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Age is the primary risk factor for many common human diseases. Here, we quantify the relative contributions of genetics and aging to gene expression patterns across 27 tissues from 948 humans. We show that the predictive power of expression quantitative trait loci is impacted by age in many tissues. Jointly modelling the contributions of age and genetics to transcript level variation we find expression heritability ( h 2 ) is consistent among tissues while the contribution of aging varies by >20-fold with R age 2 > h 2 in 5 tissues. We find that while the force of purifying selection is stronger on genes expressed early versus late in life (Medawar’s hypothesis), several highly proliferative tissues exhibit the opposite pattern. These non-Medawarian tissues exhibit high rates of cancer and age-of-expression-associated somatic mutations. In contrast, genes under genetic control are under relaxed constraint. Together, we demonstrate the distinct roles of aging and genetics on expression phenotypes. Age is a risk factor for many diseases, but the impact of aging on molecular phenotypes is not fully understood. Here, the authors quantify the relative contributions of genetics and aging to gene expression patterns across 27 tissues in humans, showing that age and genetics each play distinct roles in shaping expression phenotypes.

Motor BCIs, with the help of Artificial Intelligence (AI) and machine learning, have shown promise in decoding neural signals for restoring motor function. Structures beyond motor cortex have provided additional sources for movement signals. New evidence points to the role of the insula in motor control, specifically directional hand-movements. In this study, we applied AI and machine learning techniques to decode directional hand-movements from high-gamma band (70–200 Hz) activity in the insular cortex. Seven participants with medication-resistant epilepsy underwent stereo electroencephalographic (SEEG) implantation of depth electrodes for seizure monitoring in the insula. SEEG data were sampled throughout a cued motor task involving three conditions: left-hand movement, right-hand movement, or no movement. Neural signal processing focused on high-gamma band activity. Demixed Principal Component Analysis (dPCA) was used for dimension reduction (d = 10) and feature extraction from the time-frequency analysis. For movement classification, we implemented a bidirectional Long Short-Term Memory (LSTM) architecture with a single layer, utilizing the capacity to process temporal sequences in forward and back directions for optimal decoding of movement direction. Our findings revealed robust directional-specific high-gamma modulation within the insular cortex during motor execution. Temporal decomposition through dPCA demonstrated distinct spatiotemporal patterns of high-gamma activity across movement conditions. Subsequently, LSTM networks successfully decoded these condition-specific neural signatures, achieving a classification accuracy of 72.6% ± 13.0% (mean ± SD), which significantly exceeded chance-level performance of 33.3% ( p  < 0.0001, n  = 16 sessions). Furthermore, we identified a strong negative correlation between temporal distance of training-testing sessions and decoding performance ( r = -0.868, p  < 0.0001), indicating temporal difference of the neural representations. Our study highlights the potential role of deep brain structures, such as the insula, in conditional movement discrimination. We demonstrate that LSTM networks and high-gamma band analysis can advance the understanding of neural mechanisms underlying movement. These insights may pave the way for improvements in SEEG-based BCI.

CD26, dipeptidyl peptidase IV, was discovered firstly as a membrane-associated peptidase on the surface of leukocyte. We previously demonstrated that a subpopulation of CD26+ cells were associated with the development of distant metastasis, enhanced invasiveness and chemoresistance in colorectal cancer (CRC). In order to understand the clinical impact of CD26, the expression was investigated in CRC patient's specimens. This study investigated the prognostic significance of tumour CD26 expression in patients with CRC. Examination of CD26+ cells has significant clinical impact for the prediction of distant metastasis development in colorectal cancer, and could be used as a selection criterion for further therapy. Tumour CD26 expression levels were studied by immunohistochemistry using Formalin-fixed paraffin embedded (FFPE) tissues in 143 patients with CRC. Tumour CD26 expression levels were correlated with clinicopathological features of the CRC patients. The prognostic significance of tumour tissue CD26 expression levels was assessed by univariate and multivariate analyses. CD26 expression levels in CRC patients with distant metastasis were significantly higher than those in non-metastatic. High expression levels of CD26 were significantly associated with advanced tumour staging. Patients with a high CD26 expression level had significantly worse overall survival than those with a lower level (p<0.001). The expression of CD26 was positively associated with clinicopathological correlation such as TNM staging, degree of differentiation and development of metastasis. A high CD26 expression level is a predictor of poor outcome after resection of CRC. CD26 may be a useful prognostic marker in patients with CRC.

Background A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), which play critical roles in gene regulation, make up only a small fraction of the genome. Furthermore, cell type-specific CREs contain a large proportion of complex disease heritability. Results We evaluate genomic deep learning models in chromatin accessibility regions with varying degrees of cell type specificity. We assess two modeling directions in the field: general purpose models trained across thousands of outputs (cell types and epigenetic marks) and models tailored to specific tissues and tasks. We find that the accuracy of genomic deep learning models, including two state-of-the-art general purpose models―Enformer and Sei―varies across the genome and is reduced in cell type-specific accessible regions. Using accessibility models trained on cell types from specific tissues, we find that increasing model capacity to learn cell type-specific regulatory syntax―through single-task learning or high capacity multi-task models―can improve performance in cell type-specific accessible regions. We also observe that improving reference sequence predictions does not consistently improve variant effect predictions, indicating that novel strategies are needed to improve performance on variants. Conclusions Our results provide a new perspective on the performance of genomic deep learning models, showing that performance varies across the genome and is particularly reduced in cell type-specific accessible regions. We also identify strategies to maximize performance in cell type-specific accessible regions.

The overall prognosis of colorectal cancer (CRC) patients is unsatisfactory due to cancer metastasis after operation. This study aims to investigate the clinical significance of plasma osteopontin (OPN) levels as minimally invasive, predictive, and surrogate biomarkers for prognosis of CRC patients. This randomized study design consists of pre-operative and post-operative plasma samples from a total of 79 patients. We determined plasma levels of OPN by ELISA and examined their correlation with the clinicopathological parameters of CRC patients. The effects of endogenous and exogenous OPN on CRC metastasis were investigated by examination of the effect on regulators of epithelial to messenchymal transition and migration assay. Our findings demonstrated for the first time the clinical correlation of plasma OPN with metastasis of CRC patients. High post-operative plasma OPN level (>153.02 ng/ml) associated with development of metastasis after curative resection (p<0.001). Moreover, post-operative plasma OPN level correlated with disease-free survival of CRC patients (p=0.009) and was an independent factor for predicting development of metastasis in CRC patients after curative resection (p=0.036). Our in vitro model showed that OPN ectopic expression induced DLD1 cell migration through Snail and Twist1 overexpression and E-cadherin repression, and secretory OPN level enhanced cell migration. The results of the current study suggest that post-operative plasma OPN correlated with post-operative metastasis, suggesting that it is a potential non-invasive biomarker for the development of future metastasis in CRC patients. In addition, OPN was shown to be involved in the metastatic process and thus inhibition of OPN is a potential therapeutic approach to treat CRC patients.

Background Immune checkpoint inhibitors (ICIs) are widely used for cancer therapy and are associated with immune‐related adverse events (irAEs) in various organ systems. However, data on sinonasal irAEs remain limited. This study investigates the association between ICI therapy and sinonasal conditions, including chronic rhinosinusitis (CRS) and nasal polyps, using a national health database. Methods This retrospective cohort study utilized the TriNetX US Network to analyze adults diagnosed with malignant neoplasms for which ICIs are an accepted treatment option. Patients treated with FDA‐approved ICIs (pembrolizumab, nivolumab, cemiplimab, atezolizumab, durvalumab, avelumab, or ipilimumab) were compared to those not receiving ICIs. Exclusion criteria included sinonasal neoplasms and prior sinus surgery. Propensity score matching on age, race, sex, and asthma diagnosis was performed. Outcomes included first‐time diagnoses of CRS, nasal polyps, and cardinal symptoms of CRS. Subgroup analyses by ICI mechanism of action and a post hoc analysis of all‐cause mortality were conducted. Results ICI therapy was associated with a decreased likelihood of CRS diagnosis (OR 0.90, 95% CI 0.85–0.96), nasal polyp diagnosis (OR 0.65, 95% CI 0.51–0.83), and facial pain (OR 0.74, 95% CI 0.56–0.99). Conversely, patients receiving ICIs had an increased likelihood of anosmia/parosmia or parageusia (OR 1.86, 95% CI 1.68–2.07), and rhinorrhea (OR 1.16, 95% CI 1.10–1.22). Subgroup analyses supported these findings across different ICI categories. Risk of mortality was higher among ICI‐treated patients (HR 4.09, 95% CI 4.02–4.16). Conclusion This is the first propensity‐matched study to evaluate the relationship between ICI therapy and sinonasal conditions, revealing a decreased risk of CRS and nasal polyps in patients undergoing ICI therapy. Future studies are needed to explore the clinical significance and mechanism of ICI‐related sinonasal symptoms. Level of Evidence 3.

Background Biomass valorization has been suggested as a sustainable alternative to petroleum-based energy and commodities. In this context, the copper radical oxidases (CROs) from Auxiliary Activity Family 5/Subfamily 2 (AA5_2) are attractive biocatalysts for the selective oxidation of primary alcohols to aldehydes. Originally defined by the archetypal galactose 6-oxidase from Fusarium graminearum, fungal AA5_2 members have recently been shown to comprise a wide range of specificities for aromatic, aliphatic and furan-based alcohols. This suggests a broader substrate scope of native CROs for applications. However, only 10% of the annotated AA5_2 members have been characterized to date. Results Here, we define two homologues from the filamentous fungi Fusarium graminearum and F. oxysporum as predominant aryl alcohol oxidases (AAOs) through recombinant production in Pichia pastoris, detailed kinetic characterization, and enzyme product analysis. Despite possessing generally similar active-site architectures to the archetypal FgrGalOx, FgrAAO and FoxAAO have weak activity on carbohydrates, but instead efficiently oxidize specific aryl alcohols. Notably, both FgrAAO and FoxAAO oxidize hydroxymethyl furfural (HMF) directly to 5-formyl-2-furoic acid (FFCA), and desymmetrize the bioproduct glycerol to the uncommon L-isomer of glyceraldehyde. Conclusions This work expands understanding of the catalytic diversity of CRO from AA5_2 to include unique representatives from Fusarium species that depart from the well-known galactose 6-oxidase activity of this family. Detailed enzymological analysis highlights the potential biotechnological applications of these orthologs in the production of renewable plastic polymer precursors and other chemicals.

To provide quantitative evidence for systematically prioritising individuals for full formal cardiovascular disease (CVD) risk assessment using primary care records with a novel tool (eHEART) with age- and sex- specific risk thresholds. eHEART was derived using landmark Cox models for incident CVD with repeated measures of conventional CVD risk predictors in 1,642,498 individuals from the Clinical Practice Research Datalink. Using 119,137 individuals from UK Biobank, we modelled the implications of initiating guideline-recommended statin therapy using eHEART with age- and sex-specific prioritisation thresholds corresponding to 5% false negative rates to prioritise adults aged 40-69 years in a population in England for invitation to a formal CVD risk assessment. Formal CVD risk assessment on all adults would identify 76% and 49% of future CVD events amongst men and women respectively, and 93 (95% CI: 90, 95) men and 279 (95% CI: 259, 297) women would need to be screened (NNS) to prevent one CVD event. In contrast, if eHEART was first used to prioritise individuals for formal CVD risk assessment, we would identify 73% and 47% of future events amongst men and women respectively, and a NNS of 75 (95% CI: 72, 77) men and 162 (95% CI: 150, 172) women. Replacing the age- and sex-specific prioritisation thresholds with a 10% threshold identify around 10% less events. The use of prioritisation tools with age- and sex-specific thresholds could lead to more efficient CVD assessment programmes with only small reductions in effectiveness at preventing new CVD events.

Objective To evaluate the CT and MRI features of pancreatic acinar cell carcinoma (pACC) and their association with patient outcome and survival. Methods This retrospective single-center study included 49 patients with pathology-proven pancreatic acinar cell carcinoma who underwent diagnostic imaging between August 1998 - September 2019. Two radiologists reviewed CT and MRI features independently. Survival was estimated using the Kaplan-Meier method, and Cox proportional-hazards regression model was used to identify factors associated with survival. Results pACC tended to present as a solid (31/49, 63.3%) pancreatic head mass (26/49, 53.1%) with ill-defined margins (32/49, 65.3%) and median maximal diameter of 4.1 cm (IQR, 2.9–6.2). Majority of lesions were hypo- or isodense (38/49, 77.6%) compared to normal pancreatic parenchyma, with heterogenous (39/49, 79.6%) enhancement pattern. Biliary ductal dilatation was uncommon, with pancreatic ductal dilatation in 22.4% (11/49) and common bile duct dilatation in 14.3% (7/49). Intralesional calcifications were seen in 6.1% (3/49). Metastasis was present in 71.4% (35/49) of patients at the time of diagnosis. On MRI, 88.9% (16/18) demonstrated diffusion restriction and 59.1% (13/22) with heterogenous enhancement. On multivariate analysis, the imaging presence of T1 hyperintensity ( p  = 0.02), hypoattenuating necrotic components ( p  = 0.02), and splenic vein invasion ( p  = 0.04) were associated with worse survival. Conclusion Pancreatic acinar cell carcinoma is a rare pancreatic neoplasm that often presents as a large ill-defined heterogeneously enhancing mass without biliary ductal dilation. T1 hyperintensity, presence of hypoattenuating necrotic components, and splenic vein invasion were independent predictors of survival.

Crew members are at an increased risk for exposure to and infection by pathogenic microbes during spaceflight. Therefore, it is imperative to characterize the species that are able to colonize and persist on spacecraft, how those organisms change in abundance and distribution over time, and their genotypic potential for and phenotypic expression of pathogenic traits (i.e., whether they encode for or exhibit traits associated with antibiotic resistance and/or virulence). Here, we describe a novel species of Microbacterium collected from the crew quarters on the International Space Station (ISS), 1F8SW-P5 T , for which we propose the name Microbacterium mcarthurae . M. mcarthurae was found to be distributed throughout the ISS with an increase in relative abundance over time. Additionally, this bacterium exhibits a unique antibiotic resistance phenotype that was not predicted from whole-genome sequencing, as well as increased virulence, suggesting the need for the identification of previously undescribed antimicrobial resistance genes and monitoring/mitigation during spaceflight.