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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
Energy yield framework to simulate thin film CIGS solar cells and analyze limitations of the technology
AbstractThis study presents a comprehensive evaluation of Copper Indium Gallium Selenide (CIGS) solar technology, benchmarked against crystalline silicon (c-Si) PERC PV technology. Utilizing a newly developed energy yield model, we analyzed the performance of CIGS in various environmental scenarios, emphasizing its behavior in low-light conditions and under different temperature regimes. The model demonstrated high accuracy with improved error metrics of normalized mean bias error (nMBE) ~ 1% and normalized root mean square error (nRMSE) of ~ 8%–20% in simulating rack mounted setup and integrated PV systems. Key findings reveal that the CIGS technology, while slightly underperforming in integrated, low-irradiance setups, shows comparable or superior performance to c-Si PERC technology in high-irradiance and high-temperature conditions. A significant focus of the study was on the low-light performance of CIGS, where it exhibited notable voltage losses. Our research highlights the importance of reducing the diode ideality factor for enhancing CIGS power conversion efficiency, particularly In low-light conditions. These insights provide a pathway for future research and technological improvements, emphasizing defect engineering, passivation strategies to advance the understanding and application of the CIGS technology.
Aurophilic interaction-based aggregation of gem-digold(I) aryls towards high spin-orbit coupling and strong phosphorescence
UHPLC-MS/MS based comprehensive phenolic profiling, antimicrobial and antioxidant activities of Indian Rhodomyrtus tomentosa fruits
Steroid hormone-induced wingless ligands tune female intestinal size in Drosophila
Abstract Female reproduction comes at great expense to energy metabolism compensated by extensive organ adaptations including intestinal size. Upon mating, endocrine signals orchestrate a 30% net increase of absorptive epithelium. Mating increases production of the steroid hormone Ecdysone released by the Drosophila ovaries that stimulates intestinal stem cell (ISC) divisions. Here, we uncover the transcription factor crooked legs (crol) as an intraepithelial coordinator of Ecdysone-induced ISC mitosis. For the precise investigation of non-autonomous factors on ISC behaviour, we establish Rapport, a spatiotemporally-controlled dual expression and tracing system for the analysis of paracrine genetic manipulation while tracing ISC behaviour. Rapport tracing reveals that Ecdysone-induced Crol controls mitogenic Wnt/Wg-ligand expression from epithelial enterocytes activating ISC mitosis. Paracrine Wg stimulation is counterbalanced by Crol-repression of string/CDC25 and CyclinB autonomously in ISC. Rapport-based ISC tumours confirm paracrine stimulation through the Ecdysone-Crol-Wg axis on mitotic behaviour, whereas the autonomous anti-proliferative role of Crol in ISC is conserved in models of colorectal cancer. Finally, mathematical modelling corroborates increasing enterocyte numbers and Wnt/Wg-degradation to set a stable post-mating intestinal size. Together, our findings provide insights into the complex endocrine growth control mechanisms during mating-induced adaptations and might help untangling pleiotropic hormonal effects observed in gastrointestinal tumorigenesis.
Novel approach to enhance the efficiency of mortar against radiations by co-incorporation of lead and boron compounds with calcium chloride
AbstractFabrication of heavy density mortar using aggregates reinforced with available solid inorganic chemical additives is of a great importance as a protective layer to mitigate radiations in nuclear facilities. The effect of lead oxide and borax decahydrate on the hydration kinetics was evaluated by determining setting time, leachability and compressive strength. To speed up the reaction, 0.5% calcium chloride was added to all formulations, and then the results were compared to their blank counterparts. Once, the optimal compositions were explored, another batch of mortar were designed to increase efficiency against radioactive sources with different photon energies. After 28 days, bulk density, linear attenuation coefficient, half-value layer, tenth-value layer, and mean-free path in the field of 137Cs and51Co were considered. Similarly, macroscopic effective removal cross-section was evaluated using radioactive source-239Pu-α-9Be. According to the previous literature, adding 0.2% PbO to cement is the optimal ratio without affecting hydration kinetics and phase composition. The study explored that, co-incorporation of PbO with 0.5% CaCl2 increases the ratio to 2.5%, while enhancing physico-mechanical and radiological characteristics against radioactive sources. Also, formulation incorporating 0.5% borax with 0.5% CaCl2 had superior attenuation against neutrons compared to other competitors.