Changes In Network Structure Research Articles

Eutrophication triggered changes in network structure and fluxes of the Comacchio Lagoon (Italy).

Coastal lagoons, which cover about 13% of coastline, are among the most productive ecosystems worldwide. However, they are subject to significant stressors, both natural and anthropogenic, which can alter ecosystem services and functioning and food web structure. In the Comacchio Lagoon (Northern Italy), eutrophication, among other minor factors, transformed the ecosystem in the early 1980s. Here, we compiled available data for the lagoon into trophic networks (pre- and post-transformation), analyzed the ecosystem using local and global network analysis, and computed trophic fluxes of the two periods. For comparability, the networks of two periods (i.e., pre- and post- transformation) were aggregated into food webs with 23 nodes. We found differences in the trophic networks before and after eutrophication, resulting in some decrease in complexity, increase of flow diversity, and an overall shortening of the food chain. A crucial aspect of this change is the disappearance of submerged vegetation in the lagoon and the increased importance of cyanobacteria in the post-eutrophication period. We provide an approach to better understand ecosystem changes after severe disturbances which can be extended to biodiversity conservation and for the management of coastal resources in general.

Unsupervised learning modeling of the impact of Black Swan events on financial network reconfiguration: New insights from the COVID-19 outbreak and the Russia-Ukraine war

The emergence of Black Swan events, such as the COVID-19 pandemic and the Russian-Ukrainian war, has presented new challenges for stock markets and necessitates a redesign of portfolio management strategies. This work investigates the impact of unexpected and rare events, like the COVID-19 pandemic and the military conflict between Russia and Ukraine, on the structure of the cross-correlation network of stock returns. This research area has not yet been explored in depth. Previous research has primarily focused on the effects on stock returns, volatility, or changes in the topological properties of complex financial networks. In contrast, this study introduces a novel two-phase approach, integrating complex networks and self-organizing maps (the Kohonen network), to analyze changes in network structure and stock classification. A total of 483 US stocks from the S&P 500 index were analyzed. The findings reveal a notable contrast between the networks constructed before and after the onset of the COVID-19 pandemic (895 quotations for each network), along with significant disparities in stock classification according to centrality measures. Moreover, in-depth analysis has revealed significant distinctions between the SOM classification and the inherent partitioning based on economic sectors for both periods. Our research highlights the process of asset reconfiguration within the cross-correlation network, triggered by uncommon and unexpected events that disrupt financial market quotations. These findings are crucial for investors, portfolio managers, policymakers, and researchers.

Transcranial Cortex-Wide Imaging of Murine Ischemic Perfusion With Large-Field Multifocal Illumination Microscopy.

Ischemic stroke is a common cause of death worldwide and a main cause of morbidity. Presently, laser speckle contrast imaging, x-ray computed tomography, and magnetic resonance imaging are the mainstay for stroke diagnosis and therapeutic monitoring in preclinical studies. These modalities are often limited in terms of their ability to map brain perfusion with sufficient spatial and temporal resolution, thus calling for development of new brain perfusion techniques featuring rapid imaging speed, cost-effectiveness, and ease of use. We report on a new preclinical high-resolution angiography technique for murine ischemic stroke imaging based on large-field high-speed multifocal illumination fluorescence microscopy. We subsequently showcase the proposed method by monitoring therapeutic effects of thrombolysis in stroke (n=6), further performing cross-strain comparison of perfusion dynamics (n=6) and monitoring the therapeutic effects of sensory stimulation-based treatment (n=11). Quantitative readings of hemodynamic and structural changes in cerebral vascular network and pial vessels were attained with 14.4-µm spatial resolution at 80-Hz frame rate fully transcranially. The in vivo perfusion maps accurately delineated the ischemic core and penumbra, further exhibiting a strong correlation (86.1±4.5%) with ex vivo triphenyl tetrazolium chloride staining, significantly higher than for the conventional laser speckle contrast imaging method. Monitoring of therapeutic effects of thrombolysis confirmed that early recanalization could effectively save the penumbra while reducing the infarct area. Cross-strain comparison of perfusion dynamics affirmed that C57BL/6 mice feature a larger penumbra and smaller infarct core as compared with BALB/c mice, which have few or no collaterals. Sensory stimulation-based treatment could effectively enhance blood flow and abolish perfusion deficits in the ischemic core and penumbra regions. A high-speed fluorescence-based angiography method for transcranial stroke imaging in mice is introduced, which is capable of localizing brain perfusion changes and accurately assessing the ischemic penumbra. Compared with the whole-brain x-ray computed tomography and magnetic resonance imaging methods, which are conventionally used for stroke diagnosis and therapeutic monitoring, the new approach is simple and cost-effective, further offering high resolution and speed for in vivo studies. It thus opens new venues for brain perfusion research under various disease conditions such as stroke, neurodegeneration, or epileptic seizures.

Evidence of sewage discharge on the coalescence mechanism of aquatic microbial communities during high amplitude hydrological periods.

Microbial community coalescence is a ubiquitous ecological process in various ecosystems. However, limited research has addressed the effects of the coalescence on microbial ecological processes and network structure, particularly in the context of sewage discharge during high amplitude hydrological periods. Employing 16S rRNA sequencing and species source tracking analysis, we investigated the coalescence pattern of bacterioplankton in the Chishui river and sewage across various hydrological periods. The results demonstrated that the downstream bacterioplankton mainly originated from the upstream water body, and the sewage discharge from the wastewater treatment plants (WWTPs) had less impact on the downstream bacterioplankton. In the low-water period, the bacterioplankton community showed significant coalescence, and the specialist species and functional taxa gathered in the downstream. Bacterioplankton displayed distinct ecological succession patterns after community coalescence, with notable variations in the abundance of dominant group. Bacterioplankton community assembly was dominated by stochastic processes in river and the sewage over different hydrological periods. The ecological networks exhibited the highest complexity in the high-water period, whereas their stability was most pronounced in the low-water period. Species diversity, as opposed to functional and phylogenetic diversity, might be a more accurate indicator to predict changes in microbial network structure. Our findings will provide new perspectives on the mechanisms of aquatic microbial community coalescence in natural environments.

Abnormalities in rich-club connections are associated with an exacerbation of genetic susceptibility to schizophrenia

BackgroundSchizophrenia (SZ) is a highly heritable and heterogeneous disorder that is often associated with widespread structural brain abnormalities. However, the causes of interindividual differences in genetic susceptibility remain largely unknown. This study attempted to address this important issue by utilizing a prospective study in which unaffected first-degree relatives of SZ (FH+) were recruited.MethodsA total of 198 participants (143 FH + and 55 healthy control participants) were recruited and completed diffusion tensor imaging scans, graph theory analysis and semiannual standardized clinical evaluations within the first three years.ResultsFH + participants who developed SZ (SZ/FH+) had similar but pronounced structural network changes at baseline compared to FH + participants who did not (HC/FH+). Additionally, among network properties, rich-club connections showed a good correlation with the severity of SZ, which was the most significant and stable effect. Logistic regression analyses showed that rich-club connections at baseline had high predictive accuracy for the subsequent occurrence of SZ.ConclusionsAmong healthy people with a familial history of SZ, those who exhibit decreased rich-club connections are susceptible to developing this disease. Our findings may aid in the development of timely interventions to prevent SZ and possibly assist researchers and clinicians in evaluating the efficacy of interventions.

Regionalization and continuing globalization scenarios as a result of re-globalization: a matter of ally-familiarity proximity in multiplex financial network

Some aspects of re-globalization were already fragmentary analyzed empirically in globalization and regionalization related research after the global financial crisis. These empirical studies suggest that re-globalization in terms of structural financial network changes did not start recently, but appears to be observed since the global financial crisis and might have been further amplified by pandemic and geopolitical tensions. The subject of re-globalization remains under-explored in current academic research, where existing studies mostly focus on theoretical aspects of re-globalization scenarios. Among possible future scenarios of re-globalization, most likely are discussed to be geographical regionalization mosaic, ally-based bipolar regionalization, and continuing globalization. Our research aims to test empirically if geographical regionalization during the post global financial crisis period has increased, bipolar regionalization has happened, or if globalization is continuing as suggested by re-globalization megatrend. Using dataset of investment flows among 234 countries during the period 2009–2020 we map 5-layer multiplex financial network and find that network appears to be already highly regionalized geographically, also globalization seems to be increasing, thus, regionalization and globalization appear to be not contradictory and mutually exclusive processes. Geographical regionalization did not increase in terms of shifting inter-regional investment to intra-regional territory. The world appears to have become bipolarly ally-regionalized with 2 main communities – US and Europe vs. China dominated blocs. However, Europe's role remains ambiguous, because not all of Europe is clustered with US, but rather its Eastern and Northern regions, while Western Europe clusters with China. Hence, the results of this research suggest friend-shoring rather than nearshoring.

Transparency and changing stakeholder roles in the digital age of sustainable agri-food supply chain networks

Society and policy demand greater sustainability of food systems, driving practitioners to improve the transparency of supply chain networks through digital innovation. Uncertainties regarding the structuring of relationships with primary and secondary stakeholders for sharing intangible data and information diminishes the potential for exploitation of digital transparency. While businesses are accustomed to organizing efficient flows of tangible goods, management research integrating digital transparency considerations to investigate and conceptualize structural changes in agri-food supply chain networks (AFSCNs) is scarce. This gap motivates the following four questions of this study: (1) Who are the primary and secondary stakeholders in the AFSCNs of the digital era? (2) What are their transparency interests? (3) How do AFSCN structures change with the emergence of digital innovations that can facilitate sustainability transition through greater transparency? (4) How to conceptualize those structural changes to AFSCNs? The netchain approach and respective transparency concept are integrated with classical stakeholder theory. Data was collected via a series of 21 semi-structured pilot interviews with technology providers in the EU agri-food sector and analyzed using structured content analysis. Results paint a complex picture of contemporary primary and secondary stakeholders of AFSCNs and their interests. Primary stakeholder interests lead to coopetition in vertical and horizontal relationships of the netchain and low transparency efforts by intermediaries. Both hamper the dissemination of digital innovations and the exploitation of their potential to improve AFSCN sustainability. Among secondary stakeholders, policymakers and governments, NGOs, and technology providers excel in being drivers of digital transparency for sustainability, with social media as a strong direct communication tool to reach netchain stakeholders, consumers, and research institutes/universities as collaborators and customers. The emergence of “information AFSCN” and “digital AFSCN” increases the complexity of the whole supply chain network through intermediation, reconfiguration, and emergence modes of change to underlying structures. Agri-food business managers, scientists, and policymakers should innovate in private and public governance to facilitate collaborative advantage and sustainability in a combination aligned with innovative digital transparency solutions.

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.

Changes in network structures of fatigue and insomnia among female intern nurses with shift work: a longitudinal study

Changes in network structures of fatigue and insomnia among female intern nurses with shift work: a longitudinal study

Using network analysis to characterize clinical improvement during cognitive processing therapy.

Cross-sectional network studies find mixed results regarding changes in network structure as a response to treatment across disorders. This study characterized improvement in mental health following Cognitive Processing Therapy (CPT) for PTSD in veterans from the perspective of network psychometrics and explored how cross-sectional networks inform our understanding of PTSD recovery. Veterans with PTSD participated in CPT-based intensive treatment programs (ITPs), offered in two-week (N=635) or three-week (N=457) formats. PTSD symptoms were self-reported on the PTSD Checklist for DSM-5 (PCL-5) at pre-, mid-, and post-treatment. Cross-sectional networks for each time point were compared using network comparison tests. Linear regression tested if the relationship of initial treatment gains from admission to mid-treatment with overall outcomes was associated with the expected influence centrality of a node. Substantial improvement in PTSD symptoms were found, but network structure remained largely unaffected, with global edge strength increasing from pre-to post-treatment. Initial treatment gains in nodes with high expected influence were associated with overall treatment outcomes. A post-hoc simulation based on a common-cause model produced similar regression results, indicating that while our findings align with spreading activation, they are not exclusive to this mechanism. The indiscernibility of cross-sectional networks between pre- and post-treatment raises questions about whether cross-sectional networks can illuminate PTSD recovery beyond traditional measures of treatment response.

Radiation-induced aberrant structural covariance networks in patients with nasopharyngeal carcinoma: a source-based morphometry study.

Radiation-induced brain injury (RBI) is a common complication in patients with nasopharyngeal carcinoma (NPC) who have undergone radiotherapy (RT), which is characterized by significant cognitive and psychological impairments. Although radiation-induced regional structural abnormalities have been well-reported, the effects of RT on the whole brain structural covariance networks are mostly unknown. Here, we performed a source-based morphometry (SBM) study to solve this issue. In this cross-sectional study, 131 NPC patients with pre- and post-RT were stratified into pre-RT (n=47) and post-RT (n=84) groups. The SBM method was adopted to investigate the radiation-induced alterations in structural covariance networks in patients with NPC. Compared to the pre-RT group, our SBM analyses revealed increased z-scores in the independent component 05 (IC05; mainly located in the posterior cingulate, precuneus areas, and superior parietal lobe) (P=0.040) and decreased z-scores in the temporal-occipital network (P=0.015) and cerebellar network (P=0.023) in post-RT NPC patients. Compared to the pre-RT group, voxel-based morphometry (VBM) revealed reduced gray matter volume in the left temporal lobe, cerebellum, bilateral thalamus, left insular, and occipital lobe in the post-RT group. Notably, a significant negative correlation was observed between the mean radiation doses of the right temporal lobe and the z-score of the cerebellar network (r=-0.349, P=0.027). This present study revealed radiation-induced changes in structural covariance networks and cortical volume in patients with NPC. These findings shed some light on the neural basis of symptom patterns in RBI and may support the development of new intervention strategies to prevent progression to radiation-induced brain necrosis.

Exploring the effects of erythropoietin treatment on cortical thickness and hippocampal volume in patients with mood disorders undergoing electroconvulsive therapy: A randomized, placebo-controlled trial.

Electroconvulsive therapy (ECT) is a highly effective treatment for severe depression. However, its utilization is limited to the most severely ill patients due to stigma, healthcare provider unfamiliarity, and concerns regarding cognitive side effects. Erythropoietin (EPO) is a promising add-on treatment during ECT due to its potential to increase neuroplasticity and cognition. To explore the effects of EPO administration on cortical thickness and hippocampal volumes. In a randomized, double-blinded, placebo-controlled trial, we previously investigated the impact of EPO (40,000 IU) versus placebo (saline) infusions on cognitive side effects of unipolar or bipolar depression patients undergoing eight ECT sessions over 2.5 weeks. This cross-sectional magnetic resonance imaging study explores the effect of EPO on cortical thickness and hippocampal volumes 3 days post-ECT in 37 of the EPO trial patients (EPO n = 21; placebo n = 16). Compared to the placebo group, EPO-treated patients displayed thicker cortex in distributed regions of the right hemisphere, predominantly in the parietal and occipital areas. There were no significant group differences in the hippocampal volumes or prefrontal cortex thickness. EPO treatment may produce a selective increase in the right-side occipito-parietal cortical thickness. In contrast, the thickness of other cognition-relevant structures was not significantly affected. This aligns with our previously reported finding that EPO has a selective effect on autobiographical memory and associated right-side parietal activity in the absence of changes in global cognition. It remains to be investigated whether longer EPO treatment and follow-up assessment may be necessary for overt structural changes in cognition-relevant brain networks.

Critical Station Identification of Metro Networks Based on the Integrated Topological-Functional Algorithm: A Case Study of Chengdu

Abstract As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel Integrated Topological-Functional (ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm is validated under different conditions. The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insights for urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.

Quantitative determination of the spatial distribution of components in single cells with CellDetail

The distribution of biomolecules within cells changes upon aging and diseases. To quantitatively determine the spatial distribution of components inside cells, we built the user-friendly open-source 3D-cell-image analysis platform Cell Detection and Analysis of Intensity Lounge (CellDetail). The algorithm within CellDetail is based on the concept of the dipole moment. CellDetail provides quantitative values for the distribution of the polarity proteins Cdc42 and Tubulin in young and aged hematopoietic stem cells (HSCs). Septin proteins form networks within cells that are critical for cell compartmentalization. We uncover a reduced level of organization of the Septin network within aged HSCs and within senescent human fibroblasts. Changes in the Septin network structure might therefore be a common feature of aging. The level of organization of the network of Septin proteins in aged HSCs can be restored to a youthful level by pharmacological attenuation of the activity of the small RhoGTPase Cdc42.

Disrupted topologic efficiency of white matter structural connectome in migraine: a graph-based connectomics study

ObjectiveTo delineate the structural connectome alterations in patients with chronic migraine (CM), episodic migraine (EM), and healthy controls (HCs).BackgroundThe pathogenesis of migraine chronification remains elusive, with structural brain network changes potentially playing a key role. However, there is a paucity of research employing graph theory analysis to explore changes in the whole brain structural networks in patients with CM and EM.MethodsThe individual structural brain connectome of 60 patients with CM, 34 patients with EM, and 39 healthy control participants were constructed by using deterministic diffusion-tensor tractography. Graph metrics including global efficiency, characteristic path length, local efficiency, clustering coefficient, and small-world parameters were evaluated to describe the topologic organization of the white matter structural networks. Additionally, nodal clustering coefficient and efficiency were considered to assess the regional characteristics of the brain connectome. A graph-based statistic was used to assess brain network properties across the groups.ResultsGraph theory analysis revealed significant disruptions in the structural brain networks of CM patients, characterized by reduced global efficiency, local efficiency, and increased characteristic path length compared to HCs. Additionally, CM patients exhibited significantly lower local efficiency than EM patients. Notably, the CM group demonstrated marked reductions in local clustering coefficient and nodal local efficiency in the frontal and temporal regions compared with the healthy control group and EM group. Nodal local efficiency can effectively distinguish CM from EM and HCs. Moreover, the disrupted topologic efficiency was significantly associated with attack frequency and MIDAS score in patients with migraine after Bonferroni correction.ConclusionDecreased structural connectivity in the frontal and temporal regions may serve as a neuroimaging marker for migraine chronification and disease progression, providing valuable insights into the pathophysiology of chronic migraine.

Unveiling the fate and potential neuroprotective role of neural stem/progenitor cells in multiple sclerosis.

Chronic pathological conditions often induce persistent systemic inflammation, contributing to neuroinflammatory diseases like Multiple Sclerosis (MS). MS is known for its autoimmune-mediated damage to myelin, axonal injury, and neuronal loss which drive disability accumulation and disease progression, often manifesting as cognitive impairments. Understanding the involvement of neural stem cells (NSCs) and neural progenitor cells (NPCs) in the remediation of MS through adult neurogenesis (ANG) and gliogenesis-the generation of new neurons and glial cells, respectively is of great importance. Hence, these phenomena, respectively, termed ANG and gliogenesis, involve significant structural and functional changes in neural networks. Thus, the proper integration of these newly generated cells into existing circuits is not only key to understanding the CNS's development but also its remodeling in adulthood and recovery from diseases such as MS. Understanding how MS influences the fate of NSCs/NPCs and their possible neuroprotective role, provides insights into potential therapeutic interventions to alleviate the impact of MS on cognitive function and disease progression. This review explores MS, its pathogenesis, clinical manifestations, and its association with ANG and gliogenesis. It highlights the impact of altered NSCs and NPCs' fate during MS and delves into the potential benefits of its modifications. It also evaluates treatment regimens that influence the fate of NSCS/NPCs to counteract the pathology subsequently.

Social health, activity behaviors, and quality of life among young adult cancer survivors: Protocol for a prospective observational study.

Approximately 85,000 adolescent and young adults (AYAs; age 15-39) are diagnosed with cancer in the United States annually. Experiencing a cancer diagnosis as an AYA can substantially impact social connections and social health. This paper describes the design and protocol of an observational study to prospectively assess social health and its association with physical activity and quality of life among AYAs after a cancer diagnosis. The study uses a longitudinal observational design to prospectively explore the relationships between social health and activity behaviors (physical activity and sedentary time) at four clinically significant timepoints over the course of 12 months among AYAs newly diagnosed with cancer. Patients are recruited at three hospitals and surveyed at each time period. Multiple dimensions of social health are assessed including social support, social roles, loneliness, social anxiety, and social networks. A wrist accelerometer is worn for one week at each assessment period. Change in social network structures will be analyzed using egocentric social network analysis. Structural equation models will be fitted to analyze the relationship between social constructs and physical activity. Findings from this study will address gaps in our understanding of the impact of a cancer diagnosis on multiple dimensions of social health for AYAs and the potential role social factors play in physical activity and quality of life. Understanding these processes will inform age-tailored interventions to improve health and quality of life outcomes for this at-risk population.

Structural brain connectivity does not associate with childhood trauma in individuals with schizophrenia

BackgroundSchizophrenia is a brain dysconnectivity disorder. However, it is not well understood whether the experience of childhood trauma (CT) affects dysconnectivity in individuals with schizophrenia (SZ). Using a network-based approach, we examined whether self-reported CT would explain additional variance compared to whole-brain topology and structural connectivity changes in SZ versus healthy controls (HC). Material and methodsCT was assessed in 51 SZ (mean age ± standard deviation 44 ± 11 years) and 140 HC (34.0 ± 12 years). Structural brain networks were constructed from T1-weighted MR and diffusion-MRI scans using non-tensor based tractography. Group differences in whole-brain topology and permutation-based statistics were examined and corrected for age and sex. ResultsSZ showed reductions in efficiency, strength, clustering and density (p < 0.01) as well as increases in path length (F(range) = 4.71–18.1, p < 0.03) when compared to HC. We also observed hypoconnectivity in a subnetwork of frontotemporal, frontoparietal and occipital regions in SZ relative to HC (T > 4.0, p < 0.001). However, we did not find that high CT levels were related to structural network differences or structural connectivity changes in SZ. ConclusionsCT did not impact on topology or subnetwork connectivity changes in SZ. High CT levels were also not associated with any differences in network organisation irrespective of diagnosis. However, our findings confirm that SZ showed both network-level reductions and increases in a subnetwork. These findings suggest that the patterns of neuroanatomical dysconnectivity in established schizophrenia may not be influenced by CT. Future studies are needed to investigate the association between CT and structural dysconnectivity in schizophrenia.

Flying by night: Comparing nocturnal pollinator networks over time in the Colorado Rocky Mountains

Abstract Where climate is seasonal, such as in high‐altitude ecosystems, the occurrence and activity patterns of insect pollinators may vary with the varying occurrence of floral resources. This high turnover of species occurrence and interactions may lead to changes in the structure and properties of plant–pollinator networks. Here, we systematically compared the properties of moth pollen‐transport networks in Colorado, USA, over the course of a season, and tested for a link between moth species specialisation and morphology. We predicted that network properties would change through the season as the abundance and diversity of available floral resources increased. We also predicted that there would be a link between moth specialisation and morphology, as moth proboscis length can restrict their ability to utilise different floral resources. We sampled moths for pollen over 9 weeks in June through August 2021. We then constructed pollen‐transport networks, and used mixed models to test for differences in network indices between different parts of the 2021 season; we also tested for a relationship between moth proboscis length, the duration of moth species' presence across the season and the number of flower species pollinated. As expected, we found high rates of species turnover and high rates of plant–pollinator interactions over the summer. However, linkage density and robustness were the only overall network metrics that changed. We also found that longer proboscis lengths and more persistent species occurrence over the season were predictive of higher generalisation among moth species. We suggest that even with high rates of species turnover, nocturnal moth pollen‐transport networks may maintain their overall structure over a season, with variations in the availability of floral resources driving limited variation in some network metrics. Our study highlights the necessity of continuing to research moth pollen‐transport networks over different temporal scales, to better understand how ecological factors can lead to changes in network structure over time.

Altered structural covariance of the cortex and hippocampal formation in patients with lung cancer after chemotherapy

ObjectiveIn this retrospective study, we aimed to investigate changes in brain morphology and structural topological networks in patients with lung cancer (LC) with or without chemotherapy. MethodsWe retrospectively recruited 191 participants for this cross-sectional study, including 113 patients with LC without chemotherapy (Ch-), 38 patients with LC with chemotherapy (Ch+), and 40 healthy controls (HC) matched for age, sex, and education. The gray matter volume (GMV) and cortical properties were compared among the three groups. We constructed the structural covariant network (SCN) based on cortical thickness, volumes of subcortical structures, and volumes of hippocampal subfields and the amygdala in all participants. The global and nodal topological properties of SCN were compared among groups. In addition, 23 patients with LC (8 Ch+ and 15 Ch-) who received two identical brain magnetic resonance scans were enrolled in the follow-up study. The paired t-test was used to compare group differences in brain morphology and topological properties in the structural network. ResultsThe GMV of the bilateral caudate and thalamus were smaller in the Ch- and Ch + groups compared to the HC group using threshold-free cluster enhancement and permutation (P < 0.05, 5000 times permutations) for multiple comparison correction. The cortical SCN analysis suggested multiple enhanced nodal properties in several brain areas in Ch+ and Ch-compared to HC, mainly in the temporal gyrus, using permutations test and false discovery rate (FDR) (P < 0.05) corrections. Moreover, an increased sigma was found in the Ch + compared with HC (P = 0.0238). The reduced nodal degree (P = 0.0002) and betweenness (P = 0.0008) in the right amygdala of Ch + compared to HC were detected by subcortical SCN analysis. Furthermore, reduced gamma (P = 0.0342) and sigma (P < 0.0001) were found in Ch-compared with HC in the SCN analysis of subfields of the amygdala-hippocampal complex. In the follow-up study, reduced nodal degree (P < 0.0001) was found in the right anterior amygdala, and reduced clustering coefficient and local efficiency were found in patients with LC after the permutation test. ConclusionsOur study showed GMV defects and structural topological property abnormalities related to LC and chemotherapy. Such morphological changes associated with LC and chemotherapy could be used as imaging markers for clinical assessments and pathological indicators.