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Nanoparticles (NPs) are increasingly used to target bacteria as an alternative to antibiotics. Nanotechnology may be particularly advantageous in treating bacterial infections. Examples include the utilization of NPs in antibacterial coatings for implantable devices and medicinal materials to prevent infection and promote wound healing, in antibiotic delivery systems to treat disease, in bacterial detection systems to generate microbial diagnostics, and in antibacterial vaccines to control bacterial infections. The antibacterial mechanisms of NPs are poorly understood, but the currently accepted mechanisms include oxidative stress induction, metal ion release, and non-oxidative mechanisms. The multiple simultaneous mechanisms of action against microbes would require multiple simultaneous gene mutations in the same bacterial cell for antibacterial resistance to develop; therefore, it is difficult for bacterial cells to become resistant to NPs. In this review, we discuss the antibacterial mechanisms of NPs against bacteria and the factors that are involved. The limitations of current research are also discussed.

Extracellular vesicles (EVs), including exosomes, microvesicles, and apoptotic bodies, are nanosized membrane vesicles derived from most cell types. Carrying diverse biomolecules from their parent cells, EVs are important mediators of intercellular communication and thus play significant roles in physiological and pathological processes. Owing to their natural biogenesis process, EVs are generated with high biocompatibility, enhanced stability, and limited immunogenicity, which provide multiple advantages as drug delivery systems (DDSs) over traditional synthetic delivery vehicles. EVs have been reported to be used for the delivery of siRNAs, miRNAs, protein, small molecule drugs, nanoparticles, and CRISPR/Cas9 in the treatment of various diseases. As a natural drug delivery vectors, EVs can penetrate into the tissues and be bioengineered to enhance the targetability. Although EVs' characteristics make them ideal for drug delivery, EV-based drug delivery remains challenging, due to lack of standardized isolation and purification methods, limited drug loading efficiency, and insufficient clinical grade production. In this review, we summarized the current knowledge on the application of EVs as DDS from the perspective of different cell origin and weighted the advantages and bottlenecks of EV-based DDS.

The surface frustrated Lewis pairs (SFLPs) on defect-laden metal oxides provide catalytic sites to activate H 2 and CO 2 molecules and enable efficient gas-phase CO 2 photocatalysis. Lattice engineering of metal oxides provides a useful strategy to tailor the reactivity of SFLPs. Herein, a one-step solvothermal synthesis is developed that enables isomorphic replacement of Lewis acidic site In 3+ ions in In 2 O 3 by single-site Bi 3+ ions, thereby enhancing the propensity to activate CO 2 molecules. The so-formed Bi x In 2-x O 3 materials prove to be three orders of magnitude more photoactive for the reverse water gas shift reaction than In 2 O 3 itself, while also exhibiting notable photoactivity towards methanol production. The increased solar absorption efficiency and efficient charge-separation and transfer of Bi x In 2-x O 3 also contribute to the improved photocatalytic performance. These traits exemplify the opportunities that exist for atom-scale engineering in heterogeneous CO 2 photocatalysis, another step towards the vision of the solar CO 2 refinery. Surface frustrated Lewis pairs (SFLPs) provide a unique class of active sites that enable efficient gas-phase CO 2 photocatalysis. How to tailor the reactivity of the SFLPs represents a major challenge, which the authors address here by single-site Bi 3+ ion substitution of the SFLPs.

Chronic constipation (CC) is a highly prevalent and burdensome gastrointestinal disorder. Accumulating evidence highlights the link between imbalances in the gut microbiome and constipation. However, the mechanisms by which the microbiome and microbial metabolites affect gut movement remain poorly understood. In this review, we discuss recent studies on the alteration in the gut microbiota in patients with CC and the effectiveness of probiotics in treating gut motility disorder. We highlight the mechanisms that explain how the gut microbiome and its metabolism are linked to gut movement and how intestinal microecological interventions may counteract these changes based on the enteric nervous system, the central nervous system, the immune function, and the ability to modify intestinal secretion and the hormonal milieu. In particular, microbiota-based approaches that modulate the levels of short-chain fatty acids and tryptophan catabolites or that target the 5-hydroxytryptamine and Toll-like receptor pathways may hold therapeutic promise. Finally, we discuss the existing limitations of microecological management in treating constipation and suggest feasible directions for future research.

The smoothing parameter on lattices is crucial for lattice-based cryptographic design. In this study, we establish a new upper bound for the lattice smoothing parameter, which represents an improvement over several significant classical findings. For one-dimensional integer lattices, under specific and optimized conditions, we have achieved a more precise upper bound compared to previous research. Regarding general high-dimensional lattices, when the lattice dimension is large enough and the error parameter is within a particular range, we have derived a new upper bound. In the practical applications of lattice-based cryptography, where the lattice dimension is typically large, our new bound enables a more natural and smaller setting for the error parameter, thereby improving the upper bounds on all known smoothing parameters.

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species' geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species' ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.

Let be a sequence with elements from an additive finite abelian group . is called a tiny zero-sum sequence if is non-empty, and . Let be the smallest integer such that every sequence of elements (repetition allowed) from contains a tiny zero-sum sequence. In this article, we mainly focus on the explicit value of and compute this value for a new class of groups, namely ones of the form , where is a prime number such that

CO2 capture from the flue gas is a promising approach to mitigate global warming. However, regulating the carbon-based adsorbent in terms of textural and surface modification is still a challenge. To overcome this issue, the present study depicts the development of cost-effective and high-performance CO2 adsorbents derived from petroleum coke, an industrial by-product, using a two-step process involving thiourea modification and KOH activation. A series of N,S-codoped porous carbons was synthesized by varying activation temperatures and KOH quantity. The optimized sample exhibited a high specific surface area of 1088 m2/g, a narrow micropore volume of 0.52 cm3/g, and considerable heteroatom doping (1.57 at.% nitrogen and 0.19 at.% sulfur). The as-prepared adsorbent achieved a CO2 adsorption capacity of 3.69 and 5.08 mmol/g at 1 bar, 25 °C and 0 °C, respectively, along with a CO2/N2 selectivity of 17. Adsorption kinetics showed 90% of equilibrium uptake was achieved within 5 min, while cyclic studies revealed excellent stability with 97% capacity retention after five cycles. Thermodynamic analysis indicated moderate isosteric heat of adsorption (Qst) values ranging from 18 to 47 kJ/mol, ensuring both strong adsorption and efficient desorption. These findings highlight the potential of petroleum coke-derived porous carbons for sustainable and efficient CO2 capture applications.

Microorganisms consume and transform dissolved organic matter (DOM) into various forms. However, it remains unclear whether the ecological patterns and drivers of DOM chemodiversity are analogous to those of microbial communities. Here, a large-scale investigation is conducted along the Chinese coasts to resolve the intrinsic linkages among the complex intertidal DOM pools, microbial communities and environmental heterogeneity. The abundance of DOM molecular formulae best fits log-normal distribution and follows Taylor’s Law. Distance-decay relationships are observed for labile molecular formulae, while latitudinal diversity gradients are noted for recalcitrant molecular formulae. Latitudinal patterns are also observed for DOM molecular features. Negative cohesion, bacterial diversity, and molecular traits are the main drivers of DOM chemodiversity. Stochasticity analyses demonstrate that determinism dominantly shapes the DOM compositional variations. This study unveils the intrinsic mechanisms underlying the intertidal DOM chemodiversity and microbial communities from ecological perspectives, deepening our understanding of microbially driven chemical ecology. Intertidal DOM follows similar ecological patterns and underlying mechanisms to microbes, suggesting that there may exist universal ecological models explaining the patterns of both living and non-living biological entities in the Earth’s biosphere.