Glycomyces niveus sp. nov., a novel actinomycete isolated from sandy soil.

A novel mycelium-forming actinomycete, designated strain NEAU-S30T, was isolated from the sandy soil of a sea beach in Shouguang city, Shandong province, PR China. The strain developed long chains of non-motile cylindrical spores with smooth surfaces on aerial mycelia. The results of a polyphasic taxonomic study indicated that NEAU-S30T represented a member of the genus Glycomyces. The results of 16S rRNA gene sequence analysis indicated that NEAU-S30T was closely related to 'Glycomycesluteolus' (98.97 % sequence similarity), Glycomycesalgeriensis (98.90 %), 'Glycomyces tritici' (98.83 %) and Glycomyces lechevalierae (98.76 %). The average nucleotide identity (ANI) values between NEAU-S30T and 'G. luteolus' NEAU-A15, G. algeriensis DSM 44727T, 'G. tritici' NEAU-C2 and G. lechevalierae DSM 44724T were 87.77, 87.53, 87.41 and 87.80 %, respectively. The digital DNA G+C content of the genomic DNA was 70.5 %. The whole-cell sugars contained ribose and xylose. The predominant menaquinones were MK-10(H2), MK-10(H4) and MK-10(H6). The predominant fatty acids were anteiso-C15 : 0, iso-C16 : 0, anteiso-C17 : 0 and iso-C15 : 0. The polar lipid profile consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphoglycolipid, phosphatidylinositol, phosphatidylinositol mannoside and an unidentified glycolipid. On the basis of the results of comparative analysis of genotypic, phenotypic and chemotaxonomic data, the novel actinomycete strain NEAU-S30T (=JCM 33975T=CGMCC 4.7890T) represents the type strain of a novel species within the genus Glycomyces, for which the name Glycomyces niveus sp. nov. is proposed.

Differential diagnosis of benign and lung adenocarcinoma presenting as larger solid nodules and masses based on multiscale CT radiomics.

PURPOSE: To develop a better radiomic model for the differential diagnosis of benign and lung adenocarcinoma lesions presenting as larger solid nodules and masses based on multiscale computed tomography (CT) radiomics. MATERIALS AND METHODS: This retrospective study enrolled 205 patients with solid nodules and masses from Center 1 between January 2010 and February 2022 and Center 2 between January 2019 and February 2022. After applying the inclusion and exclusion criteria, we retrospectively enrolled 165 patients from two centers and assigned them to the training dataset (n = 115) or the test dataset (n = 50). Radiomics features were extracted from volumes of interest on CT images. A gradient boosting decision tree (GBDT) was used for data dimensionality reduction to perform the final feature selection. Four models were developed using clinical data, conventional imaging features and radiomics features, namely, the clinical and image model (CIM), the plain CT radiomics model (PRM), the enhanced CT radiomics model (ERM) and the combined model (CM). Model performance was evaluated to determine the best model for identifying benign and lung adenocarcinoma presenting as larger solid nodules and masses. RESULTS: In the training dataset, the areas under the curve (AUCs) for the CIM, PRM, ERM, and CM were 0.718, 0.806, 0.819, and 0.917, respectively. The differential diagnostic capability of the ERM was better than that of the PRM and the CIM. The CM was optimal. Intermediate and junior radiologists and respiratory physicians achieved improved obviously diagnostic results with the radiomics model. The senior radiologists showed slight improved diagnostic results after using the radiomics model. CONCLUSION: Radiomics may have the potential to be used as a noninvasive tool for the differential diagnosis of benign and lung adenocarcinoma lesions presenting as larger solid nodules and masses.

Growth assessment of pure ground-glass nodules on CT: comparison of density and size measurement methods.

PURPOSE: To investigate the differences of size and density measurements in assessing pure ground-glass nodules (pGGNs) growth, and compare the growth rates and growth proportions of the two methods during follow-up period. METHODS: Ninety patients with at least 3 consecutive thin-section chest CTs and confirmed 103 pGGNs on baseline CT were enrolled retrospectively. Using the two definitions of size and density to evaluate pGGNs growth with semi-automated segmentation. Then, the two methods were compared to assess differences in pGGNs growth. RESULTS: For the size and density methods to assess nodule growth, 50.5% and 26.2% showed interval growth at the last CT (p < 0.001). Among the 19 nodules that grew in both size and density, the volume doubling time (VDT) of solid component (mean, 317.1; standard deviation, 224.8 days) was shorter than total VDT (median, 942.8; range, 400.1-2315.9 days) (p < 0.001). Of the 27 growth pGGNs assessed by the density method, the growth rates at years 1 and 2 were 25.9% and 63.0%, while the growth rates of 52 growing nodules assessed by size method were 11.5% and 48.1%, respectively. Twenty of 103 (19.4%) nodules were classified into category 4A lesions, and 7 (6.8%) were 4B lesions. CONCLUSION: Compared to size measurements, observed density increases have a higher proportion of early growth and faster growth rates in growing nodules. Clinicians need to pay close attention to the nodules of new solid components and make timely decision management.

Chemical and Electronic Modulation via Atomic Layer Deposition of NiO on Porous In2O3 Films to Boost NO2 Detection.

To achieve high sensitivity under low-temperature operation is currently a challenge for metal oxide semiconductor gas sensors. In this work, a unique NiO-functionalized macroporous In2O3 thin film is designed by atomic layer deposition (ALD), which demonstrates great potential in electronic sensors for detecting NO2 at low temperature. This strategy allows for efficient engineering of the oxygen vacancy concentration and the formation of p-n heterojunctions in the hybrid In2O3/NiO thin films, which has been found to greatly impact the surface chemical and electrical properties of the sensing films. The sensor based on the optimized In2O3/NiO films exhibits a very high response of 532.2 to 10 ppm NO2, which is 26 times higher than that of the In2O3, at a relatively low operating temperature of 145 °C. In addition, an ultralow detection limit of ca. 6.9 ppb has been obtained, which surpasses most reports based on metal oxide sensors. Mechanistic investigations disclose that the improved sensor properties are resultant from the paramount surface active sites and high carrier concentration enabled by the oxygen vacancies, while excessive NiO ALD leads to a decreased sensor response due to the formed p-n heterojunctions.

Edge-enriched WS2 nanosheets on carbon nanofibers boosts NO2 detection at room temperature.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) hold great promise for room temperature (RT) NO2 sensors. However, the exposure of the edges of TMDs with high adsorption capability and electronic activity remains a great obstacle to achieve high sensor sensitivity. Herein, we demonstrate a high-performance RT NO2 gas sensor based on WS2 nanosheets/carbon nanofibers (CNFs) composite with abundant intentionally exposed WS2 edges. Few-layer WS2 nanosheets are anchored on CNFs through a hydrothermal process. The approach permits to achieve a coating presenting an optimized active surface area and accessibility of the sensing layers. The exposure of WS2 edges remarkably improves the sensing properties. Consequently, the WS2@CNFs composite exhibits excellent selectivity to NO2 at RT with improved response and much lower detection limit in comparison to the WS2 and CNFs counterparts. Density functional theory (DFT) calculations verify a surprisingly strong NO2 adsorption on WS2 edge sites (adsorption energy 3.40 eV) with a partial charge transfer of 0.394e, while a week adsorption on the basal surface of WS2 (adsorption energy 0.25 eV) with a partial charge transfer of 0.171e. The strategy proposed herein will be instructive to the design of efficient material structures for low-power NO2 sensors with optimized performances.

Unveiling the Electronic Interaction in ZnO/PtO/Pt Nanoarrays for Catalytic Detection of Triethylamine with Ultrahigh Sensitivity.

The detection of harmful volatile organic compounds is of great significance to environmental quality and human health. However, it still remains a challenge to achieve high detection sensitivity at a relatively low temperature. Herein, an ultrasensitive catalytic sensor for the detection of triethylamine (TEA) based on ZnO/PtO/Pt nanoarray thin films was realized. Sensor measurements reveal that the PtO/Pt sensitizer dramatically reduces the working temperature from 195 °C of a pristine ZnO sensor to 125 °C of ZnO/PtO/Pt sensors. The ZnO/PtO/Pt sensors exhibit an extremely high response of 3513 to 50 ppm TEA, which is three orders of magnitude higher than that of pristine ZnO. Meanwhile, an ultralow limit of detection of 8.3 ppb is achieved. The outstanding performances are superior to those in most previous reports on TEA detection. Mechanistic investigations reveal that the outstanding performances are ascribed to the strong electronic interaction between PtO and ZnO and the catalytic spillover effect of Pt.