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AIM: To evaluate the efficacy of 0.01% hypochlorous acid as a conjunctival sac disinfectant before cataract phacoemulsification and its impact on the ocular surface.METHODS: Randomized controlled clinical trial. A total of 285 patients who were scheduled for cataract phacoemulsification surgery were randomly divided into the hypochlorous acid group and the povidone iodine group. Before and after disinfection, conjunctival sac swabs were taken, and bacterial culture and colony-forming units(CFUs)testing were performed using blood agar and chocolate agar media, respectively. All patients were evaluated for ocular symptom scores and pain severity scores 2 h, 1 d, and 1 wk after disinfection, and underwent corneal fluorescein staining, eye redness index, tear meniscus height, and noninvasive breakup time(NIBUT)examination. The incidence of endophthalmitis after surgery was recorded.RESULTS: Conjunctival sac disinfection with 0.01% hypochlorous acid significantly reduced the rate of positive bacterial cultures and colony-forming ability of the conjunctival sac, with statistically significant differences compared with the pre-disinfection period(both P

Dual‐state emission luminescent materials (DSEgens), which exhibit bright emissions in boththe solid state and solution, have been attracting research interest in the design of multifunctional materials.The delicate manipulation of molecular structures remains challenging in the synthesis of DSEgens. In this article, two novel molecules with dual‐state emission were synthesized by combining tetraphenylethylene with anthracene via dihydroisoxazole. Tetraphenylethylene acts as a solid‐state emitter, while the anthracene core functions as an emitter in the solution state to achieve DSE fluorescence properties. The THF/DCM mixture resulted in successfully obtaining the crystal structures of TPE−An−H and TPE−An−Cl. The quantum yields (QYs) of TPE−An−H were 31 % and 42 % in EA and the solid state, respectively, while TPE−An−Cl exhibited QYs of 32 % and 34 %. The novel synthesis method in this paper combines AIE with ACQ via dihydroisoxazole to achieve dual‐state emission, offering a new and concise approach. [ABSTRACT FROM AUTHOR]

Summary: Land surface phenology (LSP), the characterization of plant phenology with satellite data, is essential for understanding the effects of climate change on ecosystem functions. Considerable LSP variation is observed within local landscapes, and the role of biotic factors in regulating such variation remains underexplored.In this study, we selected four National Ecological Observatory Network terrestrial sites with minor topographic relief to investigate how biotic factors regulate intra‐site LSP variability. We utilized plant functional type (PFT) maps, functional traits, and LSP data to assess the explanatory power of biotic factors for the start and end of season (SOS and EOS) variability.Our results indicate that PFTs alone explain only 0.8–23.4% of intra‐site SOS and EOS variation, whereas including functional traits significantly improves explanatory power, with cross‐validation correlations ranging from 0.50 to 0.85. While functional traits exhibited diverse effects on SOS and EOS across different sites, traits related to competitive ability and productivity were important for explaining both SOS and EOS variation at these sites.These findings reveal that plants exhibit diverse phenological responses to comparable environmental conditions, and functional traits significantly contribute to intra‐site LSP variability, highlighting the importance of intrinsic biotic properties in regulating plant phenology. [ABSTRACT FROM AUTHOR]

Detection of flowering and quantification of flowering phenology are key to monitoring the reproduction of tropical trees and their response to global change. However, effective monitoring of flowering over various scales from individuals to forest ecosystem levels is lacking due to the relatively small sizes of flowers, diverse flowering strategies across species, and the short duration of flowering, making accurate flower detection difficult. Drone-based surveys require less time and human resources than traditional ground-based flower surveys and thus may be able to help address this in a cost-effective manner but remain underexplored in species-rich tropical forest ecosystems. Here, we developed a method that integrated the Residual Networks 50 (ResNet50) deep learning algorithm with high resolution imagery (c. 0.05 m) from monthly drone surveys done in a 50-ha tropical forest plot on Barro Colorado Island (BCI), Panamá, over 2018–2020 to detect a diversity of flowering species in this tree community and to track the timing of flowering throughout the year. We built a comprehensive training library of canopy components (flower, leaf, branch, and shade) from this forest plot throughout the study period, trained a single deep learning model across all drone imagery, and validated it using five-fold cross validation at the pixel scale. We further generated image- and tree-crown-specific supervised classifications to evaluate the deep learning model at the tree-crown scale. Our deep learning method accurately classified flowers (User's accuracy = 95.3 %, Producer's accuracy = 85.8 %) while maintaining high predictive power for the other three classes (Overall accuracy = 98.4 %). Our results also demonstrated high consistency against tree-crown-specific supervised classifications for flower (r2 = 0.85), leaf (r2 = 0.84), and branch (r2 = 0.92) components, with lower agreement observed for the shade component (r2 = 0.59). These results demonstrate the effectiveness of our method in advancing fine-scale flower monitoring in the tropics, with potential to be extended to other regions or other remote sensing platforms with frequent high-resolution monitoring. The method will allow us to better monitor flowering in tropical forests and improve our understanding of how phenology and reproductive success may be affected by climate change. [ABSTRACT FROM AUTHOR]

Leaf phenology variations within plant communities shape community assemblages and influence ecosystem properties and services. However, questions remain regarding quantification, drivers, and productivity impacts of intra-site leaf phenological diversity. With a 50-ha subtropical forest plot in China's Heishiding Provincial Nature Reserve (part of the global ForestGEO network) as a testbed, we gathered a unique dataset combining ground-derived abiotic (topography, soil) and biotic (taxonomic diversity, functional diversity, functional traits) factors. We investigated drivers underlying leaf phenological diversity extracted from high-resolution PlanetScope data, and its influence on aboveground biomass (AGB) using structural equation modeling (SEM). Our results reveal considerable fine-scale leaf phenological diversity across the subtropical forest landscape. This diversity is directly and indirectly influenced by abiotic and biotic factors (e.g. slope, soil, traits, taxonomic diversity; r 2  = 0.43). While a notable bivariate relationship between AGB and leaf phenological diversity was identified (r = -0.24, P < 0.05), this relationship did not hold in SEM analysis after considering interactions with other biotic and abiotic factors (P > 0.05). These findings unveil the underlying mechanism regulating intra-site leaf phenological diversity. While leaf phenology is known to be associated with ecosystem properties, our findings confirm that AGB is primarily influenced by functional trait composition and taxonomic diversity rather than leaf phenological diversity., (© 2024 The Authors. New Phytologist © 2024 New Phytologist Foundation.)

Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex m d SUGAR isob a ric-labeling g uide fi n gerprint embedd i ng (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex md SUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 10 3 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.

Background: The larval stages of Echinococcus granulosus sensu lato ( E. granulosus s.l ) infection can alter B cell function and affect host anti-infective immunity, but the underlying mechanism remains unclear. The newly emerging immunometabolism highlights that several metabolites are key factors in determining the fate of immune cells, which provides a new insight for exploring how larval E. granulosus s.l . infection remodels B cell function. This study investigated the metabolomic profiles of B cells in mice infected with E. granulosus s.l . protoscoleces (PSC). Results: Total CD19 + B cells, purified from the spleen of infected mice, showed significantly increased production of IL-6, TNF-α, and IL-10 after exposure to LPS in vitro . Moreover, the mRNA expression of metabolism related enzymes in B cells was remarkably disordered post infection. In addition, differential metabolites were identified in B cells after infection. There were 340 differential metabolites (83 upregulated and 257 downregulated metabolites) identified in the positive ion model, and 216 differential metabolites (97 upregulated and 119 downregulated metabolites) identified in the negative ion mode. Among these, 64 differential metabolites were annotated and involved in 68 metabolic pathways, including thyroid hormone synthesis, the metabolic processes of glutathione, fructose, mannose, and glycerophospholipid. Furthermore, several differential metabolites such as glutathione, taurine, and inosine were validated to regulate the cytokine production in LPS stimulated B cells. Conclusion: Infection with the larval E. granulosus s.l . causes metabolic reprogramming in the intrinsic B cells of mice, which provides the first evidence for understanding the role and mechanism of B cells in parasite anti-infective immunity from the viewpoint of immunometabolism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Guo, Xu, Fang, Xu, Liu, Xu, Zhou, Bu, Zhao, He, Yang, Pan, Shen and Sun.)

Secretion of recombinant proteins aims to reproduce the correct posttranslational modifications of the expressed protein while simplifying its recovery. In this study, secretion signal sequences from an abundantly secreted 34-kDa protein (P34) from Pseudozyma flocculosa were cloned. The efficiency of these sequences in the secretion of recombinant green fluorescent protein (GFP) was investigated in two Pseudozyma species and compared with other secretion signal sequences, from S. cerevisiae and Pseudozyma spp. The results indicate that various secretion signal sequences were functional and that the P34 signal peptide was the most effective secretion signal sequence in both P. flocculosa and P. antarctica. The cells correctly processed the secretion signal sequences, including P34 signal peptide, and mature GFP was recovered from the culture medium. This is the first report of functional secretion signal sequences in P. flocculosa. These sequences can be used to test the secretion of other recombinant proteins and for studying the secretion pathway in P. flocculosa and P. antarctica.

The basidiomycetous fungus Pseudozyma flocculosa represents a promising new host for the expression of complex recombinant proteins. Two novel heterologous promoter sequences, the Ustilago maydis glyceraldehyde-3-phosphate dehydrogenase (GPD) and Pseudozyma tsukubaensis alpha-glucosidase promoters, were tested for their ability to provide expression in P. flocculosa. In liquid medium, these two promoters produced lower levels of intracellular green fluorescent protein (GFP) as compared to the U. maydis hsp70 promoter. However, GPD and alpha-glucosidase sequences behaved as constitutive promoters whereas the hsp70 promoter appeared to be morphology-dependent. When using the hsp70 promoter, the expression of GFP increased proportionally to the concentration of hygromycin in the culture medium, indicating possible induction of the promoter by the antibiotic. Optimal solid-state culture conditions were designed for high throughput screening of hygromycin-resistant transformants with the hsp70 promoter in P. flocculosa.

The DNA fragment ecoding the Signal peptide of inulinase of Kluyveromyces smarxianu was synthesized chemically. This fragment was cloned in-frame in the expression vector pYES2 of Saccharomyces cerevisiae, resulting in a set of new secreting expression vectors pYES2 I, pYES2 II, pYES2 III. The L-Asparaginase gene (ASN) of E. coli and alpha-acetylactate decarboxylase gene (ALDC) of B. brevis which were amplified by PCR and cloned into the new vectors respectively were transformed into Saccharomyces cerevisia, and most of enzyme activities were secreted into the medium. The new secreting expression vectors still have excellent segregational stability even after growth for 100 h in the absence of selective pressure.