Functional Networks Research Articles

Striatal-hippocampal functional connectivity contributes to real-life positive anticipatory experiences and subjective well-being.

Positive anticipatory experiences are key to daily well-being. However, the brain's functional architecture underlying real-world positive anticipatory experiences and well-being remains unexplored. In the present study, we combined an ecological momentary assessment and resting-state functional neuroimaging to identify the neural predictors of real-world positive anticipatory experiences and explore their relationships with subjective well-being (SWB). With a model-based approach, we quantified participants' accuracy in predicting positive events and the degree to which participants' affective states were influenced by the positive anticipation. We found that individuals with higher accuracy in predicting upcoming positive events showed greater SWB, and this relationship was mediated by greater positive anticipatory feelings. Importantly, functional connectivity of the dorsal and ventral striatal-hippocampal networks significantly predicted the accuracy and positive anticipatory feelings, respectively. These functional networks were further predictive of SWB. Our findings provide novel and ecologically valid evidence that the interplay between neural systems for reward-processing and memory plays an important role in real-life positive anticipatory experiences and everyday SWB.

Delayed Administration of IGFBP7 Improved Bone Defect Healing via ZO-1 Dependent Vessel Stabilization.

The vascular response following injury is pivotal for successful bone-defect repair but constitutes a major hurdle in the field of regenerative medicine. Throughout this process, vessel stabilization is crucial to provide an adequate nutrient supply and facilitate efficient waste removal. Therefore, this study investigated whether promoting vascular stabilization improves bone defect repair outcomes. The findings show that insulin-like growth factor-binding protein (IGFBP) 7 exhibits a novel biological function in attenuating vascular permeability and enhancing vascular wall integrity. The potential underlying mechanism involves the up-regulation of insulin-like growth factor 1 receptor (IGF1R) expression by IGFBP7 on endothelial cell membrane, followed by activation of the downstream PI3K/AKT signaling pathway and upregulated expression of the tight junction protein zonula occludens-1 (ZO-1). IGFBP7 delayed administration in mice with cranialdefects significantly improved bone defect healing by increasing ZO-1 and CD31 co-localization within vessel walls and optimizing the perfusion function of the final vascular network. Furthermore, the application of the typical tight junction regulator AT1001 effectively promoted ZO-1-dependent vascular stabilization and facilitated bone defect repair. This study presents a new approach to enhance bone defect healing via vascular stabilization-targeted interventions and significantly advances the understanding of the complex interplay between osteogenesis and angiogenesis in bone defect healing.

Altered dynamic functional connectivity in antagonistic state in first-episode, drug-naïve patients with major depressive disorder

ObjectiveMajor depressive disorder (MDD) is known to be characterized by disrupted brain functional network connectivity (FNC) patterns, while the dynamic change mode of different functional networks is unclear. This study aimed to characterize specific dynamic alterations pattern on intrinsic FNC in MDD by combining static FNC (sFNC) and dynamic FNC (dFNC).MethodsA total of 48 first-episode drug-naïve MDD and 48 matched healthy controls (HCs) were included in this study. The sFNC and dFNC were analyzed using complete time-series and sliding window approach, respectively. Both sFNC and dFNC differences between groups were analyzed and associations between disease severity and aberrant FNC were explored.ResultsMDD patients exhibited lower sFNC within and between sensory and motor networks than HC. Four dFNC states were identified, including a globally-weakly-connected state, a cognitive-control-dominated state, a globally-positively-connected state, and an antagonistic state. The antagonistic state was marked by strong positive connections within the sensorimotor domain and their anti-correlations with the executive-motor control domain. Notably, MDD patients exhibited significantly longer dwell time in the globally-weakly-connected state, at the cost of significantly shorter dwell time in the antagonistic state. Further, only the mean dwell time of this antagonistic state was significantly anticorrelated to disease severity measures.ConclusionsOur study highlights the altered dynamics of the antagonistic state as a fundamental aspect of disrupted FNC in early MDD.

Functional Neuroanatomy of the Normal and Pathological Basal Ganglia.

The term "basal ganglia" refers to a group of interconnected subcortical nuclei engaged in motor planning and movement initiation, executive functions, behaviors, and emotions. Dopamine released from the substantia nigra is the underlying driving force keeping the basal ganglia network under proper equilibrium and, indeed, reduction of dopamine levels triggers basal ganglia dysfunction, setting the groundwork for several movement disorders. The canonical basal ganglia model has been instrumental for most of our current understanding of the normal and pathological functioning of this subcortical network. This model explains how cortical information flows through the basal ganglia nuclei back to the cortex by going through two pathways with opposing effects that together lead to the proper execution of a given movement. The basal ganglia model has paved the way for the standard clinical management of Parkinson's disease, where pharmacological and neurosurgical treatments in place collectively afford an impressive symptomatic alleviation. Although much of the model has remained, the canonical model has been enriched with new arrivals gathered from evidence provided in the last three decades. Here, we sought to provide a comprehensive review of the basal ganglia network, with emphasis on structure, connectivity patterns, and basic operational principles, both in normal and pathological conditions.

Functional and structural cerebellar-behavior relationships in aging.

Healthy aging is associated with deficits in cognitive performance and brain changes, including in the cerebellum. Cerebellar communication with the cortex via closed-loop circuits through the thalamus have been established and these circuits are closely related to the functional topography of the cerebellum. In this study, we sought to elucidate relationships between cerebellar structure and function with cognition in healthy aging. We explored this relationship in 138 healthy adults (aged 35-86, 53% female) using resting-state functional connectivity MRI (fcMRI), cerebellar volume, and cognitive and motor assessments. Behavioral tasks assessed attention, processing speed, working memory, episodic memory, and motor abilities. We expected to find negative relationships between lobular volume with age, and positive relationships between specific lobular volumes with motor and cognitive behavior, respectively. We predicted lower cerebello-cortical fcMRI with increased age. Behaviorally, we expected higher cerebello-frontal and cerebello-association area fcMRI cerebellar connectivity to correlate with better behavioral performance. Correlations were conducted between cerebellar lobules I-IV, V, Crus I, Crus II, vermis VI and behavioral measures. We found lower volumes with increased age as well as both higher and lower cerebellar connectivity relationships with increased age, consistent with literature on functional connectivity and network segregation in aging. Further, we revealed unique associations between cerebellar structure and connectivity with comprehensive behavioral measures in a healthy aging population. Our findings further highlight the role of the cerebellum in aging.

Shape-based disease grading via functional maps and graph convolutional networks with application to Alzheimer’s disease

Shape analysis provides methods for understanding anatomical structures extracted from medical images. However, the underlying notions of shape spaces that are frequently employed come with strict assumptions prohibiting the analysis of incomplete and/or topologically varying shapes. This work aims to alleviate these limitations by adapting the concept of functional maps. Further, we present a graph-based learning approach for morphometric classification of disease states that uses novel shape descriptors based on this concept. We demonstrate the performance of the derived classifier on the open-access ADNI database differentiating normal controls and subjects with Alzheimer’s disease. Notably, the experiments show that our approach can improve over state-of-the-art from geometric deep learning.

Implementation and Experimental Application of Industrial IoT Architecture Using Automation and IoT Hardware/Software

The paradigms of Industry 4.0 and Industrial Internet of Things (IIoT) require functional architectures to deploy and organize hardware and software taking advantage of modern digital technologies in industrial systems. In this sense, a lot of the literature proposes and describes this type of architecture with a conceptual angle, without providing experimental validation or with scarce details about the involved equipment under real operation. Aiming at overcoming these limitations, this paper presents the experimental application of an IIoT architecture divided into four functional layers, namely, Sensing, Network, Middleware and Application layers. Automation and IoT hardware and software are used to implement and apply the architecture. Special attention is put on the software Grafana, chosen in the top layer to deploy graphical user interfaces that are remotely accessible via web. A pilot microgrid integrating photovoltaic energy and hydrogen served as scenario to test and prove the suitability of the architecture in four application cases.

Altered gray matter structural covariance networks in young adults with obesity.

Overwhelming evidence showed that obesity was associated with abnormal brain functional networks. However, the changes of structural covariance networks (SCNs) based on cortical thickness (CT) and cortical surface area (CSA) in obesity is still unclear. In this study, 243 young adults with obesity and matched 243 lean individuals were enrolled from the Human Connectome Project Release S1200 dataset. All participants underwent magnetic resonance imaging scans following clinical and neuropsychological assessments. SCNs matrices were constructed by Brain Connectivity Toolbox based on both CT and CSA. Nonparametric permutation tests were adopted to examine group differences of these matrices. Young adults with obesity exhibited lower CSA of left entorhinal cortex, but higher CT of both left rostral anterior cingulate cortex and right superior parietal lobule, as well as lower CT of left temporal pole. While in terms of global network measures, there were no significant group differences; in terms of nodal network measures, young adults with obesity exhibited alterations in widespread brain regions including left posterior cingulate cortex, bilateral superior frontal gyrus, left entorhinal cortex and right insula. Young adults with obesity exhibited abnormal nodal network measures in widespread brain regions involved in default mode network, central executive network and salience network. These findings indicate the adverse effects of obesity on young adults might be associated with the altered triple network.

Advancements in Global Phosphoproteomics Profiling: Overcoming Challenges in Sensitivity and Quantification.

Protein phosphorylation introduces post-genomic diversity to proteins, which plays a crucial role in various cellular activities. Elucidation of system-wide signaling cascades requires high-performance tools for precise identification and quantification of dynamics of site-specific phosphorylation events. Recent advances in phosphoproteomic technologies have enabled the comprehensive mapping of the dynamic phosphoproteomic landscape, which has opened new avenues for exploring cell type-specific functional networks underlying cellular functions and clinical phenotypes. Here, we provide an overview of the basics and challenges of phosphoproteomics, as well as the technological evolution and current state-of-the-art global and quantitative phosphoproteomics methodologies. With a specific focus on highly sensitive platforms, we summarize recent trends and innovations in miniaturized sample preparation strategies for micro-to-nanoscale and single-cell profiling, data-independent acquisition mass spectrometry (DIA-MS) for enhanced coverage, and quantitative phosphoproteomic pipelines for deep mapping of cell and disease biology. Each aspect of phosphoproteomic analysis presents unique challenges and opportunities for improvement and innovation. We specifically highlight evolving phosphoproteomic technologies that enable deep profiling from low-input samples. Finally, we discuss the persistent challenges in phosphoproteomic technologies, including the feasibility of nanoscale and single-cell phosphoproteomics, as well as future outlooks for biomedical applications.

A critical role of action-related functional networks in Gilles de la Tourette syndrome

Gilles de la Tourette Syndrome (GTS) is a chronic tic disorder, characterized by unwanted motor actions and vocalizations. While brain stimulation techniques show promise in reducing tic severity, optimal target networks are not well-defined. Here, we leverage datasets from two independent deep brain stimulation (DBS) cohorts and a cohort of tic-inducing lesions to infer critical networks for treatment and occurrence of tics by mapping stimulation sites and lesions to a functional connectome derived from 1,000 healthy participants. We find that greater tic reduction is linked to higher connectivity of DBS sites (N = 37) with action-related functional resting-state networks, i.e., the cingulo-opercular (r = 0.62; p < 0.001) and somato-cognitive action networks (r = 0.47; p = 0.002). Regions of the cingulo-opercular network best match the optimal connectivity profiles of thalamic DBS. We replicate the significance of targeting cingulo-opercular and somato-cognitive action network connectivity in an independent DBS cohort (N = 10). Finally, we demonstrate that tic-inducing brain lesions (N = 22) exhibit similar connectivity to these networks. Collectively, these results suggest a critical role for these action-related networks in the pathophysiology and treatment of GTS.

Revisiting the standard for modeling functional brain network activity: Application to consciousness.

Functional connectivity (FC) of resting-state fMRI time series can be estimated using methods that differ in their temporal sensitivity (static vs. dynamic) and the number of regions included in the connectivity estimation (derived from a prior atlas). This paper presents a novel framework for identifying and quantifying resting-state networks using resting-state fMRI recordings. The study employs a linear latent variable model to generate spatially distinct brain networks and their associated activities. It specifically addresses the atlas selection problem, and the statistical inference and multivariate analysis of the obtained brain network activities. The approach is demonstrated on a dataset of resting-state fMRI recordings from monkeys under different anesthetics using static FC. Our results suggest that two networks, one fronto-parietal and cingular and another temporo-parieto-occipital (posterior brain) strongly influences shifts in consciousness, especially between anesthesia and wakefulness. Interestingly, this observation aligns with the two prominent theories of consciousness: the global neural workspace and integrated information theories of consciousness. The proposed method is also able to decipher the level of anesthesia from the brain network activities. Overall, we provide a framework that can be effectively applied to other datasets and may be particularly useful for the study of disorders of consciousness.

Dynamic Evolution of the Power Structure and Contracting State Status in the Regional Trade Agreement Network and Its Trade Feedback Effects

ABSTRACT Against the backdrop of the serious setback in WTO multilateral negotiations, countries around the world have signed a large number of regional trade agreements (RTAs) to further reduce trade barriers and promote trade liberalization. These RTAs have formed a complex network of crisscrossing and mutually reinforcing dependencies that reshape the trade effects of individual RTAs. This paper uses the complex network analysis method to discuss the construction and development issues of RTAs among countries around the world and reveals the historical changes in the power structure of the economic and trade rules network and the dynamic evolution of the network status of core countries in international trade since 1995. Based on this, the feedback mechanism of the overall structure of the network and the node country status on the trade effect of RTAs is explored and tested. The analysis results show the following: (1) The global RTA network follows a power law distribution, the unbalanced characteristics of bipolarization in international economic and trade rules are very significant, and the gap in national network status is enormous. European countries are almost always in the center of the network, and China’s network status has not improved significantly. (2) The network shows obvious competitive and balancing relationships, and the pattern of international economic and trade rules has a trend toward short-term multi-polarization. (3) The test results of the trade effect feedback mechanism of the network show that the redundancy relationship of the overall network and the concentration of power structure have a negative influence on the trade effect of RTAs, while the bridging cluster function and transitivity of the overall network have a positive feedback effect on the trade effect of RTAs. The core position and control of a single country in the network form a positive feedback and high return on the trade effect of RTAs.

Differences in Network Functional Connectivity in Response to Sub-Symptomatic Exercise Between Elite Adult Athletes after Sport-Related Concussion and Healthy Matched Controls: A Pilot Study.

Resting-state electroencephalography (rsEEG) has developed as a method to explore functional network alterations related to sport-related concussion (SRC). Although exercise is an integral part of an athlete's return to sport (RTS) protocol, our understanding of the effects of exercise on (impaired) brain network activity in elite adult athletes is limited. However, this information may be beneficial to inform recovery and RTS progressions. Recording (128-channel) rsEEG datasets before and after a standardized moderate aerobic bike exercise test, this study aimed to explore functional connectivity patterns in whole brain and relevant functional networks in a group of elite adult athletes post-injury compared with healthy matched controls. The following networks were selected a priori: whole brain (68 regions of interest [ROIs]), default mode network (14 ROIs), central autonomic network (CAN, 24 ROIs), and visual network (8 ROIs). Twenty-one SRC athletes and 21 age-, sex-, sport type-, and skill level-matched healthy controls participated in this study. The SRC athletes were recruited during their RTS protocol (days since injury: 2-140 days). All athletes were able to achieve the exercise goal of reaching a moderate intensity (70% of their age-calculated maximum heart rate) while staying sub-symptomatic. Before and after exercise, functional connectivity was calculated by the phase locking value, in the alpha band (7-13 Hz). Mann-Whitney U and Wilcoxon signed rank tests were used to explore neurophysiological differences between and within groups, respectively. Whole-brain connectivity increased significantly from pre- to post-exercise within both groups (SRC: 0.264-0.284; p = 0.011 vs. controls: 0.253-0.257; p = 0.011). While CAN connectivity significantly increased only within the SRC group from pre-(0.298) to post-exercise (0.317; p = 0.003). Although all athletes reached their exercise goal without exacerbation of symptoms, the impact of exercise on the CAN appears to be greater for the SRC athletes, than matched healthy controls. The potential clinical significance of this finding is that it may have revealed an underlying mechanism for the cardiac autonomic alterations post-injury. This study merits further investigation into the CAN, as a network of interest more closely aligned with the clinical features (e.g., autonomic dysfunction) during athletes' RTS.

Early human collective practices and symbolism in the Early Upper Paleolithic of Southwest Asia

Identifying communal rituals in the Paleolithic is of scientific importance, as it reflects the expression of collective identity and the maintenance of group cohesion. This study provides evidence indicating the practice of deep cave collective rituals in the Levant during the Early Upper Paleolithic (EUP) period. It is demonstrated that these gatherings occurred within a distinct ritual compound and were centered around an engraved object in the deepest part of Manot Cave, a pivotal EUP site in southwest Asia. The ritual compound, segregated from the living areas, encompasses a large gallery partitioned by a cluster of remarkable speleothems. Within this gallery, an engraved boulder stands out, displaying geometric signs suggesting a unique representation of a tortoise. Isotopic analysis of calcite crusts on the boulder's grooves revealed alignment with values found in speleothems from the cave dated to ~37 to 35 ka BP. Additionally, meticulous shape analysis of the grooves' cross-section and the discernible presence of microlinear scratches on the grooves' walls confirmed their anthropogenic origin. Examination of stalagmite laminae (36 ka BP) near the engraved boulder revealed a significant presence of wood ash particles within. This finding provides evidence for using fire to illuminate the dark, deep part of the cave during rituals. Acoustic tests conducted in various cave areas indicate that the ritual compound was well suited for communal gatherings, facilitating conversations, speeches, and hearing. Our results underscore the critical role of collective practices centered around a symbolic object in fostering a functional social network within the regional EUP communities.

Clinical and instrumental characteristics of mild traumatic brain injury and acubarotrauma due to the impact of an explosive shock wave

BACKGROUND: Traumatic brain injuries are widespread and need to be studied, having a serious impact on health and the economy. Every year, about 69 million people experience traumatic brain injuries, including road accidents and military conflicts. A number of studies show that up to 20% of veterans who have returned from Iraq and Afghanistan, got a mild head injury. 83% of those hospitalized between 2001 and 2018 had a mild traumatic brain injuries. Pathophysiological processes in traumatic brain injuries include axon loss and demyelination, which disrupts the functioning of neural networks and manifests itself in the form of instability, cognitive decline, and mental changes. The causes of instability can be associated with damage to the vestibular apparatus, conducting pathways and connections of the cerebellum and cortical analyzers, which can be detected by modern neuroimaging methods. Stabilometry using a power platform is a promising diagnostic method for light therapy. traumatic brain injuries, which allows you to study the equilibrium function. AIM: to determine the clinical and instrumental characteristics of mild traumatic brain injury and acubarotrauma due to the impact of a shock blast wave separately and in combination. MATERIALS AND METHODS: 66 patients were selected (n = 66) aged 18 to 56 years (38.28 ± 9.98 years) who were exposed to a shock wave. Of these, 28 (42.4%) patients with mild traumatic brain injury (group 1), 21 (31.8%) patients with isolated acubarotrauma (group 2), with a combination of mild traumatic brain injury and acubarotrauma in 17 (25.8%) patients (group 3). Age, presence of chronic diseases, neurological status, neuropsychological examination, stabilometric examination, computed tomography and magnetic resonance imaging of the brain were evaluated. The table editor (MS Excel 2019) was used for statistical data processing and the program for medical and biological research (STATISTICA 12). RESULTS: the diagnosis of mild traumatic brain injury and acubarotrauma was established based on clinical recommendations. In the neurological status of all patients in groups 1 and 3, scattered organic symptoms were detected. In group 2, patients had a few isolated unstable neurological signs. According to neuropsychological testing, there was a deterioration in the results in group 3 compared to the group 1 and 2 (p 0.05). A stabilometric study showed that in group 3 significantly worse indicators of the speed of the general center of pressure, the area of the statokinesiogram with both open and closed eyes were noted compared to the other groups (p 0.05). According to the data of magnetic resonance imaging of the brain, including using SWI/SWAN sequences, diffuse micro-hemorrhages in the brain substance were not detected in the study groups. CONCLUSION: the main characteristics of mild traumatic brain injury in combination with acubarotrauma include pronounced postural instability, deterioration of stabilometric parameters and cognitive functions.

Diffusion‐Based Causality‐Preserving Neural Network for Dementia Recognition

ABSTRACTAnalyzing large‐scale functional brain networks for brain disorders often relies on undirected correlations in activation signals between brain regions. While focusing on co‐occurring activations, this approach overlooks the potential for directionality inherent in brain connectivity. Established research indicates the causal nature of brain networks, suggesting that activation patterns co‐occur and potentially influence one another. To this end, we propose a novel dffusion vector auto‐regressive (Diff‐VAR) method, enabling the assessment of whole‐brain effective connectivity (EC) as a directed and weighted network by integrating the search objectives into the deep neural network model as learnable parameters. The EC learned by our method identifies widespread differences in flow of influence within the brain network for individuals with impaired brain function compared to those with normal brain function. Moreover, we introduce an adaptive smoothing mechanism to enhance the stability and reliability of inferred EC. We evaluated the results of our proposed method on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The model's performance is compared with existing correlation‐based and causality‐based methods. The results revealed that the brain networks constructed by our method achieve high classification accuracy and exhibit features consistent with physiological mechanisms. The code is available at https://github.com/SaqibMamoon/Diff‐VAR.

Physical mechanisms of human brain functions

AbstractIn recent years, exploring the physical mechanisms of brain functions has been a hot topic in the fields of nonlinear dynamics and complex networks, and many important achievements have been made, mainly based on the characteristic features of time series of human brain. To speed up the further study of this problem, herein we make a brief review on these important achievements, which includes the aspects of explaining: (i) the mechanism of brain rhythms by network synchronization, (ii) the mechanism of unihemispheric sleep by chimera states, (iii) the fundamental difference between the structural and functional brain networks by remote synchronization, (iv) the mechanism of stronger detection ability of human brain to weak signals by remote firing propagation, and (v) the mechanism of dementia patterns by eigen‐microstate analysis. As a brief review, we will mainly focus on the aspects of basic ideas, research histories, and key results but ignore the tedious mathematical derivations. Moreover, some outlooks will be discussed for future studies.

FMRI used to observe the acute craniocerebral response of esophageal cancer related depressive patients treated by rTMS: Initial experience.

To observe the immediate craniocerebral response, changes of spontaneous nerve activity and functional connection after repeated transcranial magnetic stimulation (rTMS) in esophageal cancer patients with depression (ECPD) by functional magnetic resonance imaging (fMRI), and to explore the therapeutic effect, neuroactivity response and mechanism. Eleven patients with ECPD were enrolled to treated with single rTMS. The patients were examined by fMRI before and after the treatment. The changes of low frequency amplitude (ALFF) and the functional connection network between different brain regions of ALFF in patients were compared before and after rTMS treatment. Compared with those before rTMS treatment, the Hamilton Depression Rating Scale (HAMD) score decreased significantly after rTMS treatment (t = -7.63, P = .0001). The ALFF of bilateral putamen, left thalamus, left posterior cingulate gyrus and right middle temporal gyrus decreased significantly (P = .02). In addition, the functional connection between the cortex-limbic system-striatum-thalamus nerve loop increased in patients after rTMS treatment. rTMS may achieve the effect of rehabilitation treatment by improving the spontaneous neural activity and regulating the neural connection network of cortical-limbic systems-triatum-thalamus loop in ECPD.

3D printed β-TCP scaffolds loaded with SVVYGLR peptide for promoting revascularization and osteoinduction

It is crucial for the successful transplantation of large segmental bone defects to achieve rapid vascularization within bone scaffolds. However, there are certain limitations including uncontrolled angiogenesis and inadequate vascular function. Therefore, there is an urgent need to develop bone scaffolds with functional vascular networks. In our study, porousβ-tricalcium phosphate (β-TCP) scaffolds with varying pore sizes were prepared by 3D printing technology, loaded with osteopontin derived peptide Ser-Val-Val-Tyr-Gly-Leu-Arg (SVVYGLR) to induce osteoinduction and angiogenesis.In vitro, the proliferation and migration behaviors of human umbilical vein endothelial cell on scaffolds were assessed by Cell Counting Kit-8, confocal laser scanning microscopy and scanning electron microscopy. And the osteogenic ability of bone marrow mesenchymal stem cells was assessed using alkaline phosphatase staining and Alizarin Red S staining. The messenger ribonucleic acid (mRNA) expression levels of cell adhesion molecule (CD31), vascular endothelial growth factor and hypoxia inducible factor-1αin each group were detected by quantitative real-time fluorescence polymerase chain reaction (PCR) analysis.In vivo, cube scaffolds were subcutaneously implanted on the right hips of Sprague-Dawley (SD) rats for 6 weeks. Hematoxylin and Eosin staining, Masson's trichrome staining, and immunohistochemical analysis of osteocalcin and CD31 were performed on slices for every sample with three sections to explore the effect of SVVYGLR-loaded scaffolds on angiogenesis and osteogenic induction for bone reconstruction. The results indicate that 3D printedβ-TCP scaffolds loaded with the SVVYGLR peptide offer superior revascularization and osteoinduction to the scaffolds without the SVVYGLRin situ. Moreover, scaffolds with a pore size of 400 µm demonstrate higher effectiveness compared to those with a 150 µm pore size. The distinct hollow channel scaffolds and the specific SVVYGLR peptide substantially improve cell adhesion, spreading, and proliferation, as well as promote angiogenesis and bone formation. Furthermore, scaffolds with a pore size of 400 µm may exhibit greater efficacy compared to those with a pore size of 150 µm. The results of this study provide an idea for the development of practical applications for tissue-engineered bone scaffolds.

BIRC5 as a prognostic and diagnostic biomarker in pan-cancer: an integrated analysis of expression, immune subtypes, and functional networks

IntroductionBIRC5 (Survivin) is a crucial anti-apoptotic protein overexpressed in various cancers, promoting tumor growth and treatment resistance. This study investigates its expression across 33 cancer types and explores its diagnostic, prognostic, and immune-related significance.MethodsWe analyzed RNA-seq data from TCGA and protein expression data from the Human Protein Atlas. Expression levels were compared between tumor and normal tissues. Correlations with molecular and immune subtypes were explored using TISIDB. Prognostic significance was evaluated through survival analysis, Cox regression, and ROC curve analysis. The PPI network was constructed using STRING.ResultsBIRC5 was significantly overexpressed in tumor tissues across 33 cancer types, with higher expression levels observed in tumors compared to normal tissues. The protein expression analysis revealed a similar trend. BIRC5 expression was significantly correlated with various molecular and immune subtypes in multiple cancer types. Survival analysis indicated that high BIRC5 expression was associated with poor prognosis across multiple cancers, including lung adenocarcinoma (LUAD) and kidney renal clear cell carcinoma (KIRC). ROC analysis showed that BIRC5 exhibited strong diagnostic potential, with high AUC values (&amp;gt;0.9) in several cancers. The PPI network analysis identified key interacting proteins involved in the cell cycle and tumor progression, further supporting BIRC5's role in cancer biology. Functional experiments in lung adenocarcinoma (LUAD) revealed that BIRC5 upregulation enhances cell proliferation, migration, and invasion, while its knockdown suppresses these activities.DiscussionBIRC5 is a promising diagnostic and prognostic biomarker in multiple cancers. Its association with immune subtypes suggests a potential role in the tumor immune microenvironment. These findings support BIRC5 as a therapeutic target for cancer treatment.