Sinomonas terricola sp. nov., a plant-beneficial bacterium isolated from litchi rhizosphere soil in Guangdong, China.

A novel plant-beneficial bacterium strain, designated as JGH33T, which inhibited Peronophythora litchii sporangia germination, was isolated on Reasoner's 2A medium from a litchi rhizosphere soil sample collected in Gaozhou City, Guangdong Province, PR China. Cells of strain JGH33T were Gram-stain-positive, aerobic, non-motile, bent rods. The strain grew optimally at 30-37 °C and pH 6.0-8.0. Sequence similarity analysis based on 16S rRNA genes indicated that strain JGH33T exhibited highest sequence similarity to Sinomonas albida LC13T (99.2 %). The genomic DNA G+C content of the isolate was 69.1 mol%. The genome of JGH33T was 4.7 Mbp in size with the average nucleotide identity value of 83.45 % to the most related reference strains, which is lower than the species delineation threshold of 95 %. The digital DNA-DNA hybridization of the isolate resulted in a relatedness value of 24.9 % with its closest neighbour. The predominant respiratory quinone of JGH33T was MK-9(H2). The major fatty acids were C15 : 0 anteiso (43.4 %), C16 : 0 iso (19.1 %) and C17 : 0 anteiso (19.3 %), and the featured component was C18 : 3 ω6c (1.01 %). The polar lipid composition of strain JGH33T included diphosphatidylglycerol, phosphatidylglycerol, dimannosylglyceride, phosphatidylinositol and glycolipids. On the basis of polyphasic taxonomy analyses data, strain JGH33T represents a novel species of the genus Sinomonas, for which the name Sinomonas terricola sp. nov. is proposed, with JGH33T (=JCM 35868T=GDMCC 1.3730T) as the type strain.

Operando Decoding of Surface Chemical and Thermal Events in Photoelectrocatalysis via a Lab-Around-Microfiber Sensor.

Operando decoding of the key parameters of photo-electric catalysis provides reliable information for catalytic effect evaluation and catalytic mechanism exploration. However, to capture the details of surface-localized and rapid chemical and thermal events at the nanoscale in real-time is highly challenging. A promising approach based on a lab-around-microfiber sensor capable of simulating photo-electric catalytic reactions on the surface of optical fibers as well as monitoring reactant concentration changes and catalytic heat generation processes is demonstrated. Due to the penetration depth of submicron size and the fast response ability of the evanescent field, the lab-around-microfiber sensor overcame the difficulty of reading instantaneous surface parameters in the submicron range. This sensor operando dismantled the changes in reactant concentration and temperature on the catalyst surface induced by light and voltage, respectively. It also decoded the impact of catalyst composition on the adsorption efficiency and catalytic efficiency across various wavelengths and determined the synchronized occurrence of pollutant degradation and catalytic thermal effects. Stable correlations between the real-time parameters and catalytic activities are obtained, helping to provide a basic understanding of the catalytic process and mechanism. This approach fills an important gap in the current monitoring methods of catalytic processes and heat production.

Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.

BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic features to diagnose cervical LNM in patients with NSCLC. METHODS: This study included NSCLC patients who underwent neck ultrasound examination followed by cervical lymph node (LN) biopsy between January 2019 and January 2022 from three institutes. Radiomic features were extracted from the ultrasound images at the maximum cross-sectional areas of cervical LNs. Logistic regression (LR) and random forest (RF) models were developed. Model performance was assessed by the area under the curve (AUC) and accuracy, validated internally and externally by fivefold cross-validation and hold-out method, respectively. RESULTS: In total, 313 patients with a median age of 64 years were included, and 276 (88.18%) had cervical LNM. Three descriptive semantic features, including long diameter, shape, and corticomedullary boundary, were selected by multivariate analysis. Out of the 474 identified radiomic features, 9 were determined to fit the LR model, while 15 fit the RF model. The average AUCs of the semantic and radiomics models were 0.876 (range: 0.781-0.961) and 0.883 (range: 0.798-0.966), respectively. However, the average AUC was higher for the semantic-radiomics combined LR model (0.901; range: 0.862-0.927). When the RF algorithm was applied, the average AUCs of the radiomics and semantic-radiomics combined models were improved to 0.908 (range: 0.837-0.966) and 0.922 (range: 0.872-0.982), respectively. The models tested by the hold-out method had similar results, with the semantic-radiomics combined RF model achieving the highest AUC value of 0.901 (95% CI, 0.886-0.968). CONCLUSIONS: The ultrasound radiomic models showed potential for accurately diagnosing cervical LNM in patients with NSCLC when integrated with descriptive semantic features. The RF model outperformed the conventional LR model in diagnosing cervical LNM in NSCLC patients.

Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (tumor-SLNs) dual-region computed tomography (CT) radiomics model for predicting SLNM in NSCLC. METHODS: This retrospective study included NSCLC patients who underwent lung resection and SLNs dissection between January 2017 and December 2020. The radiomic features of the tumor and SLNs were extracted from preoperative CT, respectively. Ninety machine learning (ML) models were developed based on tumor region, SLNs region, and tumor-SLNs dual-region. The model performance was assessed by the area under the curve (AUC) and validated internally by fivefold cross-validation. RESULTS: In total, 202 patients were included in this study. ML models based on dual-region radiomics showed good performance for SLNM prediction, with a median AUC of 0.794 (range, 0.686-0.880), which was superior to those of models based on tumor region (median AUC, 0.746; range, 0.630-0.811) and SLNs region (median AUC, 0.700; range, 0.610-0.842). The ML model, which is developed by using the naive Bayes algorithm and dual-region features, had the highest AUC of 0.880 (range of cross-validation, 0.825-0.937) among all ML models. The optimal logistic regression model was inferior to the optimal ML model for predicting SLNM, with an AUC of 0.727. CONCLUSIONS: The CT radiomics showed the potential for accurately predicting SLNM in NSCLC patients. The ML model with dual-region radiomic features has better performance than the logistic regression or single-region models.

2D Ruddlesden-Popper Polycrystalline PerovskitePyro-Phototronic Photodetectors.

Two-dimensional (2D) Ruddlesden-Popper (RP) layered halide perovskite has attracted wide attentions due to its unique structure and excellent optoelectronic properties. With inserting organic cations, inorganic octahedrons are forced to extend in a certain direction, resulting in an asymmetric 2D perovskite crystal structure and causing spontaneous polarization. The pyroelectric effect resulted from spontaneous polarization exhibits a broad prospect in the application of optoelectronic devices. Herein, 2D RP polycrystalline perovskite (BA)2 (MA)3 Pb4 I13 film with excellent crystal orientation is fabricated by hot-casting deposition, and a class of 2D hybrid perovskite photodetectors (PDs) with pyro-phototronic effect is proposed, achieving temperature and light detection with greatly improved performance by coupling multiple energies. Because of the pyro-phototronic effect, the current is ≈35 times to that of the photovoltaic effect current under 0 V bias. The responsivity and detectivity are 12.7 mA W-1 and 1.73 × 1011 Jones, and the on/off ratio can reach 3.97 × 103 . Furthermore, the influences of bias voltage, light power density, and frequency on the pyro-phototronic effect of 2D RP polycrystalline perovskite PDs are explored. The coupling of spontaneous polarization and light facilitates photo-induced carrier dissociation and tunes the carrier transport process, making 2D RP perovskites a competitive candidate for next-generation photonic devices.

Differential effects of low and high temperature stress on pollen germination and tube length of mango (Mangifera indica L.) genotypes.

Mango flowering is highly sensitive to temperature changes. In this research, the maximum values of pollen germination rate (PGR), pollen tube length (PTL) and their cardinal temperatures (Tmin, Topt and Tmax) were estimated by using quadratic equation and modified bilinear model under the conditions of 14-36 °C. The pollen germination rate in four mango varieties ranged from 29.1% ('Apple mango') to 35.5% ('Renong No. 1'); the length of pollen tube ranged from 51.2 µm ('Deshehari') to 56.6 µm ('Jinhuang'). The cardinal temperatures ranges (Tmin, Topt and Tmax) of pollen germination were 20.3-22.8 °C, 26.7-30.6 °C and 30.4-34.3 °C, respectively; similarly, cardinal temperatures (Tmin, Topt and Tmax) of pollen tube growth were 20.3-21.2 °C, 27.9-32.1 °C and 30.2-34.4 °C respectively. Of those, 'Renong No. 1' could maintain relatively high pollen germination rate even at 30 °C, however, 'Deshehari' had the narrowest adaptive temperature range. These results were further confirmed by changes of superoxide dismutase, catalase activity and malondialdehyde content. These results showed that mango flowering was highly sensitive to temperature changes and there were significant differences in pollen germination rate and pollen tube length among different varieties. Current research results were of great significance for the introduction of new mango varieties in different ecological regions, the cultivation and management of mango at the flowering stage and the breeding of new mango varieties.

Isolation of a Novel Thermophilic Methanogen and the Evolutionary History of the Class Methanobacteria.

Methanogens can produce methane in anaerobic environments via the methanogenesis pathway, and are regarded as one of the most ancient life forms on Earth. They are ubiquitously distributed across distinct ecosystems and are considered to have a thermophilic origin. In this study, we isolated, pure cultured, and completely sequenced a single methanogen strain DL9LZB001, from a hot spring at Tengchong in Southwest China. DL9LZB001 is a thermophilic and hydrogenotrophic methanogen with an optimum growth temperature of 65 °C. It is a putative novel species, which has been named Methanothermobacter tengchongensis-a Class I methanogen belonging to the class Methanobacteria. Comparative genomic and ancestral analyses indicate that the class Methanobacteria originated in a hyperthermal environment and then evolved to adapt to ambient temperatures. This study extends the understanding of methanogens living in geothermal niches, as well as the origin and evolutionary history of these organisms in ecosystems with different temperatures.

Transcriptome and Metabolome Analyses Reveal the Involvement of Multiple Pathways in Flowering Intensity in Mango.

Mango (Mangifera indica L.) is famous for its sweet flavor and aroma. China is one of the major mango-producing countries. Mango is known for variations in flowering intensity that impacts fruit yield and farmers' profitability. In the present study, transcriptome and metabolome analyses of three cultivars with different flowering intensities were performed to preliminarily elucidate their regulatory mechanisms. The transcriptome profiling identified 36,242 genes. The major observation was the differential expression patterns of 334 flowering-related genes among the three mango varieties. The metabolome profiling detected 1,023 metabolites that were grouped into 11 compound classes. Our results show that the interplay of the FLOWERING LOCUS T and CONSTANS together with their upstream/downstream regulators/repressors modulate flowering robustness. We found that both gibberellins and auxins are associated with the flowering intensities of studied mango varieties. Finally, we discuss the roles of sugar biosynthesis and ambient temperature pathways in mango flowering. Overall, this study presents multiple pathways that can be manipulated in mango trees regarding flowering robustness.

Aquaporin 1 mediates early responses to osmotic stimuli in endothelial cells via the calmodulin pathway.

The aquaporins (AQPs) are a family of integral membrane proteins which play critical roles in controlling transcellular water movement in various tissues throughout the body. AQP1 helps mediate the cellular response to osmotic stress and tissue water permeability. However, the mechanism by which AQP1 mediates changes in cell volume is not completely clear. Here, we investigated how AQP1 responds to and controls cell volume upon osmotic stimuli during the early phase after the immediate response. Cells overexpressing AQP1 were exposed to hypotonic or hypertonic medium in the presence or absence of staurosporine or W-7 hydrochloride, and fluorescence imaging was performed at 0, 5, 10, and 15 min later. Osmotic stimuli induced redistribution of AQP1 into the cell membrane, hypotonic stimuli caused cell enlargement, and hypertonic stimuli induced a reduction in cell size, which was blocked by T157A/T239A mutations. Changes in cell size induced by osmotic stimuli were blocked by an antagonist of calmodulin kinase, W-7 hydrochloride, but not by the PKC inhibitor staurosporine. These results suggest that calmodulin kinase regulates AQP1 activity during the early response to osmotic stimuli.

Inhibitory effect of phloroglucinol on α-glucosidase: Kinetics and molecular dynamics simulation integration study.

Regulation of α-glucosidase (EC 3.2.1.20) and its inhibitors is of great interest to researchers due to its clinical relevance as a target enzyme for the treatment of α-glucosidase-mediated diseases, such as type 2 diabetes mellitus and Pompe disease. In this study, we conducted a phloroglucinol-induced inhibition kinetics assay and performed computational molecular dynamics (MD) simulations to assess binding manner in α-glucosidase. The results showed that phloroglucinol reversibly inhibited α-glucosidase in a dose-dependent but non-competitive manner (Ki=2.07±0.16mM). Interestingly, the maximum peak wavelength and the hydrophobic surface remained unchanged during the inhibition reaction, with computational MD simulations further revealing that phloroglucinol bound in front of the active site pocket rather than in the α-glucosidase active site. Therefore, we speculate that phloroglucinol-specific inhibition is mild and the inhibitor likely binds to a single binding site near but not in the active site. Our study provided insight into the effects and mechanisms associated with a mild inhibitor of α-glucosidase activity and promotes fundamental research and potential applications of inhibitors for treatment of α-glucosidase-mediated clinical disease.

Metabolic responses and arginine kinase expression of juvenile cuttlefish (Sepia pharaonis) under salinity stress.

The pharaoh cuttlefish Sepia pharaonis is particularly sensitive to environmental changes in its breeding environment. The breeding of S. pharaonis larvae was carried out in different salinities for 48h, and the changes in survival rate, histological structure, energy metabolism, and anti-oxidative stress parameters were investigated and correlated with arginine kinase (AK) expression changes in muscle and liver tissues. The suitable salinity for larvae cultivation ranged from 24 to 30‰, and the survival rate showed a significant decline at 21‰ salinity. Histological observations of muscle and liver showed that changes in salinity and osmotic pressure had an adverse effect on tissue structure. Measurements of glycogen and lactic acid levels suggested that S. pharaonis could dynamically adjust energy metabolism to provide additional energy under unsuitable salinity. The protein levels and enzyme activities of AK in muscle significantly increased at 21‰ salinity. The results were consistent with prompt replenishment of phosphoarginine stores during salinity stress to maintain a dynamic ATP balance, suggesting that AK plays an important role in the regulation of energy metabolism. This study provides insight into metabolic changes during salinity stress and sheds light on the functional role of AK in S. pharaonis.

[Progress in lytic polysaccharide monooxygenase].

Lignocellulose is the most abundant renewable biomass resource. Enzymatic breakdown of lignocellulose into oligosaccharides or monosaccharides is the key to exploit lignocellulosic biomass. However, traditional glycoside hydrolases are insufficient to degrade lignocellulose. The emergence of lytic polysaccharide monooxygenase, a novel enzyme for lignocellulose degradation, has enriched the deconstruction schema and accelerated the enzymatic conversion of polysaccharides, by introducing new chain breaks that allow hydrolases to initiate further degradation. Here, we review the discovery, classification and catalytic mechanism of the enzyme, as well as the methods for assaying its activity. The prospect for its application in feed additive, functional food and biofuel development is further discussed.

Detection of Atmospheric Methyl Mercaptan Using Wavelength Modulation Spectroscopy with Multicomponent Spectral Fitting.

Detection of methyl mercaptan (CH3SH) is essential for environmental atmosphere assessment and exhaled-breath analysis. This paper presents a sensitive CH3SH sensor based on wavelength modulation spectroscopy (WMS) with a mid-infrared distributed feedback interband cascade laser (DFB-ICL). Multicomponent spectral fitting was used not only to enhance the sensitivity of the sensor but also to determine the concentration of interferents (atmospheric water and methane). The results showed that the uncertainties in the measurement of CH3SH, H2O, and CH4 were less than 1.2%, 1.7% and 2.0%, respectively, with an integration time of 10 s. The CH3SH detection limit was as low as 7.1 ppb with an integration time of 295 s. Overall, the reported sensor, boasting the merits of high sensitivity, can be used for atmospheric methyl mercaptan detection, as well as multiple components detection of methyl mercaptan, water, and methane, simultaneously.