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Macrophage activation syndrome (MAS) is a rare but life‐threatening disorder that is associated with multiple organ involvement. Here, we described cutaneous granuloma annulare in MAS. This novel histological finding is a reminder to explore the underlying mechanisms of skin involvement in MAS, which may reveal its pathogenesis. We found a novel cutaneous histological characteristic of MAS, namely, granuloma annulare, which has not been reported to date.

Invasive fungal disease (IFD) has high morbidity and mortality, the spectrum of pathogenic fungi and high-risk groups have also changed. Fewer literature focus on the overall incidence of IFD in various departments of general hospitals. Among the adult inpatients in four Chinese tertiary hospitals located in Beijing, Shanghai, Nanning and Nanchang, proven or probable cases of IFD were included prospectively in this study between May 1, 2021 and May 1, 2022. The clinical data were collected and analyzed. A total of 330 patients (342 episodes) with 278 of proven and 64 of probable IFDs were included, including invasive candidiasis (IC) (132, 40.0%), cryptococcosis (64, 19.4%), invasive aspergillosis (IA) (54, 16.4%), Talaromyces marneffei ( TsM ) infection (43, 13.0%), Pneumocystis pneumonia (PCP) (16, 4.8%), mixed fungal infection (10, 3.0%), other mold or yeast infection. 37.9% occurred in elderly patients (age ≥ 65 years). Nosocomial infection accounted for 44.5%, the proportion of nosocomial infection was highest in patients with IC (81.8%). Diabetes (19.7%) was the most common underlying disease. 83.9% of the 342 episodes of IFD had evidence of fungal culture, while the proportion of microscopic examination and histopathology as mycological evidence was 26.9% and 3.5%, respectively. The cumulative all-cause mortality at 180 days after diagnosis of IFD was 38.5%. Age ≥ 65 years old (HR = 1.670, P  = 0.009), ICU (HR = 2.002, P  = 0.001), nosocomial infection (HR = 1.630, P  = 0.016) and diabetes (HR = 1.679, P  = 0.013) were associated with increased death in IFD patients. The prognosis of IFD patients was poor. Doctors should pay attention to nosocomial fungal infection especially in old and diabetes.

Computational super-resolution methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells. Here, we develop zero-shot deconvolution networks (ZS-DeconvNet) that instantly enhance the resolution of microscope images by more than 1.5-fold over the diffraction limit with 10-fold lower fluorescence than ordinary super-resolution imaging conditions, in an unsupervised manner without the need for either ground truths or additional data acquisition. We demonstrate the versatile applicability of ZS-DeconvNet on multiple imaging modalities, including total internal reflection fluorescence microscopy, three-dimensional wide-field microscopy, confocal microscopy, two-photon microscopy, lattice light-sheet microscopy, and multimodal structured illumination microscopy, which enables multi-color, long-term, super-resolution 2D/3D imaging of subcellular bioprocesses from mitotic single cells to multicellular embryos of mouse and C. elegans . The authors introduce ZS-DeconvNet, an unsupervised computational super-resolution method for multiple types of microscopes, that enhances image resolution by more than 1.5 times over the diffraction limit with 10 times lower fluorescence than regular superresolution imaging conditions.

Detection noise significantly degrades the quality of structured illumination microscopy (SIM) images, especially under low-light conditions. Although supervised learning based denoising methods have shown prominent advances in eliminating the noise-induced artifacts, the requirement of a large amount of high-quality training data severely limits their applications. Here we developed a pixel-realignment-based self-supervised denoising framework for SIM (PRS-SIM) that trains an SIM image denoiser with only noisy data and substantially removes the reconstruction artifacts. We demonstrated that PRS-SIM generates artifact-free images with 20-fold less fluorescence than ordinary imaging conditions while achieving comparable super-resolution capability to the ground truth (GT). Moreover, we developed an easy-to-use plugin that enables both training and implementation of PRS-SIM for multimodal SIM platforms including 2D/3D and linear/nonlinear SIM. With PRS-SIM, we achieved long-term super-resolution live-cell imaging of various vulnerable bioprocesses, revealing the clustered distribution of Clathrin-coated pits and detailed interaction dynamics of multiple organelles and the cytoskeleton.

This paper proposes a data-driven analysis method to accurately partition large-scale resting-state functional brain networks from fMRI data. The method is based on a spectral clustering algorithm and combines eigenvector direction selection with Pearson correlation clustering in the spectral space. The method is an improvement on available spectral clustering methods, capable of robustly identifying active brain networks consistent with those from model-driven methods at different noise levels, even at the noise level of real fMRI data. •We introduce a method for partitioning brain into different resting-state networks.•The method is a data-driven analysis method without the need of prior knowledge of brain anatomy.•The method shows improved accuracy compared to current methods.•The method can retain the true locations of brain networks in real fMRI data.

Platinum-based catalysts are promising materials for the propane dehydrogenation (PDH). The Pt sintering and carbon deposition are still the urgent problems to be solved in this system. This paper investigates an investigation of effect of perovskite-type oxide (PTO) lattice confinement on the catalytic performance of Zn(Ni)TiO 3 /SiO 2 supported Pt–Ni bimetallic catalysts for PDH. The supported PTO precursors and derived catalysts were analyzed by XRD, H 2 -TPR, TEM, XPS and TG techniques. The results show that the Pt–Ni alloy nanoparticles (NPs) are formed and highly dispersed on Zn(Ni)TiO 3 /SiO 2 . The optimized Pt loading amount is 0.4 wt%, which enhances the propane conversion to 38.6% and propene selectivity of 96.6%. The superior catalytic performance and anti-sintering and carbon deposition ability of Pt–Ni/Zn(Ni)TiO 3 /SiO 2 catalyst are ascribed to the addition of appropriate Pt amount, which is beneficial to being confined in PTO lattice and building the abundant Pt–Ni alloy sites and moderate Pt–Ni interaction. The unconfined Pt coming from excessive Pt addition and impregnated Pt can result in Pt sintering and carbon formation. Graphic Abstract

Bovine viral diarrhea virus (BVDV) is a major pathogen affecting livestock health in China. However, the current epidemiological status in yaks ( ), particularly in Qinghai Province, remains insufficiently understood. In the present study, a comprehensive serological and molecular investigation of BVDV in yaks was conducted across broad geographic areas of eight administrative regions including Yushu, Guoluo, Huangnan, Hainan, Haidong, Haixi, Haibei, and Xining in Qinghai Province. The results revealed widespread BVDV exposure in Qinghai yak, with an overall antibody prevalence of 84.52% (1158/1370) and substantial herd variation (12.00~98.07%). Active infections were confirmed through antigen detection, revealing prevalence ranging from 0.34% (Haixi) to 4.90% (Huangnan). Genetic characterization identified two circulating subgenotypes: BVDV-1a (n=3) and the predominant BVDV-1u (n=30), with the latter dominating across all regions. These results highlight the endemic circulation of BVDV in Qinghai yak populations and uncover unexpected genetic diversity, emphasizing the need for control measures to mitigate the adverse impacts of BVDV infection in yaks in high-altitude pastoral systems.

Asphalt suffers from a series of aging processes in the natural environment. This is a significant factor in asphalt pavement diseases. Research of the properties of the decay processes in the natural weathering of asphalt will be helpful in distinguishing the characteristics of the various types of asphalt and in the selection of pavement materials. Neat asphalt A70, a styrene-butadiene-styrene- (SBS-) modified asphalt, and crumb-rubber-modified asphalt AR are exposed to outdoor conditions to weather naturally. This process is traced by testing the basic physical properties and the surface free energy of asphalts, using the sessile drop method. Results illustrate that the basic physical properties of asphalt change significantly during the natural weathering process and that the rubber asphalt has the superior aging resistance, while the neat asphalt A70 has a high aging susceptibility. Furthermore, the presence of the SBS and rubber-powder modifiers transforms the change trend of the surface free energy of neat asphalt. The adhesion work between aggregate and asphalt can be used to quantitatively evaluate the adhesive properties between them. Meanwhile, the presence of moisture between the asphalt and aggregate changes cohesive failure into adhesive failure.

ObjectiveSepsis related injury has gradually become the main cause of death in non-cardiac patients in intensive care units, but the underlying pathological and physiological mechanisms remain unclear. The Third International Consensus Definitions for Sepsis and Septic Shock (SEPSIS-3) definition emphasized organ dysfunction caused by infection. Neutrophil extracellular traps (NETs) can cause inflammation and have key roles in sepsis organ failure; however, the role of NETs-related genes in sepsis is unknown. Here, we sought to identify key NETs-related genes associate with sepsis.MethodsDatasets GSE65682 and GSE145227, including data from 770 patients with sepsis and 54 healthy controls, were downloaded from the GEO database and split into training and validation sets. Differentially expressed genes (DEGs) were identified and weighted gene co-expression network analysis (WGCNA) performed. A machine learning approach was applied to identify key genes, which were used to construct functional networks. Key genes associated with diagnosis and survival of sepsis were screened out. Finally, mouse and human blood samples were collected for RT-qPCR verification and flow cytometry analysis. Multiple organs injury, apoptosis and NETs expression were measured to evaluated effects of sulforaphane (SFN).ResultsAnalysis of the obtained DEGs and WGCNA screened a total of 3396 genes in 3 modules, and intersection of the results of both analyses with 69 NETs-related genes, screened out seven genes ( S100A12 , SLC22A4 , FCAR , CYBB , PADI4 , DNASE1 , MMP9 ) using machine learning algorithms. Of these, CYBB and FCAR were independent predictors of poor survival in patients with sepsis. Administration of SFN significantly alleviated murine lung NETs expression and injury, accompanied by whole blood CYBB mRNA level.ConclusionCYBB and FCAR may be reliable biomarkers of survival in patients with sepsis, as well as potential targets for sepsis treatment. SFN significantly alleviated NETs-related organs injury, suggesting the therapeutic potential by targeting CYBB in the future.

Mushroom’s specialized secondary metabolites possess important pharmacological activities, but their biosynthetic pathway elucidation is extremely challenging, not to mention reprogramming of their biosynthetic networks to target metabolites. By taking Ganoderma lucidum , a famous traditional medicinal mushroom, as a lead example, here we decoded the biosynthetic networks of type II ganoderic acids (TIIGAs), a group of its main bioactive metabolites by studying the coordinated gene expression in G. lucidum , identifying endogenous or heterologous enzymes capable of C22 hydroxylation, configuration conversion of C3 hydroxyl group, and acetylation on C3, C15 and C22 hydroxyl groups. Notably, we revealed the catalytic mechanism of the C22 hydroxylase CYP512W6, and an unexpected bifunctional acetyltransferase GlAT that is required to transfer acetyl groups to C15 and C22. Using a fluorescence-guided integration method, we achieved efficient biosynthesis of significant TIIGAs applicable to industrial fermentation. After introducing all the identified enzymes to baker’s yeast, we observed that biosynthesis of downstream TIIGAs was severely impeded, and dredged the metabolic block by temporally regulating the expression of acetyltransferases. By reprogramming of the biosynthetic networks of TIIGAs, we were able to produce over 30 TIIGAs, exhibiting 1–4 orders of magnitude higher titers or efficiencies than those from farmed mushrooms. The work enables the access to valuable TIIGAs, facilitates their widespread application, and sheds light on research of other mushroom products.