Browse Articles

Correction for Zhu et al., Bioinspired nanogels as cell-free DNA trapping and scavenging organelles for rheumatoid arthritis treatment

Carboxylate and coordination influence on the formation of an active RuV Oxo species

Abstract Understanding the structure of Ru(V)-oxo species is crucial for designing novel catalysts for sustainable energy applications, such as water splitting for green hydrogen production. This study reports the EPR detection of a Ru(V)-oxo intermediate stabilized by terpyridine and phenanthroline carboxylate ligands. The interaction between the carboxylate group and the ruthenium center, along with PCET-dependent hemilability under oxidative conditions, plays a critical role in achieving the high-valent state. Subtle changes in the coordination environment around the central metal also proved to be essential. Low-temperature NMR, high-resolution mass spectrometry, UV–Vis spectroscopy, and density functional theory calculations support these findings.

The power spectrum and functional connectivity characteristics of resting-state EEG in patients with generalized anxiety disorder

Abstract Recent studies have suggested a relationship between abnormal neurophysiological functions and generalized anxiety disorder (GAD). However, studies on its electrophysiological characteristics, such as its power spectrum and functional connectivity are relatively few and scattered than those on other mental disorders (e.g., depression, ADHD, etc.). The present study aims to reveal the multidimensional electrophysiological characteristics of GAD via comparative analysis of electroencephalogram (EEG) data between GAD patients and healthy controls. Specifically, resting-state EEG, with a duration of 10 min, was recorded from 98 GAD patients and 92 healthy control participants. The electrophysiological characteristics, including the power spectrum, alpha asymmetry, and functional connectivity, were extracted and compared between the two groups. The results revealed significantly increased beta-band activity; decreased ipsilateral fronto-temporal and parieto-temporal functional connectivities in the lower frequency bands (theta–beta band); as well as decreased frontal‒parietal and frontal‒occipital connectivities in the higher frequency bands (beta‒gamma band) in GAD patients. Additionally, alpha asymmetry analysis revealed a significantly greater rightward temporal alpha asymmetry in GAD patients. These findings suggest the existence of significant EEG characteristics in patients with GAD, supporting previous conclusions regarding abnormal neurophysiological functions in psychiatric disorders and potentially leading to the identification of biomarkers for clinical diagnosis.

SGLT2 inhibitors reduce the risk of renal failure in CKD stage 5 patients with Type 2 DM

Two-factor authentication for intellectual property transactions based on improved zero-knowledge proof

Study on the mechanism of decomposition of methane hydrate by the compound inhibitor

Predictors of anemia among HIV-infected children in Ethiopia: systematic review and meta-analysis

Water agriculture nexus a system dynamics approach for the next three decades

The Rhizophagus irregularis permease RiFTR1 functions without a ferroxidase partner for reductive iron transport

Abstract The contribution of arbuscular mycorrhizal fungi (AM fungi) to plant iron (Fe) acquisition has been demonstrated in several studies. A previous investigation revealed that the AM fungus Rhizophagus irregularis utilizes a high-affinity reductive pathway for Fe uptake, mediated by the Fe transporter RiFTR1. In this study, we used a genome-wide approach in R. irregularis to find genes encoding ferroxidases of the multicopper oxidase (MCO) gene family in an attempt to identify the ferroxidase partner of RiFTR1. Nine genes putatively encoding MCOs (RiMCO1-9) were identified. Yeast complementation assays demonstrated that RiMCO1 and RiMCO3 can function as ferroxidases, suggesting their involvement in the reductive Fe uptake pathway. Surprisingly, RiFTR1 was capable of transporting Fe in yeast without a ferroxidase partner, resembling the Fe transport mechanism of plant IRT1-like systems. RiFTR1 exhibited increase expression in arbuscules. Overexpression of RiFTR1 in Medicago truncatula roots led to enhanced mycorrhizal colonization and arbuscule abundance, highlighting the significance of Fe for AM symbiosis.

Correction to Supporting Information for Guo et al., Structural basis for coupling of the WASH subunit FAM21 with the endosomal SNX27–Retromer complex

Metabolic profiling and transcriptome analysis of Sinomenium acutum provide insights into the biosynthesis of structurally diverse benzylisoquinoline alkaloids

Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury

Production of protein-rich fungal biomass from pistachio dehulling waste using edible Neurospora intermedia

Abstract Pistachio dehulling waste, known as Pistachio byproduct mixture (PBM), is a valuable resource that is often overlooked. An effective sustainable approach involves utilizing this agricultural waste through a fermentation process using edible filamentous fungi, demonstrating potential applications in nutrition and animal feed. The focus of this study was on converting PBM extract obtained from a hot water extraction pre-treatment into a protein-rich fungal biomass of Neurospora intermedia. The optimal conditions for growth were achieved at 72 h, pH 5.5, and 30 °C which are achieved by one-factor-at-a-time approach (OFAT), resulting in 6.7 g/L of dried fungal biomass, with a protein content of 20.4%. The conversion efficiency, expressed as grams of fungal biomass per gram of initial Total COD, was 0.37 g/g, highlighting the significant potential of PBM extract with high COD levels and low sugar content for fermentation processes. Additionally, an investigation was carried out to assess the impact of inoculation method, culture adaptation, COD/N ratio, and pH control on fungal biomass growth during cultivation. The results of optimal conditions with response of fungal biomass growth showed production of 0.44, 0.45, and 0.49 g of fungal biomass per gram of initial total COD, with protein contents of 20.2%, 27.1%, and 18.6%, respectively, leading to improved fungal biomass yield. The resulting protein-rich fungal biomass with a focus on the biorefinery platform to complete the value-added cycle, holds promise for applications in various sectors including food, animal feed, biochemical, and biomaterial industries.

A nomogram for predicting T315I-free survival in chronic phase chronic myeloid leukemia patients: a multicenter retrospective study

Spatiotemporal evolution effects of habitat quality with the conservation policies in the Upper Yangtze River, China

Author Correction: The failure mechanism of the Baishi landslide in Beichuan County, Sichuan, China

Fuzzy and crisp computational analysis of certain graphs structures via machine learning techniques

AI protocol for retrieving protein dynamic structures from two-dimensional infrared spectra

Understanding the dynamic evolution of protein structures is crucial for uncovering their biological functions. Yet, real-time prediction of these dynamic structures remains a significant challenge. Two-dimensional infrared (2DIR) spectroscopy is a powerful tool for analyzing protein dynamics. However, translating its complex, low-dimensional signals into detailed three-dimensional structures is a daunting task. In this study, we introduce a machine learning-based approach that accurately predicts dynamic three-dimensional protein structures from 2DIR descriptors. Our method establishes a robust “spectrum-structure” relationship, enabling the recovery of three-dimensional structures across a wide variety of proteins. It demonstrates broad applicability in predicting dynamic structures along different protein folding trajectories, spanning timescales from microseconds to milliseconds. This approach also shows promise in identifying the structures of previously uncharacterized proteins based solely on their spectral descriptors. The integration of AI with 2DIR spectroscopy offers insights and represents a significant advancement in the real-time analysis of dynamic protein structures.

Catalytic reduction of SO2 to elemental sulfur with methane over CuOx/γ-Al2O3 catalysts

Applying deep learning and the ecological home range concept to document the spatial distribution of Atlantic salmon parr (Salmo salar L.) in experimental tanks

Abstract Measuring and monitoring fish welfare in aquaculture research relies on the use of outcome- (biotic) and input-based (e.g., abiotic) welfare indicators (WIs). Incorporating behavioural auditing into this toolbox can sometimes be challenging because sourcing quantitative data is often labour intensive and it can be a time-consuming process. Digitalization of this process via the use of computer vision and artificial intelligence can help automate and streamline the procedure, help gather continuous quantitative data and help process optimisation and assist in decision-making. The tool introduced in this study (1) adapts the DeepLabCut framework, based on computer vision and machine learning, to obtain pose estimation of Atlantic salmon parr under replicated experimental conditions, (2) quantifies the spatial distribution of the fish through a toolbox of metrics inspired by the ecological concepts home range and core area, and (3) applies it to inspect behavioural variability in and around feeding. This proof of concept study demonstrates the potential of our methodology for automating the analysis of fish behaviour in relation to home range and core area, including fish detection, spatial distribution and the variations within and between tanks. The impact of feeding on these patterns is also briefly outlined, using 5 days of experimental data as a demonstrative case study. This approach can provide stakeholders with valuable information on how the fish use their rearing environment in small-scale experimental settings and can be used for the further development of technologies for measuring and monitoring the behaviour of fish in research settings in future studies.