Isoproterenol modulates expiratory activities in the brainstem spinal cord preparation in neonatal mice in vitro

Motor behaviors such as breathing required temporal coordination of different muscle groups to insured efficient ventilation and provide oxygen to the body. This action is the result of interactions between neural networks located within the brainstem. Inspiration and expiration depend at least in part on interactions between two separate oscillators: inspiration is driven by a neural network located in the preBötzinger complex (PreBötC) and active expiration is driven by a network in the parafacial respiratory group (pFRG). Neurons of the pFRG are silent at rest and become active when the respiratory drive increased. This study investigated the temporal coordination between the brainstem respiratory network and the lumbar spinal network that generates spontaneous activities that is different of the induced fictive locomotion. The remaining question is how these activities coordinate early during the development. Results of this study show that brainstem networks contribute to the temporal coordination of the lumbar spontaneous activity during inspiration since lumbar motor activity occurs exclusively during the expiratory time. This study also investigated the role of the β-noradrenergic modulation on the respiratory activities. β-noradrenergic receptors activation increased the frequency of the double bursts and increased expiratory activity at the lumbar level. These results suggest interactions between brainstem and spinal networks and reveal a descending drive that may contribute to the coordination of the respiratory and lumbar spontaneous activities.

Lung Tissue Multi-Layer Network Analysis Uncovers the Molecular Heterogeneity of COPD

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous condition. We hypothesized that the unbiased integration of different COPD lung omics using a novel multi-layer approach may unravel mechanisms associated with clinical characteristics.

METHODS

We profiled mRNA, miRNA and methylome in lung tissue samples from 135 former smokers with COPD. For each omic (layer) we built a patient network based on molecular similarity. The three networks were used to build a multi-layer network, and optimization of multiplex-modularity was employed to identify patient communities across the three distinct layers. Uncovered communities were related to clinical features.

RESULTS

We identified five patient communities in the multi-layer network which were molecularly distinct and related to clinical characteristics, such as FEV1 and blood eosinophils. Two communities (C#3 and C#4) had both similarly low FEV1 values and emphysema, but were molecularly different: C#3, but not C#4, presented B and T cell signatures and a downregulation of secretory (SCGB1A1/SCGB3A1) and ciliated cells. A machine learning model was set up to discriminate C#3 and C#4 in our cohort, and to validate them in an independent cohort. Finally, using spatial transcriptomics we characterized the small airway differences between C#3 and C#4, identifying an upregulation of T/B cell homing chemokines, and bacterial response genes in C#3.

CONCLUSIONS

A novel multi-layer network analysis is able to identify clinically relevant COPD patient communities. Patients with similarly low FEV1 and emphysema can have molecularly distinct small airways and immune response patterns, indicating that different endotypes can lead to similar clinical presentation.

Priorities for improving predictions of vessel-mediated marine invasions

Nonindigenous marine species are impacting the integrity of marine ecosystems worldwide. The invasion rate is increasing, and vessel traffic, the most significant human-assisted transport pathway for marine organisms, is predicted to double by 2050. The ability to predict the transfer of marine species by international and domestic maritime traffic is needed to develop cost-effective proactive and reactive interventions that minimise introduction, establishment and spread of invasive species. However, despite several decades of research into vessel-mediated species transfers, some important knowledge gaps remain, leading to significant uncertainty in model predictions, often limiting their use in decision making and management planning. In this review, we discuss the sequential ecological process underlying human-assisted biological invasions and adapt it in a marine context. This process includes five successive stages: entrainment, transport, introduction, establishment, and the subsequent spread. We describe the factors that influence an organism's progression through these stages in the context of maritime vessel movements and identify key knowledge gaps that limit our ability to quantify the rate at which organisms successfully pass through these stages. We then highlight research priorities that will address these knowledge gaps and improve our capability to manage biosecurity risks at local, national and international scales. We identified four major data and knowledge gaps: (1) quantitative rates of entrainment of organisms by vessels; (2) the movement patterns of vessel types lacking maritime location devices; (3) quantifying the release (introduction) of organisms as a function of vessel behaviour (e.g. time spent at port); and (4) the influence of a species' life history on establishment success, for a given magnitude of propagule pressure. We discuss these four research priorities and how they can be addressed in collaboration with industry partners and stakeholders to improve our ability to predict and manage vessel-mediated biosecurity risks over the coming decades.

Early life stress and functional network topology in children

Brain networks are continuously modified throughout development, yet this plasticity can also make functional networks vulnerable to early life stress. Little is currently known about the effect of early life stress on the functional organization of the brain. The current study investigated the association between environmental stressors and network topology using data from the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study. Hierarchical modeling identified a general factor of environmental stress, representing the common variance across multiple stressors, as well as four subfactors including familial dynamics, interpersonal support, neighborhood SES deprivation, and urbanicity. Functional network topology metrics were obtained using graph theory at rest and during tasks of reward processing, inhibition, and affective working memory. The general factor of environmental stress was associated with less specialization of networks, represented by lower modularity at rest. Local metrics indicated that general environmental stress was also associated with less efficiency in the subcortical-cerebellar and visual networks while showing greater efficiency in the default mode network at rest. Subfactors of environmental stress were associated with differences in specialization and efficiency in select networks. The current study illustrates that a wide range of stressors in a child's environment are associated with differences in brain network topology.

The Modulatory Effects of Atomoxetine on Aberrant Connectivity During Attentional Processing in Cocaine Use Disorder

BACKGROUND

Cocaine use disorder is associated with cognitive deficits that reflect dysfunctional processing across neural systems. Because there are currently no approved medications, treatment centers provide behavioral interventions that have only short-term efficacy. This suggests that behavioral interventions are not sufficient by themselves to lead to the maintenance of abstinence in patients with cocaine use disorder. Self-control, which includes the regulation of attention, is critical for dealing with many daily challenges that would benefit from medication interventions that can ameliorate cognitive neural disturbances.

METHODS

To address this important clinical gap, we conducted a randomized, double-blind, placebo-controlled, crossover design study in patients with cocaine use disorder (n = 23) and healthy control participants (n = 28). We assessed the modulatory effects of acute atomoxetine (40 mg) on attention and conflict monitoring and their associated neural activation and connectivity correlates during performance on the Eriksen flanker task. The Eriksen flanker task examines basic attentional processing using congruent stimuli and the effects of conflict monitoring and response inhibition using incongruent stimuli, the latter of which necessitates the executive control of attention.

RESULTS

We found that atomoxetine improved task accuracy only in the cocaine group but modulated connectivity within distinct brain networks in both groups during congruent trials. During incongruent trials, the cocaine group showed increased task-related activation in the right inferior frontal and anterior cingulate gyri, as well as greater network connectivity than the control group across treatments.

CONCLUSIONS

The findings of the current study support a modulatory effect of acute atomoxetine on attention and associated connectivity in cocaine use disorder.

Individualized, connectome-based, non-invasive stimulation of OCD deep-brain targets: A proof-of-concept

Treatment-resistant obsessive-compulsive disorder (OCD) generally improves with deep-brain stimulation (DBS), thought to modulate neural activity at both the implantation site and in connected brain regions. However, its invasive nature, side-effects, and lack of customization, make non-invasive treatments preferable. Harnessing the established remote effects of cortical transcranial magnetic stimulation (TMS), connectivity-based approaches have emerged for depression that aim at influencing distant regions connected to the stimulation site. We here investigated whether effective OCD DBS targets (here subthalamic nucleus [STN] and nucleus accumbens [NAc]) could be modulated non-invasively with TMS. In a proof-of-concept study with nine healthy individuals, we used 7T magnetic resonance imaging (MRI) and probabilistic tractography to reconstruct the fiber tracts traversing manually segmented STN/NAc. Two TMS targets were individually selected based on the strength of their structural connectivity to either the STN, or both the STN and NAc. In a sham-controlled, within-subject cross-over design, TMS was administered over the personalized targets, located around the precentral and middle frontal gyrus. Resting-state functional 3T MRI was acquired before, and at 5 and 25 min after stimulation to investigate TMS-induced changes in the functional connectivity of the STN and NAc with other regions of the brain. Static and dynamic seed-to-voxel correlation analyses were conducted. TMS over both targets was able to modulate the functional connectivity of the STN and NAc, engaging both overlapping and distinct regions, and unfolding following different temporal dynamics. Given the relevance of the engaged connected regions to OCD pathology, we argue that a personalized, connectivity-based procedure is worth investigating as potential treatment for refractory OCD.

Neural correlates of mindfulness meditation and hypnosis on magnetic resonance imaging: similarities and differences. A scoping review

BACKGROUND

Mindfulness meditation (MM) and hypnosis practices are gaining interest in mental health, but their physiological mechanisms remain poorly understood. This study aimed to synthesize the functional, morphometric and metabolic changes associated with each practice using magnetic resonance imaging (MRI), and to identify their similarities and differences.

METHODS

MRI studies investigating MM and hypnosis in mental health, specifically stress, anxiety, and depression, were systematically screened following PRISMA guidelines from four research databases (PubMed, Web of Science, Embase, PsycINFO) between 2010 and 2022.

RESULTS

In total, 97 references met the inclusion criteria (84 for MM and 13 for hypnosis). This review showed common and divergent points regarding the regions involved and associated brain connectivity during MM practice and hypnosis. The primary commonality between mindfulness and hypnosis was decreased default mode network intrinsic activity and increased central executive network - salience network connectivity. Increased connectivity between the default mode network and the salience network was observed in meditative practice and mindfulness predisposition, but not in hypnosis.

CONCLUSIONS

While MRI studies provide a better understanding of the neural basis of hypnosis and meditation, this review underscores the need for more rigorous studies.

Depth effects on bacterial community altitudinal patterns and assembly processes in the warm-temperate montane forests of China

Soil bacterial communities are essential for ecosystem function, yet their response along altitudinal gradients in different soil strata remains unclear. Understanding bacterial community co-occurrence networks and assembly patterns in mountain ecosystems is crucial for comprehending microbial ecosystem functions. We utilized Illumina MiSeq sequencing to study bacterial diversity and assembly patterns of surface and subsurface soils across a range of elevations (700 to 2100 m) on Dongling Mountain. Our results showed significant altitudinal distribution patterns concerning bacterial diversity and structure in the surface soil. The bacterial diversity exhibited a consistent decrease, while specific taxa demonstrated unique patterns along the altitudinal gradient. However, no altitudinal dependence was observed for bacterial diversity and community structure in the subsurface soil. Additionally, a shift in bacterial ecological groups is evident with changing soil depth. Copiotrophic taxa thrive in surface soils characterized by higher carbon and nutrient content, while oligotrophic taxa dominate in subsurface soils with more limited resources. Bacterial community characteristics exhibited strong correlations with soil organic carbon in both soil layers, followed by pH in the surface soil and soil moisture in the subsurface soil. With increasing depth, there is an observable increase in taxa-taxa interaction complexity and network structure within bacterial communities. The surface soil exhibits greater sensitivity to environmental perturbations, leading to increased modularity and an abundance of positive relationships in its community networks compared to the subsurface soil. Furthermore, the bacterial community at different depths was influenced by combining deterministic and stochastic processes, with stochasticity (homogenizing dispersal and undominated) decreasing and determinism (heterogeneous selection) increasing with soil depth.

All-optical interrogation of millimeter-scale networks and application to developing ferret cortex

BACKGROUND

Perception and behavior require coordinated activity of thousands of neurons operating in networks that span millimeters of brain area. In vivo calcium imaging approaches have proven exceptionally powerful for examining the structure of these networks at large scales, and optogenetics can allow for causal manipulations of large populations of neurons. However, realizing the full potential of these techniques requires the ability to simultaneously measure and manipulate distinct circuit elements on the scale of millimeters.

NEW METHOD

We describe an opto-macroscope, an artifact-free, all-optical system capable of delivering patterned optogenetic stimulation with high spatial and temporal resolution across millimeters of brain while simultaneously imaging functional neural activity.

RESULTS

We find that this approach provides direct manipulation of cortical regions ranging from hundreds of microns to several millimeters in area, allowing for the perturbation of individual brain areas or networks of functional domains. Using this system we find that spatially complex endogenous networks in the developing ferret visual cortex can be readily reactivated by precisely designed patterned optogenetic stimuli.

COMPARISON WITH EXISTING METHODS

Our opto-macroscope extends current all-optical optogenetic approaches which operate on a cellular scale with multiphoton stimulation, and are poorly suited to investigate the millimeter-scale of many functional networks. It also builds upon other mesoscopic optogenetic techniques that lack simultaneous optical readouts of neural activity.

CONCLUSIONS

The large-scale all-optical capabilities of our system make it a powerful new tool for investigating the contribution of cortical domains and brain areas to the functional neural networks that underlie perception and behavior.

Hospital padrino: a collaborative strategy model to tackle maternal mortality: a mixed methods study in a middle-income region

Background

Reducing maternal mortality ratio (MMR) remains a paramount goal for low- and middle-income countries (LMICs), especially after COVID-19's devastating impact on maternal health indicators. We describe our experience implementing the Hospital Padrino Strategy (HPS), a collaborative model between a high-complexity hospital (Fundación Valle del Lili) and 43 medium- and low-complexity hospitals in one Colombian department (an administrative and territorial division) from 2021 to 2022, to sustain the trend towards reducing MMR. The study aimed to assess the effects of implementing HPS on both hospital performance and maternal health indicators in Valle del Cauca department (VCD).

Methods

A mixed-methods study was conducted, comprising two phases. In the first phase, we investigated a cohort of hospitals through prospective follow-up to assess the outcomes of HPS implementation on hospital performance and maternal health indicators in VCD. In the second phase, qualitative data were collected through focus groups with 131 health workers from 33 hospitals to explore the implications of the HPS implementation on healthcare personnel. All data were obtained from records within the HPS implementation and from the Health Secretary of VCD.

Findings

Evidence shows that in the context of HPS, 51 workshops involved 980 healthcare workers, covering the entire territory. Substantial improvements were observed in hospital conditions and healthcare personnel's technical competencies when providing obstetric care. Seven hundred eighty-five pregnant women with obstetric or perinatal emergencies received care through telehealth systems, with a progressive increase in technology adoption. Nine percent required Intensive Care Unit (ICU) admission, and none died. The MMR decreased from 78.8 in 2021 to 12.0 cases per 100,000 live births by 2022. Improvements in indicators and conducted training sessions instilled confidence and empowerment among the healthcare teams in the sponsored hospitals, as evidenced in focus groups derived from a sample of 131 healthcare workers from 33 hospitals.

Interpretation

Implementing the Hospital Padrino Strategy led to a significant MMR reduction, and consolidated a model of social healthcare innovation replicable in LMICs.

Funding

The Hospital Padrino Strategy was funded by the Fundación Valle del Lili and the Health Secretary of Valle del Cauca. Furthermore, this study received funding from a general grant for research from Tecnoquimicas S.A.

Intensive pasture management alters the composition and structure of plant-pollinator interactions in Sibiu, Romania

Background

Land management change towards intensive grazing has been shown to alter plant and pollinator communities and the structure of plant-pollinator interactions in different ways across the world. Land-use intensification in Eastern Europe is shifting highly diverse, traditionally managed hay meadows towards intensive pastures, but few studies have examined how this influences plant-pollinator networks. We hypothesized that the effects of intensive grazing on networks will depend on how plant communities and their floral traits change.

Methods

We investigated plant and pollinator diversity and composition and the structure of plant-pollinator interactions near Sibiu, Romania at sites that were traditionally managed as hay meadows or intensive pastures. We quantified the identity and abundance of flowering plants, and used transect walks to observe pollinator genera interacting with flowering plant species. We evaluated the effects of management on diversity, composition and several indices of network structure.

Results

Pollinator but not plant diversity declined in pastures and both plant and pollinator taxonomic composition shifted. Functional diversity and composition remained unchanged, with rather specialized flowers having been found to dominate in both hay meadows and pastures. Apis mellifera was found to be the most abundant pollinator. Its foraging preferences played a crucial role in shaping plant-pollinator network structure. Apis mellifera thus preferred the highly abundant Dorycnium herbaceum in hay meadows, leading to hay meadows networks with lower Shannon diversity and interaction evenness. In pastures, however, it preferred less abundant and more generalized flower resources. With pollinators being overall less abundant and more generalized in pastures, we found that niche overlap between plants was higher.

Discussion

With both hay meadows and pastures being dominated by plant species with similar floral traits, shifts in pollinator preferences seem to have driven the observed changes in plant-pollinator interaction networks. We thus conclude that the effects of grazing on pollinators and their interactions are likely to depend on the traits of plant species present in different management types as well as on the effects of grazing on plant community composition. We thereby highlight the need for better understanding how floral abundance shapes pollinator visitation rates and how floral traits may influence this relationship.

New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study

BACKGROUND

Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield.

RESULTS

Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield.

CONCLUSIONS

Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.

Consensus-based indicators for evaluating and improving the quality of regional collaborative networks of intensive care units: Results of a nationwide Delphi study

PURPOSE

To select a consensus-based set of relevant and feasible indicators for monitoring and improving the quality of regional ICU network collaboratives.

METHODS

A three-round Delphi study was conducted in the Netherlands between April and July 2022. A multidisciplinary expert panel prioritized potentially relevant and feasible indicators in two questionnaire rounds with two consensus meetings between both rounds. The RAND/UCLA appropriateness method was used to categorize indicators and synthesize results. A core set of highest ranked indicators with consensus-based levels of relevance and feasibility were finally tested in two ICU networks to assess their measurability.

RESULTS

Twenty-four indicators were deemed as relevant and feasible. Seven indicators were selected for the core set measuring the standardized mortality rate in the region (n = 1) and evaluating the presence, content and/or follow-up of a formal plan describing network structures and policy agreements (n = 3), a long-term network vision statement (n = 1), and network meetings to reflect on and learn from outcome data (n = 2). The practice tests led to minor reformulations.

CONCLUSIONS

This study generated relevant and feasible indicators for monitoring and improving the quality of ICU network collaboratives based on the collective opinion of various experts. The indicators may help to effectively govern such networks.

The "Small World of Words" free association norms for Rioplatense Spanish

Large-scale word association datasets are both important tools used in psycholinguistics and used as models that capture meaning when considered as semantic networks. Here, we present word association norms for Rioplatense Spanish, a variant spoken in Argentina and Uruguay. The norms were derived through a large-scale crowd-sourced continued word association task in which participants give three associations to a list of cue words. Covering over 13,000 words and +3.6 M responses, it is currently the most extensive dataset available for Spanish. We compare the obtained dataset with previous studies in Dutch and English to investigate the role of grammatical gender and studies that used Iberian Spanish to test generalizability to other Spanish variants. Finally, we evaluated the validity of our data in word processing (lexical decision reaction times) and semantic (similarity judgment) tasks. Our results demonstrate that network measures such as in-degree provide a good prediction of lexical decision response times. Analyzing semantic similarity judgments showed that results replicate and extend previous findings demonstrating that semantic similarity derived using spreading activation or spectral methods outperform word embeddings trained on text corpora.

Social networks, secondary syringe exchange, and opioid agonist therapy retention among people who inject drugs in Hartford, CT

BACKGROUND

Opioid agonist therapies (OAT) and  harm reduction such as syringe service programs (SSP) have been shown to be effective in preventing adverse outcomes such as overdose deaths, HIV and Hepatitis C infections among people who inject drugs (PWID). The importance of social network influence on disease transmission is well established, yet the interplay between harm reduction and network structures is, generally, not well understood. This study aims to analyze how social networks can mediate the harm reduction effects associated with secondary exchange through syringe service programs (SSP) and opioid agonist therapies (OAT) among injection network members.

METHODS

Sociometric data on networks on people who inject drugs from Hartford, CT, which were collected in 2012-2013, provided assessment of risk behaviors among 1574 injection network members, including participation in OAT and SSP. Subject's network characteristics were examined in relation to retention in OAT, as well as secondary syringe exchange using exponential random graph model (ERGM) and regression.

RESULTS

Based on the analysis, we found that probability of individuals being retained in OAT was positively associated with the OAT retention status of their peers within the network. Using simulations, we found that higher levels of positive correlation of OAT retention among network members can result in reduced risk of transmission of HIV to network partners on OAT. In addition, we found that secondary syringe exchange engagement was associated with higher probability of sharing of paraphernalia and unsterile needles at the network level.

CONCLUSIONS

Understanding how networks mediate risk behaviors is crucial for making progress toward ending the HIV epidemic.

Multi-omics Resources for Understanding Gene Regulation in Response to ER Stress in Plants

Proteotoxic stress of the endoplasmic reticulum (ER) is a potentially lethal condition that ensues when the biosynthetic capacity of the ER is overwhelmed. A sophisticated and largely conserved signaling, known as the unfolded protein response (UPR), is designed to monitor and alleviate ER stress. In plants, the emerging picture of gene regulation by the UPR now appears to be more complex than ever before, requiring multi-omics-enabled network-level approaches to be untangled. In the past decade, with an increasing access and decreasing costs of next-generation sequencing (NGS) and high-throughput protein-DNA interaction (PDI) screening technologies, multitudes of global molecular measurements, known as omics, have been generated and analyzed by the research community to investigate the complex gene regulation of plant UPR. In this chapter, we present a comprehensive catalog of omics resources at different molecular levels (transcriptomes, protein-DNA interactomes, and networks) along with the introduction of key concepts in experimental and computational tools in data generation and analyses. This chapter will serve as a starting point for both experimentalists and bioinformaticians to explore diverse omics datasets for their biological questions in the plant UPR, with likely applications also in other species for conserved mechanisms.

Life meaning and feelings of ineffectiveness as transdiagnostic factors in eating disorder and comorbid internalizing symptomatology - A combined undirected and causal network approach

The field of eating disorders is facing problems ranging from a suboptimal classification system to low long-term success rates of treatments. There is evidence supporting a transdiagnostic approach to explain the development and maintenance of eating disorders. Meaning in life has been proposed as a promising key transdiagnostic factor that could potentially not only bridge between the different eating disorder subtypes but also explain frequent co-occurrence with symptoms of comorbid psychopathology, such as anxiety and depression. The present study used self-report data from 501 participants to construct networks of eating disorder and comorbid internalizing symptomatology, including factors related to meaning in life, i.e., presence of life meaning, perceived ineffectiveness, and satisfaction with basic psychological needs. In an undirected network model, it was found that ineffectiveness is a central node, also bridging between eating disorder and other psychological symptoms. A directed network model displayed evidence for a causal effect of presence of life meaning both on the core symptomatology of eating disorders and depressive symptoms via ineffectiveness. These results support the notion of meaning in life and feelings of ineffectiveness as transdiagnostic factors within eating disorder symptomatology in the general population.

Towards Inferring Network Properties from Epidemic Data

Epidemic propagation on networks represents an important departure from traditional mass-action models. However, the high-dimensionality of the exact models poses a challenge to both mathematical analysis and parameter inference. By using mean-field models, such as the pairwise model (PWM), the high-dimensionality becomes tractable. While such models have been used extensively for model analysis, there is limited work in the context of statistical inference. In this paper, we explore the extent to which the PWM with the susceptible-infected-recovered (SIR) epidemic can be used to infer disease- and network-related parameters. Data from an epidemics can be loosely categorised as being population level, e.g., daily new cases, or individual level, e.g., recovery times. To understand if and how network inference is influenced by the type of data, we employed the widely-used MLE approach for population-level data and dynamical survival analysis (DSA) for individual-level data. For scenarios in which there is no model mismatch, such as when data are generated via simulations, both methods perform well despite strong dependence between parameters. In contrast, for real-world data, such as foot-and-mouth, H1N1 and COVID19, whereas the DSA method appears fairly robust to potential model mismatch and produces parameter estimates that are epidemiologically plausible, our results with the MLE method revealed several issues pertaining to parameter unidentifiability and a lack of robustness to exact knowledge about key quantities such as population size and/or proportion of under reporting. Taken together, however, our findings suggest that network-based mean-field models can be used to formulate approximate likelihoods which, coupled with an efficient inference scheme, make it possible to not only learn about the parameters of the disease dynamics but also that of the underlying network.

Efficient organisation of the contralateral hemisphere connectome is associated with improvement in intelligence quotient after paediatric epilepsy surgery

OBJECTIVE

Aims of epilepsy surgery in childhood include optimising seizure control and facilitating cognitive development. Predicting which children will improve cognitively is challenging. We investigated the association of the pre-operative structural connectome of the contralateral non-operated hemisphere with improvement in intelligence quotient (IQ) post-operatively.

METHODS

Consecutive children who had undergone unilateral resective procedures for epilepsy at a single centre were retrospectively identified. We included those with pre-operative volume T1-weighted non-contrast brain magnetic resonance imaging (MRI), no visible contralateral MRI abnormalities, and both pre-operative and two years post-operative IQ assessment. The MRI of the hemisphere contralateral to the side of resection was anatomically parcellated into 34 cortical regions and the covariance of cortical thickness between regions was used to create binary and weighted group connectomes.

RESULTS

Eleven patients with a post-operative IQ increase of at least 10 points at two years were compared with twenty-four patients with no change in IQ score. Children who gained at least 10 IQ points post-operatively had a more efficiently structured contralateral hemisphere connectome with higher global efficiency (0.74) compared to those whose IQ did not change at two years (0.58, p = 0.014). This was consistent across thresholds and both binary and weighted networks. There were no statistically significant group differences in age, sex, age at onset of epilepsy, pre-operative IQ, mean cortical thickness, side or site of procedure, two year post-operative Engel scores or use of anti-seizure medications between the two groups.

CONCLUSIONS

Surgical procedures to reduce or stop seizures may allow children with an efficiently structured contralateral hemisphere to achieve their cognitive potential.

[Interprofessional recommendations on behalf of Société française de radiothérapie oncologique for the prevention, protection and management of cyberattacks in radiation oncology]

Cybersecurity is currently a major issue. Large hospitals are no longer the only main targets of attacks, but all healthcare organizations and establishments, without distinction of size or activities. The information system is defined as all the resources needed to collect images, store and process them with general distribution of multiple information within an organization. Systems are therefore crucial for the functioning of a medical department. Radiation oncology is one of the specialties most dependent on digital resources, for imaging, data transfer, dosimetry, treatment and so on.. Radiation oncology departments are therefore a prime target for ransomware attacks, which have increased significantly in recent years. Cybersecurity can be likened to a viral or bacterial attack. It is based on the two usual pillars of antimicrobial protection : hygiene and prophylaxis. In this article, we will detail by analogy the three classic levels of prevention of a bacillary attack: "primary prevention", which acts upstream of the infection; "secondary prevention", which acts at an early stage of its evolution; and "tertiary prevention", which acts on complications and risks of recurrence. This article is the result of an interprofessional group on behalf of SFRO, the French society of radiation oncology, with the aim of helping all teams to implement safety adapted to the specificities of a radiation oncology department in France.

Supporting implementation science and health equity in cancer prevention and control through research networks

The Cancer Prevention and Control Research Network (CPCRN) is a national network of academic, public health, and community organizational partners across multiple geographic sites who collaborate to reduce the cancer burden in diverse communities. Given key recommendations that suggest the need for cross-disciplinary collaboration in cancer prevention and control, we sought to explore the historical and contemporary evolution of health equity and disparities research as an area of focus within the CPCRN over time. We conducted 22 in-depth interviews with former and current leaders, co-investigators, and other members of the network. Several key themes emerged from data that were analyzed and interpreted using a constructivist, reflexive, thematic analysis approach. Nearly all participants reported a strong focus on studying health disparities since the inception of the CPCRN, which offered the network a distinct advantage in recent years for incorporating an intentional focus on health equity. Recent law enforcement injustices and the inequities observed during the COVID-19 pandemic have further invigorated network activities around health equity, such as development of a health equity-focused workgroup toolkit, among other cross-center activities. Several participants noted that, in terms of deep, meaningful, and impactful health equity-oriented research, there are still great strides for the network to make, while also acknowledging CPCRN as well-aligned with the national dialogue led by federal agency partners around health equity. Finally, several future directions were mentioned by the participants, including a focus on supporting a diverse workforce and engaging organizational partners and community members in equity-focused research. Findings from these interviews provide direction for the network in advancing the science in cancer prevention and control, with a strengthened focus on health equity.

[Identification of regional hospice and palliative care networks in Germany - Results of a multi-method survey]

INTRODUCTION

In the course of the implementation of the German Healthcare Development Act [Gesundheitsversorgungsweiterentwicklungsgesetz] of 2021, a funding structure according to sect. 39d of the Social Code Book V [SGB V] was established to promote regional hospice and palliative care networks (RHPN). The funded networks are expected to support the multiprofessional cooperation of hospice and palliative care providers at the structural level. It is still unclear how many existing and newly established network structures are eligible for funding according to sect. 39d SGB V and where these network structures are located regionally. The proportion of actually funded networks is also unknown.

METHODS

Between January and March 2023, network structures of hospice and palliative care were identified in a tripartite, multi-method survey procedure, consisting of a) research of databases, literature, and internet; b) open quantitative online-survey via SoSciSurvey software, and c) telephone survey of federal offices of health insurers. The data were first documented separately. Then, the research and survey data were combined and analysed via descriptive statistics using SPSS.

RESULTS

Based on the aggregated data from the literature-, database- and internet research and the online survey, n=308 network structures of hospice and palliative care could be identified, of which n=37 have applied for network funding according to sect. 39d SGB V. In the survey period, n=47 applications for network funding according to sect. 39d SGB V were submitted to the health insurance funds. There is a high density of network structures in the northern, southern and western federal states, while there are only a few networks in the eastern states. According to the online-survey, 56% (n=136) of all the identified network structures with known sponsorship are organised by providers of specialised outpatient palliative care. 47% (n=29) of the networks with funding interest are organised as independent structures. Of the network structures with known funding status, 18% (n=26) plan to apply for funding according to sect. 39d SGB V in 2024 for the first time.

DISCUSSION

There are numerous network structures in hospice and palliative care, but they are differently distributed among the German federal states. The multi-method survey was able to provide a first nation-wide inventory of network structures as well as an assessment of networks with funding interest according to sect. 39 SGB V. A clear distinction between general network structures and structural networks according to sect. 39d SGB V is a challenge. In the next years the number of funding applications is expected to rise.

CONCLUSION

The identification of existing and funded network structures of hospice and palliative care in Germany can be a starting point for a deeper analysis of the structure and the activities of the networks. A quality assessment tool that takes into account both the heterogeneity of the networks and the different dimensions of networking would be helpful.

Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is an immune-mediated neurological disorder, and up to 50% of patients experience depression. We investigated how white matter network disruption is related to depression in MS.

METHODS

Using electronic health records, 380 participants with MS were identified. Depressed individuals (MS+Depression group; n = 232) included persons who had an ICD-10 depression diagnosis, had a prescription for antidepressant medication, or screened positive via Patient Health Questionnaire (PHQ)-2 or PHQ-9. Age- and sex-matched nondepressed individuals with MS (MS-Depression group; n = 148) included persons who had no prior depression diagnosis, had no psychiatric medication prescriptions, and were asymptomatic on PHQ-2 or PHQ-9. Research-quality 3T structural magnetic resonance imaging was obtained as part of routine care. We first evaluated whether lesions were preferentially located within the depression network compared with other brain regions. Next, we examined if MS+Depression patients had greater lesion burden and if this was driven by lesions in the depression network. Primary outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain.

RESULTS

MS lesions preferentially affected fascicles within versus outside the depression network (β = 0.09, 95% CI = 0.08 to 0.10, p < .001). MS+Depression patients had more lesion burden (β = 0.06, 95% CI = 0.01 to 0.10, p = .015); this was driven by lesions within the depression network (β = 0.02, 95% CI = 0.003 to 0.040, p = .020).

CONCLUSIONS

We demonstrated that lesion location and burden may contribute to depression comorbidity in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression patients had more disease than MS-Depression patients, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Examining the Interrelationships Between Social Isolation and Loneliness and Their Correlates Among Older British Adults Before and During the COVID-19 Lockdown: Evidence From Four British Longitudinal Studies

Background and Objectives

Unprecedented social restrictions during the coronavirus disease 2019 (COVID-19) pandemic have provided a new lens for considering the interrelationship between social isolation and loneliness in later life. We present these interrelationships before and during the COVID-19 restrictions and investigate to what extent demographic, socioeconomic, and health factors associated with such experiences differed during the pandemic.

Research Design and Methods

We used data from four British longitudinal population-based studies (1946 NSHD, 1958 NCDS, 1970 BCS, and ELSA, N = 12,129). Rates, co-occurrences, and correlates of social isolation and loneliness are presented prior to and during the early stage of the COVID-19 pandemic and the interrelationships between these experiences are elucidated in both periods.

Results

Across the Four studies, prepandemic proportions reporting social isolation ranged from 15% to 54%, with higher rates in older ages (e.g., 32% of individuals aged 70-79 years and 54% of those more than 80). During the pandemic, the percentage of older people reporting both social isolation and loneliness and isolation only slightly increased. The interrelationship between social isolation and loneliness did not change. Associations between sociodemographic and health characteristics and social isolation and loneliness also remained consistent, with greater burden among those with higher economic precarity (females, nonhomeowners, unemployed, illness, and greater financial stress).

Discussion and Implications

There were already large inequalities in experiences of social isolation and loneliness and the pandemic had a small impact on worsening extent and inequalities in these. The concepts of loneliness and social isolation are not interchangeable, and clarity is needed in how they are conceptualized, operationalized, and interpreted. Given many older adults experience high levels of social isolation, there should be greater emphasis on reducing social isolation and the inequalities observed in who experiences greater isolation and loneliness.

Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a lateral aspect of the right dorsolateral prefrontal cortex (latDLPFC) in migraine patients. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this latDLPFC region, and diffusion weighted imaging (DWI) verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

Temporal and Probabilistic Comparisons of Epidemic Interventions

Forecasting disease spread is a critical tool to help public health officials design and plan public health interventions. However, the expected future state of an epidemic is not necessarily well defined as disease spread is inherently stochastic, contact patterns within a population are heterogeneous, and behaviors change. In this work, we use time-dependent probability generating functions (PGFs) to capture these characteristics by modeling a stochastic branching process of the spread of a disease over a network of contacts in which public health interventions are introduced over time. To achieve this, we define a general transmissibility equation to account for varying transmission rates (e.g. masking), recovery rates (e.g. treatment), contact patterns (e.g. social distancing) and percentage of the population immunized (e.g. vaccination). The resulting framework allows for a temporal and probabilistic analysis of an intervention's impact on disease spread, which match continuous-time stochastic simulations that are much more computationally expensive. To aid policy making, we then define several metrics over which temporal and probabilistic intervention forecasts can be compared: Looking at the expected number of cases and the worst-case scenario over time, as well as the probability of reaching a critical level of cases and of not seeing any improvement following an intervention. Given that epidemics do not always follow their average expected trajectories and that the underlying dynamics can change over time, our work paves the way for more detailed short-term forecasts of disease spread and more informed comparison of intervention strategies.

A dynamic framework for making sense of partnerships between universities and informal education providers

We present a conceptual framework rooted in the practices and experiences of nine collaborative partnerships between universities and informal science education organizations. Our analysis and resulting framework aim to support those brokering, designing, and evaluating partnerships in making sense of the dynamism of interorganizational efforts to collaborate in achieving broader impacts of research. We highlight the critical role of brokers in modulating attentions between interorganizational, intraorganizational, and networked dimensions of their collaborations to maintain partnership health and continue progress toward shared goals.

Analysis of the emerging physical network in young mycelia

Filamentous fungi develop intricate hyphal networks that support mycelial foraging and transport of resources. These networks have been analyzed recently using graph theory, enabling the development of models that seek to predict functional traits. However, attention has focused mainly on mature colonies. Here, we report the extraction and analysis of the graph corresponding to Trichoderma atroviride mycelia only a few hours after conidia germination. To extract the graph for a given mycelium, a mosaic conformed of multiple bright-field, optical microscopy images is digitally processed using freely available software. The resulting graphs are characterized in terms of number of nodes and edges, average edge length, total mycelium length, hyphal growth unit, maximum edge length and mycelium diameter, for colonies between 8 h and 14 h after conidium germination. Our results show that the emerging hyphal network grows first by hyphal elongation and branching, and then it transitions to a stage where hyphal-hyphal interactions become significant. As a tangled hyphal network develops with decreasing hyphal mean length, the mycelium maintains long (∼2 mm) hyphae-a behavior that suggests a combination of aggregated and dispersed architectures to support foraging. Lastly, analysis of early network development in Podospora anserina reveals striking similarity with T. atroviride, suggesting common mechanisms during initial colony formation in filamentous fungi.

Developing an understanding of networks with a focus on LMIC health systems: How and why clinical and programmatic networks form and function to be able to change practices: A realist review

Networks are an increasingly employed approach to improve quality of care, service delivery, and health systems performance, particularly in low-and-middle income country (LMIC) health systems. The literature shows that networks can improve the provision and quality of services and health system functioning but there is limited evidence explaining how and why networks are established and work to achieve their reported results. We undertook a realist review to explore this. The objective of this realist review was to develop a programme theory outlining the underlying mechanisms and interactions of contexts that explain how and why a network's set-up and function enable high-quality care and services and improved clinical outcomes in LMIC health systems. We followed Pawson's five steps for realist reviews. The search strategy was based on a previously published scoping review with additional searches. Literature was selected based on its relevance to the programme theory and rigour. Context-mechanism-outcome configurations were developed from the extracted data to refine the initial programme theory with causal explanations. Theories on social movements and organisations supported the identification of mechanism and brought additional explanatory power to the programme theory. The programme theory explains how networks are initiated, formed, and function in a way that sets them up for network leadership and committed, engaged, and motivated network members to emerge and to change practices, which may lead to improved quality of care, service delivery, and clinical outcomes through the following phases: identify a problem, developing a collective vision, taking action to solve the problem, forming purposeful relationships, linkages, and partnerships, building a network identity and culture, and the creation of a psychological safe space. This deeper understanding of networks formation and functioning can lead to a more considered planning and implementation of networks, thereby improving health system functioning and performance.

Practice development amidst a pandemic: a pilot programme to develop leadership in infection prevention and control professionals

PURPOSE

This paper aims to describe the design and evaluation of a pilot leadership development programme for infection prevention and control (IPAC) professionals during the COVID-19 pandemic. The programme's aim was to improve IPAC knowledge and capacity in the health-care system by developing the leadership skills and capacities of novice and advanced Infection Control Professionals (ICPs), to respond flexibly, and competently, in their expanding and ever-changing roles.

DESIGN/METHODOLOGY/APPROACH

The leadership programme was piloted with seven nurses, who were part of a clinical nursing team in New South Wales, Australia, over a 12-month period between 2021 and 2022. The programme was designed using a leadership development framework underpinned by transformational leadership theory, practice development approaches and collaborative and experiential learning. These principles were applied during programme design, with components adapted to learners' interests and regular opportunities provided for collaboration in active learning and critical reflection on workplace experiences.

FINDINGS

The authors' evaluation suggests that the programme was feasible, acceptable and considered to be effective by this cohort. Moreover, participants valued the opportunities to engage in active and experience-based learning with peers, and with the support of senior and experienced ICPs. The action learning sets were well-received and allowed participants to critically reflect on and learn from one another's experiences. The mentoring programme allowed them to apply their developing leadership skills to real workplace challenges that they face.

RESEARCH LIMITATIONS/IMPLICATIONS

Despite a small sample size, the authors' results provide empirical evidence about the effectiveness of using a practice development approach for strengthening ICP leadership capacity. The success of this pilot study has paved the way for a bigger second cohort of participants in the programme, for which further evaluation will be conducted.

PRACTICAL IMPLICATIONS

The success of this leadership programme reflects both the need for leadership development in the IPAC professions and the applicability of this approach, with appropriate facilitation, for other professions and organizations.

ORIGINALITY/VALUE

ICP leadership programmes have not been previously reported in the literature. This pilot study builds on the growing interest in IPAC leadership to foster health system responsiveness and change.

Unveiling Potential Targeted Therapeutic Opportunities for Co-Overexpressed Targeting Protein for Xklp2 and Aurora-A Kinase in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most prevalent and leading causes of cancer deaths globally, with limited diagnostic and clinically significant therapeutic targets. Identifying the genes and processes involved in developing and progressing LUAD is crucial for developing effective targeted therapeutics and improving patient outcomes. Therefore, the study aimed to explore the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) and gene expression profile datasets involving GSE10072, GSE31210, and GSE32863 from the Gene Expression Omnibus (GEO) databases. The differential gene expression and the downstream analysis determined clinically significant biomarkers using a network-based approach. These therapeutic targets predominantly enriched the dysregulation of mitotic cell cycle regulation and revealed the co-overexpression of Aurora-A Kinase (AURKA) and Targeting Protein for Xklp2 (TPX2) with high survival risk in LUAD patients. The hydrophobic residues of the AURKA-TPX2 interaction were considered as the target site to block the autophosphorylation of AURKA during the mitotic cell cycle. The tyrosine kinase inhibitor (TKI) dacomitinib demonstrated the strong binding potential to hinder TPX2, shielding the AURKA destabilization. This in silico study lays the foundation for repurposing targeted therapeutic options to impede the Protein-Protein Interactions (PPIs) in LUAD progression and aid in future translational investigations.

Tetrabromobisphenol A transformation by biochar supported post-sulfidated nanoscale zero-valent iron: Mechanistic insights from shell control and solvent kinetic isotope effects

Post-sulfidated nanoscale zero-valent iron with a controlled FeS_X shell thickness deposited on biochar (S-nZVI/BC) was synthesized to degrade tetrabromobisphenol A (TBBPA). Detailed characterizations revealed that the increasing sulfidation degree altered shell thickness/morphology, S content/speciation/distribution, hydrophobicity, and electron transfer capacity. Meanwhile, the BC improved electron transfer capacity and hydrophobicity and inhibited the surface oxidation of S-nZVI. These properties endowed S-nZVI/BC with highly reactive (∼8.9-13.2 times) and selective (∼58.4-228.9 times) over nZVI/BC in TBBPA transformation. BC modification improved the reactivity and selectivity of S-nZVI by 1.77 and 1.96 times, respectively. The difference of S-nZVI/BC in reactivity was related to hydrophobicity and electron transfer, particularly FeS_X shell thickness and morphology. Optimal shell thickness of ∼32 nm allowed the maximum association between Fe⁰ core and exterior FeS_X, resulting in superior reactivity. A thicker shell with abundant networks increased the roughness but decreased the surface area and electron transfer. The higher [S/Fe]_surface and [S/Fe]_particle were conducive to the selectivity, and [S/Fe]_particle was more influential than [S/Fe]_surface on selectivity upon similar hydrophobicity. The solvent kinetic isotope effects (SKIEs) exhibited that increasing [S/Fe]_dose tuned the relative contributions of atomic H and electron in TBBPA debromination but failed to alter the dominant debromination pathway (i.e., direct electron transfer) in (S)-nZVI/BC systems. Mechanism of electron transfer rather than atomic H contributed to higher selectivity. This work demonstrated that S-nZVI/BC was a prospective material for the remediation of TBBPA-contaminated groundwater.

Eco-evolutionary dynamics in finite network-structured populations with migration

We consider the effect of network structure on the evolution of a population. Models of this kind typically consider a population of fixed size and distribution. Here we consider eco-evolutionary dynamics where population size and distribution can change through birth, death and migration, all of which are separate processes. This allows complex interaction and migration behaviours that are dependent on competition. For migration, we assume that the response of individuals to competition is governed by tolerance to their group members, such that less tolerant individuals are more likely to move away due to competition. We look at the success of a mutant in the rare mutation limit for the complete, cycle and star networks. Unlike models with fixed population size and distribution, the distribution of the individuals per site is explicitly modelled by considering the dynamics of the population. This in turn determines the mutant appearance distribution for each network. Where a mutant appears impacts its success as it determines the competition it faces. For low and high migration rates the complete and cycle networks have similar mutant appearance distributions resulting in similar success levels for an invading mutant. A higher migration rate in the star network is detrimental for mutant success because migration results in a crowded central site where a mutant is more likely to appear.

Alcohol Dependence Modifies Brain Networks Activated During Withdrawal and Reaccess: A c-Fos-Based Analysis in Mice

BACKGROUND

High-level alcohol consumption causes neuroplastic changes in the brain that promote pathological drinking behavior. Some of these changes have been characterized in defined brain circuits and cell types, but unbiased approaches are needed to explore broader patterns of adaptations.

METHODS

We used whole-brain c-Fos mapping and network analysis to assess patterns of neuronal activity during alcohol withdrawal and following reaccess in a well-characterized model of alcohol dependence. Mice underwent 4 cycles of chronic intermittent ethanol to increase voluntary alcohol consumption, and a subset underwent forced swim stress to further escalate consumption. Brains were collected either 24 hours (withdrawal) or immediately following a 1-hour period of alcohol reaccess. c-fos counts were obtained for 110 brain regions using iDISCO and ClearMap. Then, we classified mice as high or low drinkers and used graph theory to identify changes in network properties associated with high-drinking behavior.

RESULTS

During withdrawal, chronic intermittent ethanol mice displayed widespread increased c-Fos expression relative to air-exposed mice, independent of forced swim stress. Reaccess drinking reversed this increase. Network modularity, a measure of segregation into communities, was increased in high-drinking mice after alcohol reaccess relative to withdrawal. The cortical amygdala showed increased cross-community coactivation during withdrawal in high-drinking mice, and cortical amygdala silencing in chronic intermittent ethanol mice reduced voluntary drinking.

CONCLUSIONS

Alcohol withdrawal in dependent mice causes changes in brain network organization that are attenuated by reaccess drinking. Olfactory brain regions, including the cortical amygdala, drive some of these changes and may play an important but underappreciated role in alcohol dependence.

Comparative assessment of Ca2+ oscillations in 2- and 3-dimensional hiPSC derived and isolated cortical neuronal networks

Human induced Pluripotent Stem Cell (hiPSC) derived neural cells offer great potential for modelling neurological diseases and toxicities and have found application in drug discovery and toxicology. As part of the European Innovative Medicines Initiative (IMI2) NeuroDeRisk (Neurotoxicity De-Risking in Preclinical Drug Discovery), we here explore the Ca2+ oscillation responses of 2D and 3D hiPSC derived neuronal networks of mixed Glutamatergic/GABAergic activity with a compound set encompassing both clinically as well as experimentally determined seizurogenic compounds. Both types of networks are scored against Ca2+ responses of a primary mouse cortical neuronal 2D network model serving as an established comparator assay. Parameters of frequency and amplitude of spontaneous global network Ca2+ oscillations and the drug-dependent directional changes to these were assessed, and predictivity of seizurogenicity scored using contingency table analysis. In addition, responses between models were compared between both 2D models as well as between 2D and 3D models. Concordance of parameter responses was best between the hiPSC neurospheroid and the mouse primary cortical neuron model (77% for frequency and 65% for amplitude). Decreases in spontaneous Ca2+ oscillation frequency and amplitude were found to be the most basic shared determinants of risk of seizurogenicity between the mouse and the neurospheroid model based on testing of clinical compounds with documented seizurogenic activity. Increases in spontaneous Ca2+ oscillation frequency were primarily observed with the 2D hIPSC model, though the specificity of this effect to seizurogenic clinical compounds was low (33%), while decreases to spike amplitude in this model were more predictive of seizurogenicity. Overall predictivities of the models were similar, with sensitivity of the assays typically exceeding specificity due to high false positive rates. Higher concordance of the hiPSC 3D model over the 2D model when compared to mouse cortical 2D responses may be the result of both a longer maturation time of the neurospheroid (84-87 days for 3D vs. 22-24 days for 2D maturation) as well as the 3-dimensional nature of network connections established. The simplicity and reproducibility of spontaneous Ca2+ oscillation readouts support further investigation of hiPSC derived neuronal sources and their 2- and 3-dimensional networks for neuropharmacological safety screening.

Shape-recovering nanocellulose networks: Preparation, characterization and modeling

Development of strong cellulose nanofibril (CNF) networks for advanced applications, such as in the biomedical field, is of high importance owing to the biocompatible nature and plant-based origin of cellulose nanofibrils. Nevertheless, lack of mechanical strength and complex synthesis methods hinder the application of these materials in areas where both toughness and manufacturing simplicity are required. In this work, we introduce a facile method for the synthesis of a low solid content (< 2 wt%), covalently crosslinked CNF hydrogel where Poly (N-isopropylacrylamide) (NIPAM) chains are utilized as crosslinks between the nanofibrils. The resulting networks have the capability to fully recover the shape in which they were formed after various drying and rewetting cycles. Characterization of the hydrogel and its constitutive components was performed using X-ray scattering, rheological investigations and uniaxial testing in compression. Influence of covalent crosslinks was compared with networks crosslinked by the addition of CaCl₂. Among other things the results show that the mechanical properties of the hydrogels can be tuned by controlling the ionic strength of the surrounding medium. Finally, a mathematical model was developed based on the experimental results, which describes and predicts to a decent degree the large-deformation, elastoplastic behavior, and fracture of these networks.

Patterns of collaboration and knowledge generated by an Australian rural research centre over 20 years: a co-authorship network analysis

BACKGROUND

People living in rural areas have poorer health than their urban counterparts. Although rural health research centres have been promoted as vehicles for improving rural health by contributing evidence to address rural health disadvantage and building research capacity, their characteristics and evolution are poorly understood. Collaboration is known to have an important positive influence on research outputs and research quality. In this study we examine publication outputs from an Australian rural research centre to evaluate how researchers have engaged in research collaboration over a two-decade period.

METHODS

A retrospective longitudinal study of publications in peer-reviewed journals from a rural research centre-University Centre for Rural Health (UCRH) -between January 2002 and December 2021. Organisational co-author networks across four periods (2002-2006; 2007-2011; 2012-2016; 2017-2021) were constructed based on author organisational affiliations and examined using social network analysis methods. Descriptive characteristics included organisation types, study design, region of study focus, thematic research trends, Aboriginal and Torres Strait Islander and female authorship, and journal characteristics.

RESULTS

We identified 577 publications with 130 different UCRH-affiliated authors. Publications and the co-author network increased in number and diversity over each period, with an acceleration and a consolidation of the network in the final period. Over time there was an increase in publications related to Aboriginal and Torres Strait Islander health, coupled with an increase in Aboriginal and Torres Strait Islander authorship and collaborations with Aboriginal and Torres Strait Islander organisations; rise in female senior authorship and publication in quartile 1 journals. About two-thirds of publications make no reference to regional or remote populations.

CONCLUSION

Collaboration in publications increased, expanded, and consolidated, which coincided with an increase in the number and diversity of both co-authoring organisations and UCRH-affiliated authors in the final period. The findings highlight the value of collaborations (including urban and international) in building and strengthening rural health research capacity. With increased capacity and consolidation of the network it is now imperative that research becomes more focussed on understanding and addressing rural health inequities.

Necessary and sufficient conditions for exact closures of epidemic equations on configuration model networks

We prove that it is possible to obtain the exact closure of SIR pairwise epidemic equations on a configuration model network if and only if the degree distribution follows a Poisson, binomial, or negative binomial distribution. The proof relies on establishing the equivalence, for these specific degree distributions, between the closed pairwise model and a dynamical survival analysis (DSA) model that was previously shown to be exact. Specifically, we demonstrate that the DSA model is equivalent to the well-known edge-based Volz model. Using this result, we also provide reductions of the closed pairwise and Volz models to a single equation that involves only susceptibles. This equation has a useful statistical interpretation in terms of times to infection. We provide some numerical examples to illustrate our results.

The spread of COVID-19 in London: Network effects and optimal lockdowns

We generalise a stochastic version of the workhorse SIR (Susceptible-Infectious-Removed) epidemiological model to account for spatial dynamics generated by network interactions. Using the London metropolitan area as a salient case study, we show that commuter network externalities account for about 42% of the propagation of COVID-19. We find that the UK lockdown measure reduced total propagation by 44%, with more than one third of the effect coming from the reduction in network externalities. Counterfactual analyses suggest that: (i) the lockdown was somehow late, but further delay would have had more extreme consequences; (ii) a targeted lockdown of a small number of highly connected geographic regions would have been equally effective, arguably with significantly lower economic costs; (iii) targeted lockdowns based on threshold number of cases are not effective, since they fail to account for network externalities.

Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life

How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing.

A hierarchical intervention scheme based on epidemic severity in a community network

As there are no targeted medicines or vaccines for newly emerging infectious diseases, isolation among communities (villages, cities, or countries) is one of the most effective intervention measures. As such, the number of intercommunity edges ([Formula: see text]) becomes one of the most important factor in isolating a place since it is closely related to normal life. Unfortunately, how [Formula: see text] affects epidemic spread is still poorly understood. In this paper, we quantitatively analyzed the impact of [Formula: see text] on infectious disease transmission by establishing a four-dimensional [Formula: see text] edge-based compartmental model with two communities. The basic reproduction number [Formula: see text] is explicitly obtained subject to [Formula: see text] [Formula: see text]. Furthermore, according to [Formula: see text] with zero [Formula: see text], epidemics spread could be classified into two cases. When [Formula: see text] for the case 2, epidemics occur with at least one of the reproduction numbers within communities greater than one, and otherwise when [Formula: see text] for case 1, both reproduction numbers within communities are less than one. Remarkably, in case 1, whether epidemics break out strongly depends on intercommunity edges. Then, the outbreak threshold in regard to [Formula: see text] is also explicitly obtained, below which epidemics vanish, and otherwise break out. The above two cases form a severity-based hierarchical intervention scheme for epidemics. It is then applied to the SARS outbreak in Singapore, verifying the validity of our scheme. In addition, the final size of the system is gained by demonstrating the existence of positive equilibrium in a four-dimensional coupled system. Theoretical results are also validated through numerical simulation in networks with the Poisson and Power law distributions, respectively. Our results provide a new insight into controlling epidemics.

Temporal Mapper: Transition networks in simulated and real neural dynamics

Characterizing large-scale dynamic organization of the brain relies on both data-driven and mechanistic modeling, which demands a low versus high level of prior knowledge and assumptions about how constituents of the brain interact. However, the conceptual translation between the two is not straightforward. The present work aims to provide a bridge between data-driven and mechanistic modeling. We conceptualize brain dynamics as a complex landscape that is continuously modulated by internal and external changes. The modulation can induce transitions between one stable brain state (attractor) to another. Here, we provide a novel method-Temporal Mapper-built upon established tools from the field of topological data analysis to retrieve the network of attractor transitions from time series data alone. For theoretical validation, we use a biophysical network model to induce transitions in a controlled manner, which provides simulated time series equipped with a ground-truth attractor transition network. Our approach reconstructs the ground-truth transition network from simulated time series data better than existing time-varying approaches. For empirical relevance, we apply our approach to fMRI data gathered during a continuous multitask experiment. We found that occupancy of the high-degree nodes and cycles of the transition network was significantly associated with subjects' behavioral performance. Taken together, we provide an important first step toward integrating data-driven and mechanistic modeling of brain dynamics.

Target set selection in social networks with tiered influence and activation thresholds

Thanks to the mass adoption of internet and mobile devices, users of the social media can seamlessly and spontaneously connect with their friends, followers and followees. Consequently, social media networks have gradually become the major venue for broadcasting and relaying information, and is casting great influences on the people in many aspects of their daily lives. Thus locating those influential users in social media has become crucially important for the successes of many viral marketing, cyber security, politics, and safety-related applications. In this study, we address the problem through solving the tiered influence and activation thresholds target set selection problem, which is to find the seed nodes that can influence the most users within a limited time frame. Both the minimum influential seeds and maximum influence within budget problems are considered in this study. Besides, this study proposes several models exploiting different requirements on seed nodes selection, such as maximum activation, early activation and dynamic threshold. These time-indexed integer program models suffer from the computational difficulties due to the large numbers of binary variables to model influence actions at each time epoch. To address this challenge, this paper designs and leverages several efficient algorithms, i.e., Graph Partition, Nodes Selection, Greedy algorithm, recursive threshold back algorithm and two-stage approach in time, especially for large-scale networks. Computational results show that it is beneficial to apply either the breadth first search or depth first search greedy algorithms for the large instances. In addition, algorithms based on node selection methods perform better in the long-tailed networks.

Leadership and international collaboration on COVID-19 research: reducing the North-South divide?

The COVID-19 pandemic triggered unprecedented scientific efforts worldwide and launched several initiatives to promote international cooperation. Because international scientific collaborations between high-income countries (HICs) and low- and middle-income countries (LMICs) are not always balanced, analyzing research leadership helps to understand the global dynamics of knowledge production during COVID-19. In this study, we focused on HIC-LMIC collaborations on COVID-19 research in 469,937 scientific publications during the first 2 years of the pandemic (2020-2021). Co-authorship and authors' affiliation were used to identify international collaborations, according to country income level. The leadership analysis considered the countries of the first and last authors of publications. The results show that (i) most publications with international collaborations (49.3%) involved researchers from HICs and LMICs; (ii) collaborative research between HICs and LMICs addressed relevant public health needs; (iii) HIC-LMIC collaborations were primarily led by researchers from the United States, China, the United Kingdom, and India; (iv) most HIC-LMIC publications (44%) had shared leadership, with research interests linked to national expertise and global interests. This study contributes to the analysis of research collaborations on COVID-19 and sheds light on North-South relations in the production and dissemination of scientific knowledge.

Functional hyperconnectivity between corticocerebellar networks and altered decision making in young adult cannabis users: Evidence from 7T and multivariate pattern analysis

Decision-making (DM) impairments are important predictors of cannabis initiation and continued use. In cannabis users, how decision-making abnormalities related to structural and functional connectivity in the brain are not fully understood. We employed a three-method multimodal image analysis and multivariate pattern analysis (MVPA) on high dimensional 7 tesla MRI images examining functional connectivity, white matter microstructure and gray matter volume in a group of cannabis users and non-users. Neuroimaging and cognitive analyses were performed on 92 CU and 92 age- matched NU from a total of 187 7T scans. CU were selected on the basis of their scores on the Semi-Structured Assessment for the Genetics of Alcoholism. The groups were first compared on a decision-making test and then on ICA based functional connectivity between corticocerebellar networks. An MVPA was done as a confirmatory analysis. The anatomy of these networks was then assessed using Diffusion Tensor imaging (DTI) and cortical volume analyses. Cannabis Users had significantly higher scores on the Iowa Gambling task (IGT) [Gambling task Percentage larger] and significantly lower scores on the [Gambling task reward Percentage smaller]. Left accumbens (L NAc) volume was significantly larger in cannabis users. DTI analysis between the groups yielded no significant (FWE corrected) differences. Resting state FC analysis of the left Cerebellum region 9 showed enhanced functional connectivity with the right nucleus accumbens and left pallidum and left putamen in CU. In addition, posterior cerebellum showed enhanced functional connectivity (FWE corrected) with 2 nodes of the DMN and left and right paracingulate (sub genual ACC) and the sub callosal cortex in CU. IGT percentage larger scores correlated with posterior cerebellar functional connectivity in non-user women. A multivariate pattern analysis confirmed this cerebellar hyperconnectivity in both groups. Our results demonstrate for the first time that deficits in DM observed in cannabis users are mirrored in hyper connectivity in corticocerebellar networks. Cortical volumes of some of the nodes of these networks showed increases in users. However, the underlying white matter was largely intact in CU. The observed DM deficits and hyper connectivity in resting networks may contribute to difficulties in quitting and/or facilitating relapse.

Exchange rates and multicommodity international trade: insights from spatial price equilibrium modeling with policy instruments via variational inequalities

In this paper, we construct a multicommodity international trade spatial price equilibrium model of special relevance to agriculture in which exchange rates are included along with policy instruments in the form of tariffs, subsidies as well as quotas. The model allows for multiple trade routes between country origin nodes and country destination nodes and these trade routes can include different modes of transportation and transport through distinct countries. We capture the impacts of exchange rates through the definition of effective path costs and identify the governing multicommodity international trade spatial price equilibrium conditions, which are then formulated as a variational inequality problem in product path flows. Existence results are established and a computational procedure presented. The illustrative numerical examples and a case study are inspired by the impacts of the war against Ukraine on agricultural trade flows and product prices. The modeling and algorithmic framework allows for the quantification of the impacts of exchange rates and various trade policies, as well as the addition or deletion of supply markets, demand markets and/or routes, on supply and demand market prices in local currencies, and on the volume of product trade flows with implications for food security.

Operationalizing anthropological theory: four techniques to simplify networks of co-occurring ethnographic codes

The use of data and algorithms in the social sciences allows for exciting progress, but also poses epistemological challenges. Operations that appear innocent and purely technical may profoundly influence final results. Researchers working with data can make their process less arbitrary and more accountable by making theoretically grounded methodological choices. We apply this approach to the problem of simplifying networks representing ethnographic corpora, in the interest of visual interpretation. Network nodes represent ethnographic codes, and their edges the co-occurrence of codes in a corpus. We introduce and discuss four techniques to simplify such networks and facilitate visual analysis. We show how the mathematical characteristics of each one are aligned with an identifiable approach in sociology or anthropology: structuralism and post-structuralism; identifying the central concepts in a discourse; and discovering hegemonic and counter-hegemonic clusters of meaning. We then provide an example of how the four techniques complement each other in ethnographic analysis.

A Study of Healthcare Team Communication Networks using Visual Analytics

Cooperation among teams or individuals of healthcare professionals (HCPs) is one of the crucial factors towards patients' survival outcome. However, it is challenging to uncover and understand such factors in the complex Multiteam System (MTS) communication networks representing daily HCP cooperation. In this paper, we present a study on MTS communication networks constructed with real-world cancer patients' Electronic Health Record (EHR) access logs. We adopt a visual analytics workflow to extract associations between semantic characteristics of MTS communication networks and the patients' survival outcomes. The workflow consists of a neural network learning phase to classify the data based on the chosen input and output attributes, a dimensionality reduction and optimization phase to produce a simplified set of results for examination, and finally an interpreting phase conducted by the user through an interactive visualization interface. We provide the insights found using this workflow with two case studies and an expert interview.

Getting our hopes up: How actors perceive network effectiveness and why it matters

Health care's grand challenges, such as continuously increasing costs, challenge the sustainability of health systems. Purpose-oriented networks are considered a favorable mode of organization to address these grand challenges. Therefore, it is crucial that they are effective. While network effectiveness is a heavily theorized, multi-dimensional concept that is often measured as a perception of actors, little is known about how network actors perceive effectiveness in practice and how this influences their behavior. In this study, we explored how network actors perceive network effectiveness using 32 interviews with representatives from network member organizations and regulatory agencies actor, 28 h of network meeting observations, and 1.272 pages of documents such as meeting minutes and media outlets. Our results show that actors primarily see hard outcomes (e.g. changes in cost or quality of care) as effectiveness but given the temporal nature of these goals and difficulties quantifying them, they resort to the collaborative process as a proxy to assess effectiveness. Actors engage in networks to solve grand challenges. However, conforming to expectations and environmental pressures also play a substantial role for actors to (continue to) participate in networks. In the absence of hard outcomes, actors legitimize their continued participation in networks using the collaborative process of networks. Actors therefore take purpose-oriented networks for granted as a legitimate way of organizing. Besides attempting to solve grand challenges, networks thus also seem to be adopted because of powerful institutional rules that function as rationalized myths, to gain legitimacy. Future research should be aware of and further unravel the institutional pressures in networks.