drug candidates. Results We identified 22 DESRGs that were predominantly enriched in DNA replication and cell cycle pathways rather than canonical sphingolipid metabolic processes. PPI consensus prioritized three hub genes--Top2a, Ttk, and Ccna2--with Top2a exhibiting the highest expression in epithelial cells and significant downregulation after smoke exposure. ScRNAseq revealed immune cell infiltration and epithelial differentiation trajectories. Virtual knockout showed that Top2a depletion affected the largest transcriptomic fraction (~0.4%) and was enriched in lysosome biogenesis, innate immunity, phagocytosis, and lipid catabolism. Molecular docking identified thalidomide as a high affinity ligand for Top2a (Vina score: -8.5 kcal/mol). Conclusion Our multiomics integrative framework identifies Top2a as a central regulatory hub linking sphingolipid associated inflammation to epithelial responses in WSI, and nominates thalidomide as a potential drug repurposing candidate. These findings provide prioritized targets for future translational investigation.

Background & Aims: Fatigue is a central symptom of chronic liver disease (CLD), substantially impacting health-related quality of life (HRQoL). This study aimed to further understand CLD symptomatology, including fatigue, and its impact on HRQoL from a patient perspective. Methods: Abbott Global Assessment of Patients unmet needs (aGAP) was a multinational, cross-sectional survey in adults with compensated CLD in China, India and Mexico, conducted between July and November 2024. Adult participants who self-reported that they had physician-diagnosed CLD and were experiencing fatigue completed a quantitative survey to assess symptom burden and included three HRQoL patient-reported outcome (PRO) questionnaires (Patient-Reported Outcomes Measurement Information System [PROMIS]-29+2, Work Productivity and Activity Impairment - Specific Health Problem version 2.0 [WPAI: SHP], Multidimensional Fatigue Inventory [MFI]). Results: Overall, 505 participants (China: 200; Mexico: 105; India: 200) completed the study. Participants reported that their CLD-related fatigue sometimes, often or always affected their self-esteem/confidence (45.1%) and ability to maintain or acquire new employment (38.6%). Most participants reported moderate (51.3%) or serious (26.9%) fatigue, with 33.5% experiencing fatigue every day or almost every day. Many participants felt their social life was negatively impacted by their fatigue (47.3%) and that there were related financial difficulties (53.9%). Use of validated PRO tools demonstrated severe fatigue (MFI: overall mean [SD] 13.9 [3.4] general fatigue and 13.4 [3.6] physical fatigue) as well as substantial levels of work and activity impairment (WPAI: SHP overall mean [SD] 53.0 [26.4]) and high levels of anxiety, pain interference, depression and sleep interference (PROMIS T-scores [≥]54). Conclusions: Fatigue has a substantial impact on HRQoL among adults with CLD across several countries, highlighting a global unmet need for targeted interventions to effectively identify and manage the condition.

Conventional univariate reference intervals (UniRIs) are widely used to identify abnormal biomarker values, but they evaluate each biomarker independently and do not account for coordinated deviations between biomarkers. We developed and evaluated a joint reference region (JRR) framework for plasma proteomics data using the Olink proteomics dataset generated by the UK Biobank Pharma Proteomics Project, covering approximately 3,000 plasma proteins. JRRs were estimated for selected protein pairs in a healthy reference subset, while UniRIs were estimated separately for individual proteins using the nonparametric method. Both approaches were then evaluated in ICD-defined disease subsets. Biomarker discovery revealed sparse and heterogeneous disease--protein associations, with some proteins recurring across multiple phenotypes and others showing more disease-specific patterns. The added value of JRRs varied across diseases and protein pairs. Across evaluated protein pairs, 56.5\% showed higher sensitivity under the JRR framework than the UniRI of the first protein, and 47.3\% showed higher sensitivity than the UniRI of the second protein. At the disease level, the median proportion of protein pairs with improved JRR sensitivity was 0.57. JRRs were most informative when univariate detection was limited but a subset of diseased observations was flagged only by the joint region. These findings suggest that JRRs provide a complementary approach to UniRIs by capturing abnormal joint biomarker configurations in high-dimensional proteomics data.

Ethnopharmacological relevance: Australian Indigenous medicinal plants represent a valuable yet underexplored source of bioactive compounds with potential therapeutic relevance. The Iningai community of Central Queensland has traditionally used native plants to manage conditions associated with inflammation, pain, infection, and general illness. Scientific evaluation of these plants may provide evidence for their customary applications and identify bioactivities relevant to anticancer biodiscovery. Aim of the study: This study evaluated leaf and stem extracts of seven medicinal plants-Pittosporum angustifolium, Alphitonia excelsa, Calytrix microcoma, Geijera parviflora, Melaleuca uncinata, Gossypium australe, and Eucalyptus similis-traditionally used by the Iningai community, focusing on three biological processes relevant to cancer: oxidative stress, inflammation, and cellular proliferation. Materials and methods: Antioxidant activity was assessed using DPPH radical-scavenging and ferric reducing antioxidant power (FRAP) assays. Anti-inflammatory activity was evaluated in lipopolysaccharide (LPS)-stimulated THP-1 macrophage-like cells by profiling IFN-, TNF-, IL-6, IL-12, IL-18, and IL-23. Antiproliferative activity was assessed using MTT-based viability assays in human and murine liver cancer cell lines (Huh7, Hep3B, Hep-55.1c, and A52). Results: The extracts exhibited distinct biological activity profiles. G. parviflora stem and C. microcoma leaf extracts showed the strongest antioxidant activities, whereas P. angustifolium stem exhibited the weakest radical-scavenging capacity. Cytokine responses were extract-specific, with E. similis leaf extract demonstrating broad and pronounced suppression of multiple LPS-induced pro-inflammatory cytokines. Several extracts produced concentration-dependent reductions in liver cancer cell viability, with P. angustifolium stem exhibiting the most consistent and potent antiproliferative activity across the cell lines tested. Notably, strong antioxidant or anti-inflammatory activity did not necessarily correspond with antiproliferative activity. Conclusion: Australian Indigenous medicinal plant extracts demonstrated distinct antioxidant, immunomodulatory, and antiproliferative activities rather than uniform bioactivity across experimental systems. The divergent activities of G. parviflora, C. microcoma, E. similis, and P. angustifolium highlight the importance of integrated biological screening and support the value of Indigenous knowledge-guided biodiscovery. These plants represent promising sources for further investigation of selective bioactive compounds with potential relevance to anticancer drug discovery.

Metabolic dysfunction-associated steatotic liver disease (MASLD), the leading cause of chronic liver pathologies worldwide, represents a growing clinical burden. Its diagnosis remains reliant on liver biopsy that limits early detection and the ability to capture molecular changes across disease progression. A systematic understanding of stage-dependent gene expression changes is essential to identify biomarkers and effectively characterize disease mechanisms. Therefore recent studies provided databases for searching genes as well as prediction of multi-gene signatures for disease progression. However, there is still a need for interactive and comprehensive meta-analysis of datasets of MASLD patients with available histological metadata. Herein, we performed a meta-analysis of RNA-seq datasets using NAFLD Activity Score (NAS; n = 897) and fibrosis stage (n = 856) upon conducting pairwise comparisons across histological stages and identified differentially expressed genes associated with disease progression. Most importantly, we provide our findings via a dedicated web server, the MASLD-META NETWORK (https://masld.scilicium.com), enabling users to interactively explore meta-analysis results across diverse network modalities. In addition, we characterized gene expression dynamics across increasing disease stages to identify consistent progression-associated pathways using Louvain clustering. Network-based parameters such as centrality in combination with meta-analysis scores further highlighted central genes and pathways implicated in disease mechanisms. Accordingly, MASLD-META NETWORK enabled an integrative reassessment of recently published gene signatures, identifying COL1A1, COL3A1, THBS2, FBLN5, and PDGFA as the most central genes, and SULF2, MMP14, IL32, GPNMB, and COL3A1 as candidate markers of earlier transcriptional alterations. Network analysis of MASLD associated biological modules further identified LAMA2 and LAMA3 as previously unrecognized central candidate targets.

Viral infections have long been proposed as environmental contributors to neurodegenerative diseases, including Parkinson's disease (PD), yet the molecular mechanisms linking infection and neurodegeneration are not well defined. Neuroinflammation and disruption of central nervous system (CNS) homeostasis have emerged as potential mediators. In this study, we used severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, as a model pathogen to investigate convergent molecular pathways between viral infection and PD. Single-nucleus RNA sequencing (snRNA-seq) was performed on post-mortem striatal tissue from 14 individuals stratified into four groups: COVID-19 only (COVID-19), PD only (PD), comorbid PD with COVID-19 (PD/COVID-19), and controls (Control). The PD/COVID-19 group exhibited an expanded astrocytic population and a pronounced interferon-associated molecular signature characterized by increased expression of canonical interferon-stimulated genes, including IFI44L (average log2FC= 3.9; adjusted p=2.3 x 10-373), IFI44 (average log2FC=2.9; adjusted p=8.0 x 10-266), ISG15 (average log2FC=3.1; adjusted p=1.2 x 10-197), and RSAD2 (average log2FC= 3.5; adjusted p=8.6 x 10-111). Pathway analyses demonstrated activation of innate immune and antiviral signaling pathways, particularly within microglia and astrocytes, including interferon signaling, pattern-recognition receptor pathways, and complement-associated responses. In parallel, genes involved in lipid metabolism, cholesterol homeostasis, synaptic maintenance, and neuronal signaling were reduced across disease groups. Proteomic analyses independently confirmed enrichment of antiviral and interferon-associated pathways and identified convergent suppression of sterol, cholesterol, and lipid metabolic processes. Our findings identify a convergent molecular signature linking PD and COVID-19, pronounced in comorbid individuals and characterized by interferon-driven innate immune activation, glial inflammatory responses, and dysregulation of lipid metabolic homeostasis. Collectively, the data support a model in which severe viral infection amplifies biological pathways already implicated in PD pathogenesis.

High-protein diets increase hepatic sulfur amino acid metabolism, but the underlying transcriptional mechanisms remain unclear. This study investigated whether Kruppel-like factor 15 (KLF15) directly regulates cystathionine {gamma}-lyase (CTH), a key enzyme linking methionine transsulfuration to hydrogen sulfide (H2S) and taurine production. Promoter-reporter assays, electrophoretic mobility shift assays, and chromatin immunoprecipitation identified two functional KLF15-binding elements, designated 1-1 and 2-2, within the proximal Cth promoter. Mutation of either element attenuated KLF15-dependent promoter activation, whereas mutation of both largely abolished it. In vivo luciferase imaging further demonstrated that these elements were required for the hepatic transcriptional response to a high-protein diet. KLF15 loss of function reduced high-protein-diet-induced Cth expression and altered the hepatic sulfur amino acid profile. Methionine, cystathionine, and cystine accumulated, whereas taurine production and the high-protein-diet-induced increase in hepatic H2S were attenuated. Gene expression analyses further indicated that KLF15 selectively regulates components of methionine, taurine, and H2S metabolism rather than controlling the entire sulfur metabolic program. Collectively, these findings establish the high-protein diet-KLF15-CTH axis as a physiologically relevant transcriptional pathway that amplifies hepatic sulfur amino acid disposal and directs sulfur toward H2S and taurine production.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major cause of chronic liver disease, with weight loss as the pivotal therapeutic strategy. However, the metabolic and molecular adaptations underlying rapid weight loss remain incompletely defined. In this pilot study, women with obesity and MASLD but without diabetes consumed a very low-calorie diet (VLCD) for 8 weeks. Clinical parameters, hepatic steatosis measured by controlled attenuation parameter (CAP), circulating metabolites, and microRNAs (miRs) were assessed before and after the dietary intervention. Integrated correlation and hierarchical clustering analyses were performed to identify molecular networks associated with clinical improvement. VLCD was well tolerated, resulting in significant weight loss (~11%) with ~80% adherence. Significant improvements in metabolic parameters were observed, including fat mass, waist circumference, blood pressure, insulinemia, HOMA-IR, HbA1c, and triglycerides, with unchanged liver enzymes. Hepatic steatosis decreased markedly, as indicated by a reduction in CAP, while stiffness remained unchanged. Metabolomic profiling revealed elevated ketone bodies and broad reductions in amino acid levels, consistent with enhanced fatty acid oxidation and a catabolic metabolic state. Correlation analysis identified distinct metabolite signatures associated with hepatic steatosis, with changes in CAP positively associated with changes in amino acids and inversely associated with changes in ketone bodies and tricarboxylic acid cycle intermediates. Circulating miRs underwent selective rather than global remodeling, with only a limited subset showing strong associations with clinical parameters, including CAP and HOMA-IR. Specifically, VLCD altered the circulating levels of miR-148a-3p, miR-140-3p, miR-10b-5p, and miR-345-5p. Integration of metabolomic and miR datasets identified coordinated metabolite-miR modules involving glucose metabolism, branched-chain amino acid catabolism, mitochondrial metabolism, purine metabolism, microbial metabolites, and cellular redox pathways. These findings demonstrate that improvement in hepatic steatosis during VLCD-induced weight loss is accompanied by coordinated remodeling of circulating metabolite-miR networks. Integrated multi-omics analysis identifies candidate molecular signatures associated with metabolic adaptation and highlights circulating miR-metabolite modules as potential biomarkers of therapeutic response in MASLD.

Background: Fibrosis, characterised by excessive accumulation of collagen type I (COL1), is a common feature of chronic diseases, including liver diseases (LDs), chronic kidney disease (CKD) and heart failure (HF). COL1 degradation products can be detected in urine by proteomics/ peptidomics analyses and may serve as non-invasive biomarkers of fibrosis. We aimed to identify a common molecular signature of fibrosis across these diseases that may ultimately guide interventions to slow disease progression and prevent organ damage. Methods: Using capillary electrophoresis coupled to mass spectrometry (CE-MS), naturally occurring COL1 degradation products (peptides) in the urine of patients with fibrotic disease, LDs (n=127), CKD (n=263) or HF (n=187), were investigated and compared with the same number of matched controls. Disease-associated COL1 peptides were identified separately for each condition, and peptides showing consistent associations across the three diseases were selected to define a common fibrosis signature. A support vector machine model based on the selected peptides was developed and validated in independent cohorts of patients with LDs (n=110), CKD (n=93), HF (n=32) and controls (n=643). Results: We identified a common fibrotic signature consisting of 50 COL1 degradation products, mainly downregulated in fibrosis. A model based on these peptides achieved a strong performance, with an area under the receiver operating characteristic curve (AUC) of 0.935 (95% confidence interval (CI) 0.917-0.953, p<0.0001) in an external validation cohort comprising pooled disease groups (LDs, CKD, and HF) and controls. Performance was maintained in LDs, CKD and HF, with AUCs of 0.917 (95% CI 0.890-0.944, p<0.0001), 0.951 (95% CI 0.931-0.971, p<0.0001) and 0.950 (95% CI 0.903-0.997, p<0.0001), respectively. The model scores were significantly associated with fibrosis stage in LDs (p=0.0097) and with interstitial fibrosis and tubular atrophy in CKD (p=0.045). Conclusion: A model of urinary COL1 peptides captures a shared collagen degradation signature across organs and diseases, enabling the non-invasive assessment of fibrosis irrespective of its origin. As these peptides exclusively reflect collagen degradation, the findings suggest impaired collagen degradation as a driver in fibrosis. Future clinical studies are warranted to evaluate the utility of this model for early fibrosis detection and earlier implementation of anti-fibrotic interventions.

Plant cold acclimation emerges from coordinated adjustments in photosynthesis, primary metabolism, and intracellular carbon allocation. Yet, the regulatory role of subcellular metabolite compartmentation in natural variation of cold acclimation remains insufficiently understood. Here, we investigated four Arabidopsis thaliana accessions grown either individually or in bulk to determine how growth configuration and genotype shape the metabolism of sugars and organic acids during cold exposure. Using non-aqueous fractionation, we quantified plastidial, cytosolic, and vacuolar sugar pools alongside whole-cell carbohydrates, organic acids, enzyme activities, photosynthetic parameters, and stress markers. A neural-network classifier revealed that subcellular sugar distribution together with sugar amounts and organic acids provided the strongest discriminatory power among accessions, surpassing photosynthetic traits and enzyme activities. Our findings demonstrate that natural variation in cold acclimation is strongly determined by genotype-specific subcellular metabolite architectures, and that the cultivation strategy modulates these intracellular signatures. We conclude that subcellular compartmentation of metabolites represents a cellular control layer for natural variation of cold acclimation and resilience in Arabidopsis thaliana.

Background and Objectives: Preterm infants are commonly transfused, yet direct cardiorespiratory effects of red blood cell (RBC) transfusions remain poorly understood. We explored the feasibility of using multicentre electronic health data (EHD) to study such cardiorespiratory responses. Methods: Highly granular routine EHD were collected from preterm infants born <32 weeks gestational age at three European centres. Heart rate, oxygen saturation, and respiratory rate were evaluated 12 hours before and after the RBC transfusion. Results: A total of 321 transfusions in 164 infants were analysed. Overall, there was no significant change in the rate of bradycardia and apnoea following transfusion. Cardiorespiratory parameters varied substantially between infants; e.g. 20% of transfusions were associated with an unexpected, significant increase in heart rate. Respiratory rate and oxygen saturation exhibited similarly heterogenous patterns following transfusion. In sub-group analysis, the proportion of transfusions with increased heart rate was significantly higher within the first two weeks than later (32% vs 13%, p=0.0019). Conclusions: Multicentre EHD extraction allows to identify otherwise masked short-term effects of RBC transfusions on cardiorespiratory parameters, possibly indicating cardiac or pulmonary overload. Such effects may vary with adaptation to anaemia. Analysing EHD may ultimately enable personalized transfusion practice.

We identified Sleep Bursts (SBs), as a novel phenomenon of brief (1-2 sec), often periodic bursts in cranial forces occurring during human sleep. Our goal was to characterize SBs in normal subjects, then compare SB in a cohort of subjects with neurodegenerative disease (NDD). We recorded 32 cognitively healthy subjects (23 -87 years) and 13 subjects with NDD (51 - 84 years). SBs occurred in all 45 subjects. SBs occurred at 0.57 SB/min (once per 105 seconds) in controls and 0.40 SB/min (once per 150 seconds) in NDD (p = 0.0043). SB occurred with equal rates across all sleep stages in both groups. When occurring periodically, SBs had modal intervals (3.75 bursts/min (0.0625 Hz) - 2.67 bursts/min (0.044 Hz)). EEG power increased in the delta range 1-2 seconds before and following the SB. EEG delta power during a SB was significantly lower in all NDD subjects across sleep stages compared to controls. The relatively low frequency of SB events and synchronization with EEG power has no parallel in human sleep; we hypothesize that SBs may represent a brain-generated pulsatile component of brain glymphatic drainage.

Lysophosphatidic acid (LPA) is widely recognized as an extracellular lipid mediator; however, the functional significance of intracellularly produced LPA remains poorly understood. Here, we investigated the regulatory mechanism and functional role of a LPA-producing lysophospholipase D GDE4, also known as GDPD1, in prostate cancer cells. GDE4 expression is induced under ER stress conditions in a PERK-dependent manner and requires the transcription factor ATF3. Disruption of GDE4 expression resulted in altered intracellular levels of LPA and LPA precursor lysophosphatidylethanolamine, accompanied by reduced cell proliferation. RNA sequencing and subsequent validation identified a set of genes downregulated in GDE4-depleted cells. Pharmacological inhibition experiments indicated that peroxisome proliferator-activated receptor and {gamma} (PPAR and PPAR{gamma}) signaling pathways contribute to the regulation of these GDE4-dependent genes. Collectively, our findings suggest that GDE4-dependent lipid remodeling is associated with PPAR/{gamma}-mediated transcriptional regulation under ER stress conditions. These results provide a potential framework for understanding the link between intracellular lipid metabolism and stress-responsive gene regulation.

Background: Evidence suggests chronic distress influences ovarian cancer (OC) etiology and metabolomic profiles. Here, we evaluated the association of a metabolite-based distress score (MDS) and OC risk. Methods: We included two matched case-control studies nested within the Nurses' Health Studies (N=584) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (N=348). Metabolites were measured 3-27 years before diagnosis using liquid-chromatography tandem mass spectrometry. We examined the association of quintiles of MDS and 19 constituent metabolites with OC risk using unconditional logistic regression and stratified by tumor histotype, menopausal status, and age at diagnosis. Results: We observed women in the highest versus lowest quintile of MDS had an increased OC risk (OR=1.62,95%CI=1.03-2.54,ptrend=0.07), and type 2 tumors (OR=1.71,95%CI=1.03-2.83,ptrend=0.11). Associations were suggestively stronger for premenopausal and <69-year-old women, and driven by pseudouridine, and N2,N2-dimethylguanosine. Conclusion: Our findings suggest chronic distress-associated metabolic dysregulation may represent a novel OC risk factor, especially among younger women.

Purpose: To evaluate the safety, procedural performance, sample recovery, and surgeon preference of an ophthalmic needle designed specifically for anterior chamber (AC) paracentesis. Methods: In this multicenter study, AC paracentesis was performed in clinic and operating-room settings using a 32-gauge x 4-mm needle with low dead space. The procedure was evaluated using a standardized physician survey. Prespecified outcomes included procedure-related adverse events (primary outcome), needle entry and handling, aspiration and sample recovery, comparative performance versus a 30-gauge needle, and physician preference for future use. Results: A total of 110 needle uses by eight surgeons were included. No ocular complications occurred, including lens or iris injury, hyphema, AC collapse, wound leak, hypotony, infection, or retinal complication, and no procedure required needle exchange or conversion to another device. Two technical events without ocular sequelae were noted, in which needle entry was partial thickness and did not reach the AC (1.8%; exact 95% CI, 0.2%-6.4%). Physicians rated needle entry, handling and sample recovery as good or excellent. Compared with a 30-gauge needle, the study needle was rated as at least comparable across all assessed domains. All surgeons rated it better or much better for intra-procedural safety and preferred it for future AC taps. Conclusions and Relevance: This short, 32-gauge low-dead-space ophthalmic needle demonstrated a favorable safety profile and was preferred over a 30-gauge needle by all surgeons. As aqueous humor liquid biopsy expands in clinical diagnostics and trials, an ophthalmic-specific needle design may help improve the consistency and safety of aqueous humor collection for molecular analysis and broader clinical use. Keywords: Anterior chamber paracentesis; Aqueous humor; Liquid biopsy; Low dead space; Ophthalmic needle