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Abstract Delineation of microbial habitats within the soil matrix and characterization of their environments and metabolic processes are crucial to understand soil functioning, yet their experimental identification remains persistently limited. We combined single- and triple-energy X-ray computed microtomography with pore specific allocation of¹³C labeled glucose and subsequent stable isotope probing to demonstrate how long-term disparities in vegetation history modify spatial distribution patterns of soil pore and particulate organic matter drivers of microbial habitats, and to probe bacterial communities populating such habitats. Here we show striking differences between large (30-150 µm Ø) and small (4-10 µm Ø) soil pores in (i) microbial diversity, composition, and life-strategies, (ii) responses to added substrate, (iii) metabolic pathways, and (iv) the processing and fate of labile C. We propose a microbial habitat classification concept based on biogeochemical mechanisms and localization of soil processes and also suggests interventions to mitigate the environmental consequences of agricultural management. 

Abstract BackgroundBreast cancer poses a significant health risk to women worldwide, with approximately 30% being diagnosed annually in the United States. The identification of cancerous mammary tissues from non-cancerous ones during surgery is crucial for the complete removal of tumors. ResultsOur study innovatively utilized machine learning techniques (Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN)) alongside Raman spectroscopy to streamline and hasten the differentiation of normal and late-stage cancerous mammary tissues in mice. The classification accuracy rates achieved by these models were 94.47% for RF, 96.76% for SVM, and 97.58% for CNN, respectively. To our best knowledge, this study was the first effort in comparing the effectiveness of these three machine-learning techniques in classifying breast cancer tissues based on their Raman spectra. Moreover, we innovatively identified specific spectral peaks that contribute to the molecular characteristics of the murine cancerous and non-cancerous tissues. ConclusionsConsequently, our integrated approach of machine learning and Raman spectroscopy presents a non-invasive, swift diagnostic tool for breast cancer, offering promising applications in intraoperative settings. 

Abstract Leafhoppers comprise over 20,000 plant‐sap feeding species, many of which are important agricultural pests. Most species rely on two ancestral bacterial symbionts,SulciaandNasuia, for essential nutrition lacking in their phloem and xylem plant sap diets. To understand how pest leafhopper genomes evolve and are shaped by microbial symbioses, we completed a chromosomal‐level assembly of the aster leafhopper's genome (ALF;Macrosteles quadrilineatus). We compared ALF's genome to three other pest leafhoppers,Nephotettix cincticeps,Homalodisca vitripennis, andEmpoasca onukii, which have distinct ecologies and symbiotic relationships. Despite diverging ~155 million years ago, leafhoppers have high levels of chromosomal synteny and gene family conservation. Conserved genes include those involved in plant chemical detoxification, resistance to various insecticides, and defence against environmental stress. Positive selection acting upon these genes further points to ongoing adaptive evolution in response to agricultural environments. In relation to leafhoppers' general dependence on symbionts, species that retain the ancestral symbiont,Sulcia, displayed gene enrichment of metabolic processes in their genomes. Leafhoppers with bothSulciaand its ancient partner,Nasuia, showed genomic enrichment in genes related to microbial population regulation and immune responses. Finally, horizontally transferred genes (HTGs) associated with symbiont support ofSulciaandNasuiaare only observed in leafhoppers that maintain symbionts. In contrast, HTGs involved in non‐symbiotic functions are conserved across all species. The high‐quality ALF genome provides deep insights into how host ecology and symbioses shape genome evolution and a wealth of genetic resources for pest control targets. 

Room-temperature sodium-sulfur (RT Na-S) batteries have attracted ever-increasing attention because of their enhanced energy density and low price. Although the performance of RT Na-S batteries is obtained in many other research, the basic mechanism and kinetics have not involved yet, especially in discharge product growth, which affects electrochemical performance. Meanwhile, designed additional redox activities (in the presence of oxygen) could simultaneously suppress sodium polysulfide shuttling and enhance energy density according to our group reported. However, the kinetic study of the intermediate has not been explored. In this work, we discussed the deposition of low-order sodium polysulfide (Na₂S_x, x ≤ 2) in different potentials and types of glyme-solvents in Na-S and Na/(O₂)-S system. The results show that the morphology of deposition Na₂S_x(x ≤ 2) is affected by interfacial energy barrier controlled by overpotentials and the radius of sodium ions, which produced the precipitation of particle shape rather than film. Potentiostatic experiments show the kinetics are elevated in the presence of oxygen. In addition, the exchange current density of different sodium polysulfides was studied. The high-order sodium polysulfide has a lower exchange current density than that of low-order sodium polysulfide in Na-S system, requiring greater driving force, while transformation of the intermediate from high-order oxy-sulfur to low-order oxy-sulfur species require less impulse in Na/(O₂)-S systems. This paper provides new understandings of the deposition mechanism and kinetics of Na₂S_x(x ≤ 2) Na-S and Na/(O₂)-S system in and to choose the appropriate solvent and potential.