The legacy of bacterial invasions on soil native communities

Soil microbial communities are often not resistant to the impact caused by microbial invasions, both in terms of structure and functionality, but it remains unclear whether these changes persist over time. Here, we used three strains of Escherichia coli O157:H7 (E. coli O157:H7), a species used for modelling bacterial invasions, to evaluate the resilience of the bacterial communities from four Chinese soils to invasion. The impact of E. coli O157:H7 strains on soil native communities was tracked for 120 days by analysing bacterial community composition as well as their metabolic potential. We showed that soil native communities were not resistant to invasion, as demonstrated by a decline in bacterial diversity and shifts in bacterial composition in all treatments. The resilience of native bacterial communities (diversity and composition) was inversely correlated with invader's persistence in soils (R2 = 0.487, p < 0.001). Microbial invasions also impacted the functionality of the soil communities (niche breadth and community niche), the degree of resilience being dependent on soil or native community diversity. Collectively, our results indicate that bacteria invasions can potentially leave a footprint in the structure and functionality of soil communities, indicating the need of assessing the legacy of introducing exotic species in soil environments

Antenna array calibration methods based on simultaneous perturbation

Antenna arrays have gained significant interest in millimetre-wave communication systems as an enabling technology to achieve higher capacity and mitigate the high propagation loss. Such arrays with a large bandwidth need to be efficiently calibrated to maximise their performance. An antenna array calibration method based on a stochastic approximation algorithm and simultaneous perturbation has been developed and the procedures to implement it in both frequency and time domains have been presented. The approaches to define objective functions and establish gradient approximations to fulfill a successful convergence for acquiring calibration coefficients in both domains have been explored. In the time domain implementation, only a fraction of the measurement time was required to calibrate an antenna array of ultrawide bandwidth compared with other methods using a perturbation technique. The effectiveness of the proposed method has been validated via numerical experiments in both domains

Multi-omics profiling reveal responses of three major Dendrobium species from different growth years to medicinal components

Dendrobium is a perennial herb found in Asia that is known for its medicinal and ornamental properties. Studies have shown that the stem is the primary medicinal component of Dendrobium spp. To investigate the effect of the species and age of Dendrobium (in years) on the content of its medicinal components, we collected the stems of 1-to-4-year-old D. officinale, D. moniliforme, and D. huoshanense, sequenced the transcriptome, metabolome, and microbiome, and analyzed the data in a comprehensive multi-omics study. We identified 10,426 differentially expressed genes (DEGs) with 644 differentially accumulated metabolites (DAMs) from 12 comparative groups and mapped the flavonoid pathway based on DEGs and DAMs. Transcriptomic and metabolomic data indicated a general trend of the accumulation of flavonoids exhibiting pharmacological effects in the three Dendrobium species. In addition, joint metabolome and microbiome analyses showed that actinobacteria was closely associated with flavonoid synthesis with increasing age. Our findings provide novel insights into the interactions of flavonoids of Dendrobium with the transcriptome and microbiome

Contemporaneous symptom networks and correlates during endocrine therapy among breast cancer patients: A network analysis

BackgroundEndocrine therapy-related symptoms are associated with early discontinuation and quality of life among breast cancer survivors. Although previous studies have examined these symptoms and clinical covariates, little is known about the interactions among different symptoms and correlates. This study aimed to explore the complex relationship of endocrine therapy-related symptoms and to identify the core symptoms among breast cancer patients.MethodsThis is a secondary data analysis conducted based on a multicenter cross-sectional study of 613 breast cancer patients in China. All participants completed the 19-item Chinese version of the Functional Assessment of Cancer Therapy-Endocrine Subscale (FACT-ES). Multivariate linear regression analysis was performed to identify significant factors. A contemporaneous network with 15 frequently occurring symptoms was constructed after controlling for age, payment, use of aromatase inhibitors, and history of surgery. Network comparison tests were used to assess differences in network structure across demographic and treatment characteristics.ResultsAll 613 participants were female, with an average age of 49 years (SD = 9.4). The average duration of endocrine therapy was 3.6 years (SD = 2.3) and the average symptom score was 18.99 (SD = 11.43). Irritability (n = 512, 83.52%) and mood swings (n = 498, 81.24%) were the most prevalent symptoms. Lost interest in sex (mean = 1.95, SD = 1.39) and joint pain (mean = 1.57, SD = 1.18) were the most severe symptoms. The edges in the clusters of emotional symptoms (“irritability-mood swings”), vasomotor symptoms (“hot flashes-cold sweats-night sweats”), vaginal symptoms (“vaginal discharge-vaginal itching”), sexual symptoms (“pain or discomfort with intercourse-lost interest in sex-vaginal dryness”), and neurological symptoms (“headaches-dizziness”) were the thickest in the network. There were no significant differences in network structure (P = 0.088), and global strength (P = 0.330) across treatment types (selective estrogen receptor modulators vs. aromatase inhibitors). Based on an evaluation of the centrality indices, irritability and mood swings appeared to be structurally important nodes after adjusting for the clinical covariates and after performing subgroup comparisons.ConclusionEndocrine therapy-related symptoms are frequently reported issues among breast cancer patients. Our findings demonstrated that developing targeted interventions focused on emotional symptoms may relieve the overall symptom burden for breast cancer patients during endocrine therapy

A global monthly field of seawater pH over 3 decades: a machine learning approach

The continuous uptake of anthropogenic CO2 by the ocean leads to ocean acidification, which is an ongoing threat to the marine ecosystem. The ocean acidification rate was globally documented in the surface ocean but limited below the surface. Here, we present a monthly four-dimensional 1&deg;&times;1&deg; gridded product of global seawater pH, derived from a machine learning algorithm trained on pH observations at total scale and in-situ temperature from the Global Ocean Data Analysis Project (GLODAP). The constructed pH product covers the years 1992&ndash;2020 and depths from the surface to 2 km on 41 levels. Three types of machine learning algorithms were used in the pH product construction, including self-organizing map neural networks for region dividing, a stepwise algorithm for predictor selection, and feed-forward neural networks (FFNN) for non-linear relationship regression. The performance of the machine learning algorithm was validated using real observations by a cross validation method, where four repeating iterations were carried out with 25 % varied observations for each evaluation and 75 % for training. The constructed pH product is evaluated through comparisons to time series observations and the GLODAP pH climatology. The overall root mean square error between the FFNN constructed pH and the GLODAP measurements is 0.028, ranging from 0.044 in the surface to 0.013 at 2000 m. The pH product is distributed through the data repository of the Marine Science Data Center of the Chinese Academy of Sciences at http://dx.doi.org/10.12157/IOCAS.20230720.001 (Zhong et al., 2023)

NGF-p75 signaling coordinates skeletal cell migration during bone repair

: Bone regeneration following injury is initiated by inflammatory signals and occurs in association with infiltration by sensory nerve fibers. Together, these events are believed to coordinate angiogenesis and tissue reprogramming, but the mechanism of coupling immune signals to reinnervation and osteogenesis is unknown. Here, we found that nerve growth factor (NGF) is expressed following cranial bone injury and signals via p75 in resident mesenchymal osteogenic precursors to affect their migration into the damaged tissue. Mice lacking Ngf in myeloid cells demonstrated reduced migration of osteogenic precursors to the injury site with consequently delayed bone healing. These features were phenocopied by mice lacking p75 in Pdgfra+ osteoblast precursors. Single-cell transcriptomics identified mesenchymal subpopulations with potential roles in cell migration and immune response, altered in the context of p75 deletion. Together, these results identify the role of p75 signaling pathway in coordinating skeletal cell migration during early bone repair

DISCUS : an end-to-end solution for ubiquitous broadband optical access

Fiber to the premises has promised to increase the capacity in telecommunications access networks for well over 30 years. While it is widely recognized that optical-fiber-based access networks will be a necessity in the shortto medium-term future, its large upfront cost and regulatory issues are pushing many operators to further postpone its deployment, while installing intermediate unambitious solutions such as fiber to the cabinet. Such high investment cost of both network access and core capacity upgrade often derives from poor planning strategies that do not consider the necessity to adequately modify the network architecture to fully exploit the cost benefit that a fiber-centric solution can bring. DISCUS is a European Framework 7 Integrated Project that, building on optical-centric solutions such as long-reach passive optical access and flat optical core, aims to deliver a cost-effective architecture for ubiquitous broadband services. DISCUS analyzes, designs, and demonstrates end-to-end architectures and technologies capable of saving cost and energy by reducing the number of electronic terminations in the network and sharing the deployment costs among a larger number of users compared to current fiber access systems. This article describes the network architecture and the supporting technologies behind DISCUS, giving an overview of the concepts and methodologies that will be used to deliver our end-to-end network solution

Evidences for pressure-induced two-phase superconductivity and mixed structures of NiTe₂ and NiTe in type-II Dirac semimetal NiTe_(2-x) (x = 0.38 ± 0.09) single crystals

Bulk NiTe₂ is a type-II Dirac semimetal with non-trivial Berry phases associated with the Dirac fermions. Theory suggests that monolayer NiTe₂ is a two-gap superconductor, whereas experimental investigation of bulk NiTe_(1.98) for pressures (P) up to 71.2 GPa do not reveal any superconductivity. Here we report experimental evidences for pressure-induced two-phase superconductivity as well as mixed structures of NiTe₂ and NiTe in Te-deficient NiTe_(2-x) (x = 0.38±0.09) single crystals. Hole-dominant multi-band superconductivity with the P3M1 hexagonal-symmetry structure of NiTe₂ appears at P ≥ 0.5 GPa, whereas electron-dominant single-band superconductivity with the P2/m monoclinic-symmetry structure of NiTe emerges at 14.5 GPa < P < 18.4 GPa. The coexistence of hexagonal and monoclinic structures and two-phase superconductivity is accompanied by a zero Hall coefficient up to ∼ 40 GPa, and the second superconducting phase prevails above 40 GPa, reaching a maximum T_c = 7.8 K and persisting up to 52.8 GPa. Our findings suggest the critical role of Te-vacancies in the occurrence of superconductivity and potentially nontrivial topological properties in NiTe_(2-x)