Current advances in capillarity: Theories and applications

As common physical phenomena in porous media, capillarity behaviors exist in many engineering applications and natural science fields. The experimental, theoretical and numerical research on capillarity in porous media has lasted for more than a century, and the research results have been widely used in various fields, such as the development of conventional and unconventional resources. However, although the research has made great progress, the complex imbibition mechanism poses new challenges to us. The 1st National Conference on Imbibition Theory and Application in Porous Media was held in Beijing from April 22 to 24, 2023, to gather  researchers who are interested in imbibition research, exchange the latest progress and achievements in the field of imbibition in porous media, and discuss research hotspots and difficulties.Cited as: Cai, J., Sun, S., Wang, H. Current advances in capillarity: Theories and applications. Capillarity, 2023, 7(2): 25-31. https://doi.org/10.46690/capi.2023.05.0

Glucose-fueled Micromotors with Highly Efficient Visible Light Photocatalytic Propulsion

Synthetic micro/nanomotors fueled by glucose are highly desired for numerous practical applications because of the biocompatibility of their required fuel. However, currently all of the glucose-fueled micro/nanomotors are based on enzyme-catalytic-driven mechanisms, which usually suffer from strict operation conditions and weak propulsion characteristics that greatly limit their applications. Here, we report a highly efficient glucose-fueled cuprous oxide@N-doped carbon nanotube (Cu_2O@N-CNT) micromotor, which can be activated by environment-friendly visible-light photocatalysis. The speeds of such Cu_2O@N-CNT micromotors can reach up to 18.71 μm/s, which is comparable to conventional Pt-based catalytic Janus micromotors usually fueled by toxic H_2O_2 fuel. In addition, the velocities of such motors can be efficiently regulated by multiple approaches, such as adjusting the N-CNT content within the micromotors, glucose concentrations, or light intensities. Furthermore, the Cu_2O@N-CNT micromotors exhibit a highly controllable negative phototaxis behavior (moving away from light sources). Such motors with outstanding propulsion in biological environments and wireless, repeatable, and light-modulated three-dimensional motion control are extremely attractive for future practical applications

High atmospheric carbon dioxide-dependent alleviation of salt stress is linked to RESPIRATORY BURST OXIDASE 1 (RBOH1)-dependent H2O2 production in tomato (Solanum lycopersicum)

Plants acclimate rapidly to stressful environmental conditions. Increasing atmospheric CO2 levels are predicted to influence tolerance to stresses such as soil salinity but the mechanisms are poorly understood. To resolve this issue, tomato (Solanum lycopersicum) plants were grown under ambient (380 μmol mol–1) or high (760 μmol mol–1) CO2 in the absence or presence of sodium chloride (100 mM). The higher atmospheric CO2 level induced the expression of RESPIRATORY BURST OXIDASE 1 (SlRBOH1) and enhanced H2O2 accumulation in the vascular cells of roots, stems, leaf petioles, and the leaf apoplast. Plants grown with higher CO2 levels showed improved salt tolerance, together with decreased leaf transpiration rates and lower sodium concentrations in the xylem sap, vascular tissues, and leaves. Silencing SlRBOH1 abolished high CO2 -induced salt tolerance and increased leaf transpiration rates, as well as enhancing Na+ accumulation in the plants. The higher atmospheric CO2 level increased the abundance of a subset of transcripts involved in Na+ homeostasis in the controls but not in the SlRBOH1-silenced plants. It is concluded that high atmospheric CO2 concentrations increase salt stress tolerance in an apoplastic H2O2 dependent manner, by suppressing transpiration and hence Na+ delivery from the roots to the shoots, leading to decreased leaf Na+ accumulation

Antimicrobial Activity and Resistance: Influencing Factors

Rational use of antibiotic is the key approach to improve the antibiotic performance and tackling of the antimicrobial resistance. The efficacy of antimicrobials are influenced by many factors: (1) bacterial status (susceptibility and resistance, tolerance, persistence, biofilm) and inoculum size; (2) antimicrobial concentrations [mutant selection window (MSW) and sub-inhibitory concentration]; (3) host factors (serum effect and impact on gut micro-biota). Additional understandings regarding the linkage between antimicrobial usages, bacterial status and host response offers us new insights and encourage the struggle for the designing of antimicrobial treatment regimens that reaching better clinical outcome and minimizing the emergence of resistance at the same time

Shu-Xie decoction alleviates oxidative stress and colon injury in acute sleep-deprived mice by suppressing p62/KEAP1/NRF2/HO1/NQO1 signaling

Introduction: Sleep disorders are common clinical psychosomatic disorders that can co-exist with a variety of conditions. In humans and animal models, sleep deprivation (SD) is closely related with gastrointestinal diseases. Shu-Xie Decoction (SX) is a traditional Chinese medicine (TCM) with anti-nociceptive, anti-inflammatory, and antidepressant properties. SX is effective in the clinic for treating patients with abnormal sleep and/or gastrointestinal disorders, but the underlying mechanisms are not known. This study investigated the mechanisms by which SX alleviates SD-induced colon injury in vivo.Methods: C57BL/6 mice were placed on an automated sleep deprivation system for 72 h to generate an acute sleep deprivation (ASD) model, and low-dose SX (SXL), high-dose SX (SXH), or S-zopiclone (S-z) as a positive control using the oral gavage were given during the whole ASD-induced period for one time each day. The colon length was measured and the colon morphology was visualized using hematoxylin and eosin (H&E) staining. ROS and the redox biomarkers include reduced glutathione (GSH), malondialdehyde (MDA), and superoxide dismutase (SOD) were detected. Quantitative real-time PCR (qRT-PCR), molecular docking, immunofluorescence and western blotting assays were performed to detect the antioxidant signaling pathways.Results: ASD significantly increased FBG levels, decreased colon length, moderately increased the infiltration of inflammatory cells in the colon mucosa, altered the colon mucosal structure, increased the levels of ROS, GSH, MDA, and SOD activity compared with the controls. These adverse effects were significantly alleviated by SX treatment. ASD induced nuclear translocation of NRF2 in the colon mucosal cells and increased the expression levels of p62, NQO1, and HO1 transcripts and proteins, but these effects were reversed by SX treatment.Conclusion: SX decoction ameliorated ASD-induced oxidative stress and colon injury by suppressing the p62/KEAP1/NRF2/HO1/NQO1 signaling pathway. In conclusion, combined clinical experience, SX may be a promising drug for sleep disorder combined with colitis

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data