Experimental Evidence for the Role of Dynamics in pH-Dependent Enzymatic Activity.

Enzymatic activity is heavily influenced by pH, but the rationale for the dynamical mechanism of pH-dependent enzymatic activity has not been fully understood. In this work, combined neutron scattering techniques, including quasielastic neutron scattering (QENS) and small angle neutron scattering (SANS), are used to study the structural and dynamic changes of a model enzyme, xylanase, under different pH and temperature environments. The QENS results reveal that xylanase at optimal pH exhibits faster relaxational dynamics and a lower energy barrier between conformational substates. The SANS results demonstrate that pH affects both xylanase's stability and monodispersity. Our findings indicate that enzymes have optimized stability and function under their optimal pH conditions, with both structure and dynamics being affected. The current study offers valuable insights into enzymatic functionality mechanisms, allowing for broad industrial applications.

Pseudostellaria heterophylla improves intestinal microecology through modulating gut microbiota and metabolites in mice.

BACKGROUND: Pseudostellaria heterophylla is a Chinese medicine and healthy edible that is widely used to for its immunomodulatory, antioxidant, antidiabetic and antitussive properties. However, the potential function of P. heterophylla in intestinal microecology remains unclear. In this study, we investigated the impact of P. heterophylla on immune functions and evaluated its potential to regulate the gut microbiota and metabolome. RESULTS: The results showed that P. heterophylla significantly increased the content of red blood cells, total antioxidant capacity and expression of immune factors, and decreased platelet counts when compared to the control under cyclophosphamide injury. In addition, P. heterophylla altered the diversity and composition of the gut bacterial community; increased the abundance of potentially beneficial Akkermansia, Roseburia, unclassified Clostridiaceae, Mucispirillum, Anaeroplasma and Parabacteroides; and decreased the relative abundance of pathogenic Cupriavidus and Staphylococcus in healthy mice. Metabolomic analyses showed that P. heterophylla significantly increased the content of functional oligosaccharides, common oligosaccharides, vitamins and functional substances. Probiotics and pathogens were regulated by metabolites across 11 pathways in the bacterial-host co-metabolism network. CONCLUSION: We demonstrated that P. heterophylla increased the abundance of probiotics and decreased pathogens, and further stimulated host microbes to produce beneficial secondary metabolites for host health. Our studies highlight the role of P. heterophylla in gut health and provide new insights for the development of traditional Chinese medicine in the diet. © 2024 Society of Chemical Industry.

Discovery of Novel Rhizoctonia solani DHFR Inhibitors as Fungicides Using Virtual Screening.

Dihydrofolate reductase (DHFR) is an essential enzyme in the folate pathway and has been recognized as a well-known target for antibacterial and antifungal drugs. We discovered eight compounds from the ZINC database using virtual screening to inhibit Rhizoctonia solani (R. solani), a fungal pathogen in crops. These compounds were evaluated with in vitro assays for enzymatic and antifungal activity. Among these, compound Hit8 is the most active R. solani DHFR inhibitor, with the IC50 of 10.2 µM. The selectivity of inhibition is 22.3 against human DHFR with the IC50 of 227.7 µM. Moreover, Hit8 has higher antifungal activity against R. solani (EC50 of 38.2 mg L-1) compared with validamycin A (EC50 of 67.6 mg L-1), a well-documented fungicide. These results suggest that Hit8 may be a potential fungicide. Our study exemplifies a computer-aided method to discover novel inhibitors that could target plant pathogenic fungi.

Engineered Cancer Cells as Signal Probes for Fluorescence-Assisted Digital Counting Analysis.

Fluorescence-assisted digital counting analysis allowed sensitive quantification of targets by measuring individual fluorescent labels. However, traditional fluorescent labels suffered from low brightness, small size, and sophisticated preparation procedures. Herein, engineering fluorescent dye-stained cancer cells with magnetic nanoparticles were proposed to construct single-cell probes for fluorescence-assisted digital counting analysis by quantifying the target-dependent binding or cleaving events. Various engineering strategies of cancer cells including biological recognition and chemical modification were developed for rationally designing single-cell probes. Introduction of suitable recognition elements into single-cell probes allowed digital quantification of each target-dependent event via counting the colored single-cell probes in the representative image taken using a confocal microscope. The reliability of the proposed digital counting strategy was corroborated by traditional optical microscopy- and flow cytometry-dependent counting technologies. The advantages of single-cell probes, including high brightness, big size, ease of preparation, and magnetic separation, contributed to the sensitive and selective analysis of targets of interest. As proof-to-concept assays, indirect analysis of exonuclease III (Exo III) activity, as well as direct quantitation of cancer cells, were investigated, and the potential in biological sample analysis was also assessed. This sensing strategy will open a new avenue for the development of biosensors.

Investigations of structural and dynamical mechanisms of ice formation regulated by graphene oxide nanosheets.

Recent research indicates that graphene oxide (GO) nanosheets can be used to regulate ice formation by controlling critical ice nucleus growth in water at supercooling temperatures. In addition, the study of ice formation mechanisms regulated by GO nanosheets, a good model system for antifreeze proteins (AFPs), will shed light on how AFPs regulate ice formation in nature. In this work, time-resolved small-angle x-ray scattering (TR-SAXS) and quasi-elastic neutron scattering (QENS) experiments were carried out to investigate the structural and dynamical mechanisms of ice formation regulated by GO nanosheets. Strikingly, a transient intermediate state was observed in TR-SAXS experiments that only exists in the aqueous dispersions with a larger GO size (11 nm). This serves as evidence that the size of GO is critical for regulating ice formation. Elastic neutron scattering results indicate that ice is formed in all samples and thermal hysteresis occurs in GO aqueous dispersions in both H2O and D2O. The structural and dynamics information about water molecules in GO, extracted from QENS, reveals different dynamical behaviors of water molecules in GO aqueous dispersions when approaching the ice formation temperature.

Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method.

Satellite altimeters can be used to derive long-term and large-scale sea ice thickness changes. Sea ice thickness retrieval is based on measurements of freeboard, and the conversion of freeboard to thickness requires knowledge of the snow depth and snow, sea ice, and sea water densities. However, these parameters are difficult to be observed concurrently with altimeter measurements. The uncertainties in these parameters inevitably cause uncertainties in sea ice thickness estimations. This paper introduces a new method based on least squares adjustment (LSA) to estimate Arctic sea ice thickness with CryoSat-2 measurements. A model between the sea ice freeboard and thickness is established within a 5 km × 5 km grid, and the model coefficients and sea ice thickness are calculated using the LSA method. Based on the newly developed method, we are able to derive estimates of the Arctic sea ice thickness for 2010 through 2019 using CryoSat-2 altimetry data. Spatial and temporal variations of the Arctic sea ice thickness are analyzed, and comparisons between sea ice thickness estimates using the LSA method and three CryoSat-2 sea ice thickness products (Alfred Wegener Institute (AWI), Centre for Polar Observation and Modelling (CPOM), and NASA Goddard Space Flight Centre (GSFC)) are performed for the 2018-2019 Arctic sea ice growth season. The overall differences of sea ice thickness estimated in this study between AWI, CPOM, and GSFC are 0.025 ± 0.640 m, 0.143 ± 0.640 m, and -0.274 ± 0.628 m, respectively. Large differences between the LSA and three products tend to appear in areas covered with thin ice due to the limited accuracy of CryoSat-2 over thin ice. Spatiotemporally coincident Operation IceBridge (OIB) thickness values are also used for validation. Good agreement with a difference of 0.065 ± 0.187 m is found between our estimates and the OIB results.

Gout in the Chest Misdiagnosed as Ankylosing Spondylitis.

Gout is a crystal-related joint disease caused by single sodium urate deposition in the joints or in soft tissues. In recent years, the incidence of gout has increased, but cases of urate crystals deposited in the chest-ribs are rare. Here, we describe a 39-year-old man who complained of frequent pain and a feeling of tightness in chest-ribs and was misdiagnosed as ankylosing spondylitis. In addition, treatment with non-steroidal anti-inflammatory drugs (NSAIDs) and etanercept for 6 months showed no improvement, which confirmed the misdiagnosis. After physical examination, blood examination, and dual-energy CT examination, the patient was diagnosed with gout and received 50 mg benzbromarone once a day with treatment of low serum uric acid. In conclusion, gout in the chest and ribs is an unusual manifestation and has rarely been reported in the literature. This case highlights an important but overlooked history of hyperuricemia in the diagnosis, and dual-energy CT is the preferred method for differential diagnosis of chest-ribs gout.

Underlying Mechanism of Wild Radix pseudostellariae in Tolerance to Disease Under the Natural Forest Cover.

Replanting disease caused by negative plant-soil feedback in continuous monoculture of Radix pseudostellariae is a critical factor restricting the development of this common and popular Chinese medicine, although wild R. pseudostellariae plants were shown to grow well without occurrence of disease in the same site for multiple years. Therefore, we aimed to identify the changes in microbial community composition in the rhizosphere soil of wild R. pseudostellariae thus providing a potential method for controlling soil-borne diseases. We analyzed differences in soil physicochemical properties, changes in soil microbial community structure, and root exudates of wild R. pseudostellariae under different biotopes. And then, simple sequence repeats amplification was used to isolate and collect significantly different formae speciales of Fusarium oxysporum. Finally, we analyzed the pathogenicity testing and influence of root exudates on the growth of F. oxysporum. We found that the different biotopes of R. pseudostellariae had significant effects on the soil microbial diversity. The soil fungal and bacterial abundances were significantly higher and the abundance of F. oxysporum was significantly lower under the rhizosphere environment of wild R. pseudostellariae than under consecutive monoculture. The relative abundances of most genera were Penicillium, Aspergillus, Fusarium, Nitrobacter, Nitrospira, Streptomyces, Actinoplanes, and Pseudomonas. Venn diagram and LEfSe analyses indicated numerously specific microbiome across all the samples, and the numbers of specific fungi were higher than the shared ones in the four biotopes. Eight types of phenolic acids were identified across all the rhizosphere soils. Mixed phenolic acids and most of the examined single phenolic acids had negative effects on the growth of isolated pathogenic F. oxysporum strains and promoted the growth of non-pathogenic strains. Similarly, correlation analysis suggested that most of the identified phenolic acids were positively associated with beneficial Pseudomonas, Nitrobacter, Nitrospira, Streptomyces, and Bacillus. This study suggested that wild R. pseudostellariae was able to resist or tolerate disease by increasing soil microbial diversity, and reducing the accumulation of soil-borne pathogens.

Modeling and Forecasting the GPS Zenith Troposphere Delay in West Antarctica Based on Different Blind Source Separation Methods and Deep Learning.

Tropospheric delay is an important error source in global positioning systems (GPS), and the water vapor retrieved from the tropospheric delay is widely used in meteorological research such as climate analysis and weather forecasting. Most zenith tropospheric delay (ZTD) models are presently used as positioning corrections, and few models are used for the estimation of water vapor, especially in Antarctica. Through two blind source separation algorithms (principal component analysis (PCA) and independent component analysis (ICA)), a back-propagation (BP) neural network and a deep learning technique (long short-term memory (LSTM) network), we establish an hourly high-accuracy ZTD model for GPS meteorology using the GPS-ZTD from 52 GPS stations in West Antarctica. Our results show that under the condition in which the principal components (PCs) and independent components (ICs) remain fixed after decomposition, the mean accuracy of the models for West Antarctica using PCA or ICA are better than 10 mm. Compared with the ZTDs from the nonmodeling stations, the mean root mean square (RMS) of the PCA and ICA models are 9.3 and 8.9 mm, respectively, and the correlation coefficients between the GPS-ZTD and model-ZTDs all exceed 90%. The accuracy of the ICA model is slightly higher than that of the PCA model, and the ICs of the ICA model show more consistent spatial responses. The six-hour forecast is the best among the forecast results, with a mean correlation coefficient of 90.6% and a mean RMS of 7.2 mm using GPS-ZTD. The long-term forecast result is significantly inaccurate, as the correlation coefficient between the 24-h forecast and GPS-ZTD is only 63.2%. Generally modest results have been achieved (HSS ≤ 0.38). Furthermore, the forecast accuracy in coastal areas is lower than that in inland areas. Our study confirms that the combined use of ICA and deep learning in ZTD modeling can effectively restore the original signals, and short-term forecasting can be effectively used in GPS meteorology. However, further development of the technology is necessary.

c-Myc induced upregulation of long non-coding RNA SNHG16 enhances progression and carcinogenesis in oral squamous cell carcinoma.

Small nucleolar RNA host gene 16 (SNHG16) has been documented to be involved in the pathogenesis of human cancers. Here, we elucidated the biological roles and regulatory mechanism of SNHG16 in the pathogenesis of oral squamous cell carcinoma (OSCC). In this paper, we found that c-Myc and SNHG16 were overexpressed in OSCC tissues and cell lines compared with normal tissues and normal human oral keratinocytes cells. There was a notable positive correlation between SNHG16 and c-Myc expression in OSCC tissues. c-Myc silencing by either shRNA c-Myc or by 10058-F4 (c-Myc inhibitor) resulted in a dose-dependent reduction in SNHG16 levels in CAL-27 and TSCCA cells; conversely, upregulation of c-Myc by pcDNA c-Myc markedly increased SNHG16 expression. Depletion of SNHG16 in CAL-27 cells strikingly inhibited cell proliferation, migration and invasion, as indicated by downregulation of proliferating cell nuclear antigen (PCNA), matrix metalloproteinase (MMP)-2 and MMP-9. Moreover, depletion of SNHG16 induced cell apoptosis and inhibited epithelial-to-mesenchymal transition as indicated by induction of cleaved caspase-3 and epithelial cadherin (E-cadherin) along with reduction of N-cadherin and Snail. Intriguingly, c-Myc knockdown led to the similar functional effects as that of SNHG16 knockdown in TSCCA cells. However, these changes caused by c-Myc knockdown were abrogated by SNHG16 overexpression. Knockdown of SNHG16 conspicuously repressed tumor growth in nude mice. Similarly, silencing of c-Myc markedly inhibited tumor growth and reduced SNHG16 expression in nude mice. Moreover, overexpression of SNHG16 blocked the inhibitory effect of c-Myc silencing on tumor growth in vivo. Thus, we conclude that c-Myc-induced upregulation of SNHG16 enhances progression and carcinogenesis in OSCC.