Regional Network Research Articles

The Global Measles and Rubella Laboratory Network Supports High-Quality Surveillance.

With 762 laboratories, the Global Measles and Rubella Laboratory Network (GMRLN) is the largest laboratory network coordinated by the World Health Organization (WHO). Like the Global Polio Laboratory Network, the GMRLN has multiple tiers, including global specialized laboratories, regional reference laboratories, national laboratories, and, in some countries, subnational laboratories. Regional networks are supervised by regional laboratory coordinators reporting to a global coordinator at WHO headquarters. Laboratories in the GMRLN have strong links to national disease control and vaccination programs. The GMRLN's goal is to support member states in obtaining timely, complete, and reliable laboratory-based surveillance data for measles and rubella as part of the strategy for achieving measles and rubella elimination. Surveillance data are reported to the national program and are included in annual reports on the status of measles and rubella elimination to national verification committees for review by regional verification commissions. Quality within the GMRLN is ensured by monitoring performance through external quality assurance programs, confirmatory and quality control testing, accreditation, and coordination of corrective action and training where needed. The overall performance of the laboratories has remained high over the years despite many challenges, particularly the COVID-19 pandemic. The GMRLN is well-positioned to support high-quality laboratory-based surveillance for measles and rubella and to transition to supporting laboratory testing for other pathogens, including vaccine-preventable diseases.

Studying the spatiotemporal variations of the ecological network and carbon utilization efficiency in Southeast Tibet based on complex network theory

Currently, with the gradual advancement of urbanization and industrialization, ecological patches are severely fragmented and corridors are cut off, leading to the construction of regional ecological networks that can connect fragmented patches and corridors with regional characteristics. However, there is limited research on the relationship between ecological networks and Carbon Utilization Efficiency (CUE) based on complex network theory. This paper takes the ecologically fragile Southeast Tibet as the research area and investigates the variation patterns of CUE through the establishment of ecological spatial networks. The Graphab Model is employed to extract the ecological space network of Southeast Tibet. The Graphab Model integrates the complex network with the ecological space network to compute the topological index of ecological nodes and the overall ecological network. Later, MOD17A2HGF GPP and MOD17A2HGF PSNnet data from 2013 to 2021 are used as the primary data for calculating the CUE of ecological nodes. The connection between topological index and ecological nodes is analysed. The results indicate that, with interannual variations, ecological nodes dropped by 15, and the number of ecological galleries decreased by 7. However, the average values of various topological indices showed an increasing trend, suggesting that the ecological remediation items in Southeast Tibet have made some achievements. Nevertheless, the analysis of CUE in Southeast Tibet reveals a downward trend in the carbon fixation rate of vegetation in recent years. Through correlation analysis, it was found that the correlation between various topological indices and CUE was the lowest and insignificant in 2013, while from 2015 to 2021, all topological indices were significantly positively correlated with CUE. Through Principal Component Analysis (PCA), It is recommended to reduce and shorten redundant ecological corridors by aggregating small ecological patches and increasing stepping stone patches, and increase ecological galleries to enhance the carbon fixation ability of plants. This research lays a scientific foundation for addressing ecological issues, landscape patterns, and developing ecological networks in Southeast Tibet.

Impact of digital logistics platforms to facilitate more regional food in the hospitality sector and communal catering

PurposeThis paper studies digitalization projects aiming to increase the share of regional food in the hospitality sector and communal catering. The focus is set on influencing factors and underlying feedback structures that arise through the digitalization of regional food supplies. The results can guide stakeholders to get a better understanding of key influencing factors and complexities from a holistic perspective.Design/methodology/approachA systems thinking approach is employed to model regional food networks. The influencing factors were found in the literature and in two model regions. Feedback loops and underlying structures were explained and validated through semi-structured interviews. Findings are visualized in causal loop diagrams (CLDs) and are used for theory development.FindingsThe presentation in CLDs helps understanding the influence of digital logistics platforms on the entire system of regional food supply and not just on isolated parts. Among others, cooperation, trust and digital solutions were identified as key success factors when aiming to increase the share of regional food in the hospitality sector and communal catering.Research limitations/implicationsThe work focused on the underlying feedback structures occurring in regional food supply in two, rural Bavarian regions in Germany with their unique geographical settings. Findings may, consequently, not be entirely transferable to other regions with varying characteristics. Further research needs to be done to see how much these regional parameters influence digital logistics platforms.Originality/valueThe paper contributes to the existing scientific literature by showing the impact coming from digital logistics platforms on regional food supply systems. Developing CLDs provides a basis for future work and facilitates discussion for researchers and practitioners to support future real-world implementations.

A method for estimating the rotation errors of BDS broadcast ephemeris using global satellite laser ranging data

Abstract The BeiDou-3 Navigation Satellite System (BDS-3) generates navigation messages from a regional ground tracking network and inter-satellite links, relying on predicted station coordinates and Earth rotation parameters (ERPs). These procedures, however, may lead to orientation errors in the broadcast ephemeris, termed constellation rotation errors. Traditionally, these errors are monitored through Helmert transformation analysis comparing broadcast and post-processed orbits, a method that highlights discrepancies between the global navigation satellite system (GNSS) terrestrial reference frame (TRF) and the International TRF (ITRF) but suffers from a two-week evaluation delay. This study proposes a near real-time approach for estimating constellation rotation errors using high-precision satellite laser ranging (SLR) data, representing the difference between GNSS TRF and ITRF through the International laser ranging service TRF. The impact of SLR data quantity and distribution on rotation estimation accuracy is investigated, and the effectiveness of this method on BDS-3 orbits with ERP-induced orientation deficiencies is validated. Results show that the root mean square of broadcast orbit errors and the orbit user ranging error reduce from 0.8/0.7/0.2 m to 0.1/0.1/0.1 m, respectively. This demonstrates the method’s capability for real-time monitoring and correcting orientation errors within BDS-3 navigation messages.

A health equity ECHO for clinicians of individuals with SCD

Abstract SCD is the most common genetic disorder in the United States, affecting nearly 100 000 Americans, with the majority of affected individuals identifying as Black. Studies have shown that both children and adults with SCD face stigmatization resulting in low-quality care stemming from institutional racism and implicit bias by clinicians. Clinician biases often result from a lack of awareness of their own racial identity, failure to develop an anti-racist or social justice lens, and absence of skills to mitigate racist practices and policies. The Sickle Treatment and Outcomes Research in the Midwest (STORM) multi-state regional learning network developed a health equity training curriculum that was delivered as a continuing education learning series using the Project ECHO® virtual telementoring framework supplemented with an online learning management system. The curriculum addressed foundations of race, racism, and whiteness along with social justice strategies for the individual and institutional level and was piloted with 2 clinician cohorts to assess its feasibility, acceptability, and the potential impact on clinician self-efficacy. Feasibility and acceptability data, including qualitative feedback, suggest that this is a promising method for multidisciplinary clinicians and trainees for raising self-awareness about racism and bias, providing a safe community for self-reflection, and building skills to address inequities within healthcare settings.

Brain mechanisms discriminating enactive mental simulations of running and plogging.

Enactive cognition emphasizes co-constructive roles of humans and their environment in shaping cognitive processes. It is specifically engaged in the mental simulation of behaviors, enhancing the connection between perception and action. Here we investigated the core network of brain regions involved in enactive cognition as applied to mental simulations of physical exercise. We used a neuroimaging paradigm in which participants (N = 103) were required to project themselves running or plogging (running while picking-up litter) along an image-guided naturalistic trail. Using both univariate and multivariate brain imaging analyses, we find that a broad spectrum of brain activation discriminates between the mental simulation of plogging versus running. Critically, we show that self-reported ratings of daily life running engagement and the quality of mental simulation (how well participants were able to imagine themselves running) modulate the brain reactivity to plogging versus running. Finally, we undertook functional connectivity analyses centered on the insular cortex, which is a key region in the dynamic interplay between neurocognitive processes. This analysis revealed increased positive and negative patterns of insular-centered functional connectivity in the plogging condition (as compared to the running condition), thereby confirming the key role of the insular cortex in action simulation involving complex sets of mental mechanisms. Taken together, the present findings provide new insights into the brain networks involved in the enactive mental simulation of physical exercise.

High-precision GPS orbit determination by integrating the measurements from regional ground stations and LEO onboard receivers

High-precision Global Navigation Satellite System (GNSS) orbit and clock products are crucial for precise applications. An evenly distributed global network enables continuous tracking for GNSS satellites, while a regional network may result in tracking gaps in the areas where monitoring stations are not deployed. This also means that the orbit determination accuracy based on a regional network is not comparable to that with a global network. Integrating the measurements from regional ground stations and Low Earth Orbit (LEO) satellites onboard receivers is a potential approach for generating GNSS orbit and clock products with centimeter-level accuracy, which is particularly important for BDS and the local commercial providers relying on a regional network. In the integrated Precise Orbit Determination (POD), LEO satellites are used to compensate for the drawback of regional ground stations in the precise orbit and clock determination of GNSS satellites. To validate the role of LEO satellites in the orbit determination with a regional network, 6 International GNSS Service stations around China and 13 LEO satellites from January 20 to 26, 2019, including GRACE-C/D, SWARM-A/B/C, Jason-3, Sentinel-3A/B, and SAT-A/B/C/D/E are selected in this study to perform the integrated POD. The orbit and clock accuracies of GPS and LEO satellites are evaluated by comparison with precise products. The average Root Mean Square (RMS)of GPS orbit errors in the radial (R), along-track (T) and cross-track (N) directions are 2.27 cm, 3.45 cm, and 3.08 cm, respectively, and the clock accuracy is better than 0.15 ns based on a comparison with the final products provided by Center for Orbit Determination in Europe (CODE). The LEO orbit accuracy is better than 2 cm in the R direction, and the position errors are mostly within 4 cm. The results indicate that the integrated POD can generate high-precision orbit and clock products for GPS and LEO satellites based on regional network stations. Finally, the integrated POD products are assessed for Precise Point Positioning (PPP). Simulated kinematic PPP has a comparable performance in terms of the convergence time and positioning accuracy. With more LEO satellites available, the orbit and clock determination accuracy and PPP positioning accuracy can be improved.

The spatio-temporal evolution of spatial structure and supply-demand relationships of the ecological network in the Yellow River Delta region of China

Rapid urbanization has caused unregulated transformation of land use/land cover, further exacerbating the imbalance in ecological supply-demand relationships. Constructing the ecological supply-demand network by integrating natural ecological processes and human ecological demands into a unified spatio-temporal framework and considering their internal dynamic flow characteristics is an effective approach to address this issue. However, there is currently a lack of evaluation methods for the coordination of ecological network supply-demand relationships, which could provide essential guidance and reference. This article takes Yellow River Delta region (YRDR) as an example and utilizes the integrated traditional ecological network paradigm and ecosystem services theory to simulate the ecological supply-demand network for the years 2000, 2010, and 2020 in the study area. Then, a novel evaluation index system for the ecological network supply-demand relationships was proposed from the perspectives of intensity, capacity, and equilibrium. Based on this, combined with a graph-based network structure evaluation system, it reveals the spatio-temporal evolution process of the spatial structure and supply-demand relationship of the ecological network in the study area. The study results showed that: (1) The quantity of elements in the ecological supply network and the demand network show opposite trends, leading to an exacerbation of the spatial imbalance in the arrangement of ecological supply-demand network elements. (2) Although the structural changes in the ecological supply network were significantly greater than those in the ecological demand network, the overall structure of the ecological supply-demand network gradually improved. (3) However, under the coupled influence of imbalanced change in the spatial distribution and connectivity of ecological elements, the overall coordination of the ecological supply-demand relationships within the YRDR's ecological network is gradually deteriorating. (4) The proposed optimization strategy, "Two zones, Three belts, Four corridors", for the ecological security pattern in YRDR can accommodate the ecological process cycle and human ecological demand. This study can provide scientific references for "harmonious coexistence between humans and nature" ecological protection and sustainable development planning under the background of rapid urbanization.

Colombia as the ‘Laboratory’ for Transitional Justice: Consolidation and Innovation of Global Formulas

ABSTRACT∞ This article examines the standardization of transitional justice, using Colombia—regarded by international observers as a contemporary laboratory—as a case. It investigates the extent to which transitional justice, as a global blueprint for addressing past atrocities, is being embraced in Colombia and how Colombian experiences contribute to both innovation and advancement of transitional justice internationally. Colombia offers a unique perspective on how transitional justice experts and institutions engage in and construct national, regional and international networks experimentally, under the guidance of international lab certifiers and informal standardizers. Drawing on a study focused on the justice pillar of transitional justice, the article argues that the significant level of local agency, coupled with international recognition and involvement, has contributed to strengthening, rather than weakening, the international transitional justice standard through innovation and localization.

The formation of external innovation linkages of the periphery within multiplex regional networks: a multilayer exponential random graph modelling approach

ABSTRACT Innovation in peripheral areas relies more on external linkages to overcome peripherality than in core areas. We study how these linkages are formed, especially through the interaction with diverse networks like transport and investment networks that connect the periphery with external areas. Using data from peripheral Zhejiang, China, we construct a four-layer network with co-patenting and three explanatory layers: transport, investment, and university headquarters-branch linkages. We use multilayer exponential random graph modelling to examine factors driving the formation of the co-patent network, specifically cross-layer interactions between co-patenting and the other three networks. Results show a tendency for the periphery to be linked to the core through co-patenting. All the other three layers have a positive association with the co-patent network, and their intersections show a stronger correlation with the network. This is especially true for the university headquarter-branch network and its intersection with the investment network. The main contribution of this paper is expanding the analysis of peripheral innovation by considering broader intercity networks rather than solely focusing on innovation linkages. Our findings also have policy implications for overcoming innovation constraints in peripheral areas and reducing spatial disparities in Zhejiang and similar regions.

Functional network characteristics in anxiety- and mania-based subgroups of bipolar I disorder

BackgroundBipolar disorder I (BD-I) is a heterogeneous disorder with a high prevalence of comorbid anxiety. The aim of this study was to investigate whether anxiety and mania symptoms define distinct subgroups within BD-I and to explore potential differences in functional network characteristics between these subgroups. MethodsSubgroups were identified using scores from clinical anxiety and mania scales. After dimension reduction of these scores, data-driven clustering analysis with cross-validation was employed to reveal the existence of subgroups. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were pre-processed using fMRIPrep. After parcellation and network construction, global and regional graph theoretical measures were calculated per subgroup. ResultsClustering results revealed that, based on anxiety symptomatology, subjects fell into two distinct subgroups, whereas mania symptoms divided subjects into four unique subgroups. These subgroups varied notably on several symptom scales. Network assortativity was significantly associated with anxiety subgroups. Post-hoc pairwise comparisons did not reveal significant global functional network differences between the anxiety subgroups or between mania subgroups. Regional network differences between clinical subgroups were especially apparent for strength and degree in the temporal and frontal lobes. LimitationsSmall sample size of some subgroups is a limitation of this study as is the categorical rather than continuous representation of anxiety and mania symptoms. ConclusionsBD-I populations may be stratified into robust subgroups based on anxiety and mania symptoms, showing differences in functional network connectivity. Our findings highlight new avenues of research for investigating heterogeneity in psychiatric populations.

A Spectral Precursor Indicative of Artificial Water Reservoir-Induced Seismicity: Observations from the Xiangjiaba Reservoir, Southwestern China

Spectral analysis is an effective tool for processing seismic signals, particularly when time-domain characteristics are challenging to capture. In this study, we developed a method using P-wave signals to calculate the power spectrum, enabling the estimation of two spectral parameters—peak frequency and shape factor—for earthquakes recorded by regional seismic networks in the Xiangjiaba (XJB) reservoir area from 2010 to 2015. The temporal evolution of the two spectral parameters was analyzed, revealing that the mean values of individual spectral parameters remain relatively stable despite variations in reservoir water levels. However, a notable increase in the ratio of the shape factor to the peak frequency is observed when the XJB reservoir reaches its maximum water level, suggesting its potential as a precursor indicator for reservoir-induced seismicity (RIS). Furthermore, we performed spatial interpolation on the spectral parameters, and the results show that reservoir impoundment significantly influences the spatial distribution of these parameters. In addition, several regions between the two faults in the tail section of the XJB reservoir exhibit an elevation in the proposed precursor indicator. This study presents a new approach for monitoring and early warning of RIS.

Regional brain structural network topology mediates the associations between white matter damage and disease severity in first-episode, Treatment-naïve pubertal children with major depressive disorder

Puberty is a vulnerable period for the onset of major depressive disorder (MDD) due to considerable neurodevelopmental changes. Prior diffusion tensor imaging (DTI) studies in depressed youth have had heterogeneous participants, making assessment of early pathology challenging due to illness chronicity and medication confounds. This study leveraged whole-brain DTI and graph theory approaches to probe white matter (WM) abnormalities and disturbances in structural network topology related to first-episode, treatment-naïve pediatric MDD. Participants included 36 first-episode, unmedicated adolescents with MDD (mean age 15.8 years) and 29 age- and sex-matched healthy controls (mean age 15.2 years). Compared to controls, the MDD group showed reduced fractional anisotropy in the internal and external capsules, unveiling novel regions of WM disruption in early-onset depression. The right thalamus and superior temporal gyrus were identified as network hubs where betweenness centrality changes mediated links between WM anomalies and depression severity. A diagnostic model incorporating demographics, DTI, and network metrics achieved an AUROC of 0.88 and a F1 score of 0.80 using a neural network algorithm. By examining first-episode, treatment-naïve patients, this work identified novel WM abnormalities and a potential causal pathway linking WM damage to symptom severity via regional structural network alterations in brain hubs.

The effects of musicality on brain network topology in the context of Alzheimer’s disease and memory decline

Abstract Music’s role in modulating brain structure, particularly in neurodegenerative contexts such as Alzheimer’s Disease (AD), has been increasingly recognized. While previous studies have hinted at the potential neuroplastic benefits of musical engagement and training, the mechanisms through which music impacts structural connectivity in neurodegenerative pathways remain underexplored. We aimed to examine the impact of music perception skills, active musical engagement, and musical training on structural connectivity in areas relating to memory, emotion, and learning in individuals with worsening memory impairment, investigating the potential neuroplastic effects of music. Employing diffusion tensor imaging (DTI) based structural connectivity and graph theoretical analysis, we investigated brain topological features in 78 participants aged 42 to 85 with a range of memory impairments. Participants were assessed for musical training, engagement, and perception skills. The study analyzed regional and local network topological metrics to examine the influence of musical activities on graph metrics, while controlling for stages of objective memory impairment (SOMI) and diagnosis, separately. This study aimed to elucidate the effects of musical perception skills, active musical engagement, and musical training on structural connectivity within memory, emotion, and learning-related brain areas in individuals with varying degrees of memory impairment. We found enhanced structural connectivity of the right hippocampus and the right posterior cingulate cortex was associated with stronger local network metrics, such as clustering coefficient and betweenness centrality, with increased music perception skills like melody and beat perception. Musical training specifically impacted the clustering coefficient of the right hippocampus and the node degree of the right mid cingulate gyrus. Active musical engagement influenced the eigenvector centrality of the right hippocampus. Furthermore, musical training was associated with enhanced global metrics, such as global efficiency and characteristic path length. Our study integrates diffusion magnetic resonance imaging (MRI) and graph theoretical analysis to reveal significant effects of musical activities on structural connectivity in key brain regions. The results highlight the potential of musical activities to serve as a non-invasive modulatory tool for cognitive resilience, especially in memory impairment and neurodegeneration contexts. These insights contribute to the understanding of delaying AD onset and aiding early-stage patients through music-based interventions, emphasizing the importance of musical engagement in maintaining cognitive and brain health.

Resilience of regional container port network: based on projection correlation and dynamic spatial Markov Chain

ABSTRACT Ports are interconnected by shipping routes within the global logistics network. Shocks and risks stemming from financial crises, epidemics, ecology, and so on have prompted shifts in cross-border labor division towards regional cooperation, reflecting an ‘anti-globalization’ trend. Despite these dynamics, few studies have analyzed the spatial structure and dynamic evolution of resilience within regional container port network. Addressing this gap, this study considers spatial and dynamic attributes to identify influential factors of resilience and introduces the concept of spatial lag-multidimensional resistance (SL-MR) to strengthen the understanding and cognition of regional container port network resilience (RCPNR). By ports in Tianjin and Hebei, China, it constructs a dynamic spatial Markov chain (DSMC) based on the projection correlation (PC index) to dissect transition trajectories amid financial crises and other conflicts. The findings indicate: (1) The regional container port network often experiences a low-level path dependence like ‘poverty trap.’ (2) Hierarchical spatial lags significantly influence the transition probability of container port network resilience degradation, with regional port relationships being unidirectional rather than cooperative. (3) The impact of the 2008 financial crisis and the COVID-19 pandemic on regional port resilience varies, serving as key determinants in shaping diverse resilience types.

A novel method to determine bias-dependent source and drain parasitic series resistances in AlGaN/GaN high electron mobility transistors

The AlGaN/GaN high electron mobility transistors (HEMTs) with T-gate that suitable for high frequency applications were fabricated. A novel method to extract the bias-dependent source and drain parasitic series resistances (Rs and Rd) of AlGaN/GaN HEMTs is proposed. By analyzing the distributed capacitance and current generator network in the velocity saturated regions of the AlGaN/GaN HEMTs, a new restriction relationship between small-signal equivalent circuit elements is found. The Rs and Rd can be determined under active bias through wideband S-parameter measurements, which can better reflect the physical mechanism of AlGaN/GaN HEMTs under normal operation. The S-parameters and extrinsic transconductance calculated based the small-signal equivalent circuit element values extracted by the method proposed in this paper are very consistent with the experimental values, which reflects the accuracy of this element extraction method. In this paper, the physical mechanism that causes Rs and Rd to vary with bias voltage is also studied. This study has a deeper insight into the bias-dependence of Rs and Rd, which modifies the understanding for physical mechanisms of AlGaN/GaN HEMTs. The research results provide new ideas for establishing small-signal equivalent circuit models containing more physical effects and is of great significance to GaN-based integrated circuit design.

“I didn’t even wonder why I was on the floor” – mixed methods exploration of stroke awareness and help-seeking behaviour at stroke symptom onset

IntroductionTo better target stroke awareness efforts (pre and post first stroke) and thereby decrease the time window for help-seeking, this study aims to assess quantitatively whether stroke awareness is associated with appropriate help-seeking at symptom onset, and to investigate qualitatively why this may (not) be the case.MethodsThis study conducted in a German regional stroke network comprises a convergent quantitative-dominant, hypothesis-driven mixed methods design including 462 quantitative patient questionnaires combined with qualitative interviews with 28 patients and seven relatives. Quantitative associations were identified using Pearson’s correlation analysis. Open coding was performed on interview transcripts before the quantitative results were used to further focus qualitative analysis. Joint display analysis was conducted to mix data strands. Cooperation with the Patient Council of the Department of Neurology ensured patient involvement in the study.ResultsOur hypothesis that stroke awareness would be associated with appropriate help-seeking behaviour at stroke symptom onset was partially supported by the quantitative data, i.e. showing associations between some dimensions of stroke awareness and appropriate help-seeking, but not others. For example, knowing stroke symptoms is correlated with recognising one’s own symptoms as stroke (r = 0.101; p = 0.030*; N = 459) but not with no hesitation before calling help (r = 0.003; p = 0.941; N = 457). A previous stroke also makes it more likely to recognise one’s own symptoms as stroke (r = 0.114; p = 0.015*; N = 459), but not to be transported by emergency ambulance (r = 0.08; p = 0.872; N = 462) or to arrive at the hospital on time (r = 0.02; p = 0.677; N = 459). Qualitative results showed concordance, discordance or provided potential explanations for quantitative findings. For example, qualitative data showed processes of denial on the part of patients and the important role of relatives in initiating appropriate help-seeking behaviour on patients’ behalf.ConclusionsOur study provides insights into the complexities of the decision-making process at stroke symptom onset. As our findings suggest processes of denial and inabilities to translate abstract disease knowledge into correct actions, we recommend to address relatives as potential saviours of loved ones, increased use of specific situational examples (e.g. lying on the bathroom floor) and the involvement of patient representatives in the preparation of informational resources and campaigns. Future research should include mixed methods research from one sample and more attention to potential reporting inconsistencies.

Context matters: task relevance shapes neural responses to emotional facial expressions

Recent research shows that emotional facial expressions impact behavioral responses only when their valence is relevant to the task. Under such conditions, threatening faces delay attentional disengagement, resulting in slower reaction times and increased omission errors compared to happy faces. To investigate the neural underpinnings of this phenomenon, we used functional magnetic resonance imaging to record the brain activity of 23 healthy participants while they completed two versions of the go/no-go task. In the emotion task (ET), participants responded to emotional expressions (fearful or happy faces) and refrained from responding to neutral faces. In the gender task (GT), the same images were displayed, but participants had to respond based on the posers’ gender. Our results confirmed previous behavioral findings and revealed a network of brain regions (including the angular gyrus, the ventral precuneus, the left posterior cingulate cortex, the right anterior superior frontal gyrus, and two face-responsive regions) displaying distinct activation patterns for the same facial emotional expressions in the ET compared to the GT. We propose that this network integrates internal representations of task rules with sensory characteristics of facial expressions to evaluate emotional stimuli and exert top-down control, guiding goal-directed actions according to the context.

Analysing micrologistics initiatives in rural areas – Approaches to typologise and assess complex logistics solutions in regional supply networks

While demand for regional products increases and societal expectations towards a regionalisation of production are on the rise in Germany, little attention is given to the logistical challenges of local producers. At the same time, rural areas are confronted with declining supply options for goods of daily needs. Logistical challenges in rural areas are primarily caused by a scarcity of actors, low or fluctuating quantities of goods and long transport distances. A lack of economies of scale makes supply and logistics very costly. Given the rising interest and new possibilities created by digitisation, numerous private and public initiatives are developing solutions for sustainable regional logistics to secure and improve supply in rural areas - so called micrologistics solution. However, a meta-analysis of such regional logistics solutions is missing that identifies similarities and differences and indicates which characteristics are essential for the development of long-term viable regional logistics solutions.This article therefore aims at providing a general overview and at systematising current micrologistics solutions in rural regions, introducing a typology which is based on a meta-analysis of approximately 80 micrologistics initiatives in Germany and beyond. Referring to two case studies – Smart Village St. Wendel and UCKER Warentakt - we then focus analysis on solutions aiming at providing goods of daily need to the population in rural areas. We share lessons learnt on their characteristics, challenges and factors of success. This is done using a specifically developed morphological box, a viability and impact-oriented assessment framework for micrologistics initiatives as well as results of interviews with initiators and operators of such initiatives. We conclude on the usefulness of the analytical approaches developed for this new research field as well as further research needs.

The Identification of Potential Anti-Depression/Anxiety Drug Targets by Stress-Induced Rat Brain Regional Proteome and Network Analyses.

Depression and anxiety disorders are prevalent stress-related neuropsychiatric disorders and involve multiple molecular changes and dysfunctions across various brain regions. However, the specific and shared pathophysiological mechanisms occurring in these regions remain unclear. Previous research used a rat model of chronic mild stress (CMS) to segregate and identify depression-susceptible, anxiety-susceptible, and insusceptible groups; then the proteomes of six distinct brain regions (the hippocampus, prefrontal cortex, hypothalamus, pituitary, olfactory bulb, and striatum) were separately and quantitatively analyzed. To gain a comprehensive and systematic understanding of the molecular abnormalities, this study aimed to investigate and compare differential proteomics data from the six regions. Differentially expressed proteins (DEPs) were identified in between specific regions and across all regions and subjected to a series of bioinformatics analyses. Regional comparisons showed that stress-induced proteomic changes and corresponding gene ontology and pathway enrichments were largely distinct, attributable to differences in cell populations, protein compositions, and brain functions of these areas. Additionally, a notable degree of overlap in the significantly enriched terms was identified, potentially suggesting strong connections in the enrichment across different regions. Furthermore, intra-regional and inter-regional protein-protein interaction networks and drug-target-DEP networks were constructed. Integrated analysis of the three association networks in the six regions, along with the DisGeNET database, identified ten DEPs as potential targets for anti-depression/anxiety drugs. Collectively, these findings revealed commonalities and differences across different brain regions at the protein level induced by CMS, and identified several novel protein targets for the development of new therapeutics for depression and anxiety.