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•Gliomas localise to hubs of high connectivity.•Dopaminergic, cholinergic, μ-opioid, and serotonergic neurotransmission are strongly associated with glioma distribution, also in IDHmt-LCNs and IDHwt-LCNs.•IDHmut-LCNs and IDHwt-LCNs exhibit the IDH-1 status influencing glioma distribution, with the involvement of important brain structures. Low-grade gliomas (LGGs) and high-grade gliomas (HGGs) often exhibit distinct spatial distributions, a phenomenon that remains incompletely understood. Based on previous research, we hypothesized that functional networks, neurotransmitters, and isocitrate dehydrogenase-1 (IDH-1) status characterize the spatial patterns of LGG and HGG. We analyzed 399 patients diagnosed with primary gliomas. First, we generated glioma frequency maps based on tumor grade, neurotransmitters, and IDH-1 status and constructed a brain functional connectivity network to explore heterogeneity in glioma location. Second, all tumor masks were mirror-symmetrized onto the brain’s left hemisphere to facilitate feature extraction. We performed independent component analysis on merged four-dimensional files using Multivariate Exploratory Linear Optimized Decomposition into Independent Component (MELODIC), identifying four IDH-1 wild-type lesion covariance networks (IDHwt-LCNs) and three IDH-1 mutant lesion covariance networks (IDHmut-LCNs) with distinct spatial distributions, and analyzing correlation between the neurotransmitter levels and the IDH-wt/mut specific LCNs. Finally, we compared 42 white matter fibers extracted using XTRACT with 39 functional brain connectivity networks from the multi-subject dictionary learning (MSDL) atlas, revealing significant associations among the frontal aslant tract (FAT) and the intraparietal sulcus (IPS). Our findings revealed high anatomical heterogeneity between LGG and HGG. Moreover, the high node strength played a critical role in the distinct spatial distribution of glioma. Significant correlations were observed between glioma frequency maps and dopaminergic, cholinergic, μ-opioid, and serotonergic neurotransmission. Furthermore, IDHwt/mut-LCNs analysis demonstrated that IDH-1 status influences glioma distribution, involving key brain structures. Lastly, we also found significant correlations between IDHwt/mut-LCNs and the neurotransmission of dopaminergic, cholinergic, μ-opioid, and serotonergic systems. Our study highlighted the mechanisms by which functional networks, neurotransmitter systems, and IDH-1 status collectively contribute to the anatomical heterogeneity observed in LGG and HGG.

Healing of cutaneous wounds is a complex and well-coordinated process requiring cooperation among multiple cells from different lineages and delicately orchestrated signaling transduction of a diversity of growth factors, cytokines, and extracellular matrix (ECM) at the wound site. Most skin wound healing in adults is imperfect, characterized by scar formation which results in significant functional and psychological sequelae. Thus, the reconstruction of the damaged skin to its original state is of concern to doctors and scientists. Beyond the traditional treatments such as corticosteroid injection and radiation therapy, several growth factors or cytokines-based anti-scarring products are being or have been tested in clinical trials to optimize skin wound healing. Unfortunately, all have been unsatisfactory to date. Currently, accumulating evidence suggests that the ECM not only functions as the structural component of the tissue but also actively modulates signal transduction and regulates cellular behaviors, and thus, ECM should be considered as an alternative target for wound management pharmacotherapy. Of particular interest are small leucine-rich proteoglycans (SLRPs), a group of the ECM, which exist in a wide range of connecting tissues, including the skin. This manuscript summarizes the most current knowledge of SLRPs regarding their spatial-temporal expression in the skin, as well as lessons learned from the genetically modified animal models simulating human skin pathologies. In this review, particular focus is given on the diverse roles of SLRP in skin wound healing, such as anti-inflammation, pro-angiogenesis, pro-migration, pro-contraction, and orchestrate transforming growth factor (TGF)β signal transduction, since cumulative investigations have indicated their therapeutic potential on reducing scar formation in cutaneous wounds. By conducting this review, we intend to gain insight into the potential application of SLRPs in cutaneous wound healing management which may pave the way for the development of a new generation of pharmaceuticals to benefit the patients suffering from skin wounds and their sequelae.

Zinc is an essential mineral for the body, with chelated zinc valued for its superior absorption efficiency and bioavailability. This review systematically examines peptide–zinc interactions, covering fundamental concepts, historical evolution, current insights, clinical relevance, technological innovations, and future outlooks. It delves into chelation mechanisms and structural theories, summarizes historical milestones in bioavailability research—particularly aquatic protein–zinc interactions—and details current studies on chelation efficacy and interaction dynamics. Clinical applications in nutritional supplements, therapeutic potential, and trial progress are discussed, alongside advances in analytical techniques, complex synthesis, and computational modeling. Future directions highlight emerging trends, application prospects, and challenges in bioavailability research, offering a comprehensive framework for subsequent investigations and practical implementations.

Depth perception is crucial for spatial awareness, enabling animals to interpret three-dimensional environments. Although the primary visual cortex (V1) is known to process depth information, the specific contributions of V1 neurons to various aspects of depth perception remain underexplored. In this study, we investigated how V1 neurons engage in both passive and active depth-related tasks, examining whether distinct neuronal populations support different aspects of depth processing. Using in vivo calcium imaging in freely moving mice, we observed that specific groups of V1 neurons are selectively active in passive (visual cliff) and active (depth discrimination) tasks, suggesting functional segregation within V1. Additionally, neurons in the primary visual cortex prefer encoding objective positions rather than egocentric distances in non-depth-based tasks. Moreover, egocentric distance discrimination, as reflected by the primary visual cortex, appears to be more prospective. These findings provide insight into V1’s versatility, highlighting its potential role in spatial navigation and decision-making.

Automatically extract lake water bodies of optical remote sensing images is a very challenging task, because there are many small lakes in such images, these small lakes have the characteristics of weak target information and are easily interfered by noise information. Regarding above problems, this paper proposes an automatic extraction method of lake water based on semantic segmentation. Firstly, a multi-scale information enhancement network is designed based on the encoder-decoder structure, and the deep dilation residual structure is used in the encoder module of the network to improve the network’s ability to mine the deep feature information and the context information of the lake water bodies. Secondly, the two-way channel attention mechanism is introduced into the network, which can reduce the interference of noise information on the lake boundaries and improve the accuracy of the network to the lake boundaries segmentation. Finally, the up-sampling convolution operation is used in the decoder module of the network to reduce the information loss during the up-sampling process. In this paper, the performance of the designed network is tested by using remote sensing images of lakes of different map scales and various evaluation indexes. The experimental results show that the designed network has better segmentation accuracy than other semantic segmentation networks.

To explore meibomian gland dysfunction (MGD) may determine the severity of dry eye conditions in visual display terminal (VDT) workers. Prospective, case-control study carried out in China.106 eyes of 53 patients (VDT work time >4 hour per day) were recruited as the Long time VDT group; 80 eyes of 40 control subjects (VDT work time ≤ 4 hour per day) served as the Short time VDT group. A questionnaire of Ocular Surface Disease Index (OSDI) and multiple tests were performed. Three dry eye tests: tear film breakup time (BUT), corneal fluorescein staining, Schirmer I test; and three MGD parameters: lid margin abnormality score, meibum expression assessment (meibum score), and meibomian gland dropout degree (meiboscore) using Keratograph 5 M. OSDI and corneal fluorescein score were significantly higher while BUT was dramatically shorter in the long time VDT group than the short time VDT group. However, the average of Schirmer tear volumes was in normal ranges in both groups. Interestingly, the three MGD parameters were significantly higher in the long time VDT group than the short time one (P<0.0001). When 52 eyes with Schirmer <10 mm and 54 eyes with Schirmer ≥ 10 mm were separated from the long time VDT workers, no significant differences were found between the two subgroups in OSDI, fluorescein staining and BUT, as well as the three MGD parameters. All three MGD parameters were positively correlated with VDT working time (P<0.0001) and fluorescein scores (P<0.0001), inversely correlated with BUT (P<0.05), but not correlated with Schirmer tear volumes in the VDT workers. Our findings suggest that a malfunction of meibomian glands is associated with dry eye patients in long term VDT workers with higher OSDI scores whereas some of those patients presenting a normal tear volume.

Queuing is almost inevitable in tourist service experiences, but most tourists are reluctant to wait. Drawing on prospect theory, this study examined how comparative framing influences tourists’ waiting intention. Across three scenario-based experiments, the research found that, compared with non-comparative framing, comparative framing can effectively enhance tourists’ waiting intention. Perceived waiting costs play a mediating role in the impact of the comparative framing on waiting intention. Additionally, the queuing settings play a moderating role, and the mediating effect is stronger in physical queues than in virtual queues. This research shifts the analytical focus from objective waiting time to the framing of waiting-time information, reveals a psychological cost assessment mechanism based on reference points, and enriches the theoretical explanation of tourists’ immediate decision-making in tourism services. It also provides practical references for optimizing service information and queue management during peak hours.

Segregative phase separation technology demonstrates substantial potential for precise molecular fractionation in food and biomaterial applications. The investigation elucidates the causal relationship between viscosity variations and phase separation dynamics, which govern molecular fractionation in GA/HPMC composite systems. By conducting a comparative analysis of two GA subtypes (CGA and SGA) and three HPMC grades with controlled viscosity gradients, we utilized gel permeation chromatography-multi-angle laser light scattering (GPC-MALLS) coupled with rheological characterization to elucidate the critical relationship between continuous phase viscosity and fractionation efficiency. Notably, increasing HPMC viscosity significantly intensified phase separation, resulting in selective enrichment of arabinogalactan-protein complexes: from 6.3% to 8.5% in CGA/HPMC systems and from 27.3% to 36.5% in SGA/HPMC systems. Further mechanistic investigation revealed that elevated HPMC viscosity enhances thermodynamic incompatibility while slowing interfacial mass transfer, synergistically driving component redistribution. These findings establish a quantitative viscosity–fractionation relationship, offering theoretical insights for optimizing GA/HPMC systems in emulsion stabilization, microencapsulation, and functional biopolymer purification via viscosity-mediated phase engineering.

Abstract Deep learning has made substantial progress in crowd counting, but in practical applications, due to interference factors such as perspective distortion and complex background, the existing methods still have large errors in counting. In response to the above problems, this paper designs a multi-scale feature fusion network (IA-MFFCN) based on the reverse attention mechanism, which maps the image to the crowd density map for counting. The network consists of three parts: feature extraction module, inverse attention module, and back-end module. First, to overcome the problem of perspective distortion, deeper single-column CNNs was designed as a feature extraction module to extract multi-scale feature information and merge them; second, to avoid interference of complex backgrounds, the inverse attention module was designed, through the multi-scale inverse attention mechanism, reducing the influence of noise on counting accuracy. Finally, to generate a high-quality crowd density map, dilation convolution was introduced. Simultaneously, to enhance the sensitivity of the network to crowd counting, a comprehensive loss function based on Euclidean loss and predicted population loss is designed to improve training accuracy, to produce a more accurate density value. Experiments show that compared with the comparison algorithm, the algorithm in this paper has a significant reduction in the mean absolute error (MAE) and mean square error (MSE) on the ShanghaiTech dataset, UCF_CC_50 dataset and WorldExpo`10 dataset.

Recently, phosphorylation has been applied to peptides to enhance their physiological activity, taking advantage of its modification benefits and the extensive study of functional peptides. In this study, water-soluble peptides (WSPs) of sea cucumber ovum were phosphorylated in order to improve the latter’s calcium binding capacity and calcium absorption. Enzymatic hydrolysis methods were screened via ultraviolet-visible absorption spectroscopy (UV–Vis), the fluorescence spectrum, and calcium chelating ability. Phosphorylated water-soluble peptides (P-WSPs) were characterized via high-performance liquid chromatography, the circular dichroism spectrum, Fourier transform infrared spectroscopy (FTIR), UV–Vis spectroscopy, surface hydrophobicity, and fluorescence spectroscopy. The phosphorus content, calcium chelation rate and absorption rate were investigated. The results demonstrated that phosphorylation enhanced the calcium chelating capacity of WSPs, with the highest capacity reaching 0.96 mmol/L. Phosphate ions caused esterification events, and the carboxyl, amino, and phosphate groups of WSPs and P-WSPs interacted with calcium ions to form these bonds. Calcium-chelated phosphorylated water-soluble peptides (P-WSPs-Ca) demonstrated outstanding stability (calcium retention rates > 80%) in gastrointestinal processes. Our study indicates that these chelates have significant potential to develop into calcium supplements with superior efficacy, bioactivity, and stability.