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Ocean acidification modulates material flux linked with coral calcification and photosynthesis
Abstract Coral reefs are essential for the foundation of marine ecosystems. However, ocean acidification (OA), driven by rising atmospheric carbon dioxide (CO 2 ) threatens coral growth and biological homeostasis. This study examines two Hawaiian coral species— Montipora capitata and Pocillopora acuta to elevated pCO 2 simulating OA. Utilizing pH and O 2 microsensors under controlled light and dark conditions, this work characterized interspecific concentration boundary layer (CBL) traits and quantified material fluxes under ambient and elevated pCO 2 . The results of this study revealed that under increased pCO 2 , P. acuta showed a significant reduction in dark proton efflux, followed by an increase in light O 2 flux, suggesting reduced calcification and enhanced photosynthesis. In contrast, M. capitata did not show any robust evidence of changes in either flux parameters under similar increased pCO 2 conditions. Statistical analyses using linear models revealed several significant interactions among species, treatment, and light conditions, identifying physical, chemical, and biological drivers of species responses to increased pCO 2 . This study also presents several conceptual models that correlate the CBL dynamics measured here with calcification and metabolic processes, thereby justifying our findings. We indicate that elevated pCO 2 exacerbates microchemical gradients in the CBL and may threaten calcification in vulnerable species such as P. acuta , while highlighting the resistance of M. capitata . Therefore, this study advances our understanding of how interspecific microenvironmental processes could influence coral responses to changing ocean chemistry.
Photographic evaluation of clinical activity score in thyroid eye disease
Purpose Given the subjective nature of clinical activity score (CAS) and variability between observers, this study evaluated the inter-observer variability of soft tissue signs (STS) in the CAS using periocular photographs and compared the diagnostic performance of photographic CAS (P-CAS) with clinical assessment for detecting active thyroid eye disease (TED). Methods This retrospective cohort study included 754 TED patients who underwent periocular photography at Seoul National University Bundang Hospital between 2006 and 2021. Five oculoplastic specialists independently evaluated five STS of CAS using periocular photographs. Inter-observer agreement and concordance between photographically (P-STS) and clinically (C-STS) assessed STS, assessment consistency, were analyzed using Kappa statistics. Diagnostic accuracy of P-CAS was evaluated via receiver operating characteristic (ROC) curves with additional analysis incorporating demographic variables such as sex, age, and smoking dose. Results Assessment consistency was moderately good for redness of eyelid and conjunctiva (Kappa = 0.418, 0.499). The diagnostic performance of P-CAS (area under the curve, AUC = 0.774) was lower than that of clinical CAS (C-CAS) (AUC = 0.818, p = 0.007), However, it significantly improved when demographic factors were added (AUC = 0.851). Conclusion Periocular photography provides a reproducible and clinically valuable adjunct for assessing TED activity. The redness-related items showed higher agreement than swelling-related ones, and integrating demographic variables enhances diagnostic performance. This approach may contribute to standardizing TED assessment and serve as a foundation for future automated or image-based evaluation tools.
Exercise as a therapy for sickle cell-associated musculoskeletal pain among children: Healthcare professionals’ perspectives
Introduction Musculoskeletal (MSK) pain is one of the most substantial and debilitating complications of sickle cell disease (SCD), particularly in pediatric patients. Although exercise is recognized as a potential therapeutic strategy for managing SCD-associated MSK pain, the knowledge and attitudes of healthcare professionals regarding its use remain unclear. This study aimed to explore healthcare professionals’ perspectives on the role of exercise in managing MSK pain in children with SCD. Method Face-to-face semi-structured interviews were conducted with nineteen healthcare professionals (pediatric nurses and pediatricians). All interviews were transcribed verbatim; codes were generated and inductively organized into themes. Results Three major themes were identified that described healthcare professionals’ perspectives on using exercise as a therapy for MSK pain in children with SCD. These included understanding exercise in managing MSK pain in SCD, barriers to using exercise in managing MSK pain in SCD, and facilitators for implementing an exercise program for MSK pain in SCD. Conclusions Healthcare professionals acknowledge the potential benefits of exercise in managing musculoskeletal (MSK) pain in children with sickle cell disease (SCD); however, overcoming identified barriers and utilizing facilitators is essential for effective implementation.
Precise energy modeling and green retrofitting optimization of existing buildings based on BIM and deep learning approaches
The construction industry has emerged as a major contributor to global energy consumption and greenhouse gas emissions amidst continuously rising worldwide energy demands. Enhancing building energy efficiency represents a critical intervention for achieving energy conservation and emission reduction targets. In the context of smart city development, such optimization efforts provide substantial momentum for sustainable urban growth. This study introduces a novel methodology that integrates Transformer models with Graph Neural Networks (GNNs) to improve the accuracy and operability of building energy efficiency prediction through advanced deep learning techniques. By leveraging Building Information Modeling (BIM) data to model spatial structures and energy consumption patterns, GNNs effectively capture complex relationships between building components, thereby strengthening the characterization of multidimensional interactions within structures. The self-attention mechanism in Transformers enables the model to focus on key factors such as energy consumption hotspots and temporal variations, enhancing learning capabilities across both spatial and temporal dimensions. To further augment optimization performance, we incorporate Generative Adversarial Networks (GANs) to generate diverse green renovation schemes, expanding optimization pathways and enhancing model adaptability and robustness. Experimental validation using BIM data demonstrates that our integrated approach outperforms traditional energy efficiency optimization models, increasing energy savings by nearly 4 These findings establish that BIM data-integrated deep learning optimization methodologies offer significant potential for providing effective energy efficiency prediction and optimization decision support. Such approaches directly contribute to building design and operations in smart cities, advancing the realization of green buildings and sustainable urban development.
Phase II monitoring of process variability in multichannel profiles
Monitoring process variability utilizing profile data remains a significant challenge in statistical process monitoring (SPM), especially in the context of multichannel profiles. Detecting shifts in the covariance matrix of a multivariate normal process is crucial for this purpose. The complexity increases notably in high-dimensional processes because of the large number of variables and limited sample sizes. Typically, monitoring changes in the covariance matrix assumes that only a few elements deviate simultaneously from their in-control values. This study introduces a new approach for monitoring the covariance matrix in Phase II for multichannel data. The suggested approach incorporates exponentially weighted moving average (EWMA) control chart with multichannel functional principal components analysis (MFPCA) to derive proposed statistics. Simulation results represent the effectiveness and performance of the suggested approach, highlighting its superior performance in average run length under various shift patterns.
Effects of aquatic exercise on arterial stiffness and endothelial function in adults: A systematic review and meta-analyses
Objective To evaluate the effects of aquatic exercise compared with non-exercise controls and land-based exercise on arterial stiffness and endothelial function. Design Systematic review and meta-analyses of randomized controlled trials assessed using the Cochrane risk-of-bias tool and Grading of Recommendations Assessment, Development and Evaluation. Data sources PubMed/MEDLINE, CINAHL Plus, SPORTDiscus, and reference lists, searched from database inception to April 16, 2025. Eligibility criteria Studies evaluating chronic aquatic exercise (multi-session interventions) compared with land-based exercise or non-exercise comparison groups in adults, measuring arterial stiffness via pulse wave velocity (PWV) or endothelial function via flow-mediated dilation (FMD). Results This review includes 18 randomized controlled trials with 845 participants (mean age 65 ± 7 years). Studies compared aquatic exercise with non-exercise controls (8 studies), land-based exercise (6 studies), or both (4 studies). Exercise sessions averaged 50 minutes, 3 times weekly for 11 weeks. Most studies (17 out of 18) implemented moderate-to-vigorous intensity protocols. Aquatic exercise resulted in improvements in arterial stiffness compared with non-exercise controls (7 studies; SMD = –2.37, 95% CI: –4.46 to –0.29; I 2 = 98%: low certainty), with most evidence reflecting systemic and peripheral PWV. Changes in arterial stiffness did not differ from those observed after land-based exercise (6 studies; SMD = –0.07, 95% CI: –0.34 to 0.20; I 2 = 0%, moderate certainty). For endothelial function, aquatic exercise may improve outcomes versus non-exercise controls (6 studies; SMD = 0.91, 95% CI: 0.39 to 1.43; I 2 = 68%; low certainty) and may lead to greater improvements than land-based exercise (7 studies; SMD = 0.55, 95% CI: 0.05 to 1.06; I 2 = 75%; low certainty). Conclusion Aquatic exercise improves systemic and peripheral arterial stiffness as well as endothelial function compared with non-exercising controls. Changes in arterial stiffness do not differ from those observed after land-based exercise. Aquatic exercise may provide greater improvement in endothelial function than land-based exercise, though this is supported by low-certainty evidence, and substantial heterogeneity limits confidence in the generalizability of this finding. PROSPERO registration CRD42025642087.
Science sleuths raise concerns about scores of bioengineering papers
Correction: The effect of tennis on male bone mineral density: A meta-analysis
Correction: Integration of wearable devices and artificial intelligence in Alzheimer’s disease: A scoping review protocol
Prevalence of sexually transmitted infections and immunization status among registered sex workers: A pilot study in lower Bavaria, Germany
Background Sex workers are often considered at elevated risk for sexually transmitted infections (STIs). This pilot study describes the socio‑epidemiological characteristics of registered sex workers in a rural German setting, estimates the prevalence of four STIs (HIV, hepatitis B [HBV], hepatitis C [HCV], and syphilis [lues]), compares these with the local population, and assesses HBV immunization coverage. Methods Under §10 of the Prostitute Protection Act (ProstSchG), annual health consultations are mandatory; voluntary serologic testing is permitted under §19 of the Infection Protection Act. We conducted a retrospective observational monocentric pilot study using routine consultation records and voluntary serologic results from the Public Health Service (PHS) of Landshut (2017–2021). In total, 523 consultations were documented; 99 blood samples from 48 registered sex workers (2019–2021) were analyzed. Primary screening assays were followed by confirmatory tests when indicated. Crude point/period prevalences and 95% confidence intervals (95% CI) were calculated. HBV immunization was defined according to Standing Committee on Vaccination (STIKO) recommendations. Results The cohort was predominantly female (n = 47; 97.9%), mean age 34.8 ± 11.2 years; 85.3% (n = 41) had a migration background (n = 27; 56.3% from Eastern EU countries). No acute HIV, HBV, or HCV infection was detected. Evidence of past HBV infection (anti‑HBc) was found in n = 7 (14.6%; 95% CI: 6.8–26.5), past HCV in n = 1 (2.1%; 95% CI: 0.2–9.3). Syphilis serology was reactive in 12.5% (n = 6), with n = 2 (4.2%; 95% CI: 0.9–12.7) meeting criteria for treatment‑requiring infection. HBV vaccine‑induced immunity was documented in 43.8%; only 29.2% achieved titers ≥100 mIU/ml. Compared with regional surveillance data, the prevalence of acute notifiable STIs among sex workers was not increased. Conclusions In this rural setting, acute notifiable STIs were uncommon among registered sex workers, while past HBV infection and suboptimal HBV immunization were frequent. Public health efforts should prioritize HBV vaccination and syphilis prevention or treatment, and expand low‑threshold, trusted services tailored to this workforce.
Channels and countermeasures of the COVID-19 pandemic’s impact on urban economic resilience: Lessons from China
Resilience is a crucial ability of an economy to withstand sudden events and uncertain shocks. Using the entropy method, this study measures the economic resilience of 281 Chinese cities (prefecture-level and above) from 2017 to 2022, and empirically examines the impact of COVID-19 on this resilience, as well as its transmission channels. The results show that COVID-19 adversely affected overall urban economic resilience, with contrasting effects across its sub-dimensions: an insignificant negative impact on shock resistance, a significant negative impact on adaptive recovery, and an insignificant positive impact on innovative transformation. Transmission channels analysis reveals COVID-19 impaired urban economic resilience through the channels of employment structure, consumption, investment, and unrelated diversification, with consumption identified as the predominant one. Heterogeneity analysis reveals that the economic resilience of cities in both the high and low manufacturing specialization groups was more adversely affected by COVID-19 than that of cities in the medium group. Regarding services specialization, the economic resilience of cities with a medium degree of services specialization were more negatively affected by COVID-19 than that of cities with low services specialization. Furthermore, the economic resilience of cities with a higher degree of related diversification was less negatively affected by COVID-19. This study provides a replicable analytical framework and empirical evidence for enhancing urban economic resilience in China and other countries in post-pandemic era.
DeltaBreed: A BrAPI-centric breeding data information system
DeltaBreed is a unified breeding data management system designed by Breeding Insight (BI, Cornell University) to serve the wide diversity of USDA-ARS specialty crop and livestock breeding programs. DeltaBreed has a RESTful microservice architecture that utilizes the BrAPI v2.1 Java Test Server as its primary database. The system is interoperable with many BrAPI-compliant applications (BrApps), including Field Book v6.1.0, and is continually aligned with the most recent BrAPI specifications (BrAPI v2.1). Here we describe the features of DeltaBreed v1.0, a minimum viable product, and how we aligned data capture and validation with community standards. We highlight the modules for management of germplasm, observation variables, experiments and observations, genotypic sample submission, and a prototype genomic database that supports polyploid and multiallelic genomic data, as well as SNP data. Several test cases are illustrated to demonstrate the successes and challenges of interoperability with other open-source BrAPI-enabled software packages. We also discuss expansion and enhancement plans for future DeltaBreed versions, as well as outline possible solutions to known limitations. To our knowledge, DeltaBreed is the first species-agnostic, fully BrAPI-compliant breeding data management system built for transactional use.
Tracing low-level structures in cryo-electron tomography
Cryo-electron tomography is an imaging technique that provides 3D images (tomograms) in situ of cells with sub-nanometer resolution. Typically, the first step in the analysis is to classify the tomogram voxels into different structures, named semantic segmentation. However, the segmentation results are sets of voxels, hindering further quantitative analysis. In this paper, we define and implement algorithms to convert the semantic segmentation of the main structures in a cellular cryo-electron tomogram (membranes, filaments, cytosolic and membrane-bound macromolecules) into specific skeletons, preserving their topological and geometrical information. Additionally, we have defined a metric for comparing segmentations in cryo-ET coming from different methods more robust than the standard DICE. We also demonstrate how this approach can be used to trace cellular features by analyzing several in situ cellular cryo-electron tomograms.
R2GDN: RepGhost based residual dense network for image super-resolution
This study introduces a novel lightweight image super-resolution reconstruction network aimed at mitigating the challenges associated with computational complexity and memory consumption in existing super-resolution reconstruction networks. The proposed network optimizes its architecture through feature reuse and structural reparameterization, rendering it more suitable for deployment in edge computing environments. Specifically, we have developed a new lightweight reparameterization layer that derives redundant features from intrinsic features using low-cost operations and integrates them with reparameterization techniques to enhance efficient feature utilization. Furthermore, an efficient deep feature extraction module named RGAB has been designed, which retains dense connections, local feature integration, and local residual learning mechanisms while incorporating addition operations for feature integration. The resultant network, termed R 2 GDN, exhibits a significant reduction in model parameters and improved inference speed. Compared to performance-oriented super-resolution algorithms, our model reduces the number of parameters by approximately 95% and enhances inference speed by 86.8% on the edge device. When benchmarked against lightweight super-resolution algorithms, our model maintains a lower parameter count and achieves a 0.74% improvement in the structural similarity index (SSIM) on the BSD100 dataset for 4 × super-resolution reconstruction. Experimental results demonstrate that R 2 GDN effectively balances network performance and complexity.
Gender difference in self-reported empathy: Effects of task instructions and exposure to gender essentialism primes
Women often score higher on average than men on self-report measures of empathy. However, self-report estimates of empathic tendencies and other attributes could be susceptible to a range of biases. For instance, participants might respond in a manner that is socially desirable and aligns with gender stereotypes about empathic abilities. We examined whether gender differences in self-reported empathy were affected by a) manipulating task instructions or b) priming with fictive narratives describing gender differences as either fixed or malleable. In Study 1, participants (N = 154) completed questionnaire measures of empathy, social desirability and acceptance of stereotyping. Contrary to our prediction, gender differences in self-reported empathy were not larger when participants were told that we were measuring ‘empathy’. However, in both genders, average scores were higher for empathic concern in the ‘empathy’ condition than in the control condition, which suggests that describing the task as measuring empathy encouraged both male and female participants to present themselves as showing concern for others. Also, participants who scored higher on social desirability scored higher on empathic concern, suggesting a link between motivation to conform to social expectations and self-reported affective empathy. In Study 2, participants (N = 155) completed questionnaire measures of empathy, personality and gender essentialism. Gender differences in self-reported empathy were not larger in the condition that primed gender essentialism. However, women who scored high on empathic concern were more likely to align themselves with feminine adjectives, suggesting a link between self-reported consideration for others and feminine attributes. In both studies, on average, women scored significantly higher than men on self-reported empathic tendencies. Although the experimental manipulations did not impact empathy scores in either study, self-reported empathy appears to be related to social desirability and broader social attitudes, which suggests that a range of cultural and social factors might contribute to gender differences in empathy.
Sexual health and gender perspective among female physicians: a cross-sectional analytic study
Abdominojugular Reflux Test
The gift that shaped my career in science
Cooperative foraging between dolphins and fish-eating killer whales
Abstract Interspecies associations during foraging can range from competition to cooperation but are often complex and difficult to interpret. Using aerial drone and biologgers (n=9) equipped with video, acoustic and inertial sensors, we recorded interactions between fish-eating northern resident killer whales ( Orcinus orca ) and Pacific white-sided dolphins ( Lagenorhynchus obliquidens ) in the presence of adult Chinook salmon ( Oncorhynchus tshawytscha ). We observed frequent co-occurrence and coordinated movements, with the killer whales orienting towards the dolphins and following them to depth. We also recorded reduced echolocation and rolling movements by the killer whales in the presence of dolphins, suggesting that the whales may eavesdrop on dolphin echolocations to scan broader areas to locate large Chinook salmon—prey that are too big for the dolphins to capture and swallow whole. Captured fish were brought to the surface by the killer whales and broken apart for sharing with other matrilineally related pod members—while the accompanying dolphins scavenged scraps. No antagonistic interactions or avoidance behaviours were observed between the killer whales and dolphins. The spatially and temporally coordinated foraging behaviours we recorded suggest northern resident killer whales and dolphins opportunistically engage in cooperative foraging, which may improve the ability of killer whales to detect Chinook, while dolphins benefit by scavenging prey scraps—highlighting the need for further investigation into the ecological implications of these interspecific encounters.