Network Analysis Research Articles

Evaluation of stream ordering systems in the context of topography and open‐source data

AbstractSatellite‐derived digital elevation models (DEMs) and geographic information systems (GIS) offer effective means for both qualitative and quantitative analysis of drainage networks within watersheds. An extensive review of various stream order systems reveals their outdated nature, given advancements in digital technology and the availability of fine to coarse resolutions data. Analysis of open‐source DEMs with resolutions ranging from 12.5 to 225 m, along with topographical maps at scales of 1:50 000 and 1:250 000, was conducted across four physiographically distinct micro‐watersheds of approximately equal size (~300 km2). The steepest descent algorithm (D8) was utilized to derive raster stream networks, applying a channel initiation threshold (CIT) of 900 m2 as a criterion. It was observed that stream order numbers are influenced by map scale, leading to variability in mainstream order extraction across different DEM datasets and topographic maps. To address this issue, an innovative stream order system was proposed to ensure consistent mainstream order regardless of the spatial resolution of DEM data or map scale. Correlation analysis highlighted the importance of considering both spatial resolution and topographic variability in stream order analysis, underscoring the significance of accurate DEM data and landscape characteristics in understanding stream network dynamics. This method of classifying stream orders is recognized by scientists in geography, geology, hydrology and geomorphology for providing crucial information about the size and strength of waterways within stream networks, contributing to effective water management strategies.

Exome sequencing confirms the clinical diagnosis of both joubert syndrome and klinefelter syndrome with keratoconus in a han Chinese family

IntroductionJoubert syndrome a rare genetic disorder, is characterized by abnormalities in the development of the central nervous system with “molar signs” on magnetic resonance imaging of the brain and accompanied by cerebellar vermis hypoplasia, ataxia, hypotonia, and developmental delay. Keratoconus (KC) is a kind of genetically predisposed eye disease that causes blindness characterized by a dilated thinning of the central or paracentral cornea conically projected forward, highly irregular astigmatism, and severe visual impairment. Klinefelter syndrome is caused by an extra X chromosome in the cells of male patients, and the main phenotype is tall stature and dysplasia with secondary sex characteristics. This study was intended to identify the genetic etiology and determine the clinical diagnosis of one Han Chinese family with specific clinical manifestations of keratoconus and multiorgan involvement.MethodsA comprehensive ocular and related general examination was performed on one patient and his asymptomatic parents and brother. Pathogenic genes were tested by exome sequencing. CNV-seq was used to verify the copy number variation, and peripheral blood was cultured for karyotype analysis. The pathogenicity of the identified variant was determined subject to ACMG guidelines. The Gene Expression Omnibus (GEO) dataset of keratoconus-related genes in the NCBI database was obtained to analyze the differentially expressed genes in corneal tissues of the keratoconus group and the normal control group, and analysis of protein-protein interaction networks (PPI) was performed.ResultsProband, a 25-year-old male, had sudden loss of vision in the left eye for 1 week. Best corrected visual acuity (BCVA): 0.5 (−1.00DS/-5.00DC*29°) in the right eye, counting fingers/40 cm in the left eye. Slit-lamp microscopy of the right eye showed mild anterior protrusion of the cornea and thinning of the cone-topped cornea. The left eye showed marked thinning of the central region of the cornea, rounded edema in the form of a cone-like bulge, epithelial bullae, edema and turbidity of the stroma, and bulging of the Descemet’s membrane. Cranial magnetic resonance imaging (MRI) revealed changes in the midbrain and cerebellum, with a “molar sign” and a “bat-winged” ventriculus quartus cerebri. General check-up: 168 cm in height, decreased muscle tone in all four limbs, knee jerk elicited, negative Babinski sign, abdominal reflexes elicited, finger-to-nose test positive, intentional tremor evident in both hands, positive Romberg’s sign, instability of gait, level I intellectual disability, poor adaptive behavior, communication disorders, teeth all dentures, a peculiar face with blepharophimosis, wide inner canthus distance, mild ptosis, severe positive epicanthus, high palatal arches, exotropia, hypotrichosis of beard and face, inconspicuous prominentia laryngea, and short upper and lower limbs. Exome sequencing detected compound heterozygous frameshift variants M1:c.9279dup:p.His3094Thrfs*18 and M2:c.6515_6522del:p.Lys2172Thrfs*37 in the patient’s CPLANE1 gene and the presence of duplication-type CNV on the X chromosome. Sanger sequencing showed that the mother and father carried the M1 and M2 variants, respectively, and the younger brother carried the M2 variant, which was a novel variant. CNV-seq analysis showed the presence of a duplication-type CNV Xp22.33-Xq28 (2757837-156030895) of approximately 155 Mb on the X chromosome of the proband, which was a de novo variant and carried by neither of the parents. The two heterozygous frameshift variants and duplication-type CNV were pathogenic according to the ACMG guidelines. Differential expression analysis of keratoconus-related genes showed that CPLANE1 was upregulated in the corneal tissues of keratoconus patients compared with normal controls, and such a difference was statistically significant (p = 0.000515, <0.05). PPI analysis showed that the CPLANE1-NPHP3 complex protein acted as a bridge between cilia and extracellular matrix tissue. According to the genetic test results and clinical phenotype analysis, the family was finally diagnosed with Joubert syndrome combined with Keratoconus and Klinefelter syndrome.DiscussionIn this study, we report a proband in a Han Chinese family with both Joubert syndrome and X-linked Klinefelter syndrome as well as keratoconus, and the phenotype spectrum of CPLANE1-Joubert syndrome may be expanded accordingly. Meanwhile, the significance of exome sequencing was emphasized in aiding the clinical diagnosis of complex cases, which is difficult to make.

The Immunological Profile of Adipose Mesenchymal Stromal/Stem Cells after Cell Expansion and Inflammatory Priming

Background: AT-MSCs display great immunoregulatory features, making them potential candidates for cell-based therapy. This study aimed to evaluate the “RBC lysis buffer” isolation protocol and immunological profiling of the so-obtained AT-MSCs. Methods: We established an immune-comparative screening of AT-MSCs throughout in vitro cell expansion (PM, P1, P2, P3, P4) and inflammatory priming regarding the expression of 28 cell-surface markers, 6 cytokines/chemokines, and 10 TLR patterns. Findings: AT-MSCs were highly expandable and sensitive to microenvironment challenges, hereby showing plasticity in distinct expression profiles. Both cell expansion and inflammation differentially modulated the expression profile of CD34, HLA-DR, CD40, CD62L, CD200 and CD155, CD252, CD54, CD58, CD106, CD274 and CD112. Inflammation resulted in a significant increase in the expression of the cytokines IL-6, IL-8, IL-1β, IL-1Ra, CCL5, and TNFα. Depending on the culture conditions, the expression of the TLR pattern was distinctively altered with TLR1–4, TLR7, and TLR10 being increased, whereas TLR6 was downregulated. Protein network and functional enrichment analysis showed that several trophic and immune responses are likely linked to these immunological changes. Conclusions: AT-MSCs may sense and actively respond to tissue challenges by modulating distinct and specific pathways to create an appropriate immuno-reparative environment. These mechanisms need to be further characterized to identify and assess a molecular target that can enhance or impede the therapeutic ability of AT-MSCs, which therefore will help improve the quality, safety, and efficacy of the therapeutic strategy.

Three-dimensional vascular graph construction from depth information of blood vessel centerlines in optical coherence tomography angiography

Optical coherence tomography angiography (OCTA) is a noninvasive imaging technique for visualizing high-resolution volumetric vascular networks. Although OCTA has been widely employed in vascular network analysis, most studies have been limited to the analysis of two-dimensional (2D) en-face projection images because leveraging the full potential of OCTA’s three-dimensional (3D) information has been challenging due to projection artifacts beneath blood vessels. In this study, we propose a semi-automatic method for constructing a 3D vascular graph from 3D OCTA images without relying on data-driven learning strategies such as deep learning. The proposed method estimates the depth information of blood vessel centerlines in 2D en-face images and constructs a 3D vascular graph by integrating the depth estimation results for all vessel centerline segments. We demonstrate the effectiveness of the proposed method through experiments conducted on both simulated datasets and real datasets acquired from the dorsal dermis of mice.

Dynamic network analysis of electrophysiological task data

Abstract An important approach for studying the human brain is to use functional neuroimaging combined with a task. In electrophysiological data, this often involves a time-frequency analysis, in which recorded brain activity is time-frequency transformed and epoched around task events of interest, followed by trial-averaging of the power. While this simple approach can reveal fast oscillatory dynamics, the brain regions are analysed one at a time. This causes difficulties for interpretation and a debilitating number of multiple comparisons. In addition, it is now recognised that the brain responds to tasks through the coordinated activity of networks of brain areas. As such, techniques that take a whole-brain network perspective are needed. Here, we show how the oscillatory task responses from conventional time-frequency approaches can be represented more parsimoniously at the network level using two state-of-the-art methods: the HMM (Hidden Markov Model) and DyNeMo (Dynamic Network Modes). Both methods reveal frequency-resolved networks of oscillatory activity with millisecond resolution. Comparing DyNeMo, HMM, and traditional oscillatory response analysis, we show DyNeMo can identify task activations/deactivations that the other approaches fail to detect. DyNeMo offers a powerful new method for analysing task data from the perspective of dynamic brain networks.

Exploring the interconnections of anxiety, depression, sleep problems and health-promoting lifestyles among Chinese university students: a comprehensive network approach

BackgroundAnxiety, depression, and sleep problems are prevalent comorbid mental disorders among university students. The World Health Organization (WHO) emphasized a mental health promotion objective, recommending the consideration of protective health-promoting factors in strategies aimed at preventing mental disorders. Integrating theoretically significant constructs (such as protective factors) enhances our comprehension of the intricate mechanisms that underpin mental disorders. This study employed network analysis to first identify core and bridge symptoms within comorbid mental disorders and then explore how health-promoting lifestyles (HPLs) were associated with these disorders. The ultimate goal is to offer health promotion recommendations to enhance students’ quality of life.MethodsA total of 3,896 qualified university students participated in this study. Anxiety, depression, sleep problems, and HPLs were assessed using the GAD-7, PHQ-9, PSQI, and HPLP-II scales. A Gaussian Graphical Model was used to construct the networks. The Network Comparison Test was applied to determine whether the associations between HPLs and comorbid symptoms vary by gender, educational level, family sibling, and mental health status.ResultsLow energy (PHQ4) had the highest strength centrality, followed by Daytime dysfunction (PSQI7) and Trouble relaxing (GAD4). Five bridge symptoms were identified: Daytime dysfunction (PSQI7), Self-harm even suicide (PHQ9), Sad mood (PHQ2), Low energy (PHQ4), and Feeling afraid (GAD7). Regarding protective HPLs, Physical activity, Spiritual growth, and Stress management generally emerged as the top three central mental health-promoting behaviors.ConclusionTargeting core and bridge symptoms with timely and appropriate interventions can alleviate anxiety, depression, and sleep problems in this population. Moreover, promoting physical activity, fostering spiritual growth, and managing stress are likely to significantly enhance the overall mental health of university students.

Development of a Cancer-associated Fibroblast Signature for Evaluating Immunotherapy Response and Prognosis of Hepatocellular Carcinoma.

Alcohol abuse, non-alcoholic fatty liver disease (NAFLD), and hepatitis B and C are the main pathogenic factors of hepatocellular carcinoma (HCC). Though the current understanding of risk factors for HCC has been improved, patients with this type of cancer are normally diagnosed at advanced stages, posing significant challenges to effective treatment. This study analyzed the HCC datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database (GSE14520 and GSE116174). Stromal and immune cell infiltration in the tumor microenvironment (TME) was quantified by the ESTIMATE algorithm. To identify gene modules associated with cancer-associated fibroblasts (CAFs), weighted gene co-expression network analysis (WGCNA) was performed to develop gene co-expression networks. A CAF prognosis score (CAFPS) model was established based on the prognostic CAF genes screened by univariate and multivariate Cox regression analyses. To determine the role of the genes in the vital module in HCC, we conducted Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Finally, the relationship between CAFPS and drug sensitivity was analyzed using Genomic Data for Cancer Drug Sensitivity (GDSC). In this study, we found significant differences in immune scores, stromal scores, CAFs scores, and CD4/8 T-cell scores between normal samples and samples with different TNM staging. In particular, the proportion of CAFs was higher than all other cells in normal samples. Gene modules related to CAFs were identified by developing a gene co-expression network using WGCNA analysis. The lightyellow and greenyellow modules showed the highest correlation with CAF scores. Univariate COX analysis identified 12 genes related to HCC prognosis from a total of 191 genes in the two modules. The Kaplan-Meier (KM) survival analysis revealed that a high expression of these genes was associated with a lower survival chance. Based on the 12 genes obtained by univariate COX analysis, multivariate COX analysis was performed to construct a risk score model for the characteristics of CAFs (CAFPS). The KM survival curves of patients in the high CAFPS and low CAFPS groups showed that patients in the low CAFPS group had better survival. CAFs played a crucial role in the pathogenesis and treatment response of HCC. Targeting the CAFs milieu may provide therapeutic benefits, highlighting the importance of CAFS in developing a personalized treatment for HCC patients. Further studies are required to verify the current findings and explore their implications in clinical settings.

Comparing Sediment Bacterial Communities of Volcanic Lakes and Surrounding Rivers in Inner Mongolia Autonomous Region, Northeastern China

Volcanic lakes originate from a volcanic crater or caldera, and were a crucial component of aquatic ecosystems. Sediment bacteria play an important role in the nutrient cycling of aquatic ecosystems; however, their patterns distribution in volcanic lakes and the surrounding river habitats are unknown. In this study, we compare the sediment bacterial communities and their co-occurrence networks between these two habitats in the Inner Mongolia Autonomous Region, Northeastern China (the Arxan UNESCO Global Geopark), using 16S rRNA gene amplicon sequencing. The results revealed that there were significant variations in the physicochemical parameters of the sediment between these two habitats. The bacterial α-diversity, β-diversity, and community composition of the sediment also significantly differed between these two habitats. Network analysis showed that the co-occurrence patterns and keystone taxa in the sediment differed between these two habitats. The sediment bacterial communities in the river habitats were more stable than those in the lake habitats in the face of environmental change. Canonical correspondence analysis demonstrated that both physical (pH and MC) and nutrition-related factors (TN, TP, LOI, and TOC) were the most important environmental factors shaping the variations of bacterial community composition (BCC) in the sediment between these two habitats. This work could greatly improve our understanding of the sediment BCC of the sediment from aquatic ecosystems in the UNESCO Global Geopark.

Network Pharmacology Reveals Key Targets and Pathways of Madhuca longifolia for Potential Alzheimer's Disease Treatment.

Madhuca longifolia, commonly known as the mahua tree, has been traditionally used in medicine due to its anti-inflammatory, anti-diabetic, and antimicrobial properties. Its active compounds help in managing diabetes, alleviating cognitive impairment associated with Alzheimer's disease. Nonetheless, the exact neuroprotective mechanism of Madhuca longifolia against Alzheimer's disease remains unclear. This study looked into possible methods by which Madhuca longifolia protects against Alzheimer's disease using network pharmacology, molecular docking and molecular dynamic simulations studies. By applying pre-screening of active constituents, target prediction, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis, our study found that Madhuca longifolia is related to eight active ingredients (Ascorbic acid, Riboflavin, Pantothenic acid, (4 R)-2beta,3beta,23-trihydroxy-oleana-5,12-dien-28-oic acid, Quercetin, Nicotinic acid, Bassiaic acid Thiamine) and 272 common gene targets, with significant involvement in pathways such as PI3K-Akt signaling and neuroactive ligand-receptor interaction. Network analysis demonstrated how Madhuca longifolia can prevent AD by modifying important signalling networks, which may be one of the molecular mechanisms driving the plant's effectiveness against the disease. Molecular docking studies revealed that there were robust binding abilities of Quercetin, Riboflavin and Pantothenic acid to key target proteins AKT1, JUN, and STAT3. Later, molecular dynamic simulations was done to examine the successful activity of the active compounds against potential targets, and it was found that AKT1 and AKT1-Quercetin complex became stable at 260 ps. It may be seen through the study that quercetin may act as a good inhibitor for treatment. This thorough investigation provides a strong basis for future research and development efforts by advancing our understanding of Madhuca longifolia medicinal potential in Alzheimer's disease.

ACKR1+ Endothelial Cells Mediate Leukocyte Infiltration and Synergize with SFRP2/ASPN+ Fibroblasts to Promote Skin Fibrosis in Systemic Sclerosis.

Skin fibrosis is the most typical pathological manifestation of systemic sclerosis (SSc) and localized scleroderma (LS) with unclear etiology and few effective treatments. Though excessive collagen secretion by fibroblasts is the primary cause of skin fibrosis, many lines of evidence suggested that vascular damage was the initiating event and various cell types along with fibroblasts worked together to contribute to the pathogenesis of skin fibrosis. We sought to explore the relationships between vascular endothelial cell lesions and immune cell infiltration, along with the cell-cell interactions among various cell types within the fibrotic skin ecosystem. Single-cell RNA-seq (10x Genomics) was performed on skin biopsies of 3 healthy donors and 7 SSc patients in Chinese. The additional 3 localized scleroderma patients' data from NCBI database (GSE160536) were integrated by Harmony. CellChat package (v1.5.0) was applied to analyze cell communication network. Transwell assay and subcutaneous bleomycin (BLM) injection in mice were used to explore the role of ACKR1 on immune cell infiltration. Milo single-cell western blot was applied to show the activation of fibroblast subclusters. A total of 62,295 cells were obtained and subpopulations of stromal and immune cells were identified. Interaction network analysis revealed that multiple chemokines secreted by macrophages, pericytes, and pro-inflammatory fibroblasts could bind with Duffy antigen/receptor for chemokines (ACKR1), which is highly expressed on ACKR1+ endothelial cells of lesion skin. Transwell assay revealed that over-expressed ACKR1 in HUVEC facilitated leukocyte infiltration under the treatment of IL8. The BLM mice showed enhanced ACKR1 expression, massive immune cell infiltration, and fibrosis in skin, which could be attenuated by ACKR1 inhibition. Furthermore, infiltrated macrophages with TGFB1 or PDGFB high production could activate SFRP2/ASPN+ fibroblasts to contribute to excessive accumulation of extracellular matrix (ECM), and the SOX4-ASPN axis plays an important role in the TGF-β signaling cascade and the etiology of skin fibrosis. Our results reveal that highly expressed ACKR1 in endothelial cells of fibrotic skin tissue promotes immune cell infiltration, and SFRP2/ASPN+ fibroblasts synergize to exacerbate skin fibrosis.

Identification of hub genes and gene modules associated with Behçet's disease by weighted gene co-expression network analysis of neutrophil transcriptome.

Behçet's disease (BD) is a chronic inflammatory condition with recurrent skin lesions, uveitis, and oral and genital ulcers. Neutrophils are important in the pathogenis of BD, but their molecular mechanisms are unclear. We performed weighted gene co-expression network analysis on the transcriptome of neutrophils from 10 BD patients and 10 healthy controls to identify hub genes and gene modules associated with BD. We found eight co-expression modules with different biological functions. The turquoise module was involved in response to hydrogen peroxide and reactive oxygen species, the blue module was involved in response to external stimulus and inflammatory response, and the brown module was involved in the type I interferon signaling pathway. We further identified hub genes and transcription factors in each module by using module membership and gene significance. Our results reveal novel gene modules and hub genes that are associated with neutrophil activation and dysfunction in BD, which could serve as potential biomarkers and therapeutic targets for this disease.

Transcriptomic changes in the posterior pallium of male zebra finches associated with social niche conformance

Animals plastically adjust their physiological and behavioural phenotypes to conform to their social environment—social niche conformance. The degree of sexual competition is a critical part of the social environment to which animals adjust their phenotypes, but the underlying genetic mechanisms are poorly understood. We conducted a study to investigate how differences in sperm competition risk affect the gene expression profiles of the testes and two brain areas (posterior pallium and optic tectum) in breeding male zebra finches (Taeniopygia castanotis). In this pre-registered study, we investigated a large sample of 59 individual transcriptomes. We compared two experimental groups: males held in single breeding pairs (low sexual competition) versus those held in two pairs (elevated sexual competition) per breeding cage. Using weighted gene co-expression network analysis (WGCNA), we observed significant effects of the social treatment in all three tissues. However, only the treatment effects found in the pallium were confirmed by an additional randomisation test for statistical robustness. Likewise, the differential gene expression analysis revealed treatment effects only in the posterior pallium (ten genes) and optic tectum (six genes). No treatment effects were found in the testis at the single gene level. Thus, our experiments do not provide strong evidence for transcriptomic adjustment specific to manipulated sperm competition risk. However, we did observe transcriptomic adjustments to the manipulated social environment in the posterior pallium. These effects were polygenic rather than based on few individual genes with strong effects. Our findings are discussed in relation to an accompanying paper using the same animals, which reports behavioural results consistent with the results presented here.

India’s solar energy research: performance and social network analysis

India’s solar energy research: performance and social network analysis

Nascent policy subsystems in polycentric governance networks: The case of sea‐level rise governance in the San Francisco Bay Area

AbstractA policy subsystem is a system of relations between actors within the context of a specific, territorially bounded policy issue. Mature policy subsystems feature well‐established, easily distinguishable, confrontational coalitions. Recent literature has explored the behavior of nascent subsystems, which emerge in response to novel policy challenges and feature developing, rather than fully fledged, coalitions. However, as yet, we lack an empirical approach to identify and analyze the structural characteristics of nascent subsystems and assess their implications for theoretical and subsystem development. How do we recognize a nascent policy subsystem when we see one? What are the drivers of its nascent coalitional structure? We answer these questions using social network analysis in the empirical case of the governance network of adaptation to sea‐level rise in the San Francisco Bay Area, using original data collected in 2018. We find that the network portrays a nascent subsystem developing out of pre‐existing coalitions focused on two facets of environmental advocacy: environmental protection and environmental justice. We conclude with recommendations for future research on policy subsystem development.

A network analysis of self-compassion and burnout in a sample of nurses.

In the nursing profession, the concept of self-compassion has been associated with burnout. However, to date, the fine-grained relationships between different dimensions of self-compassion and symptoms of burnout have not been investigated. Network analysis provides a new avenue for exploring the fine-grained correlation paths of two related variables. To analyse the nuanced associations between self-compassion and burnout using network analysis in a large cohort of Chinese nurses. A cross-sectional multi-centre survey design study. Participants were recruited from 30 hospitals in China between April and May 2022. These nurses completed the Chinese Maslach Burnout Inventory-General Survey (C-MBI-GS) and Self-Compassion Scale-Short Form (SCS-SF). Network analysis was performed to illustrate the complex nuanced relationships between self-compassion and burnout. A total of 1467 nurses (age 32.2 [18-56] years; 89.9% were female) participated in the study. Nodes Mindfulness and Isolation had the highest centralities measured by strength. Nodes Mindfulness, reduced personal accomplishment and Isolation were the most negative and positive influential nodes that bridged self-compassion and burnout. There were no differences in terms of gender, age, professional title and job tenure in the structure or connectivity of the self-compassion and burnout network. Different components of self-compassion were specifically associated with different dimensions of burnout in registered nurses. Among these, Mindfulness, Isolation and Reduced personal accomplishment were the three most important components of self-compassion for burnout symptoms. No patient or public contribution. Understanding the intricate connections between self-compassion and burnout will allow hospital administrators to prioritize the elements of Mindfulness and Isolation within self-compassion and the dimension of Reduced personal accomplishment within burnout when designing preventative measures and interventions aimed at reducing nurse burnout.

Emerald Ash Borer Infestation-Induced Elevated Negative Correlations and Core Genera Shift in the Endophyte Community of Fraxinus bungeana

Endophytes, prevalent in plants, mediate plant–insect interactions. Nevertheless, our understanding of the key members of endophyte communities involved in inhibiting or assisting EAB infestation remains limited. Employing ITS and 16S rRNA high-throughput sequencing, along with network analysis techniques, we conducted a comprehensive investigation into the reaction of endophytic fungi and bacteria within F. bungeana phloem by comparing EAB-infested and uninfected samples. Our findings reveal that EAB infestation significantly impacts the endophytic communities, altering both their diversity and overall structure. Interestingly, both endophytic fungi and bacteria exhibited distinct patterns in response to the infestation. For instance, in the EAB-infested phloem, the fungi abundance remained unchanged, but diversity decreased significantly. Conversely, bacterial abundance increased, without significant diversity changes. The fungi community structure altered significantly, which was not observed in bacteria. The bacterial composition in the infested phloem underwent significant changes, characterized by a substantial decrease in beneficial species abundance, whereas the fungal composition remained largely unaffected. In network analysis, the endophytes in infested phloem exhibited a modular topology, demonstrating greater complexity due to an augmented number of network nodes, elevated negative correlations, and a core genera shift compared to those observed in healthy phloem. Our findings increase understanding of plant–insect–microorganism relationships, crucial for pest control, considering endophytic roles in plant defense.

Network dynamics of self-compassion, anxiety, and depression during eating disorder therapy.

Recovery processes during residential treatment for eating disorders, especially in patients with a history of maltreatment, are insufficiently understood. This study aimed to explore the temporal relationships among comorbid factors, including depression, anxiety, and self-compassion, with the influence of childhood maltreatment. Using Dynamic Time Warp (DTW), weekly scores from the Symptom Checklist-5, Eating Disorder Examination, and Self-Compassion Scale were analysed over 12weeks. The study generated undirected and directed networks to identify influential symptoms in a transdiagnostic sample, comparing patients with and without childhood maltreatment. The study included 124 patients with eating disorders (ED) (97% women), mean age of 30.9years (SD=9.7, range 18-61years). Diagnoses included anorexia nervosa (26%), bulimia nervosa (38%), and other specified feeding and eating disorders (36%). The directed DTW network showed that hopelessness, worrying, and restlessness had the highest out-strength, predicting changes in self-compassion and ED behaviour. In maltreatment cases, hopelessness and low acceptance predicted changes, while worry, restlessness, and nervousness were predictive in non-maltreatment cases. Temporal network analyses suggest that a change in hopelessness, worrying, and restlessness drives symptom improvement in ED behaviour and the development of self-compassion during residential treatment. These processes vary between patients with and without a history of childhood maltreatment separately, indicating the need for further analyses.

A career in numbers: A citation network analysis of the work of RP Millar and his contribution to GnRH research.

Here, we reflect on the long career in neuroendocrinology of a single, highly productive scientist ('Bob' Millar), by analysing his oeuvre of published papers through the lens of citation metrics. We use citation network analysis in a novel manner to identify the specific topics to which his papers have made a particular contribution, allowing us to compare the citations of his papers with those of contemporary papers on the same topic, rather than on the same broad field as generally used to normalise citations. It appears that citation rates are highest for topics on which Bob has published a relatively large number of papers that have become core to a tightly-knit community of authors that cite each other. This analysis shows that an author's impact depends on the existence of a receptive community that is alert to the potential utility of papers from that author, and which uses, amplifies, extends and qualifies the contents of their papers-activities that entail reciprocal citation between authors. The obvious conclusion is that a scientist's impact depends on the use that his or her contemporaries make of his or her contributions, rather than on the contributions in themselves.

Biogeographical distribution and community assembly of Myxococcota in mangrove sediments

BackgroundMyxococcota, characterized by their distinct social lifestyles, are widely distributed micro-predators in global sediments. They can feed on a wide range of bacterial, archaeal, and fungal prey. Myxococcota are capable of producing diverse secondary metabolites, playing key roles in microbial food webs, and regulating the microbial community structures in different ecosystems. However, Myxococcota are rarely pure cultured due to the challenging and stringent culturing conditions. Their natural distribution, niche differentiation, and predator–prey relationships in a specific habitat are poorly understood.ResultsIn this study, we conducted a comprehensive analysis of the 16S rRNA gene sequence data from public databases and our collection. We compared the abundance, diversity, and distribution patterns of Myxococcota in various habitats, with a specific focus on mangroves. We found that Myxococcota accounted for 1.45% of the total prokaryotes in global sediments based on the abundance of 16S rRNA genes. Myxococcota are abundant and diverse in mangrove sediments. They tend to be more generalistic in mangroves than in other habitats due to their wide niche breadth. Besides, the deterministic processes (variable selection) influenced the assembly of mangrove Myxococcota communities significantly more than stochastic processes. Further, we determined that environmental factors explained a greater amount of total community variation in mangrove Myxococcota than geographical variables (latitude and sediment depth). In the end, through the analysis of microbial co-occurrence networks, Myxococcota emerges as a key component and functions as a connector in the mangrove microbial community.ConclusionsOur study enhances comprehension of mangrove Myxococcota's biogeography, assembly patterns, driving factors, and co-occurrence relationships, as well as highlights their unique niche and ecological importance in mangrove sediments.

Unveiling the overlooked threat: antibiotic resistance in groundwater near an abandoned sulfuric acid plant in Xingyang, China.

Groundwater near a sulfuric acid plant in Xingyang, Henan, China was sampled from seven distinct sites to explore the prevalence of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs). Results showed that genes aadA, blaCTX-M, tetA, qnrA, and sul1 were detected with 100% frequency followed by aac(6')-Ib (85.71%), ermB (85.71%), and tetX (71.42%). Most abundant ARGs were sul1 in LSA2 (1.15 × 1011 copies/mL), tetA in LSA6 (4.95 × 1010 copies/mL), aadA in LSA2 (4.56 × 109 copies/mL), blaCTX-M in LSA4 (1.19 × 109 copies/mL), and ermB in LSA5 (1.07 × 109 copies/mL). Moreover, in LSA2, intl1 as a marker of class 1 integron emerged as the most abundant gene as part of MGE (2.25 × 1011 copies/mL), trailed by ISCR1 (1.57 × 109 copies/mL). Environmental factors explained 81.34% of ARG variations, with a strong positive correlation between the intl2 and blaCTX-M genes, as well as the ISCR1 gene and qnrA, tetA, intl2, and blaCTX-M. Furthermore, the intI1 gene had a strong positive connection with the aadA, tetA, and sul1 genes. Moreover, the aac(6')-Ib gene was associated with As, Pb, Mg, Ca, and HCO3-. The intl2 gene was also shown to be strongly associated with Cd. Notably, network analysis highlighted blaCTX-M as the most frequently appearing gene across networks of at least five genera. Particularly, Lactobacillus, Plesiomonas, and Ligilactobacillus demonstrated correlations with aadA, qnrA, blaCTX-M, intI2, and ISCR1. Based on 16S rRNA sequencing, the dominant phyla were Proteobacteria, Firmicutes, Bacteroidota, Acidobacteriota, and Actinobacteriota, with dominant genera including Pseudomonas, Ligilactobacillus, Azoarcus, Vogesella, Streptococcus, Plesiomonas, and Ferritrophicum. These findings enhance our understanding of ARG distribution in groundwater, signaling substantial contamination by ARGs and potential risks to public health.