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Application validation and high-yield mechanism analysis of the desorption superposition effect method in Fukang block 8 based on well FS-24
Acoustic performance optimization of natural-fiber micro-perforated panels backed by an optimized polyurethane–fibrogranule composite
Prognostic impact of spatial niches in prostate cancer
Abstract The formation of intratumoral spatial niches has been reported for many human malignancies. However, the translational potential of such spatial niches is understudied. Herein, we utilize digital spatial profiling (DSP) to explore the prognostic relevance of spatially defined protein expression in high-risk prostate cancer. A total of 49 patient samples were analyzed for the expression of 46 proteins in 463 regions of interest (ROIs) from the tumor center ( n = 198) and the tumor periphery ( n = 265) resulting in 21,298 primary data points (mean per patient n = 9.4). Expression data from either the tumor center or the tumor periphery were not found to be prognostic. Protein expression of tumor center and periphery was then integrated into single datapoints by calculating the log 2 -transformed relative expression between the two niches for each protein and patient. Unsupervised hierarchical clustering of these data yielded two distinct patient subgroups. These clusters did not show a statistically significant correlation with known prognostic parameters yet significantly correlated with progression-free survival ( p = 0.014, log-rank, HR 0.43; 95% CI, 0.22–0.86). Our results thus reveal that spatial protein expression contains prognostic information, however, only when expression data from both spatial niches are taken into account. In conclusion, our proof-of-concept study shows that DSP can be exploited for the development of novel prognostic biomarkers that rely on spatially resolved protein expression.
Factors influencing the well-being of elderly population in home care mode and optimization research
Research on design strategy of one-piece ski suit driven by demand
Abstract In order to effectively obtain the design requirements and weights of users when wearing one-piece ski suits, and at the same time determine and quantify them into design strategies based on the requirements, so as to effectively improve user satisfaction and enhance user wear experience. This research first constructs a user journey map through user interviews, analyzes the behavioral paths of users when wearing ski suits and sorts out user needs; secondly, creates a Kano five-order two-factor questionnaire to investigate the user’s design needs evaluation of one-piece ski suits, and uses the Kano model to analyze the characteristics of user needs; thirdly, use the AHP hierarchical analysis method to construct a one-piece ski suit design needs analysis model, and proposes a one-piece ski suit design strategy based on calculating the user demand weights at each level, and finally tests the rationality of the method through design cases. The research results show that by establishing a method of obtaining user needs with Kano-AHP, the importance of one-piece ski suit design elements is sorted and quantified, and a design strategy to improve user satisfaction is proposed more scientific and reasonable, providing new methods and ideas for related design research.
Investigation and research on germplasm resources of Lonicera oblata in China
A low-profile compact dual-sense quad-port circularly polarized MIMO antenna for 5G mmWave networks
Innovative application of a traffic-prediction spatio-temporal graph convolutional network for dengue disease forecasting
Abstract Dengue fever, a vector-borne disease, is a major public health challenge. Accurate prediction methods that can better reflect the complexity of the outbreak are essential for dengue prediction and vector control. In this study, we introduce an adapted Spatio-Temporal Graph Convolutional Network (STGCN), originally developed for traffic forecasting, to predict weekly dengue cases in nine countries in South and Central America from 2014 to 2022. In this approach, we use environmental and socio-economic data in addition to climate data and historical dengue case information to capture complex transmission dynamics. We evaluate the STGCN against a Random Forest (RF) model using the same predictors. The evaluation results show that the STGCN model effectively captures outbreak dynamics and short-term trends. This was especially evident in cases where early transmission patterns are critical. In most of the countries analyzed, STGCN outperformed the baseline random forest model, especially in short-term forecasts, and achieved lower forecast errors in most settings. Forecasting performance varied across regions, with $$\hbox {R}^2$$ values ranging from 0.78 to 0.98 and RRMSE between 0.14 and 0.43 in short-term forecasts. The strength of the STGCN algorithm lies in its ability to capture spatio-temporal dependencies and handle heterogeneous data sources. This has been particularly valuable in areas with a high dengue burden. Although performance of the model varied slightly across countries, our overall findings highlight the robustness and adaptability of STGCN as a graph-based deep learning framework for dengue surveillance and early detection of its outbreaks.
Night-eating syndrome is associated with food consumption frequency among Chinese college students
Abstract Patients with night-eating syndrome (NES) exhibit circadian rhythm dysfunction and comorbidities, including insomnia, anxiety, and depression. Therefore, understanding its potential risks and consequences is crucial. This study examined associations between night-eating syndrome (NES), food consumption frequency, and the frequency of consuming three daily meals among Chinese college students. A total of 11,856 university students (mean age 18.8 years) participated in this large-scale cross-sectional study. NES was assessed using the Nocturnal Eating Questionnaire and categorized as no NES (score < 25), mild NES (25–30), or severe NES (> 30). Food consumption frequency was evaluated across five categories—fruits, vegetables, fast food, snacks, and sugary beverages. The frequency of consuming breakfast, lunch, and dinner was also recorded. Multivariate logistic regression analyses were used to examine associations between NES severity and food consumption frequencies and meal-consumption frequency. After adjusting for confounders, NES was positively associated with higher consumption of fruits, vegetables, snacks, and sugary beverages, and with more frequent breakfast and lunch consumption. However, no significant associations were observed for fast food or dinner frequency. These findings indicate that NES is associated with distinctive eating patterns among college students and underscore the importance of considering NES when evaluating dietary behaviors in this population.
Enhancing quantum audio watermarking security through joint verification and certification
Abstract Current quantum audio watermarking schemes prioritize robustness but often overlook critical security vulnerabilities, leaving systems exposed to impersonation and unauthorized use. To address this gap, we propose a dual-security mechanism that synergistically integrates joint verification and certification of watermarks, inspired by the paging seal principle. Our framework incorporates Quantum Error Correction (QEC) coding to enhance resilience against qubit errors and malicious tampering. Experimental results show improved performance: the watermark maintains high imperceptible with SNR> 46 dB under increased embedding rates, and achieves a 62.5% reduction in average BER compared to several state-of-the-art methods at a qubit error probability of 0.10. These results suggest that the proposed approach offers enhanced security and robustness, representing a promising direction for secure quantum audio watermarking.
Meta-learning for few-shot open task recognition
GOLGB1 deficiency accelerates intervertebral disc degeneration by activating the MAPK pathway
Comparison of the properties of nanopaper from chitin nanofibers prepared by mechanical and TEMPO-oxidized methods
Parkin overexpression attenuates muscle atrophy and improves mitochondrial bioenergetics but not histological features of Duchenne muscular dystrophy in mice
Abstract Duchenne Muscular Dystrophy (DMD) is the most common childhood muscular disorder. Mitochondrial dysfunctions are key disease features of the disease, and strategies that improve mitochondrial health have emerged as promising to slow disease progression. Emerging evidence indicates that impaired/insufficient mitophagy may contribute to the accumulation of mitochondrial dysfunction seen in patients and animal models of DMD. We therefore hypothesized that overexpressing Parkin, a key mitophagy regulator, may improve mitochondrial and muscle health in a mouse model of DMD. To this end, Parkin was overexpressed using intramuscular injections of adeno-associated viruses performed in 5-week-old and 18-week-old D2.B10-Dmd mdx /J mice (D2.mdx), a widely used mouse model of DMD. Four and 16 weeks of Parkin overexpression initiated in 5-week-old and 18-week-old D2.mdx, respectively, resulted in muscle hypertrophy, as indicated by an increase in muscle mass and fiber cross-sectional area. While Parkin overexpression did not impact maximal mitochondrial respiration or mitochondrial content, it increased the Acceptor Control Ratio, an index of mitochondrial bioenergetic efficiency. Parkin overexpression also decreased mitochondrial H 2 O 2 emission, a surrogate for mitochondrial ROS production. However, Parkin overexpression failed to reduce the proportion of fibers with central nuclei and markers of muscle damage and/or necrosis. Taken all together, our results indicate that Parkin overexpression can attenuate muscle atrophy, improve mitochondrial bioenergetics and lower mitochondrial ROS production in a mouse model of DMD. These findings showcase the partial beneficial effects of overexpressing Parkin in ameliorating some, but not all, pathological features observed in a mouse model of DMD.
Socioeconomic and nutritional determinants outweigh gut microbiota influence on neurodevelopment in young children from Antananarivo, Madagascar
Abstract In 2024, stunted child growth affected 150 million children under the age of five years, underscoring its critical impact on global health. Stunting has also been associated with neurodevelopmental delays. This study explores the relationship between stunting, the fecal microbiota, and neurodevelopment in 2–5-year-old children from the Afribiota cross-sectional study in Madagascar. Children were assessed using the Ages and Stages Questionnaire (ASQ-3), covering five developmental domains (communication, personal-social, problem-solving, fine and gross motor). Fecal samples were analyzed via 16S rRNA gene amplicon sequencing. Classical bi- and multivariate analysis was combined with Structural Equation Modelling to evaluate direct and indirect associations between different clinical factors, the microbiota and neurodevelopment. Our study shows that stunting and low socioeconomic status are consistently linked to poorer neurodevelopmental outcomes, while low branched-chain amino acids and hemoglobin levels are associated with stunting. Furthermore, a higher microbial diversity within individuals (α-diversity—specifically the Shannon index-) was directly linked to improved neurodevelopment scores in one of the tested models, while gut microbiota variation between individuals (β-diversity) was not associated with neurodevelopment. These findings support the hypothesis of neurodevelopment being primarily influenced by nutritional and social factors, with a more limited role for microbiota diversity.
Correction: EgoVision: a YOLO-ViT hybrid for robust egocentric object recognition
Young honey bees Apis mellifera learn to avoid pollen contaminated with glyphosate or imidacloprid
GPR156 is required in sensory hair cells for proper auditory and vestibular function
Abstract Proper orientation of the apical cytoskeleton in auditory and vestibular hair cells is essential for their sensory function. A recently identified regulator of hair cell orientation is the G protein-coupled receptor GPR156, which signals through inhibitory heterotrimeric G proteins. In hair cells expressing the transcription factor EMX2, GPR156 is apically enriched and polarized at cell junctions. There, GPR156 signaling reverses the interpretation of tissue-level core planar cell polarity cues, effectively reversing the orientation of Emx2 -positive compared to Emx2 -negative hair cells. This mechanism establishes key anatomical features, such as the correct alignment of auditory outer hair cells and the line of polarity reversal in the otolith organs of the vestibular system. Null mice with constitutive Gpr156 inactivation exhibit severe hearing loss, mirroring congenital hearing impairment in human patients with homozygous GPR156 variants. These null mutants also display impaired swimming and vestibulo-ocular reflexes, although the nature of these vestibular deficits differs from those reported in Emx2 mutants. Here, to determine the extent to which functional deficits arise from hair cell misorientation, we conditionally inactivated Gpr156 in postmitotic hair cells in the inner ear. This targeted deletion approach recapitulated the misorientation phenotype observed in null mutants. Notably, 30–40% of cochlear and utricular hair cells affected in the null background retained normal orientation in conditional mutants, likely due to the later timing of Gpr156 inactivation. Despite reduced efficiency, conditional mutants exhibited similar, albeit predictably milder, auditory and vestibular dysfunction. As hair cells can carry out mechano-electrical transduction without GPR156, we conclude that sensory deficits mainly result from its essential role in hair cell orientation.
Molecular characteristics and prognostic insights into BRCA-associated breast cancer in Kazakhstan
Abstract Breast cancer remains the leading cause of cancer morbidity and mortality among women worldwide. Approximately 5–10% of cases involve pathogenic BRCA1/2 variants, typically associated with early-onset, aggressive disease. This study aimed to determine the frequency and spectrum of BRCA1/2 mutations among Kazakhstani breast cancer patients and to analyze their associations with clinicopathological features and survival outcomes. A total of 186 patients aged 21–90 years were examined between December 2023 and June 2024 using next-generation sequencing and retrospective chart review. The median age was 44 years for BRCA1 , 48 for BRCA2 , and 51 for BRCA -negative patients. Advanced disease (stages III-IV) was more common among mutation carriers ( p < 0.001). Pathogenic BRCA1 and BRCA2 variants were found in 22% and 9% of cases, respectively; BRCA1 tumors were predominantly triple-negative (88%), whereas BRCA2 tumors were mainly hormone receptor–positive (65%). Both subtypes were largely poorly differentiated (61% and 53%, respectively). The median progression-free survival was 34, 12, and 8 months for BRCA -negative, BRCA1 -, and BRCA2 -positive groups, respectively ( p = 0.001). To our knowledge, this is the first comprehensive analysis of BRCA1/2 mutation profiles among Kazakhstani women, highlighting distinct genotype-phenotype correlations and supporting the need for personalized therapeutic strategies in this population.