Browse Articles

Identification of common genes and biomarkers between Dermatomyositis and rheumatoid arthritis through integrated bioinformatics

Background Dermatomyositis (DM) and rheumatoid arthritis (RA) share immuno-inflammatory features, yet mechanisms underlying their comorbidity remain unclear. We aimed to define shared molecular mechanisms across gene regulatory networks and the immune microenvironment using integrated multi-omics and machine-learning analyses. Methods Microarray datasets for RA (GSE55235, GSE55457, GSE12021) and DM were retrieved from GEO. RA datasets were merged and batch-corrected with ComBat. Differentially expressed genes (DEGs) were identified using limma; key modules were derived by weighted gene co-expression network analysis (WGCNA). Intersected DEGs–module genes underwent GO/KEGG enrichment. Core genes were prioritised by LASSO regression and random-forest modelling and evaluated in external cohorts. Immune landscape was estimated with CIBERSORT and immune subpopulations profiled by single-sample GSEA. Single-cell RNA-seq (GSE159117) mapped cell-type–specific expression of core genes and inferred ligand–receptor networks. Results We identified 780 DEGs in RA and 739 in DM. Intersecting DEGs with WGCNA modules yielded 47 candidates enriched for IL-17, Toll-like receptor and chemokine signalling (all P  < 0.05). Four core genes (JUNB, NRGN, HCP5, RARRES3) were prioritised; HCP5 and RARRES3 showed significant differential expression and diagnostic performance in external datasets (AUC 0.634–0.846). CIBERSORT indicated enrichment of activated CD4 + memory T cells and a shift in macrophage polarisation with increased M2 signatures in both diseases. Core genes were dynamically associated with M1/M2 polarisation and T-cell subpopulations ( P  < 0.05). Single-cell analysis localised core gene expression to NK cells, monocytes and T/B cells, and highlighted inflammatory ligand–receptor interactions. Conclusions Integrative, ML-assisted transcriptomics reveals convergent RA–DM programmes centred on IL-17, TLR and chemokine pathways with remodelling of the immune microenvironment. HCP5 and RARRES3 emerge as reproducible, externally supported candidates with diagnostic potential and plausible links to macrophage polarisation and T-cell states. These findings nominate testable biomarkers and pathways for validation and provide a rationale for pathway-guided, cross-disease studies of RA–DM comorbidity.

Mechanistic insights into modification of clay minerals by detergent-derived surfactants and their impact on petroleum hydrocarbon uptake

Square integrable solutions and stability of a second-order stochastic integro-differential equation

Cost-effective and sustainable operation of microgrids using Improved Whale Optimization Algorithm

Abstract The global transition to sustainable energy demands efficient integration of renewable resources and resilient operation of microgrids (MGs). This study aims to develop a cost-effective and sustainable Energy Management System (EMS) for MGs operating in both grid-connected and islanded modes. The inherent variability of renewable generation and fluctuating grid prices pose significant challenges to maintaining supply-demand balance. To address this, the proposed EMS employs an Improved Whale Optimization Algorithm (IWOA), incorporating a nonlinear swimming parameter and Lévy flight mechanism to prevent premature convergence. Simulation results on a benchmark low-voltage MG reveal that IWOA achieves a 39.66% reduction in operational costs compared to standard algorithms, while maintaining competitive runtime of 4.2 min. Furthermore, a dynamic energy trading strategy is integrated to optimize real-time interactions with the main grid. The findings validate the proposed framework as a robust solution for enhancing the economic and environmental performance of modern power systems.

Correction: The collaborative evolution of trust, information flow, and social cooperation: a study on network stability based on dynamic game models

Rapid synergistic cloud point extraction of copper in environmental samples with greenness and toxicity evaluation using a triazole based Schiff base

Abstract Herein, a novel copper-triazole derivative Schiff base nanocomplex (HIT-Cu 2+ ) was obtained via the reaction of the 3-(2-(4-amino-5-mercapto-4 H-1,2,4-triazol-3-yl)hydrazineylidene)indolin-2-one (HIT) Schiff base with CuCl 2 .6H 2 O. The non-ionic surfactant Triton X-114 (TX-114) was used as the extractant. The HIT, HIT-Cu 2+ , and HIT-Cu 2+ in the organic layer were characterized by several techniques, including CHNS elemental analysis, ultraviolet-visible spectroscopy (UV–Vis), Fourier transform infrared spectroscopy (FT-IR), and transmission electron microscopy (TEM). The TEM results revealed the formation of the HIT-Cu 2+ nanocomplex, with a particle size ranging from 13 to 25 nm. Moreover, an improved preconcentration method, named rapidly synergistic cloud point extraction (RS-CPE), was established for Cu 2+ preconcentration and determination to overcome the issues investigated in CPE. Decanol acted as a cloud point revulsant and synergistic reagent, lowering the cloud point temperature (CPT) of TX-114, so that CPE could be done at room temperature without heating. Compared with traditional CPE (about 30 min for heating, incubation and cooling), RS-CPE was accomplished in 1 min with considerably high extraction efficiency. The improved extraction technique, RS-CPE, was combined with ICP-OES to improve the analytical performance and expand the application of ICP-OES determination. Various parameters that influence the Cu 2+ removal efficiency (R, %) utilizing HIT Schiff base were investigated, including the solution’s pH and volume, the concentration of HIT and Cu 2+ , type of surfactant, TX-114 concentration, equilibrium temperature and time, interfering ions, and centrifugation time and rate. At optimum conditions, the Cu 2+ linear range, the correlation coefficient, the limit of detection (LOD), and the limit of quantification (LOQ) were 0.5–5 µg.mL − 1 , 0.9999, 0.018, and 0.054 µg/L, respectively. The investigated RS-CPE/ICP-OES approach was applied to real water and pharmaceutical samples, achieving recoveries higher than 97% with a preconcentration factor of 125. The HIT-Cu 2+ CPE mechanism in the organic layer of TX-114 is elucidated. The greenness of the methods was evaluated using two recent methods: the Analytical Greenness (AGREE) calculator and the Blue Applicability Green Index (BAGI), which produced results in the ranges of 0.64–0.71 and 60-67.5, respectively. These results are strongly aligned with both green ideals and environmentally friendly practices. The predicted toxicity of HIT and HIT-Cu 2+ nanocomplex was evaluated using PROTOX 3 software.

Determination of hydrocortisone and cortisone in artificial saliva by spray assisted fine droplet formation liquid phase microextraction coupled to LC–MS/MS

New biphenylvinylanthracene-based polymers for organic electronics applications: effect of the acceptor group on optoelectronic properties

Forest loss and landscape pattern change cause watersheds to release more young water

The hydrological functions of forests are well recognized, but their influence on water storage and release dynamics remains poorly quantified. The fraction of young water ( F yw )—the proportion of streamflow younger than 2 to 3 mo—serves as an integrative indicator of a watershed’s capacity to retain and release precipitation. Here, by analyzing F yw across 657 watersheds worldwide, we found that forest cover exhibited a significant negative relationship with F yw . The causality was further corroborated through a meta-analysis of postdeforestation F yw trends, confirming that forest loss accelerates the conversion of recent precipitation into streamflow. This effect was most pronounced in watersheds with shallow groundwater, highlighting the role of forests in regulating rapid, near-surface flowpaths. Beyond total forest cover, we found that forest landscape patterns also exerted influences: A lower proportion of forest edge was associated with higher F yw , but only in sparsely forested watersheds ( ≤ ∼ 40% forest cover), where the edge-enhanced evapotranspiration was most pronounced. This global synthesis not only reinforces the hydrological value of forest conservation and restoration but also highlights that deliberate planning of forest landscape patterns can help mitigate the hydrological consequences of forest loss. Together, these findings demonstrate that integrating forest protection with forest landscape planning is essential for sustaining hydrological functions.

Correction: Assessing the potential of bacterial signal peptides for radiopharmaceutical applications

Sustainable dual-drug analysis: a synchronous spectrofluorimetric approach with integrated greenness and whiteness metrics for favipiravir and levofloxacin

Abstract Innovative and sustainable synchronous spectrofluorimetric techniques were developed for the simultaneous assessment of favipiravir (FVP) and levofloxacin (LEV). Some COVID-19 treatment plans call for these drugs to be given together, so reliable approaches are needed to confirm that the studied drugs are of good quality. FVP and LEV are determined with high sensitivity in the nanogram per milliliter range, with high accuracy (recoveries of 99.34% ± 1.10 and 98.87% ± 0.44, respectively). Method validation was conducted in accordance with ICH guidelines. Moreover, several metric systems (Analytical Eco-Scale, GAPI, AGREE) are used to assess environmental sustainability, which confirms the greenness of the proposed method. Also, blueness and whiteness criteria (BAGI, RGB 12) were used to check the usefulness and analytical effectiveness of the established method. As this spectrofluorimetric method is simple, rapid, and inexpensive, it is preferred over other analytical techniques for the routine analysis of the drug combination in bulk powders and pharmaceutical formulations.

A novel width-expanding spiral microchannel for high-throughput continuous separation of bacterial-sized particles

Daily briefing: What people with no ‘mind’s eye’ can tell us about consciousness

A comparison study to assess U-Net driven volumetric versus single-slice analysis and MRI sequences with different volume coverage to detect renal sinus fat in people with and without diabetes

Abstract Monitoring the accumulation of renal sinus fat (RSF) by non-invasive magnetic resonance imaging (MRI) holds promise for assessing the risk of nephropathy in individuals with diabetes. Automatic image segmentation using dedicated U-Net models was deployed for accurate quantification of RSF content and renal parenchyma (RP) from different MRI protocols. Therefore, the accuracy of volumetric vs single-slice analysis for quantifying RP and RSF was assessed. Further, the resulting kidney structures obtained from a whole-body MR images acquired with partial kidney coverage were compared to high-resolution MRI protocol with full-kidney coverage, in people with and without diabetes. Quantification of kidney structures showed accurate estimates of both RP and RSF volume across people with different glycaemic status and imaging protocols. A systematic overestimation of the RSF-to-RP ratio was observed when using the conventional single-slice assessment, supporting the need for volumetric kidney analysis, particularly for small structures such as the RSF. Moreover, MR images with interslice-gaps were found to substantially underestimate RSF content, highlighting the need for careful evaluation and correction of estimates from small kidney structures when data are pooled from different MR imaging protocols. In summary, automatic image segmentation enabled us to determine differences in the precision of RSF content obtained using different methodological approaches and MRI sequences with different kidney coverage.

Rapid hydrothermal triggering of induced seismicity at the Coso geothermal field

Abstract The long-term producing Coso Geothermal Field (CGF) in California operates over 100 wells tapping into a reservoir characterized by an extensive fracture network, complex fluid pathways, and regular seismic activity. Understanding the interaction between seismicity and injection can shed important light on the hydrothermal characteristics of the field. Here, we analyze 15 years of local seismic and daily operational data from the CGF, identifying a strong correlation between short-term increase in seismicity rate and seasonal volumetric and temperature variations in the reinjected fluid. Furthermore, the seismic footprint during peak injection of colder fluids reveals a near-instantaneous response up to 2 km away from the injection well, too rapid for pore pressure diffusion alone. This short-term and distant response is observed to have directional preference, indicating structural or permeability anisotropy within the reservoir. Additionally, the seismic response correlates with the initial volumetric increase of colder fluids, but also with temperature decrease during stable injection periods, suggesting thermal effects alone can play an important role in triggering distant seismicity.

Ancient DNA reconstruction of Late Holocene ecosystems within the Carpathian Basin from paleo-meanders and archaeological deposits

Abstract The diverse ecology in the Carpathian Basin supported a variety of subsistence strategies throughout the Holocene, ranging from animal husbandry to the management of woodlands, grasslands, and wetlands. The earliest evidence of aquatic resource use in the region dates back to the Early Neolithic (~ 6200−5300 cal BC), with cultural practices extending into recent times. This is reflected in the numerous open-air archaeological sites widely distributed across the landscape and on the Danube meanders. However, the archaeological record, especially organic remains and fossils, may not fully capture the region’s species diversity due to degradation and scarcity, hindering the accurate reconstruction of past human-environment interactions. Recent studies have shown that ancient DNA in sediments ( seda DNA) can survive even in the absence of visible fossils, however, these studies have primarily been limited to cave-, lake- and permanently frozen sedimentary deposits. Here, we investigate two open-air archaeological sites and three paleo meander deposits of the Danube in Serbia (southeastern Europe) using seda DNA. Our analysis reveals genetic traces from past freshwater and terrestrial ecosystems and local exploitation of the migratory sturgeon species, currently extirpated from the region. We find seda DNA preserved in sediments from unsheltered archaeological contexts and explore the associated challenges that require further investigation.

Preliminary study of polyethylene microplastics disrupting energy Metabolism, redox Balance, and prefrontal cortex structure in Wistar rats

Enhanced YOLO12 with spatial pyramid pooling for real-time cotton insect detection

Abstract Effective insect detection is crucial for sustainable cotton production, yet traditional monitoring methods remain labor-intensive, inefficient, and environmentally detrimental. This study introduces Enhanced YOLO12, a novel deep learning architecture for real-time cotton insect detection. Building on the YOLO12 framework, the proposed model integrates an optimized Spatial Pyramid Pooling (SPP) module and attention-based feature extraction to improve detection accuracy while maintaining computational efficiency. To ensure robustness, we developed and evaluated multiple baseline models (standard YOLO11 and YOLO12) and custom architectures (YOLO12_Fusion, YOLO11-BRA-Net, YOLO11_CBAM, and Enhanced Hybrid YOLO12). According to the conducted experiments, Enhanced Hybrid YOLO12 achieved the best performance, achieving 0.942, 0.876, 0.945, and 0.735 in precision, recall, mAP50 and mAP50-95, respectively. It significantly outstands the results of the standard YOLO12 (0.925, 0.848, of 0.913, and 0.662). These results demonstrate that Enhanced Hybrid YOLO12 can be considered as a state-of-the-art framework for precision agriculture, with its high detection accuracy and real-time capability. Therefore, they encourage this deep learning model in pest management applications.

Aging populations threaten conservation goals of zoos

Improvements in wildlife husbandry mean that many zoo animals are living longer. This has put pressure on the finite holding capacity of zoos, which has often been addressed through a curtailing of reproduction to reduce population growth rates. Here, we explore how such actions have impacted the demographic trends of 774 mammal populations in European and North American zoo populations between 1970 and 2023. Irrespective of whether the data are clustered by region, taxonomic group, conservation status, or breeding program type, the proportion of old individuals has increased continuously, mirrored by a decrease in juveniles and actively reproducing adults. This aging demographic trend compromises the long-term sustainability of zoo populations and thus the ability of zoos to meet ex situ conservation goals. As the observed trends do not show signs of abating, reflection on current zoo population management is required.

A DNABERT based deep learning framework for predicting transcription factor binding sites