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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
High-efficiency perovskite light-emitting diodes enabled by introducing a LiF modification layer
Surface defect passivation and exciton regulation remain a critical challenge in perovskite light-emitting diodes (PeLEDs). Organic molecules are widely used to solve these issues. However, the high sensitivity of perovskite films to the molecular groups and concentration limited their commercialization applications. Here, we develop a facile and low-cost passivation strategy that is compatible with traditional fabrication processes of PeLEDs. By depositing a thin LiF layer using vacuum thermal evaporation technique, the defects of perovskite film are effectively passivated. Simultaneously, the thin LiF layer protects the excitons formed in perovskite from quenching by the electron-transport layer. Due to the synergistic effect of LiF, an efficient green PeLED is achieved with a maximum current efficiency of 47.0 cd/A and luminance of 30 280 cd/m2, representing respective 65% and 166% increase than that of the control device without LiF modification layer (28.5 cd/A and 11 380 cd/m2). Our work provides an effective strategy and deep understanding of the interface regulation for achieving high-performance PeLEDs.
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
Optoelectronic synapse based on the Bi2O2Se/Cs3Cu2I5 heterojunction for neuromorphic computing
In this work, we report an optoelectronic synapse based on the Bi2O2Se/Cs3Cu2I5 heterojunction formed by consequently depositing Bi2O2Se and Cs3Cu2I5 thin films by chemical vapor deposition methods. The fabricated Au/Bi2O2Se/Cs3Cu2I5/Au devices exhibit the light-tunable photoresponse under visible light illumination. Synaptic functions including paired-pulse facilitation, the transition from short-term plasticity to long-term plasticity, associative learning and optical encoding, are conveniently reproduced on one single synaptic device by utilizing the light-tunable evolution of photocurrent. Furthermore, the front-end image preprocessing to enhance the accuracy and efficiency of image recognition was demonstrated based on the constructed device array (5 × 7). This indicates the potential application of Bi2O2Se/Cs3Cu2I5 optoelectronic synapses for the forthcoming neuromorphic computing.
Predicting largest expected aftershock ground motions using automated machine learning (AutoML)-based scheme
Observation of quantum strong Mpemba effect
Perspectives on various-temperature stability of p-i-n perovskite solar cells
Despite the significant breakthroughs in photoelectric conversion efficiency achieved by perovskite solar cells, their temperature stability remains a significant bottleneck to commercialization. Temperature fluctuations typically lead to structural changes and phase transformations in perovskites. Additionally, thermal stress can facilitate ion migration within the perovskite material, resulting in interface charge accumulation and electrode corrosion, which ultimately undermines the performance of perovskite devices. This brief perspective systematically discusses the mechanisms behind device performance degradation under temperature cycling conditions and presents potential improvement strategies to address these issues. Finally, we elaborate on the future challenges that must be overcome for the successful commercialization of these devices.
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
3D metamaterial broadband microwave absorber covered by structural topology-based pixelated color-changing layer
With rapid advancement in ISR (intelligence, surveillance, and reconnaissance), the demand for multispectral stealth technology has become urgent. In the field of radar stealth, 3D metamaterial absorbers have garnered significant attention due to their ultra-wideband microwave absorption. However, they face the challenge of restricted multispectral-compatible stealth capabilities, elevating the risk of being detected under ISR technology. In this study, we propose a solution by covering the absorber with a structural topology-based pixelated color-changing layer (STPCL), providing environmental camouflage and enhancing absorption intensity. Multiwall carbon nanotubes/spherical carbonyl iron/silicone rubber composites and thermochromic capsules/polydimethylsiloxane composites are used to fabricate the absorber and the STPCL, respectively. The STPCL not only provides adaptive camouflage in grassland and desert environments but also increases the characteristic dimensions to tune the absorption peaks and incorporates a grading circuit with stepped impedance to enhance impedance matching. As a result, the absorption bandwidth is slightly extended from 3.28–40 to 2.87–40 GHz, while the average reflection loss is improved from −13.55 to −16.83 dB. This approach demonstrates the potential to enhance the functionality and adaptability of metamaterial microwave absorbers in diverse operational environments.
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.