Browse Articles

IL-27Ra promotes the progression of neonatal necrotizing enterocolitis

Quantification of the radiative forcing of contrails embedded in cirrus clouds

Abstract Aviation leads to the emission of CO 2 but also exerts non-CO 2 effects on climate, such as line-shaped condensation trails (contrails) and contrail cirrus that are known to cause warming. However, little is known about the climate effect of contrails that form in already existing cirrus clouds, where conditions for contrail formation are found most often. Here, we infer the local net radiative forcing of around 40,000 embedded contrails by combining aircraft position data with height-resolved cloud observations from spaceborne lidar. Considering the period from 2015 to 2021, we find an annual mean local warming effect of 60 mW m −2 . Expanding these findings to the global scale suggests an annual global mean net radiative forcing of embedded contrails on the order of 5 mW m −2 . This corresponds to around 10% of the current estimate of the climate impact of line-shaped contrails and suggests that embedded contrails are a non-negligible contributor to aviation’s impact on climate.

Curvature-corrected retinal registration of diagnostic OCT with instrument-integrated OCT

Abstract Vitreoretinal surgery, requiring precise microscale tissue manipulation, is well-suited for robotic assistance. Image registration enhances surgeons’ visual perception by aligning high-resolution preoperative OCT images with the intraoperative environment, improving visibility of anatomical features not seen in microscope images. However, optical distortions from the cornea, lens, eye curvature, and scanning patterns challenge the use of diagnostic data in robotic navigation. This study introduces a novel technique for curvature-corrected retinal registration, integrating diagnostic OCT with instrument-integrated OCT. The pipeline comprises feature extraction, curvature correction, initial alignment, and fine registration. Experiments using an artificial model eye and ex vivo porcine eye validate the method. Curvature correction achieves accuracy comparable to existing methods, with deviations of 17 $$\upmu$$ m for the model eye and 460 $$\upmu$$ m for the porcine eye. Post-registration, the fiducial marker error reduces to 103 $$\upmu$$ m for the model eye and 318 $$\upmu$$ m for the porcine eye. Our method provides intraoperative diagnostic context, enabling reliable topological assistance in retinal robotic systems.

Identifying global hotspots of agricultural expansion into non-forest ecosystems

Abstract Ecologically important non-forest ecosystems, including grasslands, shrublands and wetlands, face substantial threats from agricultural expansion, yet their conversion dynamics remain poorly understood. This study identifies global hotspots of land conversion from non-forest (and forest) ecosystems to cultivated lands from 2000 to 2020, including conversion within Protected Areas and its impacts for biodiversity conservation. Using three state-of-the-art land cover datasets (GlobeLand30, GLCLUC and GLC_FCS30D), we find extensive and increasing non-forest conversion, often comparable to or exceeding forest conversion. Protected non-forest ecosystems cover substantially smaller area than protected forests while experiencing disproportionately high conversion rates. Non-forest and forest conversion together affected habitats of over 5,000 threatened species, over half of which depend critically on non-forest ecosystems. Our study provides important insights for improved land cover data development, while offering companies and policymakers science-based evidence to design sustainable land-use policies and integrated policy frameworks that avoid trade-offs and support broad sustainability goals.

Knowledge, attitude, and practice regarding brucellosis among confirmed cases

Abstract Brucellosis remains a major public health problem in many endemic regions of China, particularly in areas with extensive livestock farming. This study aims to explore the knowledge, attitudes, and practices regarding brucellosis among patients with the disease. The cross-sectional study was conducted in Xinjiang from June 1, 2024, to January 30, 2025. Data were collected through a self-designed questionnaire encompassing sociodemographic characteristics and three dimensions of knowledge, attitudes, and practices. Of the 507 questionnaires distributed, 398 were valid and included in the analysis. Most respondents were male (62.81%) and worked in occupations involving contact with animals (65.08%). The mean scores for knowledge, attitude, and practice were 8.45 ± 3.06, 37.81 ± 3.89, and 38.62 ± 5.47, respectively. Structural equation modeling indicated that knowledge was positively associated with both attitudes (β = 0.579, p  < 0.001) and practices (β = 0.351, p  < 0.001), while attitudes also influenced practices (β = 0.270, p  = 0.002). Knowledge further affected practices indirectly through attitudes (β = 0.156, p  = 0.010). Brucellosis patients demonstrated relatively low knowledge scores but exhibited positive attitudes and proactive practices regarding the disease. The Structural equation modeling indicated that knowledge was associated with both attitudes and practices. Providing targeted educational interventions could help strengthen positive attitudes and improve preventive practices among brucellosis patients, ultimately supporting better disease control and management. In conclusion, strengthening patient-centered education and integrating it into routine public health programs are essential steps toward reducing the burden of brucellosis in endemic regions.

Genetically informed causal links between gut microbiota and bone mass: pleiotropy and metabolic mediation

Validation of the Utrecht work engagement scale (UWES-9) in the Czech Republic

Abstract The Utrecht Work Engagement Scale (UWES) is the most widely used work engagement measure. However, its cultural validity regarding factor structure and other psychometric characteristics remains unclear in certain cultural contexts. Thus, this study aimed to assess UWES-9, shortened version of UWES, in the Czech cultural environment psychometrically. A Sample of 707 employees (Age: M  = 43.65, SD  = 10.08, Females: 38.47%) recruited from various companies in the Czech Republic was used. Neuroticism, extraversion, self-efficacy, spirituality, chronic health diseases, and frequency of health risk behavior were measured. Higher UWES-9 total scores were reported for professional staff, managers, and people with higher vocational school or university scores. Additionally, a significant difference was also found in family status, with individuals in a relationship reporting higher work absorption. Among the tested factor models the modified three-factor solution: χ 2 (20) = 158.853; p  < .0.001; CFI = 0.987; TLI = 0.976; RMSEA = 0.077; SRMR = 0.017 reached the highest fit with the data. Measurement equivalence testing suggested that on configural, metric, scalar, and strict levels, the UWES-9 assesses work engagement invariantly between genders. A positive association with extraversion, self-efficacy, and a negative association with neuroticism supported the convergent validity of the UWES-9. Internal consistency (α = 0.96, McDonald’s ω = 0.96) was excellent. Logistic regression revealed that a higher score in the UWES-9 was associated with a lower chance of developing skin diseases and pain of unclear origin. The cultural validity of the UWES-9 in terms of factor structure was supported. The UWES-9 is a valid and reliable instrument to measure work engagement in the Czech cultural context.

Single-cell multiomics analysis reveals CTCF as a key regulator of lung morphogenesis and progenitor maintenance

Cortical activation and functional connectivity during verbal fluency task in patients with chronic insomnia: a multi-channel fNIRS study

A niche-dependent redox rheostat regulates epithelial stem cell fate

Soil spring stiffnesses for laterally loaded large diameter rigid caissons

Deciphering the role of complement system genes in pancreatic cancer susceptibility and prognosis

Preserving and enhancing cultural heritage through art design using feature pyramid network optimized by modified builder optimization algorithm

Insights into natural neocentromere evolution from a cattle T2T X chromosome

Abstract The cattle genome is crucial for understanding ruminant biology, but it remains incomplete. Here we present a telomere-to-telomere haplotype-resolved X chromosome and four autosomes of cattle in a near-complete assembly that is 431 Mb (16%) longer than the current reference genome. Using this assembly (UOA_Wagyu_1) we identify 738 new protein-coding genes and support the characterization of centromeric repeats, identification of transposable elements, and enabled the detection of 2397 more structural variants from 20 Wagyu animals than using ARS-UCD2.0. We find that the cattle X centromere is a natural neocentromere with highly identical inverted repeats, no bovine satellite repeats, low CENP-A signal, low methylation, and low CpG content, in contrast to the autosomal centromeres that are comprised of typical bovine satellite repeats and epigenetic features. Our results suggest it likely formed from transposable element expansion and CpG deamination, suggesting dynamic evolution. We find eighteen X-pseudoautosomal region genes have conserved testes expression between cattle and apes. We also find all cattle X neocentromere protein-coding genes are expressed in testes, which suggests they potentially play a role in reproduction.

Exploring the operational performance of Indian smes: an integrated PLS-SEM and NCA approach

Interferometric imaging of the reversible rhodopsin dynamics in the living rat eye

Unveiling synchronization transitions in networks of coupled oscillators through persistent homology of local structures

Predictive chemoproteomics and functional validation reveal Coeae6g-mediated insecticide cross-resistance in the malaria vector Anopheles gambiae

Kademlia hash snow ablation resource optimized stride scheduling for mobile computing services in healthcare sector

Abstract Healthcare plays an essential role in every individual’s life. Smart healthcare employs a new generation of information technologies like Internet of Things (IoT), Mobile Computing (MC), and Artificial Intelligence (AI) to transform the conventional medical system into a modernized one. Many researchers have reached better healthcare solutions by ensuring robust and versatile accessibility to the people. Healthcare applications on mobile devices exchange data through communication interfaces between patients and healthcare service providers. However, every patient’s data possess a significant amount of computing resources like Central Processing Unit (CPU), network bandwidth, and memory, and hence cannot be processed and validated at the same time. In order to overcome resource limitations and make scheduling efficient, mobile devices contain patient data that is integrated with the scheduling process to provide the resource efficient mobile computing services in the healthcare sector. Kademlia HashSnow Ablation Resource Optimized Stride Scheduling (KHSAROSS) is proposed in mobile computing. The novelty of the proposed KHSAROSS method is designed to build mobile phone based remote healthcare monitoring to identify the resource optimized virtual machine and balance the overloaded virtual machine. The key advantage of the proposed KHSAROSS method is to enhance the mobile computing services in the healthcare sector while increasing makespan. The KHSAROSS method involves three distinct processes, namely the patient data collection task, optimization and scheduling. Sensors with a data acquisition unit are used to acquire patients’ physiological states like temperature, heart rate, and Electroencephalography (EEG) data to perform mobile phone based remote healthcare monitoring. The Kademlia Hash Function here generates a hash value for each patient’s collected data. Following this, Snow Ablation Optimization is carried out to identify resource optimized (i.e., CPU, network bandwidth, and memory) virtual machines (i.e., healthcare service providers) for performing scheduling of stored patient data. Finally, Stride Scheduling is used to balance overloaded virtual machines with less loaded virtual machines. This, in turn, ensures efficient resource allocation and scheduling in mobile computing. The effectiveness of the proposed and existing methods is assessed using metrics for scheduling accuracy, scheduling time, throughput and makespan.

Expanding the utility of variant effect predictions with phenotype-specific models