Senescence: An Identity Crisis Originating from Deep Within the Nucleus.

Cellular senescence is implicated in a wide range of physiological and pathological conditions throughout an organism's entire lifetime. In particular, it has become evident that senescence plays a causative role in aging and age-associated disorders. This is not due simply to the loss of function of senescent cells. Instead, the substantial alterations of the cellular activities of senescent cells, especially the array of secretory factors, impact the surrounding tissues or even entire organisms. Such non-cell-autonomous functionality is largely coordinated by tissue-specific genes, constituting a cell fate-determining state. Senescence can be viewed as a gain-of-function phenotype or a process of cell identity shift. Cellular functionality or lineage-specific gene expression is tightly linked to the cell type-specific epigenetic landscape, reinforcing the heterogeneity of senescence across cell types. Here, we aim to define the senescence cellular functionality and epigenetic features that may contribute to the gain-of-function phenotype.

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples.

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on "chromatin-state" to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.

Rapid induction of antigen-specific CD4+ T cells is associated with coordinated humoral and cellular immunity to SARS-CoV-2 mRNA vaccination.

SARS-CoV-2 mRNA vaccines have shown remarkable clinical efficacy, but questions remain about the nature and kinetics of T cell priming. We performed longitudinal antigen-specific T cell analyses on healthy SARS-CoV-2-naive and recovered individuals prior to and following mRNA prime and boost vaccination. Vaccination induced rapid antigen-specific CD4+ T cell responses in naive subjects after the first dose, whereas CD8+ T cell responses developed gradually and were variable in magnitude. Vaccine-induced Th1 and Tfh cell responses following the first dose correlated with post-boost CD8+ T cells and neutralizing antibodies, respectively. Integrated analysis revealed coordinated immune responses with distinct trajectories in SARS-CoV-2-naive and recovered individuals. Last, whereas booster vaccination improved T cell responses in SARS-CoV-2-naive subjects, the second dose had little effect in SARS-CoV-2-recovered individuals. These findings highlight the role of rapidly primed CD4+ T cells in coordinating responses to the second vaccine dose in SARS-CoV-2-naive individuals.

Oxidative status: A general but overlooked indicator of welfare across animal species?

Because of their ubiquity, plasticity, and direct effects on the nervous system, markers of oxidative status may be of great value to assess animal welfare across species and conditions in the wild. However, welfare biologists have not yet seized this opportunity, possibly because the validity of these markers as welfare indicators remains questionable. A validation process was, therefore, performed here using a meta-analytical approach considering three conditions assumed to impair the welfare of animals. With very few exceptions, two of the four considered markers consistently varied across these negatively-valenced conditions. By highlighting the current underrepresentation of markers of oxidative status in animal welfare studies, and by concretely illustrating that some of these markers can consistently reflect negative affective states, this article aims to encourage biologists to include these physiological markers in their toolbox to better measure, monitor, and perhaps also improve the welfare of animals in their natural habitat.

Fluorescent cytoskeletal markers reveal associations between the actin and microtubule cytoskeleton in rice cells.

Rice (Oryza sativa) is one of our main food crops, feeding ∼3.5 billion people worldwide. An increasing number of studies note the importance of the cytoskeleton, including actin filaments and microtubules, in rice development and environmental responses. Yet, reliable in vivo cytoskeleton markers are lacking in rice, which limits our knowledge of cytoskeletal functions in living cells. Therefore, we generated bright fluorescent marker lines of the actin and microtubule cytoskeletons in rice, suitable for live-cell imaging in a wide variety of rice tissues. Using these lines, we show that actin bundles and microtubules engage and co-function during pollen grain development, how the cytoskeletal components are coordinated during root cell development, and that the actin cytoskeleton is robust and facilitates microtubule responses during salt stress. Hence, we conclude that our cytoskeletal marker lines, highlighted by our findings of cytoskeletal associations and dynamics, will substantially further future investigations in rice biology.

Fast and flexible inference for joint models of multivariate longitudinal and survival data using integrated nested Laplace approximations.

Modeling longitudinal and survival data jointly offers many advantages such as addressing measurement error and missing data in the longitudinal processes, understanding and quantifying the association between the longitudinal markers and the survival events, and predicting the risk of events based on the longitudinal markers. A joint model involves multiple submodels (one for each longitudinal/survival outcome) usually linked together through correlated or shared random effects. Their estimation is computationally expensive (particularly due to a multidimensional integration of the likelihood over the random effects distribution) so that inference methods become rapidly intractable, and restricts applications of joint models to a small number of longitudinal markers and/or random effects. We introduce a Bayesian approximation based on the integrated nested Laplace approximation algorithm implemented in the R package R-INLA to alleviate the computational burden and allow the estimation of multivariate joint models with fewer restrictions. Our simulation studies show that R-INLA substantially reduces the computation time and the variability of the parameter estimates compared with alternative estimation strategies. We further apply the methodology to analyze five longitudinal markers (3 continuous, 1 count, 1 binary, and 16 random effects) and competing risks of death and transplantation in a clinical trial on primary biliary cholangitis. R-INLA provides a fast and reliable inference technique for applying joint models to the complex multivariate data encountered in health research.

Hierarchical cell-type identifier accurately distinguishes immune-cell subtypes enabling precise profiling of tissue microenvironment with single-cell RNA-sequencing.

Single-cell RNA-seq enabled in-depth study on tissue micro-environment and immune-profiling, where a crucial step is to annotate cell identity. Immune cells play key roles in many diseases, whereas their activities are hard to track due to their diverse and highly variable nature. Existing cell-type identifiers had limited performance for this purpose. We present HiCAT, a hierarchical, marker-based cell-type identifier utilising gene set analysis for statistical scoring for given markers. It features successive identification of major-type, minor-type and subsets utilising subset markers structured in a three-level taxonomy tree. Comparison with manual annotation and pairwise match test showed HiCAT outperforms others in major- and minor-type identification. For subsets, we qualitatively evaluated the marker expression profile demonstrating that HiCAT provide the clearest immune-cell landscape. HiCAT was also used for immune-cell profiling in ulcerative colitis and discovered distinct features of the disease in macrophage and T-cell subsets that could not be identified previously.

MSI-XGNN: an explainable GNN computational framework integrating transcription- and methylation-level biomarkers for microsatellite instability detection.

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.

Mild Hypoxia Accelerates Cerebral Cavernous Malformation Disease Through CX3CR1-CX3CL1 Signaling.

BACKGROUND: Heterogeneity in the severity of cerebral cavernous malformations (CCMs) disease, including brain bleedings and thrombosis that cause neurological disabilities in patients, suggests that environmental, genetic, or biological factors act as disease modifiers. Still, the underlying mechanisms are not entirely understood. Here, we report that mild hypoxia accelerates CCM disease by promoting angiogenesis, neuroinflammation, and vascular thrombosis in the brains of CCM mouse models. METHODS: We used genetic studies, RNA sequencing, spatial transcriptome, micro-computed tomography, fluorescence-activated cell sorting, multiplex immunofluorescence, coculture studies, and imaging techniques to reveal that sustained mild hypoxia via the CX3CR1-CX3CL1 (CX3C motif chemokine receptor 1/chemokine [CX3C motif] ligand 1) signaling pathway influences cell-specific neuroinflammatory interactions, contributing to heterogeneity in CCM severity. RESULTS: Histological and expression profiles of CCM neurovascular lesions (Slco1c1-iCreERT2;Pdcd10fl/fl; Pdcd10BECKO) in male and female mice found that sustained mild hypoxia (12% O2, 7 days) accelerates CCM disease. Our findings indicate that a small reduction in oxygen levels can significantly increase angiogenesis, neuroinflammation, and thrombosis in CCM disease by enhancing the interactions between endothelium, astrocytes, and immune cells. Our study indicates that the interactions between CX3CR1 and CX3CL1 are crucial in the maturation of CCM lesions and propensity to CCM immunothrombosis. In particular, this pathway regulates the recruitment and activation of microglia and other immune cells in CCM lesions, which leads to lesion growth and thrombosis. We found that human CX3CR1 variants are linked to lower lesion burden in familial CCMs, proving it is a genetic modifier in human disease and a potential marker for aggressiveness. Moreover, monoclonal blocking antibody against CX3CL1 or reducing 1 copy of the Cx3cr1 gene significantly reduces hypoxia-induced CCM immunothrombosis. CONCLUSIONS: Our study reveals that interactions between CX3CR1 and CX3CL1 can modify CCM neuropathology when lesions are accelerated by environmental hypoxia. Moreover, a hypoxic environment or hypoxia signaling caused by CCM disease influences the balance between neuroinflammation and neuroprotection mediated by CX3CR1-CX3CL1 signaling. These results establish CX3CR1 as a genetic marker for patient stratification and a potential predictor of CCM aggressiveness.

Biomarkers of transfusion transmitted occult hepatitis B virus infection: Where are we and what next?

Blood transfusion is a vital procedure, where transfusion-transmitted infection of hepatitis B virus (HBV) remains an important issue, especially from blood donors with occult hepatitis B virus infection (OBI). Occult hepatitis B virus infection is a complex entity to detect using surrogate blood biomarkers for intrahepatic viral transcriptional activity, requiring a continually refined battery of tests utilised for screening. This review aims to critically evaluate the latest advances in the current blood biomarkers to guide the identification of OBI donors and discuss novel HBV markers that could be introduced in future diagnostic practice. Challenges in detecting low HBV surface antigen levels, mutants, and complexes necessitate ultrasensitive multivalent dissociation assays, whilst HBV DNA testing requires improved sensitivity but worsens inaccessibility. Anti-core antibody assays defer almost all potentially infectious donations but have low specificity, and titres of anti-surface antibodies that prevent infectivity are poorly defined with suboptimal sensitivity. The challenges associated with these traditional blood HBV markers create an urgent need for alternative biomarkers that would help us better understand the OBI. Emerging viral biomarkers, such as pre-genomic RNA and HBV core-related antigen, immunological HBV biomarkers of T-cell reactivity and cytokine levels, and host biomarkers of microRNA and human leucocyte antigen molecules, present potential advances to gauge intrahepatic activity more accurately. Further studies on these markers may uncover an optimal diagnostic algorithm for OBI using quantification of various novel and traditional blood HBV markers. Addressing critical knowledge gaps identified in this review would decrease the residual risk of transfusion-transmitted HBV infection without compromising the sustainability of blood supplies.

The relationship between HIV-1 neuroinflammation, neurocognitive impairment and encephalitis pathology: A systematic review of studies investigating post-mortem brain tissue.

The activities of HIV-1 in the central nervous system (CNS) are responsible for a dysregulated neuroinflammatory response and the subsequent development of HIV-associated neurocognitive disorders (HAND). The use of post-mortem human brain tissue is pivotal for studying the neuroimmune mechanisms of CNS HIV infection. To date, numerous studies have investigated HIV-1-induced neuroinflammation in post-mortem brain tissue. However, from the commonly investigated studies in this line of research, it is not clear which neuroinflammatory markers are consistently associated with HIV neurocognitive impairment (NCI) and neuropathology (i.e., HIV-encephalitis, HIVE). Therefore, we conducted a systematic review of the association between neuroinflammation and NCI/HIVE from studies investigating post-mortem brain tissue. Our aim was to synthesise the published data to date to provide commentary on the most noteworthy markers that are associated with NCI/HIVE. PubMed, Scopus, and Web of Science databases were searched using a search protocol designed specifically for this study. Sixty-one studies were included that investigated the levels of inflammatory markers based on their gene and protein expression in association with NCI/HIVE. The findings revealed that the (1) transcript expressions of IL-1ß and TNF-α were consistently associated with NCI/HIVE, whereas CCL2 and IL-6 were commonly not associated with NCI/HIVE, (2) protein expressions of CD14, CD16, CD68, Iba-1, IL-1ß and TNF-α were consistently associated with NCI/HIVE, while CD45, GFAP, HLA-DR, IL-1 and IL-6 were commonly not associated with NCI/HIVE, and (3) gene and protein expressions of CNS IL-1ß and TNF-α were consistently associated with NCI/HIVE, while IL-6 was consistently not associated with NCI/HIVE. These markers highlight the commonly investigated markers in this line of research and elucidates the neuroinflammatory mechanisms in the HIV-1 brain that are involved in the pathophysiology of NCI/HIVE. These markers and related pathways should be investigated for the development of improved diagnostics, prognostics, and therapeutics of HAND.

Mapping interictal discharges using intracranial EEG-fMRI to predict postsurgical outcomes.

Various subjective and objective methods have been proposed to identify which interictal epileptiform discharge (IED)-related EEG-fMRI results are more likely to delineate seizure generating tissue in patients with drug-resistant focal epilepsy for the purposes of surgical planning. In this intracranial EEG-fMRI study, we evaluated the utility of these methods to localize clinically relevant regions pre-operatively and compared the extent of resection of these areas to post-operative outcome. Seventy patients admitted for intracranial video-EEG monitoring were recruited for a simultaneous intracranial EEG-fMRI study. For all analyses of blood oxygen level-dependent responses associated with IEDs, an experienced epileptologist identified the most Clinically Relevant brain activation cluster using available clinical information. The Maximum cluster (the cluster with the highest z-score) was also identified for all analyses and assigned to one of three confidence levels (low, medium, or high) based on the difference of the peak z-scores between the Maximum and Second Maximum cluster (the cluster with the second highest peak z-value). The distance was measured and compared between the peak voxel of the aforementioned clusters and the electrode contacts where the interictal discharge and seizure onset were recorded. In patients who subsequently underwent epilepsy surgery, the spatial concordance between the aforementioned clusters and the area of resection was determined and compared to post-operative outcome. We evaluated 106 different IEDs in 70 patients. Both subjective (identification of the Clinically Relevant cluster) and objective (Maximum cluster much more significant than the second maximum cluster) methods of culling non-localizing EEG-fMRI activation maps increased the spatial concordance between these clusters and the corresponding IED or seizure onset zone contacts. However, only the objective methods of identifying medium and high confidence maps resulted in a significant association between resection of the peak voxel of the Maximum cluster and post-operative outcome. Resection of this area was associated with good post-operative outcomes but was not sufficient for seizure freedom. On the other hand, we found that failure to resect the medium and high confidence Maximum clusters was associated with a poor post-surgical outcome (negative predictive value = 1.0, sensitivity = 1.0). Objective methods to identify higher confidence EEG-fMRI results are needed to localize areas necessary for good post-operative outcomes. However, resection of the peak voxel within higher confidence Maximum clusters is not sufficient for good outcomes. Conversely, failure to resect the peak voxel in these clusters is associated with a poor post-surgical outcome.

Blood inflammation relates to neuroinflammation and survival in frontotemporal lobar degeneration.

Neuroinflammation is an important pathogenic mechanism in many neurodegenerative diseases, including those caused by frontotemporal lobar degeneration (FTLD). Postmortem and in vivo imaging studies have shown brain inflammation early in these conditions, proportionate to symptom severity and rate of progression. However, evidence for corresponding blood markers of inflammation and their relationship with central inflammation and clinical outcome are limited. There is a pressing need for such scalable, accessible and mechanistically relevant blood markers as these will reduce the time, risk, and costs of experimental medicine trials. We therefore assessed inflammatory patterns of serum cytokines from 214 patients with clinical syndromes associated with FTLD as compared to healthy controls, including their correlation with brain regional microglial activation and disease progression. Serum assays used the MesoScale Discovery V-Plex-Human Cytokine 36 plex panel plus five additional cytokine assays. A sub-group of patients underwent 11C-PK11195 TSPO PET imaging, as an index of microglial activation. A Principal Component Analysis (PCA) was used to reduce the dimensionality of cytokine data, excluding cytokines that were undetectable in >50% of participants. Frequentist and Bayesian analyses were performed on the principal components, to compare each patient cohort to controls, and test for associations with central inflammation, neurodegeneration-related plasma markers and survival. The first component identified by the PCA (explaining 21.5% variance) was strongly loaded by pro-inflammatory cytokines, including TNF-α, TNF-R1, M-CSF, IL-17A, IL-12, IP-10 and IL-6. Individual scores of the component showed significant differences between each patient cohort and controls. The degree to which a patient expressed this peripheral inflammatory profile at baseline correlated negatively with survival (higher inflammation, shorter survival), even when correcting for baseline clinical severity. Higher pro-inflammatory profile scores were associated with higher microglial activation in frontal and brainstem regions, as quantified with 11C-PK11195 TSPO PET. A permutation-based Canonical Correlation Analysis confirmed the association between the same cytokine-derived pattern and central inflammation across brain regions in a fully data-based manner. This data-driven approach identified a pro-inflammatory profile across the FTLD clinical spectrum, which is associated with central neuroinflammation and worse clinical outcome. Blood-based markers of inflammation could increase the scalability and access to neuroinflammatory assessment of people with dementia, to facilitate clinical trials and experimental medicine studies.

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model.

Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challenging. We propose a dual-branch graph neural network that effectively extracts and fuses features from bimodalities, achieving 73.9% diagnostic accuracy. To explain the mechanism distinguishing autism spectrum disorder from healthy controls, we establish a perturbation model for brain imaging markers and perform a neuro-transcriptomic joint analysis using partial least squares regression and enrichment to identify potential genetic biomarkers. The perturbation model identifies brain imaging markers related to structural magnetic resonance imaging in the frontal, temporal, parietal, and occipital lobes, while functional magnetic resonance imaging markers primarily reside in the frontal, temporal, occipital lobes, and cerebellum. The neuro-transcriptomic joint analysis highlights genes associated with biological processes, such as "presynapse," "behavior," and "modulation of chemical synaptic transmission" in autism spectrum disorder's brain development. Different magnetic resonance imaging modalities offer complementary information for autism spectrum disorder diagnosis. Our dual-branch graph neural network achieves high accuracy and identifies abnormal brain regions and the neuro-transcriptomic analysis uncovers important genetic biomarkers. Overall, our study presents an effective approach for assisting in autism spectrum disorder diagnosis and identifying genetic biomarkers, showing potential for enhancing the diagnosis and treatment of this condition.

Evidence from sperm whale clans of symbolic marking in non-human cultures.

Culture, a pillar of the remarkable ecological success of humans, is increasingly recognized as a powerful force structuring nonhuman animal populations. A key gap between these two types of culture is quantitative evidence of symbolic markers-seemingly arbitrary traits that function as reliable indicators of cultural group membership to conspecifics. Using acoustic data collected from 23 Pacific Ocean locations, we provide quantitative evidence that certain sperm whale acoustic signals exhibit spatial patterns consistent with a symbolic marker function. Culture segments sperm whale populations into behaviorally distinct clans, which are defined based on dialects of stereotyped click patterns (codas). We classified 23,429 codas into types using contaminated mixture models and hierarchically clustered coda repertoires into seven clans based on similarities in coda usage; then we evaluated whether coda usage varied with geographic distance within clans or with spatial overlap between clans. Similarities in within-clan usage of both "identity codas" (coda types diagnostic of clan identity) and "nonidentity codas" (coda types used by multiple clans) decrease as space between repertoire recording locations increases. However, between-clan similarity in identity, but not nonidentity, coda usage decreases as clan spatial overlap increases. This matches expectations if sympatry is related to a measurable pressure to diversify to make cultural divisions sharper, thereby providing evidence that identity codas function as symbolic markers of clan identity. Our study provides quantitative evidence of arbitrary traits, resembling human ethnic markers, conveying cultural identity outside of humans, and highlights remarkable similarities in the distributions of human ethnolinguistic groups and sperm whale clans.

zMADM (zebrafish mosaic analysis with double markers) for single-cell gene knockout and dual-lineage tracing.

As a vertebrate model organism, zebrafish has many unique advantages in developmental studies, regenerative biology, and disease modeling. However, tissue-specific gene knockout in zebrafish is challenging due to technical difficulties in making floxed alleles. Even when successful, tissue-level knockout can affect too many cells, making it difficult to distinguish cell autonomous from noncell autonomous gene function. Here, we present a genetic system termed zebrafish mosaic analysis with double markers (zMADM). Through Cre/loxP-mediated interchromosomal mitotic recombination of two reciprocally chimeric fluorescent genes, zMADM generates sporadic (<0.5%), GFP+ mutant cells along with RFP+ sibling wild-type cells, enabling phenotypic analysis at single-cell resolution. Using wild-type zMADM, we traced two sibling cells (GFP+ and RFP+) in real time during a dynamic developmental process. Using nf1 mutant zMADM, we demonstrated an overproliferation phenotype of nf1 mutant cells in comparison to wild-type sibling cells in the same zebrafish. The readiness of zMADM to produce sporadic mutant cells without the need to generate floxed alleles should fundamentally improve the throughput of genetic analysis in zebrafish; the lineage-tracing capability combined with phenotypic analysis at the single-cell level should lead to deep insights into developmental and disease mechanisms. Therefore, we are confident that zMADM will enable groundbreaking discoveries once broadly distributed in the field.

Role of autophagy-related genes in liver cancer prognosis.

Autophagy, a highly conserved process of protein and organelle degradation, has emerged as a critical regulator in various diseases, including cancer progression. In the context of liver cancer, the predictive value of autophagy-related genes remains ambiguous. Leveraging chip datasets from the TCGA and GTEx databases, we identified 23 differentially expressed autophagy-related genes in liver cancer. Notably, five key autophagy genes, PRKAA2, BIRC5, MAPT, IGF1, and SPNS1, were highlighted as potential prognostic markers, with MAPT showing significant overexpression in clinical samples. In vitro cellular assays further demonstrated that MAPT promotes liver cancer cell proliferation, migration, and invasion by inhibiting autophagy and suppressing apoptosis. Subsequent in vivo studies further corroborated the pro-tumorigenic role of MAPT by suppressing autophagy. Collectively, our model based on the five key genes provides a promising tool for predicting liver cancer prognosis, with MAPT emerging as a pivotal factor in tumor progression through autophagy modulation.

A comprehensive analysis integrating phenotypic assessment uncovering thornless cultivar lineages in Aralia elata.

Aralia elata is an Araliaceae woody plant species found in Northeastern Asia. To understand how genetic pools are distributed for A.elata clones, we were to analyze the population structure of A.elata cultivars and identify how these are correlated with thorn-related phenotype which determines the utility of A.elata. We found that the de novo assembled genome of 'Yeongchun' shared major genomic compartments with the public A.elata genome assembled from the wild-type from China. To identify the population structure of the 32 Korean and Japanese cultivars, we identified 44 SSR markers and revealed three main sub-clusters using ΔK analysis with one isolated cultivar. Machine-learning based clustering with thorn-related phenotype correlated moderately with population structure based on SSR analysis suggested multi-layered genetic regulation of thorn-related phenotypes. Thus, we revealed genetic lineage of A.elata and uncovered isolated cultivar which can provide new genetic material for further breeding.

Effect of age and season on respiratory mucosal immune marker profiles.

BACKGROUND: The upper respiratory tract is continuously exposed to microorganisms and noxious elements, leading to local immune responses and the secretion of immune markers. While several studies describe immune marker profiles in respiratory mucosal samples in defined patient cohorts, mucosal immune profiles from the general population during the different seasons are lacking. Such baseline profiles are essential to understand the effect of various exposures to the mucosal immune system throughout life. OBJECTIVE: We sought to establish baseline local upper respiratory mucosal immune profiles in the general population and assess these profiles with regard to age, sex, seasonality, and basic health and lifestyle factors. METHODS: We measured the concentrations of 35 immune markers involved in a broad range of immunological processes at the mucosa in nasopharyngeal swab samples from 951 individuals, aged 0 to 86 years, from a nationwide study. RESULTS: Clustering analysis showed that immune marker profiles clearly reflected immunological functions, such as tissue regeneration and antiviral responses. Immune marker concentrations changed strongly with seasonality and age, with the most profound changes occurring in the first 25 years of life; they were also associated with sex, body mass index, smoking, mild symptoms of airway infection, and chronic asthma and hay fever. CONCLUSION: Immunological analyses of noninvasive mucosal samples provide insight into mucosal immune responses to microbial and noxious element exposure in the general population. These data provide a baseline for future studies on respiratory mucosal immune responses and for the development of mucosal immune-based diagnostics.

Plasma Immune Biomarkers Predictive of Progression to Active Tuberculosis in Household Contacts of TB Patients.

BACKGROUND: The progression from Mycobacterium tuberculosis infection to active tuberculosis (TB) disease varies among individuals, and identifying biomarkers to predict progression is crucial for guiding interventions. In this study, we aimed to determine plasma immune biomarker profiles in healthy household contacts of index pulmonary TB (PTB) patients who either progressed to TB or remained as non-progressors. METHODS: A cohort of household contacts of adults with PTB was enrolled, consisting of 15 contacts who progressed to TB disease and 15 non-progressors. Plasma samples were collected at baseline, 4 months, and 12 months to identify predictive TB progression markers. RESULTS: Our findings revealed that individuals in the progressor group exhibited significantly decreased levels of IFNγ, IL-2, TNFα, IL1α, IL1ß, IL-17A, and IL-1Ra at baseline, months 4 and 12. In contrast, the progressor group displayed significantly elevated levels of IFNα, IFNß, IL-6, IL-12, GM-CSF, IL-10, IL-33, CCL2, CCL11, CXCL8, CXCL10, CX3CL1, VEGF, Granzyme-B and PDL-1 compared to the non-progressor group at baseline, months 4 and 12. ROC analysis identified IFNγ, GM-CSF, IL-1Ra, CCL2 and CXCL10 as the most promising predictive markers, with an AUC of ≥90. Furthermore, combinatorial analysis demonstrated that GM-CSF, CXCL10 and IL-1Ra, when used in combination, exhibited high accuracy in predicting progression to active TB disease. CONCLUSIONS: Our study suggests that a specific set of plasma biomarkers GM-CSF, CXCL10 and IL-1Ra, can effectively identify household contacts at significant risk of developing TB disease. These findings have important implications for early intervention and preventive strategies in TB-endemic regions.