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Methylcobalamin-containing nanofiber sheets have better neuroprotective effects than small intestinal submucosa sheets

Tumor microenvironment-responsive engineered hybrid nanomedicine for photodynamic-immunotherapy via multi-pronged amplification of reactive oxygen species

GYY4137 ameliorates blood brain barrier damage by inhibiting autophagy mediated occludin degradation in cardiac arrest and resuscitation

Swarm navigation of cyborg-insects in unknown obstructed soft terrain

Investigation of mechanical behavior of slag-stabilized rammed earth reinforced by carpet polyacrylic yarn waste

Anti-aliased metasurfaces beyond the Nyquist limit

Bioinformatics approaches to multi-omics analysis of the potential of CDKN2A as a biomarker and therapeutic target for uterine corpus endometrial carcinoma

Development of nucleus-targeted histone-tail-based photoaffinity probes to profile the epigenetic interactome in native cells

Regulation of innate immune response by miRNAs up-regulated in Stevens-Johnson syndrome with severe ocular complications

MAT2A inhibitor AG-270/S095033 in patients with advanced malignancies: a phase I trial

Predicting largest expected aftershock ground motions using automated machine learning (AutoML)-based scheme

Observation of quantum strong Mpemba effect

Prediction of ECG signals from ballistocardiography using deep learning for the unconstrained measurement of heartbeat intervals

Cooperative condensation of RNA-DIRECTED DNA METHYLATION 16 splicing isoforms enhances heat tolerance in Arabidopsis

Application of urinary peptide-biomarkers in trauma patients as a predictive tool for prognostic assessment, treatment and intervention timing

AbstractTreatment of severely injured patients represents a major challenge, in part due to the unpredictable risk of major adverse events, including death. Preemptive personalized treatment aimed at preventing these events is a crucial objective of patient management; however, the currently available scoring systems provide only moderate guidance. Biomarkers from proteomics/peptidomics studies hold promise for improving the current situation, ultimately enabling precision medicine based on individual molecular profiles. To test the hypothesis that peptide biomarkers could predict patient outcomes in severely injured patients, we initiated a pilot study involving consecutive urine sampling (on days 0, 2, 5, 10, and 14) and subsequent peptidome analysis using capillary electrophoresis coupled to mass spectrometry (CE-MS) of 14 severely injured patients and two additional intensive care unit patients. The urine peptidomes of these patients were compared to those of age- and sex-matched controls. Moreover, previously established urinary peptide-based classifiers, CKD273, AKI204, and Cov50, were applied to the obtained peptidome data, and the association of the classifier’s scores with a combined endpoint (death and/or kidney failure and/or respiratory insufficiency) was investigated. CE-MS peptidome analysis identified 191 significantly altered peptides in severely injured patients. A consistent increase in the abundance of peptides from A1AT, AHSG, and HBA1 was observed, while peptides derived from PIGR and UROM were consistently decreased. Most of the significant peptides (adjusted p < 0.05) were from COL1A1, and most were reduced in abundance. Two of the previously defined and validated peptidomic classifiers, CKD273 and AKI204, showed significant associations with the combined endpoint, which was not observed for the routine scores generally applied in the clinics. This prospective pilot study confirmed the hypothesis that urinary peptides provide information on patient outcomes and may guide personalized interventions in severely injured patients based on individual molecular changes. The results obtained allow the planning of a well-powered prospective trial investigating the value of urinary peptides in this context in more detail.

Publisher Correction: A metagenomic catalogue of the ruminant gut archaeome

Plasma-assisted MnO surface engineered activated carbon felt for enhanced heavy metal adsorption

Selectively expressed RNA molecules as a versatile tool for functionalized cell targeting

AbstractTargeting of diseased cells is one of the most urgently needed prerequisites for a next generation of potent pharmaceuticals. Different approaches pursued fail mainly due to a lack of specific surface markers. Developing an RNA-based methodology, we can now ensure precise cell targeting combined with selective expression of effector proteins for therapy, diagnostics or cell steering. The specific combination of the molecular properties of antisense technology and mRNA therapy with functional RNA secondary structures allowed us to develop selectively expressed RNA molecules for medical applications. These seRNAs remain inactive in non-target cells and induce translation by partial degradation only in preselected cell types of interest. Cell specificity and type of functionalization are easily adaptable based on a modular system. In proof-of-concept studies we use seRNAs as platform technology for highly selective cell targeting. We effectively treat breast tumor cell clusters in mixed cell systems and shrink early U87 glioblastoma cell clusters in the brain of male mice without detectable side effects. Our data open up potential avenues for various therapeutic applications.

Patients with dementia with Lewy bodies display a signature alteration of their cognitive connectome

AbstractCognition plays a central role in the diagnosis and characterization of dementia with Lewy bodies (DLB). However, the complex associations among cognitive deficits in different domains in DLB are largely unknown. To characterize these associations, we investigated and compared the cognitive connectome of DLB patients, healthy controls (HC), and Alzheimer’s disease patients (AD). We obtained data from the National Alzheimer’s Coordinating Center. We built cognitive connectomes for DLB (n = 104), HC (n = 3703), and AD (n = 1985) using correlations among 24 cognitive measures mapping multiple cognitive domains. Connectomes were compared using global and nodal graph measures of centrality, integration, and segregation. For global measures, DLB showed a higher global efficiency (integration) and lower transitivity (segregation) than HC and AD. For nodal measures, DLB showed higher global efficiency in most measures, higher participation (centrality) in free-recall memory, processing speed/attention, and executive measures, and lower local efficiency (segregation) than HC. Compared with AD, DLB showed lower nodal strength and local efficiency, especially in memory consolidation. The cognitive connectome of DLB shows a loss of segregation, leading to a loss of cognitive specialization. This study provides the data to advance the understanding of cognitive impairment and clinical phenotype in DLB, with implications for differential diagnosis.

A global analysis of dairy consumption and incident cardiovascular disease