Browse Articles

Wide-angle all-optical filtering via defective distributed Bragg reflectors

Integrated two-photon and optoacoustic microscopy for functional neuroimaging

Improved IEC performance via emotional stimuli-aware captioning

Genetic prediction of immune cells, inflammatory proteins, and metabolite-mediated association between gut microbiota and COPD: a Mendelian randomization study

Association between visceral adiposity index and hyperuricemia and gout among US adults: a cross-sectional analysis of NHANES 2007–2018

Genome-wide association analysis and gene mining of flavonoids in Xanthoceras sorbifolia

Abstract Xanthoceras sorbifolia is a unique woody oilseed tree in China, and its leaves are rich in flavonoids, which are involved in plant growth, development and defense. However, the mining of flavonoid synthesis-related genes in Xanthoceras sorbifolia leaves is lacking. In this study, 226 leaves of Xanthoceras sorbifolia from eight provinces in the key distribution areas were measured for flavonoid content, and the differences in flavonoid content of Xanthoceras sorbifolia were analysed to screen out excellent seed sources and six excellent single plants with higher flavonoid content. Genome-wide association analysis (GWAS) was used to identify genes controlling the synthesis of flavonoids, and 62 significant Single nucleotide polymorphism (SNP) sites were identified, which were closely associated with 8 traits, and a total of 11 genes coding for proteins. We found that these genes mainly encode proteins such as WPP domain-associated protein (WAP) (Fragment), Protein pleiotropic regulatory locus 1 (PRL1) and Phosphomevalonate kinase, peroxisomal (PMK), etc. We found that these proteins may directly or indirectly affect the synthesis of flavonoids, which will provide a data base for molecular breeding and genetic improvement of Xanthoceras sorbifolia.

Navigating the C-Shape Canals: A Case Series on Endodontic Treatment with Bio-ceramic Sealers

Background: Atypical root canal morphologies, such as the C-shaped canal commonly found in mandibular second molars, present persistent diagnostic and therapeutic challenges. These configurations often go undetected due to their complex anatomy, increasing the risk of incomplete debridement, inadequate obturation, and ultimately, treatment failure. Accurate diagnosis, strategic planning, and clinical proficiency, along with the use of advanced diagnostic tools, are essential for achieving successful outcomes. This report presents clinical cases that highlight how effective treatment can be achieved while preserving tooth function through the integration of preoperative radiographs, magnification, and appropriate instrumentation and obturation systems. Case presentation: This case report presents three clinical scenarios in which preoperative assessment using radiographs and magnification loupes facilitated accurate identification of C-shaped canals and their anatomical variations. Management relied heavily on thorough chemical debridement rather than mechanical instrumentation. Bioceramic sealers were selected for obturation due to their excellent flow properties, ability to set in the presence of moisture, bioactivity, enhanced sealing ability, and inherent antimicrobial characteristics. Conclusion: The effective management of C-shaped canal systems is achievable through precise diagnosis, enhanced visualisation using magnification, and the use of modern endodontic technologies. Advanced rotary instrumentation, irrigant activation devices, and reliable obturation techniques such as bioceramic sealers and thermoplasticized filling—play a crucial role in achieving predictable and lasting treatment success.

Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets

Anticancer chemotherapy is an essential part of cancer treatment, but the emergence of resistance remains a major hurdle. Metabolic reprogramming is a notable phenotype associated with the acquisition of drug resistance. Here, we develop a computational framework that predicts metabolic gene targets capable of reverting the metabolic state of drug-resistant cells to that of drug-sensitive parental cells, thereby sensitizing the resistant cells. The computational framework performs single-gene knockout simulation of genome-scale metabolic models that predicts genome-wide metabolic flux distribution in drug-resistant cells, and clusters the resulting knockout flux data using uniform manifold approximation and projection, followed by k -means clustering. From the clustering analysis, knockout genes that lead to the flux data near that of drug-sensitive cells are considered drug sensitization targets. This computational approach is demonstrated using doxorubicin- and paclitaxel-resistant MCF7 breast cancer cells. Drug sensitization targets are further refined based on proteome and metabolome data, which generate GOT1 for doxorubicin-resistant MCF7, GPI for paclitaxel-resistant MCF7, and SLC1A5 as a common target. These targets are experimentally validated where treating drug-resistant cancer cells with small-molecule inhibitors results in increased sensitivity of drug-resistant cells to doxorubicin or paclitaxel. The applicability of the developed framework is further demonstrated using drug-resistant triple-negative breast cancer cells. Taken together, the computational framework predicts drug sensitization targets in an intuitive and cost-efficient manner and can be applied to overcome drug-resistant cells associated with various cancers and other metabolic diseases.

Application of wings interferential patterns (WIPs) and deep learning (DL) to classify some Culex. spp (Culicidae) of medical or veterinary importance

Abstract In this paper, we test the possibility of using Wing Interference Patterns (WIPs) and deep learning (DL) for the identification of Culex mosquitoes species to evaluate the extent to which a generic method could be developed for surveying Dipteran insects of major importance to human health. Previous applications of WIPs and DL have successfully demonstrated their utility in identifying Anopheles , Aedes , sandflies, and tsetse flies, providing the rationale for extending this approach to Culex . Accurate identification of these mosquitoes is crucial for vector-borne disease control, yet traditional methods remain labor-intensive and are often hindered by cryptic species or damaged samples. To address these challenges, we applied WIPs, generated by thin-film interference on wing membranes, in combination with convolutional neural networks (CNNs) for species classification. Our results achieved over $$95\%$$ genus-level accuracy and up to $$100\%$$ species-level accuracy. Nonetheless, challenges with underrepresented species emphasize the need for larger datasets and complementary techniques such as molecular barcoding. This study highlights the potential of WIPs and DL to enhance mosquito identification and contribute to scalable tools for broader surveys of health-relevant Dipteran insects.

Factors influencing job satisfaction among public-sector employees in the united arab emirates: a cross-sectional study

Mitogenomes of mosquito species of Harris County in Texas

Mix design and performance prediction of EPS lightweight structural concrete based on orthogonal experimentation

Analysis of 2-dimensional regional differences in the peripapillary scleral fibroblast cytoskeleton of normotensive and hypertensive mouse eyes

Multiomics analyses of gut microbiota and metabolites in people living with HIV before and during SARS-COV-2 infection

On the movement of the honeybee queen in the hive

Abstract A honeybee colony is a complex and dynamic system that emerges out of the interactions of thousands of individuals within a seemingly chaotic and heterogeneous environment. At the figurative core of this system is the honeybee queen, responsible for the growth and reproduction of the eusocial superorganism. In this study, we examine the interaction between the queen and her surrounding environment by analyzing her movement patterns using mathematical models and computational approaches. We employed a visual tracking system to observe three queens of Apis mellifera within their colonies over a three-week period and analyzed sets of quality tracklets to provide observational evidence regarding the queens’ motion-related decision-making. Contrary to expectations, we found that the queen’s short-term motion characteristics—such as speed and turning—were remarkably invariant across distinct hive regions, suggesting a lack of direct environmental modulation at short timescales. Yet, long-term patterns showed structured and strategic behavior. Inter-stop distances followed a power-law distribution, and queens repeatedly revisited specific spatial zones over multi-day timescales. These results indicate a dual-scale movement strategy that is not captured by standard random walk models, highlighting internal state or memory-based navigation. Our findings suggest that queen movement is shaped by temporally layered processes that may support brood nest stability, efficient egg-laying, and colony cohesion.

The role of promoters on NiO catalysts for methane decomposition and hydrogen production

Jaw Mobility Restoration through Physiotherapy After Prolonged Dental Procedures: A Pilot Study

Long-term dental procedures may call for extended mouth opening, which might lead to temporomandibular joint pain, trismus, reduced jaw mobility following surgery, and so on. These problems impair important skills, including chewing, speaking, and maintaining tooth cleanliness, in addition to making one uncomfortable. Physiotherapy is a non-invasive and quick fix aimed to restoring normal jaw function by lowering muscular tension, improving joint flexibility, and thereby boosting the general range of motion. This research explores the efficiency of physiotherapeutic treatments, including thermosapy, manual therapy, passive stretching, and guided jaw exercises, in aiding functional recovery of the temporomandibular joint following significant dental treatments. Patients undertaking physiotherapy reported much improved masticatory ability, less pain, and jaw mobility. The findings underline the probable benefits of adding PT into postoperative therapy strategies to help with faster recovery and improved patient quality of life. Patient education, home-based exercise adherence, and a coordinated multidisciplinary approach combining dental specialists, physiotherapists, and pain experts are guarantees of best therapeutic effects. The study confirms the fundamental component of total dental treatment— physiotherapy inclusion especially in cases when extended treatments raise a patient's functional restrictions of the jaw.

On the mechanism of photodriven hydrogenations of N ₂ and other substrates by Hantzsch ester: Buffer is key to reactive H-atom donors

The Hantzsch ester (HEH 2 ) has found considerable utility as a photoreductant in synthesis, with photodriven transfer hydrogenation reactions typically limited to activated substrates. We recently established that the addition of an organic buffer of collidinium triflate [(ColH)OTf] and collidine (Col) allows photodriven transfer hydrogenation from HEH 2 to N 2 forming NH 3 (nitrogen reduction; N 2 R) in the presence of a Mo catalyst. Given the requirements for Mo-catalyzed thermally driven N 2 R, this result suggested the generation of a significant driving force for proton-coupled electron transfer (PCET) when irradiating HEH 2 in the presence of Col-buffer. In this study, we probe how Col-buffer enables efficient photodriven proton-coupled reductions with HEH 2 . Wavelength-dependent NH 3 yields are consistent with HEH 2 photoexcitation, and the combination of HEH 2 with Col-buffer is privileged. Data are presented, suggesting that HEH 2 is statically quenched via ET to [ColH]OTf through an H-bonded association complex to release ColH • and [HEH 2 ] •+ . Transient absorbance data and EPR studies establish that the resulting [HEH 2 ] •+ intermediate is rapidly deprotonated by Col to yield HEH • , in net furnishing HEH • and ColH • as potent H-atom donors. Broader utility of this reagent combination is demonstrated in the photoreduction of a range of C=O and N=O π-bonds by HEH 2 , with a significant boost in rates and yield, and altered reactivity, observed on addition of Col-buffer. ColH • is posited as the most potent PCET donor generated (BDFE N−H of 28 kcal mol −1 ).

Dog facial landmarks detection and its applications for facial analysis

Abstract Automated analysis of facial expressions is a crucial challenge in the emerging field of animal affective computing. One of the most promising approaches in this context is facial landmarks, which are well-studied for humans and are now being adopted for many non-human species. The scarcity of high-quality, comprehensive datasets is a significant challenge in the field. This paper is the first to present a novel Dog Facial Landmarks in the Wild (DogFLW) dataset containing 3732 images of dogs annotated with facial landmarks and bounding boxes. Our facial landmark scheme has 46 landmarks grounded in canine facial anatomy, the Dog Facial Action Coding System (DogFACS), and informed by existing cross-species landmarking methods. We additionally provide a benchmark for dog facial landmarks detection and demonstrate two case studies for landmark detection models trained on the DogFLW. The first is a pipeline using landmarks for emotion classification from dog facial expressions from video, and the second is the recognition of DogFACS facial action units (variables), which can enhance the DogFACS coding process by reducing the time needed for manual annotation. The DogFLW dataset aims to advance the field of animal affective computing by facilitating the development of more accurate, interpretable, and scalable tools for analysing facial expressions in dogs with broader potential applications in behavioural science, veterinary practice, and animal-human interaction research.

Sedentary behavior accelerates biological aging mediated by body mass index in adults

Abstract Sedentary behavior is widely recognized as a detriment to health. Limited conclusions have been drawn about the relationship between sitting time and biomarkers-measured aging. 12,504 eligible adults were included from the National Health and Nutrition Examination Survey (NHANES) 2007 to 2016. Weighted logistic regression, subgroup analysis, and restricted cubic spline regression were conducted to investigate the association and dose-response relationship between sitting time and phenotypic age acceleration (PhenoAgeAccel). The mediating effect of body mass index (BMI) on this correlation was revealed by mediation analysis. After adjusting for multiple covariates, longer sitting time (4–6 h: OR 1.30, 95%CI 1.06–1.58, p = 0.013; 6–8 h: OR 1.25, 95%CI 1.01–1.55, p = 0.038; ≥8 h: OR 1.58, 95%CI 1.33–1.88, p < 0.001) significantly had higher risk of aging comparing to the reference (< 4 h). The dose-response relationship exhibited an approximately linear dependence. Additionally, BMI partially mediated the association between sitting time and PhenoAgeAccel by a 21.0% proportion. Our study revealed a strong, significant, independent, linear relationship between sitting time and phenotypic age. BMI served as a mediator of the correlation between sitting time and PhenoAgeAccel.