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Videomicroscopy reveals individual response of MCF7 cells to X-ray irradiation

Understanding the heterogeneity of cellular responses to irradiation is a key factor in cancer research to improve radiotherapy efficacy. To this aim, time-lapse 2D videomicroscopy was used to track in vitro more than 6 300 individual MCF7 breast cancer cells exposed to single X-ray irradiation, with doses ranging from 0 Gy to 5 Gy. Cell tracking and lineage reconstruction were performed using a dedicated algorithm: Cell Lineage Tracking (CLT). The CLT algorithm achieves high robustness and reliability across irradiation conditions, with more than 95% correct lineage tree assignment and over 80% agreement in reconstructed cell cycle duration. It allowed classification and study of the properties and fates of different cell categories (proliferative, transiently arrested and long-term arrested) and revealed distinct behavior, notably in individual cell surface area and diffusion properties. Cell surface area increased progressively across cell categories, from approximately 5 000 μ m 2 in proliferative cells to about 50 000 μ m 2 in long-term arrested cells, with transiently arrested cells showing intermediate values and their daughter cells approaching those of proliferative cells. Cell surface also increased with higher doses within each cell category. In contrast, diffusion decreased across cell categories, from around 0.4   μ m 2 / h  in proliferative cells to around 0.02   μ m 2 / h  in long-term arrested cells, with transiently arrested cells showing intermediate diffusion and their daughter cells approaching the dynamic behavior of proliferative cells. Within each cell category, diffusion did not show a clear dependence on dose. This novel single-cell and lineage-level framework highlights the importance of dynamic analyses in uncovering the complexity and heterogeneity of radiation responses.

River interlinking and biodiversity risks in Indian freshwater ecosystems

Cobalt-Catalyzed Syntheses of Acrylamides and Succindiamides from Alkynes and Amines Promoted by Light

SSH-YOLO: YOLOv8 improved model based on Object Detection in Complex Road Scenes

To address the problem of insufficient detection accuracy for dense targets, small targets and partially occluded objects in complex road scenarios, an improved object detection model, SSH-YOLO, is proposed. On the basis of YOLOv8n, the model optimizes and improves performance through a three-level collaborative architecture: 1) introduce the spatial and deep conversion (SPDConv) module in the backbone network to replace the traditional step downsampling with nonstep convolution, retain the fine-grained features of small targets, and solve the feature loss problem of low-resolution images; 2) embed the spatial and channel collaborative attention module (SCSA), through cross-scale feature fusion (SMSA) and channel weight progressive optimization (PCSA), focus on the key visible areas of the occluded target and suppress background interference such as roadside vegetation; and 3) add a new 160 × 160 resolution small object detection head, combined with the original P3‒P5 layer to form a four-level detection system, covering long-distance small targets < 32 × 32 pixels. The experimental results show that the improved model performs well on the self-built RoadScene-Complex dataset and four public datasets BDD100K: 0.729 (12.4% higher than YOLOv8n) on the RoadScene-Complex dataset mAP@0.5 (12.4% higher than YOLOv8n) and 0.868 (7.6% higher than the KITTI dataset) mAP@0.5). COCO small target subset mAP@0.5 to 0.585 (up 16.5%), and CityPersons occluded scene mAP@0.5 to 0.739 (up 22.8%). At the same time, it maintains lightweight characteristics and has an inference speed of up to 60 FPS to meet the needs of real-time on-board detection. The research results provide a balanced solution of “accuracy-speed-lightweight” for high-precision target detection in complex traffic scenarios, especially in small target and occlusion scenarios.

GPU-accelerated modeling of biological regulatory networks

Excited-State S _N Ar Reactions of Nitroarenes

Xanthan gum intake modifies the colon microbiota profile and causes mild colon inflammation in rats

Xanthan gum is commonly used in the food industry to adjust food consistency and to improve the safety of swallowing liquids and food in people with dysphagia. The pro-inflammatory effect of xanthan gum is acknowledged in the literature. This study aimed to examine the effect of chronic xanthan gum supplementation in the diet on intestinal inflammatory processes in adult Wistar rats at three different doses. After the tenth week of treatment, white adipose tissue (epididymal, retroperitoneal, and mesenteric) was collected, and the distal colon was dissected and processed for cytokine and immunohistochemical analysis. Fecal matter from the colon was used for microbiota analysis. In general, the addition of xanthan gum at all doses promoted an inflammatory state as demonstrated by the high presence of lymphocytes. Also, it modified the content of the pro-inflammatory cytokines IL-1β and TNF-α compared to the control group. Regarding the colon barrier markers, xanthan gum increased the Claudin 2 and ZO-1 levels. The α diversity and relative abundance of Bacterioidetes (B), Firmicutes (F), F/B ratio were similar among the groups. Elusimicrobiota was increased. Our research, using an experimental model, confirmed the clinical assumption that xanthan gum is associated with the development of necrotizing enterocolitis in neonates. We validated the biological mechanism and metabolic pathway in the intestine of the deleterious effect of continuous use of xanthan gum. In conclusion, dietary xanthan gum induced moderate-grade inflammation and modified the colon gut barrier. Recent advances in the study of xanthan gum underscore the need for translational research bridging experimental findings and clinical practice.

Uterine rupture risk during trial of labor after one cesarean in a population-based cohort study of induction method and labor management

Abstract A prior cesarean section is the primary risk factor for uterine rupture in a trial of labor after cesarean, a rare event associated with severe maternal and neonatal morbidity and mortality. This population-based cohort study aimed to determine the risk of uterine rupture in women undergoing trial of labor after one previous cesarean section in the Stockholm-Gotland Region and to examine associations between induction methods, labor management, and rupture risk. The cohort included 11,947 women with a cephalic-presenting, singleton infant at ≥ 37 + 0/6 weeks of gestation. Incidence of uterine rupture was calculated by labor onset and management strategies. Multivariable logistic regression assessed associations between labor characteristics, uterine rupture, and adverse maternal and perinatal outcomes. Overall, 216 (1.8%) women experienced uterine rupture. Induction of labor was associated with higher odds of rupture than spontaneous onset (aOR 1.63; 95% CI 1.20–2.22). Prostaglandin induction showed 2.6-fold increased odds (aOR 2.58; 95% CI 1.77–3.74), while balloon catheter showed no association (aOR 0.99; 95% CI 0.61–1.61). Prostaglandin use was thus linked to increased risk of uterine rupture, whereas balloon catheter induction was not. When induction is necessary, mechanical methods may be safer, though vigilant monitoring remains crucial.

Diastereoselective Synthesis of Housanes via the Carbocupration of Cyclopropenes

Using instant messaging applications for consultations in the emergency department: A cross-sectional survey

Study objective This study investigates how consultants and consultees use Instant Messaging Applications (IMAs) during Emergency Department (ED) consultations, examining their attitudes toward these tools and assessing perceptions of existing consultation methods and the perceived need for system improvements. Methods A cross-sectional study was conducted among clinicians involved in Emergency Department consultations at the American University of Beirut Medical Center, Lebanon. Participants completed an online questionnaire assessing their demographics, consultation patterns, IMAs usage, and opinions on consultation modalities. The recruitment period was from 13/11/2023–08/11/2024. Results A total of 120 participants were included (65 consultants, 55 consultees). Consultants were significantly older than consultees (28.7 ± 3.4 vs. 26.6 ± 1.91 years, p < 0.001). While all consultees were residents, 64.6% of consultants were residents and 35.4% were fellows (p < 0.001). All participants reported using smartphones when on call (100%). IMAs were the most preferred consultation method overall (48.3%), followed by smartphone calls (32.5%). Consultants favored smartphone calls significantly more than consultees (49.2% vs. 12.7%, p < 0.001), whereas consultees preferred workstation phone calls (30.9% vs. 0%, p < 0.001). WhatsApp was the dominant IMA used (98.9%). During night shifts, consultants demonstrated a significantly greater reliance on smartphone calls than consultees (84.6% vs. 63.6%, p = 0.008). IMAs were among the most frequently used methods during both day and night calls (80% vs. 65.2%), and two-thirds of participants (63.7%) reported concerns regarding legal implications and the need for improved consultation tools. Conclusion The findings highlight the need for structured and secure digital solutions to optimize communication between healthcare teams. With IMAs increasingly embedded in ED consultations, future work should focus on developing dedicated and potentially AI-supported platforms that enhance efficiency, documentation, and data security in clinical communication.

Casein genotypes associate with baseline and dynamic regression components of seminal quality in Murciano-Granadina bucks

Abstract This study examined associations between αS1- and κ-casein genotypes and baseline and dynamic regression components of semen quality in Murciano-Granadina bucks using cubic regression models applied to 6,868 ejaculates collected over 10 years, with age at sperm collection as the time axis. Regression decomposition into baseline (b 0 ), linear (b 1 ), curvature (b 2 ), and cubic tren (b 3 ) coefficients enabled quantification of static trait levels and age-dependent dynamics, revealing substantial coefficient variability. For αS1-casein, genotype was associated with baseline progressive motility and total added semen volume ( p  < 0.05), with moderate to large discriminant effects for progressive motility (ηp 2 = 0.277, 95% CI 0.03–0.48) and curvature-related motility and Acrosome Integrity/Intact acrosomes components (ηp 2 = 0.212–0.245), indicating genotype-related differences in modeled semen quality rather than direct fertility effects. In contrast, κ-casein genotypes showed predominantly small to moderate effects, mainly related to ejaculate volume dynamics and baseline sperm concentration (ηp 2 = 0.131–0.138), while most other components were negligible. Cubic terms captured subtle non-linear trajectories, particularly for sperm concentration and endosmosis, highlighting their relevance for long-term trait stability. Discriminant analyses indicated model-based separation of αS1–κ genotype combinations, with EE–AA ( n  = 1) and BE–AA ( n  = 3) aligning with higher sperm motility, concentration, and favorable membrane-integrity responses, whereas BB–BB ( n  = 3) aligned with higher semen volume and lower quality traits. Validation procedures were method-specific. CDA using leave-one-out cross-validation showed stronger discrimination for αS1-casein (74.03%) than κ-casein (64.94%), driven by perfect classification of the dominant BE genotype and substantial misclassification of rarer genotypes, whereas CHAID using 10-fold cross-validation showed moderate predictive performance with lower risk for αS1-casein (0.325, SE = 0.074; accuracy = 67.53%) than κ-casein (0.429, SE = 0.079; accuracy = 57.14%). Press’ Q statistics confirmed that classification accuracy for both genotypes exceeded chance expectation across methods (CDA: αS1-casein Q = 182.40, κ-casein Q = 34.60; CHAID: αS1-casein Q = 143.44, κ-casein Q = 19.64; p  < 0.05), with consistently stronger discrimination for αS1-casein genotypes. Overall, baseline and dynamic regression components capture biologically relevant, exploratory associations between casein polymorphisms and semen quality dynamics, supporting their integration into genomics-informed reproductive management strategies.

Electric Double Layer Phenomena Near Surfaces Irreversibly Trigger Assembly of Tau Protein

Acute pain sign recognition by dog owners in a home setting

To identify behavioural changes indicative for acute pain in dogs that are recognized by their owners and the wording used to describe these, we asked owners of 51 dogs treated at the Small Animal Clinic of Utrecht University, to document and video tape observed behavioural changes and estimate their dog’s level of pain within the first week after clinical discharge. Quantitative data was tested with logistic regression analysis for the predictability of certain behavioural changes to occur at higher owner-estimated pain scores. Owner-recorded videos were analysed independently by three veterinarians to provide a professional reference perspective. Free text entries from participants were analysed qualitatively and the wording used by owners whose dogs were deemed in pain according to the veterinary video evaluation, was extracted. We found that the most often reported behavioural changes on the day of discharge, and on the two days thereafter were: changes in walking (72.1% n  = 44/61), playing with an object (70.5%, n  = 43/61) and playing with the owner (68.9%, n  = 42/61). The empirical data indicated a decrease in, e.g., playing behaviour, explorative behaviour and eating. Logistic regression analyses showed a significant association between owner-estimated pain scores and behavioural changes for these tested items. No correlation was found between pain estimation by the veterinarians and the dog owners. The qualitative text analysis of entries from owners whose dogs were deemed in pain, provided insight into wording used to describe pain-related behavioural changes by owners, that may be used in the context of developing an owner-directed acute pain scoring instrument. Such an instrument is needed to help owners recognize and correctly interpret pain-induced behavioural changes, to ensure adequate pain management and animal welfare after clinical discharge.

A two-stage multi-objective optimization framework for coordinated EV charging scheduling and reactive power dispatch

Abstract Car exhaust emissions significantly contribute to the depletion of the ozone layer. Electric vehicles (EVs) present a sustainable alternative to mitigate this environmental issue. However, the large-scale adoption of EVs introduces challenges for the power grid, primarily due to irregular and uncoordinated charging patterns. This study proposes a comprehensive two-stage framework for optimizing electric vehicle (EV) charging patterns and reactive power dispatch within power distribution systems. In Stage 1, two types of EV charging schedules are developed and compared: day-ahead charging and real-time charging. Day-ahead charging involves planning EV charging over a 24-hour horizon with the objective of minimizing load variance, energy cost, active power losses, and voltage drop, while simultaneously maximizing voltage stability. Real-time charging dynamically adjusts charging behavior based on immediate grid conditions to minimize load variance and charging costs. Stage 2 focuses on optimal real-time reactive power dispatch, utilizing the reactive power capabilities of EV inverters to further reduce the active and reactive power losses. Additionally, the study analyzes EV behavior in response to sudden load changes, providing critical insights for enhancing grid performance. Different optimization algorithms are implemented to efficiently solve the proposed models, including particle swarm optimization, dandelion optimization, wild horse optimization, and slime mould optimization. The optimization is formulated as a multi-objective problem to consider both grid constraints and customer satisfaction. The proposed framework is applied and tested on a 33-bus radial distribution system with 984 electric vehicles using MATLAB M-files, while power flow calculations are performed using the MATPOWER toolbox. Simulation results demonstrate the effectiveness of the proposed framework. Daily active power losses are reduced from 4.04 MWh to 2.55 MWh and 2.77 MWh under day-ahead and real-time planning strategies—representing reductions of 36.8% and 31.4%, respectively. Similarly, EV charging costs drop from 552.31 USD to 394.19 USD and 363.68 USD, achieving cost savings of 28.63% and 34.15%. Furthermore, voltage profiles are maintained within the acceptable operational limit of 0.95 p.u. These outcomes highlight the significant advantages of the proposed methodology in enhancing grid efficiency while ensuring user satisfaction.

Operando Cu Aggregation-Induced Spin State Modulation in Fe–Cu Single Atom Catalyst for Enhanced Tandem Electrochemical Nitrate Reduction Reaction

Enhancing sustainable innovation through collaborative knowledge absorption: Insights from the development of a hybrid marine engine

Rapid technological advancements, characterized by uncertainties, together with the growing imperative for environmental sustainability, are continuously reshaping markets and business strategies. These developments necessitate integrating sustainable innovation with effective knowledge absorption to promote technological progress. While prior research has primarily examined drivers of sustainability at the macro level, comparatively limited attention has been given to the processual and micro-level dynamics through which sustainable innovation unfolds. As a result, the underlying mechanisms, individual actions, and collaborative knowledge processes that shape sustainable innovation remain insufficiently theorized and empirically explored. To address this gap, this study draws on effectuation theory and absorptive capacity to conceptualize sustainable innovation as an iterative, stakeholder-driven process in which knowledge is acquired, assimilated, transformed, and exploited. Empirically, the study adopts an in-depth case analysis of the development of a hybrid marine engine – i.e., a propulsion system for vessels that combines a conventional combustion engine with electric propulsion from batteries – to refine this framework. The results identify five distinct phases of the sustainable innovation process, each influenced by specific dimensions of individuals’ collaborative knowledge absorption. This study contributes to the sustainability and innovation literature by integrating insights from effectuation, knowledge absorption, and entrepreneurial behavior into a structured framework. In doing so, it provides both theoretical advancement and practical guidance for policymakers and business practitioners seeking to foster sustainable innovation in technology-driven contexts.

Pan-cancer analysis and breast cancer validation reveal DEAD-box helicase 23 as a crucial prognostic and immuno-biomarker

Scalable Zn Single Atom-Gluing Ru for 75-W-Scale Alkaline Membrane Fuel Cell Stacks

The role of bacteria in wastewater treatment and the impact of treated wastewater on riverine bacterial ecosystems

Spatiotemporal analysis of bacterial communities in wastewater can explain the role of bacteria in removing organic matter, phosphorus, and nitrogen as well as the impact of wastewater treatment on riverine ecosystems. This study investigated the bacterial dynamics within an anaerobic–anoxic–oxic (A 2 O) wastewater treatment plant (WWTP), comprising anaerobic, anoxic, and aerobic tanks, in Tokyo and its impact on the receiving Tama River. 16S rRNA gene analysis and ion chromatography were used to monitor bacterial composition and nutrient concentrations, respectively, to assess the effectiveness of nutrient removal across seasonal temperature variations, and the influence of treated wastewater on riverine bacterial communities. The A 2 O process effectively removed nutrients, but the nitrification efficiency was affected by temperature, with decreased temperatures correlating with reduced Nitrospira abundance, while nitrate concentrations increased due to higher influent ammonium loads. The WWTP bacterial community exhibited a polarized structure with a dominant core community that was stable over time and across tanks. The abundance of bacterial DNA introduced into the river via treated wastewater decreased downstream, indicating the spatial attenuation of the wastewater treatment impact on the riverine ecosystem. This study demonstrated the temperature sensitivity of WWTP processes, and the transient impact of treated wastewater discharge on river bacterial communities, thereby emphasizing the importance of understanding these dynamics for effective environmental conservation.

Contact force identification in pantograph–catenary system via elastic support beam theory and enhanced l1 sparse regularization scheme