Browse Articles

Discrete ecological gradient in thermokarst ponds in a palsa mire in northern Norway

Abstract Palsa mires constitute a zonal peatland type in the discontinuous permafrost region of the Northern Hemisphere. They typically consist of permafrost mounds and thermokarst ponds. Global warming has accelerated thawing of permafrost in palsa mounds and an increase in the area of thermokarst ponds in recent decades. Understanding long-term consequences of this process requires in-depth knowledge of the internal diversity of palsa mire vegetation types and their functions. Most studies so-far focused on the palsa mounds. Hereby, we focus on the thermokarst ponds, analysing their vegetation composition and habitat conditions from the top of a palsa plateau down to a fen without current palsa formation close to an adjacent river. We observed a distinct ecological gradient from Sphagnum-dominated ponds in the uppermost part of peat plateau to brown moss-dominated fen flarks at the riverside. This reflected well the poor – rich gradient typically recognised in mire vegetation, confirmed by our hydrochemical analyses. However, in contrast to the gradual shifts in species composition along typical mire zonation in temperate regions, palsa microtopography with mounds, rims, strings, and hollows, creates a sequence of mire basins forming a discrete gradient from base-poor to base-rich conditions, allowing different plant species to dominate these distinct locations.

Prediction of the risk of transplant rejection based on RNA sequencing data of PBMCs before transplantation

Abstract Novel methods for detecting transplant rejection are craved, since conventional methods can detect ongoing rejection that may sometimes have already caused irreversible damage in transplanted organs. Here, we applied a transcriptomics database of recipients’ peripheral blood mononuclear cells (PBMCs) before liver or kidney transplantation on the weighted gene co-expression network and machine learning models to evaluate the risk of rejection. Gene clusters positively correlated with rejection were enriched for genes related to antiviral response and regulation/production of interleukin-1(IL-1) in liver transplantation, and genes related to innate immune responses (IL-8 and toll-like receptor signaling pathways) and T cell responses were positively correlated with rejection in kidney transplantation. Our study presents a novel approach for feature engineering based on RNA-seq data of PBMCs collected before transplantation. The features derived from this method demonstrated potential in predicting the risk of rejection and may serve as candidate predictors in future clinically applicable models.

Diagnostic systematic review and meta-analysis of machine learning in predicting biochemical recurrence of prostate cancer

The network linking daytime sleepiness, chronotype, and emotional distress is bridged by anxiety and depression in young adults

Uric acid mediates the association of alpha-1 acid glycoprotein with gallstones in adult women in the United States

Prevalence and patterns of antiretroviral resistance in HIV-infected Latin American asylum seekers

Developing a simple artificial intelligence fuzzy-based model for estimating saturated hydraulic conductivity of soil

Abstract Saturated hydraulic conductivity is one of the important physical properties of soil in modeling water and solute transport, irrigation management, and drainage issues. Laboratory and field methods for directly measuring this parameter are time-consuming and costly. In recent years, the use of intelligent systems for estimating various soil parameters has significantly increased. Therefore, this research aims to utilize Fuzzy Inference Systems (FIS), Artificial Neural Networks (ANN), and Linear Regression (LR) to create a mapping between soil texture parameters and saturated hydraulic conductivity. The data used in this study includes physical properties related to 331 soil samples from the UNSODA soil database (170 samples) and existing data from soils in the cities of Amol, Babol, Karaj (50 samples), and Shahrekord (111 samples). After examining different models and combinations of available data, three models were proposed for estimating saturated hydraulic conductivity. In these models, saturated hydraulic conductivity was estimated using soil texture characteristics (percentage of clay, silt, and sand) and bulk density, and the performance of the models was evaluated using statistics such as root mean square error (RMSE), mean bias error (MBE), and coefficient of determination (R 2 ). Comparing the results of the proposed nonlinear models with different input parameters showed that fuzzy systems can estimate saturated hydraulic conductivity with acceptable accuracy. During the training phase, the fuzzy model with four input variables (percentage of clay, silt, sand, and bulk density) had the highest correlation (r = 0.92), and considering other evaluation parameters (R 2  = 0.84, MBE = 0.28 cm/hr, and RMSE = 1.64 cm/hr), it showed a good fit with the measured values. In the testing phase, similar results were obtained, and the fuzzy model with four parameters had the best fit. Based on the results of this research, the fuzzy model can be introduced as one of the methods for estimating saturated hydraulic conductivity with suitable accuracy.

The prognostic value of secreted frizzled-related protein 2 in elderly patients with heart failure: a single-center retrospective study

Abstract This study was conducted to assess the prognostic value of secreted frizzled-related protein 2 (SFRP2) for mortality and readmission in elderly patients with acute exacerbation of chronic heart failure (HF). Elderly patients hospitalized for worsening chronic HF were enrolled in the present study. We detected the concentration of serum SFRP2 in these patients. The primary endpoint of this study was defined as all-cause mortality and the secondary endpoint was a composite of all-cause mortality and readmission due to HF, acute myocardial infarction, and malignant arrhythmia during a median follow-up period of 450 (interquartile range 224–942) days. Multivariable Cox proportional hazard models were performed to evaluate the prognostic value of SFRP2. Of 161 patients at baseline, we observed 72 events (25 deaths and 47 readmissions). Serum SFRP2 levels were significantly elevated in elderly HF patients with events relative to those without and control subjects (all P < 0.001). The Kaplan-Meier analysis showed a significantly increased risk of all-cause mortality and cardiovascular readmissions stratified by the optimal cut-off value of serum SFRP2 level (log-rank P < 0.005). An elevated SFRP2 level and N-terminal pro-B-type natriuretic peptide (NT-proBNP) level was independently and significantly associated with the primary endpoint and secondary endpoint (adjusted hazard ratio [HR] 2.334, 95% confidence interval [CI] 1.059–5.147;P = 0.036 and HR 2.326, 95% CI 1.426–3.794;P = 0.001, respectively) in multivariable Cox regression analysis. A higher level of serum SFRP2 can be considered as an independent predictor of poorer clinical outcomes for elderly patients with acute exacerbation of chronic heart failure, indicating that evaluation of SFRP2 could provide more useful information for the long-term prognosis in these patients beyond NT-proBNP.

Deciphering nitrogen-driven microbial succession in an anaerobic membrane bioreactor-coupled A2/O ecological system for the remediation of industrial swine wastewater

Device grade solid-state pouch and coin cell supercapacitors dual assembly using consumed battery waste to best utilization

Effects of culture system and diet on amphipod (Parhyale hawaiensis) production

High-performance hydrogen energy generation via innovative metal-organic framework catalysts and integrated system design

Irrigation water quality shapes soil microbiomes: a 16 S rRNA-based biogeographic study in arid ecosystems

Abstract Soil microbiome plays a crucial role in ecosystem; however, the responses of the soil microbiome to nonconventional irrigation water sources remain poorly understood. This study employed 16 S rRNA sequencing to investigate microbial community shifts in soil samples collected from four geographically distinct locations affected by different irrigation water sources: saline ground water affected by seawater (SW), a brackish water lake (BW), a wastewater drain (WW), and a freshwater canal that receives inflows from multiple agricultural drains (FW). Our findings revealed distinct microbial signatures shaped by water quality, with Firmicutes dominating WW soils (49.2%) due to metal resistance (DESeq2, p = 3.67 × 10− 4), whereas Chloroflexi and Cyanobacteria thrived in BW environments (LEfSe, LDA > 4, p = 8.23 × 10− 6), reflecting adaptations to chloride-rich conditions. FW soils enriched Acidobacteria and Verrucomicrobia, which are associated with moderate salinity and nutrient cycling, whereas SW samples harbored halotolerant Actinobacteria and Deinococcus-Thermus (DESeq2, p = 1.47x− 05). Statistical analyses revealed key potential biomarkers, including Streptococcus (WW, DESeq2 p = 3.67x− 24), RB41 (BW, LEfSe p = 1.62x− 13), and Candidatus_Udaeobacter (SW, DESeq2 p = 1.47x− 05). Physicochemical drivers such as salinity (R² =0.319, p = 0.00041) and heavy metals (Pb/Mn in WW) strongly influence community structure. Notably, WW irrigation reduced alpha diversity (Shannon index: 4.79–5.41 vs. 6.65–7.43 in FW; Kruskal-Wallis p = 0.0056), highlighting pollutant-induced stress. These findings highlight the balance between water reuse and soil health, offering a foundation for microbiome-driven bioremediation approaches in arid environments. By utilizing native, stress-resilient microbial communities, our research promotes sustainable agricultural practices in water-limited regions.

Frailty index is positively associated with stroke risk in nationally representative cohorts from the united States and China

Synchronous surgery combined preoperative chemotherapy benefits patients suffering pancreatic ductal adenocarcinoma with liver metastases: a systematic review and meta-analysis

Body mass index, physical activity and dental caries: cross-sectional HUNT4 oral health study

Abstract Studies on the association between body mass index (BMI) and dental caries among adults are limited. Moreover, individuals with a high BMI may be either physically active or inactive, but the impact of these combinations on dental caries remains unexplored. In this study, we aimed to investigate the associations between BMI, its combination with physical activity (PA), and dental caries in the adult population. We conducted a cross-sectional analysis using data from Norwegian HUNT4 Oral Health Survey (2017–2019). BMI was categorized as < 25.0 (normal), 25.0–29.9 (overweight), or ≥ 30.0 kg/m2 (obese). The combination of BMI and PA was classified into 4 groups: (1) normal weight and active; (2) normal weight and inactive; (3) overweight-obese and active; and (4) overweight-obese and inactive. Main outcomes included the total number of decayed, missing, and filled teeth (D3MFT) and decayed teeth (D3T), while missing and sound teeth were secondary outcomes. Ratios of means (RM) with 95% confidence intervals (CI) were calculated using negative binomial regression. Effect modification by age (< 65 vs. ≥ 65 years) was assessed via the likelihood ratio test. We included 4752 individuals with a mean age of 51.9 years (SD 15.9). Compared to individuals with BMI < 25 kg/m2, those with BMI ≥ 30.0 kg/m2 was associated with an increased mean number of D3MFT (adjusted RM: 1.10, 95% CI 1.07–1.13), D3T (1.19, 95% CI 1.07–1.32), and missing teeth (1.11, 95% CI 1.00–1.22), but inversely with sound teeth (0.96, 95% CI 0.92–0.99). No combined effect of BMI and PA was observed. The association between BMI and dental caries was modified by age, with an association observed in individuals under 65 years (P likelihood ratio test < 0.001). We observed that a higher BMI was associated with a higher dental caries experience and missing teeth. However, there was no evidence of a combined effect between BMI and PA on dental caries.

Coral restoration can drive rapid increases in reef accretion potential

Abstract Coral-reef degradation is disrupting the balance between reef accretion and erosion and threatening the persistence of essential coral-reef habitats. In south Florida, most reefs are already net eroding, and without intervention, valuable ecosystem services may be lost. Coral restoration holds the potential to reverse those trends; however, typical restoration monitoring does not adequately capture key geo-ecological functions. We addressed this knowledge gap using carbonate budgets and Structure-from-Motion models to evaluate the impact of coral restoration on reef-accretion potential and structural complexity at eight offshore and three inshore coral reefs in the Lower Florida Keys. Within 2–6 years following outplanting, restoration of rapidly growing A. cervicornis populations increased reef-accretion potential to 2.8 mm y− 1 and drove significant increases in structural complexity. There was no measurable impact of restoring slower-growing, massive corals on reef-accretion potential inshore; however, whereas the severe 2023 coral-bleaching event immediately following our study caused near-complete mortality of A. cervicornis, 59% of massive corals survived, highlighting potential trade-offs between coral growth and survival on future restoration efficacy. We conclude that although restoration can produce rapid, small-scale increases in reef-accretion potential, there remain important uncertainties about how and whether ecosystem-scale benefits of restoration on important geo-ecological reef functions can persist long term.

Global spread and antimicrobial resistance of Aeromonas hydrophila in aquatic food animals: a systematic review and meta-analysis

Abstract Aeromonas hydrophila is a common zoonotic agent in aquatic environments that causes gastroenteritis and wound infections in both humans and animals through foodborne and hospital-acquired infection. Antimicrobial resistance (AMR) combination with virulence factors enhances treatment challenging. The prevalence and AMR of Aeromonas hydrophila have been increasingly reported, posing a significant threat to both animal and public health. This systematic review and meta-analysis aimed to determine the prevalence of A. hydrophila and its resistance to aquatic food animals. A comprehensive search for relevant studies was conducted on Google Scholar, PubMed, ScienceDirect, and Scopus, following the PRISMA guidelines, covering studies from January 2020 to December 2024. The quality of the included publications was evaluated using the Joanna Briggs Institute critical appraisal tool. Differences in the prevalence and AMR of A. hydrophila were assessed using a random-effect model. A total of 14,077 studies were screened, and 14 publications were included. Bacterial isolation of A. hydrophila was achieved using various standard protocols, involving culture on Rimler-Shotts (RS) agar and Tryptic Soy Agar (TSA), with or without antimicrobials. Subsequent biochemical identification confirmed the isolates. The pool prevalence of A. hydrophila (30.7%, 95% C.I.:17.0-46.3%), and the distribution of virulence genes were 71.2%. The most common resistance observed to penicillin (80.7%), oxytetracycline (69.9%) and macrolides (67.8%). The most prevalent AMR genes identified were bla TEM (67.0%), followed by tetA (63.7%). The increasing presence of A. hydrophila in aquaculture suggests a considerable risk of disease. The prevalence of both A. hydrophila and AMR was higher in Africa than in Asia, indicating regional variations in the AMR pattern. However, monitoring and surveillance of A. hydrophila remained limited. A major limitation of this study was the heterogeneity in effect estimates across the selected studies. Nonetheless, the quality assessment conducted indicated that this variability did not compromise the consistency or reliability of the findings.

Retraction Note: Applications of complex picture fuzzy soft power aggregation operators in multi-attribute decision making

Gene expression and molecular pathway analyses differentiate immunotherapy-induced myositis from spontaneous dermatomyositis

Abstract Immune checkpoint inhibitor therapy (ICI)-induced myositis (irMyositis) occurs in about 1% of patients treated with anti-PD1 or anti-CTLA-4 antibodies and can be debilitating or even fatal. We compared gene expression profiles from skeletal muscle biopsies between irMyositis patients, patients with spontaneous dermatomyositis (DM, comprising anti-Mi2-positive and anti-TIF1-γ-positive subtypes), and non-diseased controls (NDC). We used the NanoString nCounter PanCancer Immune Profiling Panel to perform differential gene expression (DGE) and pathway enrichment analyses. We identified 93 differentially expressed genes (DEGs) across conditions. Gene set enrichment analysis (GSEA) suggested activation of interferon gamma (type-II IFN) and interferon alpha/beta (type-I IFN) signaling in irMyositis and DM, respectively. For instance, type-II IFN was upregulated exclusively in irMyositis when compared to DM, which conversely showed upregulation of effector genes downstream type-I IFN. The observed fold-change of a subset of 33 genes drove the GSEA. We further characterized the DEGs using network interaction and expression correlation analyses. This allowed us to describe potential differences between regulatory hubs and cells involved in irMyositis susceptible to ICI effects. For example, the downregulation of FOXP3 we observed together with the upregulation of the chemokine CCL14 in irMyositis may have been a consequence of T cell activation upon ICI therapy. The gene expression correlation and putative molecular interactions set irMyositis apart from DM, particularly with respect to IFN response and DGE of interactors of ICI protein targets (CTLA4, PD-1, PD-L1). Our results suggest new avenues for understanding immunotherapy-related adverse events.