Prototype of a global model for regulating ecosystem services of inland wetlands.

RNA viruses are the most abundant group of pathogens on the planet; however, little is known about their association with amphipods (Crustacea: Peracarida). Here, we explore RNA virus diversity across invasive and native amphipod species inhabiting freshwater, marine, brackish and terrestrial environments around the globe, and analyse this data in relation to host invasion status, environment type, and between host taxa. We sampled tissue from 8 amphipod populations and screened an additional 152 from NCBI for RNA viruses. In total, 412 viral contigs were recovered, including 134 novel virus species, 41 with complete genomes. Viral contigs were associated with the: Articulavirales (n=35); Bunyavirales (n=38); Durnavirales (n=6); Ghabrivirales (n=28); Hepelivirales (n=43); Jingchuvirales (n=16); Martellivirales (n=4); Mononegavirales (n=139); Nidovirales (n=1); Nodamuvirales (n=2); Picornavirales (n=97); Wolframvirales (n=3). The alpha diversity of RNA viruses significantly differed between environments (freshwater, marine, and brackish) and amphipod host species. Host invasion status was not a significant driver in viral diversity. β diversity analysis revealed no significant difference in multivariate dispersion between environments, suggesting that freshwater, marine and terrestrial environments are equally rich in amphipod virus diversity; however, environment did have a significant effect on the viral community composition. This study contributes to our view of viral evolution and diversification among the Crustacea and boosts our understanding of RNA virus diversity and host range associated with invasion ecology and disease ecology within benthic communities.

Integrating multisource Earth observation data and reconstructing subsurface thermohaline structures from remote sensing at global and basin scales will provide a better understanding of oceans. However, previous methods relied on layer-by-layer modeling, which required separate reconstruction of subsurface temperature and salinity fields at different depths, resulting in many models, inefficiency, and weak vertical connections between thermohaline data at different depths. A fast deep neural network-based reconstruction can reduce models and enhance the overall consistency of thermohaline data, which is significant for the reconstruction of ocean environmental variables. This study proposes an improved Swin Transformer approach, i.e. SwinOcean3D, to perform one-shot reconstruction of three-dimensional (3-D) thermohaline structures (upper 1000 m) in different scales of Global (1° × 1°) and Indian Oceans (0.25° × 0.25°) by integrating multisource remote sensing and observation-based ocean products. SwinOcean3D combines the Swin Transformer, U-net, and dual-residual blocks to enhance the representation capability of the global scale, local detailed, and vertical features of ocean thermohaline structures. The significant advantages of SwinOcean3D in the reconstruction of multiscale 3-D thermohaline structures outperform other classical approaches. Furthermore, interpretability experiments suggest that SwinOcean3D can effectively capture the evolution of 3-D thermohaline structures from multisource observations.

Echolocating animals actively emit pulses of ultrasound and perceive acoustic reflections to determine the position of objects in dark, often three-dimensional spaces. Echolocation specificity thus depends on the properties of the calls emitted, such as frequency, duration, and call "shape", and how this ultrasound is modulated, reflected, received, and interpreted. Currently, however, there is no coherent synthesis explaining the functional adaptation of ultrasonic call design across echolocating species. To address this, here we provide the first comprehensive global macroevolutionary analysis of echolocator call design in relation to functional adaptations. From a systematic literature review, we identified 1,329 echolocating mammal and bird species, with a predominantly pan-tropical distribution, plus an additional 117 unconfirmed echolocators. To link echolocation call design to functional adaptations, we characterized calls based on 5,146 acoustic records from 2,838 terrestrial and aquatic study sites across 140 countries. From a comparative phylogenetic analysis, we established that echolocation calls were linked to (i) call frequency- and variation related parameters, which were associated with orientation function, and (ii) call type and duration, which mediated prey acquisition. Although echolocators produced highly species-specific calls, we found no support for any consistent effect of social system or sexual size dimorphism on echolocation call characteristics; however, morphological and phylogenetic constraints did substantially influence echolocation call designs at the global scale. This link between echolocation call design and function underscores how calls are adapted to overarching ecological niche conditions, explaining the conceptual macroevolutionary basis for the global distribution and adaptive radiation of echolocating species.

Measurement Properties of English and Chinese Versions of HeartQoL in a Multiethnic Asian Cohort With Cardiovascular Disease.

Nitric oxide interplay with hydrogen sulfide modulates gene expression and photosystem II function through enhanced antioxidant defense under PEG-induced osmotic stress in common bean (Phaseolus vulgaris L.).

Genetic diversity of plasmodium vivax merozoite surface protein 3α and β field isolates.

Evolutionary history shapes soil pH following forestation at global scales: A meta- analysis

Treatments for tuberculosis disease (TB) are failing on a global scale, necessitating new drug discovery efforts to identify effective therapies. Mycobacterium tuberculosis (Mtb), the obligate human pathogen and causative agent of TB, resides within alveolar macrophages and combats acidic stress by inhibiting phagosome maturation. Understanding the role of acidification in Mtb pathogenesis can aid the development of improved TB therapies. Aligning with the hypothesis that acidification affects Mtb intracellular survival, we developed a phenotypic assay to identify compounds that enhance acidification of Mtb in infected macrophages. To evaluate the assay suitability for screening purposes, we screened two compound libraries and found that early acidification does not necessarily correlate with inhibition of Mtb growth over time. Further, we found that compounds interfering with bacterial protein and DNA synthesis induced early phagosome acidification. However, other compounds, including cell wall synthesis inhibitors, did not consistently correlate with acidification or growth inhibition. Using early acidification could therefore provide a potential avenue to inform antimicrobial kinetics. By assessing Mtb's response to phagosome acidification, this work highlights the complexity of host-pathogen interactions in early infection and provides a valuable tool for investigating Mtb survival mechanisms and accelerating drug discovery efforts.

The potential impact of microplastic contamination in cow manure on maternal dung burying behavior and larval survival in the dung beetle Onthophagus taurus.

Soil organic carbon accumulation in response to vegetation restoration across global mining areas: A meta-analysis.

High-spatiotemporal-resolution column-averaged methane (XCH₄) data are crucial for mapping emission sources and supporting methane quantification and source attribution, but current satellite and ground-based observations are spatially and temporally discontinuous due to observational and atmospheric limitations, hindering the identification of local methane emission hotspots. To address this problem, we use TROPOMI XCH₄ retrievals as the target variable and ERA5 reanalysis, MCD18A1 surface downward shortwave radiation, and MCD18C2 photosynthetically active radiation as predictors in a machine-learning reconstruction framework to obtain a globally continuous daily XCH₄ dataset. The reconstructed data agree well with the original TROPOMI observations and are evaluated against independent TCCON measurements, land-cover-stratified statistics, and time-series analysis, supporting their accuracy and temporal consistency. The reconstructed XCH₄ fields are then applied to monitor anomalous methane emission sources in oil and gas production areas in Texas and in coal mining areas in Shanxi Province. The anomalous emission regions identified from the reconstructed data are generally consistent in location with emission sources detected by existing high-resolution satellite observations, suggesting their potential for identifying emission hotspots. This study provides reliable data for methane monitoring at global and regional scales and has important implications for greenhouse gas emissions accounting and climate change research.

Psychoses are often characterized by relapse and treatment resistance. Patients receiving electroconvulsive therapy (ECT) represent a high-risk subgroup. Although long-acting injectable (LAI) antipsychotics improve adherence compared with oral formulations, studies regarding their effectiveness when combined with ECT remain limited. Our study compared clinical outcomes between LAI and oral antipsychotics administered during ECT to patients with psychosis. We conducted a retrospective chart review of 65 patients, grouped according to antipsychotic formulation. Treatment response was defined by improvement on the Clinical Global Impression-Severity scale. Symptom changes were assessed using the Positive and Negative Syndrome Scale (PANSS). The LAI-ECT group showed a significantly higher response rate compared with the oral-ECT group (72.7 vs. 37.5%, P = 0.004). In multivariable analyses, LAI use remained significantly associated with treatment response ( P = 0.007). In the subgroup analysis of 48 patients, the LAI-ECT group exhibited greater reductions in total PANSS scores ( P = 0.014), which remained significant after adjustment for baseline severity ( P = 0.034). Greater symptom reductions were observed in the PANSS negative and general psychopathology subscales. These findings suggest an association between concurrent LAI antipsychotic administration during ECT and clinical outcomes, warranting further prospective validation.

Preeclampsia information on social media: A cross-sectional analysis of content, quality, and reliability.

The high placebo response in acne clinical trials has slowed down the progress of new drug development. Therefore, this study used a model-based meta-analysis method to quantitatively analyse the placebo response and explore its influencing factors. This study included 21 627 subjects from acne-related randomized double-blind placebo-controlled trials. Pharmacodynamic models were developed for four endpoints: total lesion counts absolute change, noninflammatory lesion counts absolute change, inflammatory lesion counts absolute change and treatment success rate defined by the investigator global assessment scale. Covariate modelling and subgroup analyses were performed to explore influencing factors. Placebo response under different conditions was simulated based on the final model. Model simulation results showed that for the typical population, after 12 weeks of placebo intervention, their total lesion counts, noninflammatory lesion counts and inflammatory lesion counts were reduced by 19.05 (95% confidence interval: 16.54-21.52), 10.71 (9.18-12.17) and 8.58 (7.55-9.58) from baseline, respectively; the treatment success rate was 11.83% (9.41%-14.35%). Baseline lesion counts, female proportion, Caucasians proportion, sample size, dosage form, type of control drug, skincare programme, number of centres, funding source, study locations and publication year could all influence placebo response. We also used our model to synthesize placebo arms for two single-arm studies, demonstrating the efficacy superiority of the drugs. This study quantitatively described the time-response relationship of placebo in acne clinical trials, revealing the influence of baseline characteristics and trial design characteristics, which could provide evidence for optimizing clinical trial design. PROSPERO (CRD420250649902).

Educational strategies in prenatal anomaly scanning: teaching, simulation and competence assessment.

Alloplastic temporomandibular joint replacement using patient-specific prostheses: a multicentre analysis of functional and aesthetic outcomes.

Validity evidence for the Essentials in Minimally Invasive Gynecologic Surgery laparoscopic skills: correlation with the Global Operative Assessment of Laparoscopic Skills.

ABSTRACT Landslide susceptibility assessment is essential for effective risk mitigation; however, conventional machine learning models often struggle to capture spatial heterogeneity and lack interpretability, resulting in limited generalization capability. To address these challenges, this research proposes an integrated method that combines Geographically Weighted Random Forest (GWRF) with Shapley Additive exPlanations (SHAP) for landslide susceptibility assessment. Focusing on a mountainous canyon region characterized by complex geological conditions and a vast spatial extent, RF and GWRF landslide susceptibility models were constructed from both global and subregional perspectives using watershed-based partitioning. Subsequently, SHAP was adopted to interpret model outputs and enhance interpretability and transparency. The results show that at both the global and subregional scales, the GWRF model consistently outperforms the conventional random forest model, with AUC values over 0.85. The predicted zones with high and very high landslide susceptibility are primarily spread along either side of river valleys, closely matching the observed landslide distribution. The DEM, Topographic Wetness Index (TWI), and distance to road were the dominant factors, with landslide susceptibility being positively correlated with TWI and negatively correlated with the other two factors. Overall, the GWRF–SHAP framework provides a promising way for landslide risk assessment in geologically complex areas.

The cingulate cortex is highly vulnerable in end-stage renal disease (ESRD) patients, but whether ESRD disrupts its functional gradient and the links to clinical phenotypes and underlying molecular mechanisms remain unclear. We prospectively enrolled clinical and resting-state functional MRI data from 125 participants (77 ESRD patients, 48 healthy controls) to explore cingulate gradient alterations. Associations between cingulate gradients and canonical functional networks, clinical phenotypes, and meta-analytic behavioral domains were analyzed. A gene expression decoding analysis based on the Allen Human Brain Atlas was performed to advance understanding of how molecular mechanisms relate to hierarchical changes in ESRD. Across global, network, and regional scales, patients with ESRD showed significant cingulate gradient dysfunction, with these anomalies exhibiting associations across multiple functional domains. Notably, serum urea and hemoglobin levels were correlated with cingulate gradient dysfunction. Spatially, these alterations correlated with genes enriched in neurodegenerative processes. Excitatory and inhibitory neurons' specific transcriptional changes account for most of the observed correlation with ESRD-specific cingulate gradient alterations. Our findings highlight ESRD-related cingulate gradient dysfunction and its links to clinical phenotypes and gene expression profiles, providing critical insights into the neurodegenerative underpinnings of cerebral dysfunction in ESRD.