Metabolites isolated from Penicillium HDS-Z-1E, an endophytic fungal strain isolated from Taxus cuspidata and their activation effect of catalase.

Objective: To study the compounds isolated from Penicillium HDS-Z-1E, an endophytic fungal strain isolated from Taxus cuspidata and their activation effect of catalase (CAT). Methods: The chemical constituents were isolated from Penicillium HDS-Z-1E, by using silica gel, Sephadex LH-20 and HPLC. The structural elucidations of five metabolites were elucidated on the basis of spectroscopic including 1H-NMR, 13C-NMR, HMBC and HSQC. Their activation sites of catalase have been investigated by molecular docking. Results: Five metabolites, compounds (1-5) were isolated from Penicillium HDS-Z-1E and identified as 4-hydroxy-4-methyltetrahydro-2H-pyran-2-one (1), 4-hydroxymethyl-5, 6-dihydro-pyran-2-one (2), 5, 6-dihydro-2-oxo-2H-pyran-4-carboxylic (3), N-acetyl-hydrazinobenzoic acid (4), and methyl 2-(2, 5-dihydroxyphenyl) acetate (5). Conclusion: Compound 3 is a new compound. Compounds 3 and 4 may have potential activators of catalase, providing a theoretical basis for the development of CAT activators.

Enhancing high-efficiency breeding and microbial microdroplet cultivation techniques for Ganoderma lucidum.

Ganoderma lucidum is known for its bioactive compounds, such as polysaccharides and triterpenoids, which are crucial in food and medicine. However, liquid fermentation encounters challenges in terms of strain differentiation and stability. In this research, we employed atmospheric room temperature plasma mutation and a microbial microdroplet culture system to identify strains with enhanced biomass and triterpenoid production. The three mutant strains, YB05, YB09, and YB18, exhibited accelerated growth rates and antagonized the initial strain G0023 more effectively than the controls. Notably, YB18 displayed the fastest growth, with a 17.25% increase in colony radius. Shake flask cultivation demonstrated that, compared with the initial strain, YB05 and YB18 had 26.33% and 17.85% greater biomass, respectively. Moreover, the triterpenoid production of YB05 and YB18 surpassed that of the control by 32.10% and 15.72%, respectively, as confirmed by colorimetric detection. Importantly, these mutant strains remained stable for five generations. This study revealed a comprehensive screening system utilizing atmospheric pressure, room temperature plasma mutation technology and microbial droplet cultivation. This innovative approach offers a promising pathway for obtaining advantageous Ganoderma strains for liquid fermentation. The methodology of atmospheric room temperature plasma mutation and microbial microdroplet culture systems is detailed for better comprehension.

Translation, cultural adaptation, and validation of Numerical Pain Rating Scale and Global Rating of Change in Tibetan musculoskeletal trauma patients.

Tibetan-speaking patients seeking care in predominantly Mandarin-speaking healthcare settings frequently face communication barriers, leading to potential disparities and difficulties in accessing care. To address this issue, we translated, culturally adapted, and validated the Numerical Pain Rating Scale (NPRS) and the Global Rating of Change (GRoC) into Tibetan (NPRS-Tib and GRoC-Tib), aiming to facilitate cross-linguistic and cross-cultural interactions while examining potential challenges in the adaptation process. Using standard translation-backward translation methods, expert review, pilot testing, and validation through a cross-sectional study with a short-term longitudinal component, we engaged 100 Tibetan patients with musculoskeletal trauma for psychometric validation, including 37 women (aged 22-60 years, mean age 39.1 years). The NPRS-Tib and GRoC-Tib exhibited outstanding psychometric properties, with an Intraclass Correlation Coefficient (ICC) of 0.983 for NPRS-Tib indicating superb test-retest reliability, and expert review confirming good content validity for both instruments. A Spearman's correlation coefficient (Rho) of -0.261 (P = 0.0087) revealed a significant, albeit weak, correlation between changes in NPRS-Tib scores and GRoC-Tib scores. The adaptation process also presented notable challenges, including translation discrepancies from translators' diverse backgrounds and levels of expertise, ambiguity in scale options, and the lack of established tools for criterion validity assessment in Tibetan.

One-Step Multiview Clustering via Adaptive Graph Learning and Spectral Rotation.

In graph based multiview clustering methods, the ultimate partition result is usually achieved by spectral embedding of the consistent graph using some traditional clustering methods, such as k -means. However, optimal performance will be reduced by this multistep procedure since it cannot unify graph learning with partition generation closely. In this article, we propose a one-step multiview clustering method through adaptive graph learning and spectral rotation (AGLSR). For every view, AGLSR adaptively learns affinity graphs to capture similar relationships of samples. Then, a spectral embedding is designed to take advantage of the potential feature space shared by different views. In addition, AGLSR utilizes a spectral rotation strategy to obtain the discrete clustering labels from the learned spectral embeddings directly. An effective updating algorithm with proven convergence is derived to optimize the optimization problem. Sufficient experiments on benchmark datasets have clearly demonstrated the effectiveness of the proposed method in six metrics. The code of AGLSR is uploaded at https://github.com/tangchuan2000/AGLSR.

Lipid responses to perfluorooctane sulfonate exposure for multiple rat organs.

Perfluorooctane sulfonate (PFOS) is a persistent chemical that has long been a threat to human health. However, the molecular effects of PFOS on various organs are not well studied. In this study, male Sprague-Dawley rats were treated with various doses of PFOS through gavage for 21 days. Subsequently, the liver, lung, heart, kidney, pancreas, testis, and serum of the rats were harvested for lipid analysis. We applied a focusing lipidomic analytical strategy to identify key lipid responses of phosphorylcholine-containing lipids, including phosphatidylcholines and sphingomyelins. Partial least squares discriminant analysis revealed that the organs most influenced by PFOS exposure were the liver, kidney, and testis. Changes in the lipid profiles of the rats indicated that after exposure, levels of diacyl-phosphatidylcholines and 22:6-containing phosphatidylcholines in the liver, kidney, and testis of the rats decreased, whereas the level of 20:3-containing phosphatidylcholines increased. Furthermore, levels of polyunsaturated fatty acids-containing plasmenylcholines decreased. Changes in sphingomyelin levels indicated organ-dependent responses. Decreased levels of sphingomyelins in the liver, nonmonotonic dose responses in the kidney, and irregular responses in the testis after PFOS exposure are observed. These lipid responses may be associated with alterations pertaining to phosphatidylcholine synthesis, fatty acid metabolism, membrane properties, and oxidative stress in the liver, kidney, and testis. Lipid responses in the liver could have contributed to the observed increase in liver to body weight ratios. The findings suggest potential toxicity and possible mechanisms associated with PFOS in multiple organs.

Impact of occupational noise exposure on the hearing level in hospital staffs: a longitudinal study.

The study aimed to evaluate the impact of occupational noise on hearing loss among healthcare workers using audiometry. A longitudinal study was conducted with a six-month follow-up period in a hospital with 21 participants, divided into high-noise-exposure (HNE) and low-noise-exposure (LNE) groups. Mean noise levels were higher in the HNE group (70.4 ± 4.5 dBA), and hearing loss was measured using pure-tone audiometry at baseline and follow-up. The HNE group had significantly higher mean threshold levels at frequencies of 0.25 kHz, 0.5 kHz, 4.0 kHz, and an average of 0.5, 1, 2, and 4 kHz (all p-values < 0.05) after the follow-up period. After adjusting for confounding factors, the HNE group had significantly higher hearing loss levels at 0.25 kHz, 0.5 kHz, and average frequencies of 0.5, 1, 2, and 4 kHz compared to the LNE group at the second measurement. Occupational noise levels above 65 dBA over six months were found to cause significant threshold changes at frequencies of 0.25 kHz, 0.5 kHz, and an average of 0.5-4.0 kHz. This study highlights the risk of noise-induced hearing loss among healthcare workers and emphasizes the importance of implementing effective hearing conservation programs in the workplace. Regular monitoring and assessment of noise levels and hearing ability, along with proper use of personal protective equipment, are crucial steps in mitigating the impact of occupational noise exposure on the hearing health of healthcare workers.

Graphene Failure under MPa: Nanowear of Step Edges Initiated by Interfacial Mechanochemical Reactions.

The low wear resistance of macroscale graphene coatings does not match the ultrahigh mechanical strength and chemical inertness of the graphene layer itself; however, the wear mechanism responsible for this issue at low mechanical stress is still unclear. Here, we demonstrate that the susceptibility of the graphene monolayer to wear at its atomic step edges is governed by the mechanochemistry of frictional interfaces. The mechanochemical reactions activated by chemically active SiO2 microspheres result in atomic attrition rather than mechanical damage such as surface fracture and folding by chemically inert diamond tools. Correspondingly, the threshold contact stress for graphene edge wear decreases more than 30 times to the MPa level, and mechanochemical wear can be described well with the mechanically assisted Arrhenius-type kinetic model, i.e., exponential dependence of the removal rate on the contact stress. These findings provide a strategy for improving the antiwear of graphene-based materials by reducing the mechanochemical interactions at tribological interfaces.

Endoscopic Versus Microscopic Type I Tympanoplasty: An Updated Systematic Review and Meta-analysis.

OBJECTIVE: Our objective was to perform a systematic review and meta-analysis comparing the clinical outcomes after endoscopic and microscopic type I tympanoplasty. STUDY DESIGN: Randomized controlled trials, two-arm prospective studies, and retrospective studies were included. SETTING: Medline, Cochrane, EMBASE, and Google Scholar databases were searched until March 1, 2022 using the combinations of search terms: "endoscopic," "microscopic," and "tympanoplasty." METHODS: Two independent reviewers utilized the abovementioned search strategy to identify eligible studies. If any uncertainty existed regarding eligibility, a third reviewer was consulted. Primary outcome measures were graft success rate, air-bone gap (ABG) improvement, and operative time. Secondary outcomes were the rate of need for canalplasty, the proportion of self-rated excellent cosmetic results, and pain visual analog scale (VAS). RESULTS: Forty-three studies enrolled a total of 3712 patients who were undergoing type I tympanoplasty and were finally included. The pooled result showed endoscopic approach was significantly associated with shorter operative time (difference in means: -20.021, 95% confidence interval [CI]: -31.431 to -8.611), less need for canalplasty (odds ratio [OR]: 0.065, 95% CI: 0.026-0.164), more self-rated excellent cosmetic results (OR: 87.323, 95% CI: 26.750-285.063), and lower pain VAS (difference in means: -2.513, 95% CI: -4.737 to -0.228). No significant differences in graft success rate or ABG were observed between the two procedures. CONCLUSION: Endoscopic type I tympanoplasty provides a similar graft success rate, improvement in ABG, and reperforation rate to microscopic tympanoplasty with a shorter operative time, better self-rated cosmetic results, and less pain. Unless contraindicated, the endoscopic approach should be the procedure of choice in type I tympanoplasty.

Nanoscale Wear Triggered by Stress-Driven Electron Transfer.

Wear of sliding contacts causes device failure and energy costs; however, the microscopic principle in activating wear of the interfaces under stress is still open. Here, the typical nanoscale wear, in the case of silicon against silicon dioxide, is investigated by single-asperity wear experiments and density functional theory calculations. The tests demonstrate that the wear rate of silicon in ambient air increases exponentially with stress and does not obey classical Archard's law. Series calculations of atomistic wear reactions generally reveal that the mechanical stress linearly drives the electron transfer to activate the sequential formation and rupture of interfacial bonds in the atomistic wear process. The atomistic wear model is thus resolved by combining the present stress-driven electron transfer model with Maxwell-Boltzmann statistics. This work may advance electronic insights into the law of nanoscale wear for understanding and controlling wear and manufacturing of material surfaces.

Multi-view subspace clustering via adaptive graph learning and late fusion alignment.

Multi-view subspace clustering has attracted great attention due to its ability to explore data structure by utilizing complementary information from different views. Most of existing methods learn a sample representation coefficient matrix or an affinity graph for each single view, then the final clustering result is obtained from the spectral embedding of a consensus graph using certain traditional clustering techniques, such as k-means. However, clustering performance will be degenerated if the early fusion of partitions cannot fully exploit relationships between all samples. Different from existing methods, we propose a multi-view subspace clustering method via adaptive graph learning and late fusion alignment (AGLLFA). For each view, AGLLFA learns an affinity graph adaptively to capture the similarity relationship among samples. Moreover, a spectral embedding learning term is designed to exploit the latent feature space of different views. Furthermore, we design a late fusion alignment mechanism to generate an optimal clustering partition by fusing view-specific partitions obtained from multiple views. An alternate updating algorithm with validated convergence is developed to solve the resultant optimization problem. Extensive experiments on several benchmark datasets are conducted to illustrate the effectiveness of the proposed method when compared with other state-of-the-art methods. The demo code of this work is publicly available at https://github.com/tangchuan2000/AGLLFA.

Socioeconomic factors, perceived stress, and social support effect on neonatal nurse burnout in China: a cross-sectional study.

BACKGROUND: Neonatal nurses' working environments are highly stressful, and burnout is common. This study examines the effect of socioeconomic factors, perceived stress, and social support on neonatal nurse burnout. METHODS: A total of 311 neonatal nurses participated in this study. They were administered a validated Maslach Burnout Inventory. The study employed a 14-item perceived stress scale (PSS-14) and a social support rate scale (SSRS) to examine stress, socioeconomic factors, and lifestyles. RESULTS: Of the neonatal nurses, 40.19% had burnout, 89.60% had mild burnout, and 10.40% had moderate burnout; no neonatal nurse experienced severe burnout. Young nurses and those with low technical skills, poor interpersonal relationships, irregular diet, and insufficient rest were exposed to burnout (all p < 0.05).Most burnout nurses experienced moderate-severe perceived stress, and their PSS-14 scores were higher (all p < 0.05).The scores for objective social support, subjective social support, utilization of social support, total SSRS scores, and the level of social support were all lower in burnout nurses (all p < 0.05). Perceived stress was correlated positively and significantly with emotional exhaustion and personal accomplishment (all p < 0.05). Social support correlated significantly with and reduced personal accomplishments (p < 0.05). Age, poor interpersonal relationships, perceived stress, and social support were all independent factors associated with neonatal nurse burnout (all p < 0.05). CONCLUSION: The prevalence of burnout in neonatal nurses was higher than average. Socioeconomic factors, higher perceived stress, and lower social support contribute to neonatal nurse burnout. Nursing managers should pay attention to socioeconomic factors, perceived stress, and social support among neonatal nurses and employ strategies to reduce neonatal nurse burnout.

Understanding and Preventing Lubrication Failure at the Carbon Atomic Steps.

Two-dimensional (2D) lamellar materials are normally capable of rendering super-low friction, wear protection, and adhesion reduction in nanoscale due to their ultralow shear strength between two basal plane surfaces. However, high friction at step edges prevents the 2D materials from achieving super-low friction in macroscale applications and eventually leads to failure of lubrication performance. Here, taking graphene as an example, the authors report that not all step edges are detrimental. The armchair (AC) step edges are found to have only a minor topographic effect on friction, while the zigzag (ZZ) edges cause friction two orders of magnitude larger than the basal plane. The AC step edge is less reactive and thus more durable. However, the ZZ structure prevails when step edges are produced mechanically, for example, through mechanical exfoliation or grinding of graphite. The authors found a way to make the high-friction ZZ edge superlubricious by reconstructing the (6,6) hexagon structure to the (5,7) azulene-like structure through thermal annealing in an inert gas environment. This will facilitate the realization of graphene-based superlubricity over a wide range of industrial applications in which avoiding the involvement of step edges is difficult.

The key technologies of Ganoderma lucidum liquid spawn preparation and scale expansion.

Ganoderma lucidum possesses a variety of valuable pharmacological activities, and it has long been used to prevent and treat various human diseases. Up to now, far too little attention has been paid to the liquid spawn of G. lucidum, and the development of the G. lucidum industry is constrained by them. This work aimed to study the key technologies and scale-up preparation of G. lucidum liquid spawn, to achieve large-scale preparation of liquid spawn and solve the problem of unstable quality of G. lucidum. The plate culture, primary shake flask culture, shake flask preparation, and fermentor preparation of G. lucidum liquid spawn were explored in the process of liquid fermentation. The results showed that plate broth volume significantly affected mycelial growth rate. Biomass in the primary shake flask culture is significantly influenced by the picking position of plate mycelium. An artificial neural network coupled with a genetic algorithm was used for carbon and nitrogen sources concentration optimization to increase biomass and substrate utilization. The optimized parameter combination is as follows: glucose, 14.5 g L-1; yeast extract powder, 8.5 g L-1. Under this condition, the biomass (9.82 g L-1) and biomass on reducing sugar (0.79 g g-1) increased by 18.03% and 27.41% compared to the control, respectively. The metabolic activity of liquid spawn prepared by different fermentation scales was diverse, and the liquid spawn prepared by the fermentor has better activity. Conceivably, the liquid spawn process can more conducive be applied to large-scale industrial production.

TCM as adjunctive therapy improves risks of respiratory hospitalizations in persons with type 2 diabetes: A retrospective cohort study.

Patients with type 2 diabetes are at a higher risk of chronic obstructive pulmonary disease (COPD) and asthma than the general population. In addition, emerging evidence suggests that traditional Chinese medicine (TCM) might be beneficial for patients with type 2 diabetes. We investigated whether TCM use was associated with a reduced risk of respiratory hospitalizations in patients with type 2 diabetes. Conducting a retrospective cohort study, we used data retrieved from the NDCMP database. Among 56,035 patients, 5226 were classified as TCM users; 50,809 were classified as TCM nonusers. Both groups were analyzed until the end of 2011 to examine the incidence of respiratory hospitalizations by using a Cox proportional hazards model to evaluate effects of TCM use on respiratory hospitalizations. During the 6-year study follow-up period, the incidence density rates of COPD- and asthma-related hospitalization were estimated to be 13.03 and 4.47 per 10,000 patient-years for TCM nonusers and 10.08 and 3.28 per 10,000 patient-years for TCM users, respectively. The HR of COPD-related hospitalization in TCM users was 0.88 (95% CI = 0.79-0.99); and the HR of asthma-related hospitalization in TCM users was 0.81 (95% CI = 0.66-1.00). Stratified analyses revealed that effects of TCM use were stronger among individuals who had diabetes for <3 years. As a part of Integrative Medicine, our study results demonstrate that TCM use was associated with a significant reduced risk of respiratory hospitalizations, especially in patients with diabetes for <3 years.

Layer-Dependent Nanowear of Graphene Oxide.

The mechanical performance and surface friction of graphene oxide (GO) were found to inversely depend on the number of layers. Here, we demonstrate the non-monotonic layer-dependence of the nanowear resistance of GO nanosheets deposited on a native silicon oxide substrate. As the thickness of GO increases from ∼0.9 nm to ∼14.5 nm, the nanowear resistance initially demonstrated a decreasing and then an increasing tendency with a critical number of layers of 4 (∼3.6 nm in thickness). This experimental tendency corresponds to a change of the underlying wear mode from the overall removal to progressive layer-by-layer removal. The phenomenon of overall removal disappeared as GO was deposited on an H-DLC substrate with a low surface energy, while the nanowear resistance of thicker GO layers was always higher. Combined with density functional theory calculations, the wear resistance of few-layer GO was found to correlate with the substrate's surface energy. This can be traced back to substrate-dependent adhesive strengths of GO, which correlated with the GO thickness originating from differences in the interfacial charge transfer. Our study proposes a strategy to improve the antiwear properties of 2D layered materials by tuning their own thickness and/or the interfacial interaction with the underlying substrate.

Heteroprotein complex between soy protein isolate and lysozyme: Protein conformation, lysozyme activity, and structural characterization.

Heteroprotein complexes are formed by electrostatic interactions of oppositely charged proteins in a purely aqueous environment. Understanding the relationship between their structural and functional properties will contribute to their tailor-made applications. Therefore, this study investigated the protein conformation, assembling structure, and enzyme activity of soy protein isolate/lysozyme (SPI/LYS) complexes at mass ratios of 2:1 (soluble complex) and 1:1.3 (stoichiometric ratio). Electrostatic complexation increased the surface hydrophobicity of complexes. Their surface hydrophobicity decreased with increasing NaCl concentrations and reached the theoretical values at the critical salt concentration of 200 mM NaCl. Electrostatic complexation did not decrease the LYS activity (∼43,000 units/mg). SPI/LYS complexes exhibited flocculated structures in which the two proteins were unevenly distributed; these were typical amorphous complexes. High dilution disassembled these complexes over 5 µm into particles of ∼100 nm, and NaCl reduced the size of these particles. Immobilized water was detected in the complexes formed by particle flocculation.

Adaptive Discriminative Regions Learning Network for Remote Sensing Scene Classification.

As an auxiliary means of remote sensing (RS) intelligent interpretation, remote sensing scene classification (RSSC) attracts considerable attention and its performance has been improved significantly by the popular deep convolutional neural networks (DCNNs). However, there are still several challenges that hinder the practical applications of RSSC, such as complex composition of land cover, scale-variation of objects, and redundant and noisy areas for scene classification. In order to mitigate the impact of these issues, we propose an adaptive discriminative regions learning network for RSSC, referred as ADRL-Net briefly, which locates discriminative regions effectively for boosting the performance of RSSC by utilizing a novel self-supervision mechanism. Our proposed ADRL-Net consists of three main modules, including a discriminative region generator, a region discriminator, and a region scorer. Specifically, the discriminative region generator first generates some candidate regions which could be informative for RSSC. Then, the region discriminator evaluates the regions generated by region generator and provides feedback for the generator to update the informative regions. Finally, the region scorer makes prediction scores for the whole image by using the discriminative regions. In such a manner, the three modules of ADRL-Net can cooperate with each other and focus on the most informative regions of an image and reduce the interference of redundant regions for final classification, which is robust to the complex scene composition, object scales, and irrelevant information. In order to validate the efficacy of the proposed network, we conduct experiments on four widely used benchmark datasets, and the experimental results demonstrate that ADRL-Net consistently outperforms other state-of-the-art RSSC methods.

Polyketides with anti-inflammatory activity isolated from Rhodiola tibetica endophytic fungus Penicillium sp. HJT-A-10.

Seven undescribed polyketide compounds (1-4, 9-11) and six known polyketide compounds (5-8,12, 13) were isolated from Rhodiola tibetica endophytic Penicillium sp. HJT-A-10. The structural of seven undescribed polyketides metabolites were established on the basis of spectroscopic methods. The results of anti-inflammatory activity showed that compounds 1-8，10-13 had significant inhibitory effects on LPS-induced NO production in RAW 264.7 cells.

Blunt dopamine transmission due to decreased GDNF in the PFC evokes cognitive impairment in Parkinson's disease.

Studies have found that the absence of glial cell line-derived neurotrophic factor may be the primary risk factor for Parkinson's disease. However, there have not been any studies conducted on the potential relationship between glial cell line-derived neurotrophic factor and cognitive performance in Parkinson's disease. We first performed a retrospective case-control study at the Affiliated Hospital of Xuzhou Medical University between September 2018 and January 2020 and found that a decreased serum level of glial cell line-derived neurotrophic factor was a risk factor for cognitive disorders in patients with Parkinson's disease. We then established a mouse model of Parkinson's disease induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and analyzed the potential relationships among glial cell line-derived neurotrophic factor in the prefrontal cortex, dopamine transmission, and cognitive function. Our results showed that decreased glial cell line-derived neurotrophic factor in the prefrontal cortex weakened dopamine release and transmission by upregulating the presynaptic membrane expression of the dopamine transporter, which led to the loss and primitivization of dendritic spines of pyramidal neurons and cognitive impairment. In addition, magnetic resonance imaging data showed that the long-term lack of glial cell line-derived neurotrophic factor reduced the connectivity between the prefrontal cortex and other brain regions, and exogenous glial cell line-derived neurotrophic factor significantly improved this connectivity. These findings suggested that decreased glial cell line-derived neurotrophic factor in the prefrontal cortex leads to neuroplastic degeneration at the level of synaptic connections and circuits, which results in cognitive impairment in patients with Parkinson's disease.