Lateral Inhibition in Cell Specification Mediated by Mechanical Signals Modulating TAZ Activity.

Cell fate specification by lateral inhibition typically involves contact signaling through the Delta-Notch signaling pathway. However, whether this is the only signaling mode mediating lateral inhibition remains unclear. Here we show that in zebrafish oogenesis, a group of cells within the granulosa cell layer at the oocyte animal pole acquire elevated levels of the transcriptional coactivator TAZ in their nuclei. One of these cells, the future micropyle precursor cell (MPC), accumulates increasingly high levels of nuclear TAZ and grows faster than its surrounding cells, mechanically compressing those cells, which ultimately lose TAZ from their nuclei. Strikingly, relieving neighbor-cell compression by MPC ablation or aspiration restores nuclear TAZ accumulation in neighboring cells, eventually leading to MPC re-specification from these cells. Conversely, MPC specification is defective in taz-/- follicles. These findings uncover a novel mode of lateral inhibition in cell fate specification based on mechanical signals controlling TAZ activity.

Single-cell landscape of immunological responses in patients with COVID-19.

In coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of 5 healthy donors and 13 patients with COVID-19, including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in patients with COVID-19 showed a strong interferon-α response and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ effector-GNLY (granulysin), CD8+ effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during disease progression.

A hybrid photocatalytic system enables direct glucose utilization for methanogenesis.

Integration of methanogenic archaea with photocatalysts presents a sustainable solution for solar-driven methanogenesis. However, maximizing CH4 conversion efficiency remains challenging due to the intrinsic energy conservation and strictly restricted substrates of methanogenic archaea. Here, we report a solar-driven biotic-abiotic hybrid (biohybrid) system by incorporating cadmium sulfide (CdS) nanoparticles with a rationally designed methanogenic archaeon Methanosarcina acetivorans C2A, in which the glucose synergist protein and glucose kinase, an energy-efficient route for glucose transport and phosphorylation from Zymomonas mobilis, were implemented to facilitate nonnative substrate glucose for methanogenesis. We demonstrate that the photo-excited electrons facilitate membrane-bound electron transport chain, thereby augmenting the Na+ and H+ ion gradients across membrane to enhance adenosine triphosphate (ATP) synthesis. Additionally, this biohybrid system promotes the metabolism of pyruvate to acetyl coenzyme A (AcCoA) and inhibits the flow of AcCoA to the tricarboxylic acid (TCA) cycle, resulting in a 1.26-fold augmentation in CH4 production from glucose-derived carbon. Our results provide a unique strategy for enhancing methanogenesis through rational biohybrid design and reprogramming, which gives a promising avenue for sustainably manufacturing value-added chemicals.

LIM domain only 7 negatively controls nonalcoholic steatohepatitis in the setting of hyperlipidemia.

BACKGROUND AND AIMS: Hyperlipidemia has been extensively recognized as a high-risk factor for NASH; however, clinical susceptibility to NASH is highly heterogeneous. The key controller(s) of NASH susceptibility in patients with hyperlipidemia has not yet been elucidated. Here, we aimed to reveal the key regulators of NASH in patients with hyperlipidemia and to explore its role and underlying mechanisms. APPROACH AND RESULTS: To identify the predominant suppressors of NASH in the setting of hyperlipidemia, we collected liver biopsy samples from patients with hyperlipidemia, with or without NASH, and performed RNA-sequencing analysis. Notably, decreased Lineage specific Interacting Motif domain only 7 (LMO7) expression robustly correlated with the occurrence and severity of NASH. Although overexpression of LMO7 effectively blocked hepatic lipid accumulation and inflammation, LMO7 deficiency in hepatocytes greatly exacerbated diet-induced NASH progression. Mechanistically, lysine 48 (K48)-linked ubiquitin-mediated proteasomal degradation of tripartite motif-containing 47 (TRIM47) and subsequent inactivation of the c-Jun N-terminal kinase (JNK)/p38 mitogen-activated protein kinase (MAPK) cascade are required for the protective function of LMO7 in NASH. CONCLUSIONS: These findings provide proof-of-concept evidence supporting LMO7 as a robust suppressor of NASH in the context of hyperlipidemia, indicating that targeting the LMO7-TRIM47 axis is a promising therapeutic strategy for NASH.

Diagnostic Potential of Serum Glycome Analysis in Lung Cancer: A Glycopattern Study.

Lung cancer is the leading cause of cancer-related death, with high morbidity and mortality rates due to the lack of reliable methods for diagnosing lung cancer at an early stage. Low-dose computed tomography can help detect abnormal areas in the lungs, but only 16% of cases are diagnosed early. Tests for lung cancer markers are often employed to determine genetic expression or mutations in lung carcinogenesis. Serum glycome analysis is a promising new method for early lung cancer diagnosis as glycopatterns exhibit significant differences in lung cancer patients. In this study, we employed a solid-phase chemoenzymatic method to systematically compare glycopatterns in benign cases, adenocarcinoma before and after surgery, and advanced stages of adenocarcinoma. Our findings indicate that serum high-mannose levels are elevated in both benign cases and adenocarcinoma, while complex N-glycans, including fucose and 2,6-linked sialic acid, are downregulated in the serum. Subsequently, we developed an algorithm that utilizes 16 altered N-glycans, 7 upregulated and 9 downregulated, to generate a score based on their intensity. This score can predict the stages of cancer progression in patients through glycan characterization. This methodology offers a potential means of diagnosing lung cancer through serum glycome analysis.

Ultrasound-targeted microbubble destruction facilitates cartilage repair through increased the migration of mesenchymal stem cells via HIF-1α-mediated glycolysis pathway in rats.

OBJECTIVE: Mesenchymal stem cells (MSCs) can treat osteoarthritis (OA), but their therapeutic efficacy is poor to date due to low migration efficiency. This study aimed to determine whether ultrasound-targeted microbubble destruction (UTMD) could ameliorate cartilage repair efficiency through facilitating the migration of MSCs via hypoxia-inducible factor-1α (HIF-1α)-mediated glycolysis regulatory pathway in OA model rats. METHODS: OA rats were treated with MSCs alone or in combination with UTMD, respectively, for 4 weeks. Cartilage histopathology, MSCs migration efficiency, von Frey fiber thresholds, and the expression levels of collagen II and MMP-13 were measured. Further, MSCs were extracted from the bone marrow of rats, cocultured with osteoarthritic chondrocytes, transfected to siRNA-HIF-1α, and subjected to UTMD for 4 days. Glucose consumption, lactate production, and cell migration efficiency were assessed. The protein expression levels of HIF-1α, HK2, PKM2, and GLUT1 were measured, respectively. RESULTS: In OA rat model, NC-MSCs + UTMD improved migration efficiency, increased collagen II expression, decreased MMP-13 expression, and delayed osteoarthritis progression. Silencing HIF-1α attenuated the effects induced by UTMD. In vitro, UTMD led to increases in MSC activity and migration, glucose consumption, lactate production, and the protein expression of HIF-1α, HK2, PKM2, and GLUT1 expression, all of which were reversed upon HIF-1α silencing. CONCLUSION: UTMD enhances MSCs migration and improves cartilage repair efficiency through the HIF-1α-mediated glycolytic regulatory pathway, providing a novel therapy strategy for knee osteoarthritis.

Blue valorization of lignin-derived monomers via reprogramming marine bacterium Roseovarius nubinhibens.

Biological valorization of lignin, the second most abundant biopolymer on Earth, is an indispensable sector to build a circular economy and net-zero future. However, lignin is recalcitrant to bioupcycling, demanding innovative solutions. We report here the biological valorization of lignin-derived aromatic carbon to value-added chemicals without requesting extra organic carbon and freshwater via reprogramming the marine Roseobacter clade bacterium Roseovarius nubinhibens. We discovered the unusual advantages of this strain for the oxidation of lignin monomers and implemented a CRISPR interference (CRISPRi) system with the lacI-Ptrc inducible module, nuclease-deactivated Cas9, and programmable gRNAs. This is the first CRISPR-based regulatory system in R. nubinhibens, enabling precise and efficient repression of genes of interest. By deploying the customized CRISPRi, we reprogrammed the carbon flux from a lignin monomer, 4-hydroxybenzoate, to achieve the maximum production of protocatechuate, a pharmaceutical compound with antibacterial, antioxidant, and anticancer properties, with minimal carbon to maintain cell growth and drive biocatalysis. As a result, we achieved a 4.89-fold increase in protocatechuate yield with a dual-targeting CRISPRi system, and the system was demonstrated with real seawater. Our work underscores the power of CRISPRi in exploiting novel microbial chassis and will accelerate the development of marine synthetic biology. Meanwhile, the introduction of a new-to-the-field lineage of marine bacteria unveils the potential of blue biotechnology leveraging resources from the ocean.IMPORTANCEOne often overlooked sector in carbon-conservative biotechnology is the water resource that sustains these enabling technologies. Similar to the "food-versus-fuel" debate, the competition of freshwater between human demands and bioproduction is another controversial issue, especially under global water scarcity. Here, we bring a new-to-the-field lineage of marine bacteria with unusual advantages to the stage of engineering biology for simultaneous carbon and water conservation. We report the valorization of lignin monomers to pharmaceutical compounds without requesting extra organic substrate (e.g., glucose) or freshwater by reprogramming the marine bacterium Roseovarius nubinhibens with a multiplex CRISPR interference system. Beyond the blue lignin valorization, we present a proof-of-principle of leveraging marine bacteria and engineering biology for a sustainable future.

Nuclear Magnetic Resonance-Based Metabolomics and Risk of CKD.

RATIONALE & OBJECTIVE: Chronic kidney disease (CKD) leads to lipid and metabolic abnormalities, but a comprehensive investigation of lipids, lipoprotein particles, and circulating metabolites associated with the risk of CKD has been lacking. We examined the associations of nuclear magnetic resonance (NMR)-based metabolomics data with CKD risk in the UK Biobank study. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: A total of 91,532 participants in the UK Biobank Study without CKD and not receiving lipid-lowering therapy. EXPOSURE: Levels of metabolites including lipid concentration and composition within 14 lipoprotein subclasses, as well as other metabolic biomarkers were quantified via NMR spectroscopy. OUTCOME: Incident CKD identified using ICD codes in any primary care data, hospital admission records, or death register records. ANALYTICAL APPROACH: Cox proportional hazards regression models were used to estimate hazard ratios and 95% confidence intervals. RESULTS: We identified 2,269 CKD cases over a median follow-up period of 13.1 years via linkage with the electronic health records. After adjusting for covariates and correcting for multiple testing, 90 of 142 biomarkers were significantly associated with incident CKD. In general, higher concentrations of very-low-density lipoprotein (VLDL) particles were associated with a higher risk of CKD whereas higher concentrations of high-density lipoprotein (HDL) particles were associated with a lower risk of CKD. Higher concentrations of cholesterol, phospholipids, and total lipids within VLDL were associated with a higher risk of CKD, whereas within HDL they were associated with a lower risk of CKD. Further, higher triglyceride levels within all lipoprotein subclasses, including all HDL particles, were associated with greater risk of CKD. We also identified that several amino acids, fatty acids, and inflammatory biomarkers were associated with risk of CKD. LIMITATIONS: Potential underreporting of CKD cases because of case identification via electronic health records. CONCLUSIONS: Our findings highlight multiple known and novel pathways linking circulating metabolites to the risk of CKD. PLAIN-LANGUAGE SUMMARY: The relationship between individual lipoprotein particle subclasses and lipid-related traits and risk of chronic kidney disease (CKD) in general population is unclear. Using data from 91,532 participants in the UK Biobank, we evaluated the associations of metabolites measured using nuclear magnetic resonance testing with the risk of CKD. We identified that 90 out of 142 lipid biomarkers were significantly associated with incident CKD. We found that very-low-density lipoproteins, high-density lipoproteins, the lipid concentration and composition within these lipoproteins, triglycerides within all the lipoprotein subclasses, fatty acids, amino acids, and inflammation biomarkers were associated with CKD risk. These findings advance our knowledge about mechanistic pathways that may contribute to the development of CKD.

A nomogram and heat map based on LASSO-Cox regression for predicting the risk of early-stage severe fever with thrombocytopenia syndrome patients developing into critical illness at 7-day and 14-day.

Severe fever with thrombocytopenia syndrome (SFTS) represents an emerging infectious disease characterized by a substantial mortality risk. Early identification of patients is crucial for effective risk assessment and timely interventions. In the present study, least absolute shrinkage and selection operator (LASSO)-Cox regression analysis was conducted to identify key risk factors associated with progression to critical illness at 7-day and 14-day. A nomogram was constructed and subsequently assessed for its predictive accuracy through evaluation and validation processes. The risk stratification of patients was performed using X-tile software. The performance of this risk stratification system was assessed using the Kaplan-Meier method. Additionally, a heat map was generated to visualize the results of these analyses. A total of 262 SFTS patients were included in this study, and four predictive factors were included in the nomogram, namely viral copies, aspartate aminotransferase (AST) level, C-reactive protein (CRP), and neurological symptoms. The AUCs for 7-day and 14-day were 0.802 [95% confidence interval (CI): 0.707-0.897] and 0.859 (95% CI: 0.794-0.925), respectively. The nomogram demonstrated good discrimination among low, moderate, and high-risk groups. The heat map effectively illustrated the relationships between risk groups and predictive factors, providing valuable insights with high predictive and practical significance.

Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping.

BACKGROUND: Cerebral microbleeds (CMB) are indicators of severe cerebral small vessel disease (CSVD) that can be identified through hemosiderin-sensitive sequences in MRI. Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI. PURPOSE: To automatically detect CMB on QSM, we proposed a two-stage deep learning pipeline. STUDY TYPE: Retrospective. SUBJECTS: A total number of 1843 CMBs from 393 patients (69 ± 12) with cerebral small vessel disease were included in this study. Seventy-eight subjects (70 ± 13) were used as external testing. FIELD STRENGTH/SEQUENCE: 3 T/QSM. ASSESSMENT: The proposed pipeline consisted of two stages. In stage I, 2.5D fast radial symmetry transform (FRST) algorithm along with a one-layer convolutional network was used to identify CMB candidate regions in QSM images. In stage II, the V-Net was utilized to reduce false positives. The V-Net was trained using CMB and non CMB labels, which allowed for high-level feature extraction and differentiation between CMBs and CMB mimics like vessels. The location of CMB was assessed according to the microbleeds anatomical rating scale (MARS) system. STATISTICAL TESTS: The sensitivity and positive predicative value (PPV) were reported to evaluate the performance of the model. The number of false positive per subject was presented. RESULTS: Our pipeline demonstrated high sensitivities of up to 94.9% at stage I and 93.5% at stage II. The overall sensitivity was 88.9%, and the false positive rate per subject was 2.87. With respect to MARS, sensitivities of above 85% were observed for nine different brain regions. DATA CONCLUSION: We have presented a deep learning pipeline for detecting CMB in the CSVD cohort, along with a semi-automated MARS scoring system using the proposed method. Our results demonstrated the successful application of deep learning for CMB detection on QSM and outperformed previous handcrafted methods. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Influence of Imbibition Fracturing Fluid on the Original Water and Methane Occurrence in Actual Coalbed Methane Reservoirs Using the Integrated Device of Displacement and Low-Field Nuclear Magnetic Resonance.

The original water in the coal rock pores plays a controlling role in the occurrence of gas. Furthermore, during the hydraulic fracturing process, pressurized fracturing fluid with a higher pressure than the original pore pressure in the fractures drives the fracturing fluid to infiltrate into the coal rock pores, thereby altering the occurrence pattern of gas and water in the original pores. However, due to the limitations of the indoor simulation device, a systematic conclusion on the impact of the original pore water and imbibition fracturing fluid on coalbed methane reservoirs has not yet been formed. In this paper, an integrated device combining displacement and low-field nuclear magnetic resonance was employed using underground cylindrical coal rock samples as experimental subjects. Experimental conditions were maintained at a temperature of 30 °C, a confining pressure of 23 MPa, and an approximate reservoir pressure of 15 MPa. The initial water saturation levels were altered to 0, 27.88, and 42.18% to replicate the conditions of a coalbed methane reservoir at a depth of approximately 1200 m. Fracturing fluid with a pressure of 18 MPa was injected into the experimental samples to simulate the impact of the fracturing fluid on the original reservoir during hydraulic fracturing. This allowed for a realistic assessment of the influence of initial water saturation and fracturing fluid absorption on the coalbed methane recovery rate in the reservoir. The experimental results indicate that the imbibition process promotes the desorption of adsorbed gas, and the desorption amount of adsorbed gas increases with the increase in the original water saturation. This will result in an increase in the gas pressure within the pore system. The conditions of this experiment, in comparison to the previous ones, more closely resemble real reservoir conditions. This enables a realistic assessment of how the presence of the original water content and the absorption of the fracturing fluid affect gas occurrence within the reservoir.

Tensile force field plays a crucial role in local invasion of tumor cells through a mechano-chemical coupling mechanism.

Cancer metastasis starts from early local invasion, during which tumor cells detach from the primary tumor, penetrate the extracellular matrix (ECM), and then invade neighboring tissues. However, the cellular mechanics in the detaching and penetrating processes have not been fully understood, and the underlying mechanisms that influence cell polarization and migration in the 3D matrix during tumor invasion remain largely unknown. In this study, we employed a dual tumor-spheroid model to investigate the cellular mechanisms of the tumor invasion. Our results revealed that the tensional force field developed by the active contraction of cells and tissues played a pivotal role in tumor invasion, acting as the driving force for remodeling the collagen fibers during the invasion process. The remodeled collagen fibers promoted cell polarization and migration because of the stiffening of the fiber matrix. The aligned fibers facilitated tumor cell invasion and directed migration from one spheroid to the other. Inhibiting/shielding the cellular contractility abolished matrix remodeling and re-alignment and significantly decreased tumor cell invasion. By developing a coarse-grained cell model that considers the mutual interaction between cells and fibers, we predicted the tensional force field in the fiber network and the associated cell polarization and cell-matrix interaction during cell invasion, which revealed a mechano-chemical coupling mechanism at the cellular level of the tumor invasion process. Our study highlights the roles of cellular mechanics at the early stage of tumor metastasis and may provide new therapeutic strategies for cancer therapy.

Synthesis, biological activity evaluation and mechanism of action of novel bis-isatin derivatives as potential anti-liver cancer agents.

A series of bis-isatin conjugates with lysine linker were synthesized with the aim of probing their antiproliferative potential. All the newly synthesized derivatives (0-100 µM) were first screened against liver cancer cell lines(Huh1, H22, Huh7, Hepa1-6, HepG2, Huh6 and 97H) using CCK-8 assay. Results indicated that the derivative 4d exhibited the most potent activity against Huh1 (IC50 = 17.13 µM) and Huh7(IC50 = 8.265 µM). In vivo anti-tumor study showed that compound 4d effectively inhibited tumor growth in Huh1-induced xenograft mouse model; the anti-tumor effect of compound 4d (15 mg/kg) was comparable with sorafenib (20 mg/kg). H&E staining analysis and routine blood test and blood serum biochemistry examination was performed to confirm the safety of compound 4d in xenograft models. The mechanism of action of 4d on tumor growth inhibition was further investigated by RNA-Seq analysis, which indicates a positive regulation of autophagy signaling pathway, which was further confirmed with key biomarker expression of autophagy after 4d treatment. Our results suggest that the bis-isatin conjugate compound 4d is a promising tumor inhibitory agent for some liver cancer.

Atomically Precise Mo2Cu17 Bimetallic Nanocluster: Synergistic Mo2O4-Coupled Copper Alkynyl Cluster for the Improved Hydrogen Evolution Reaction Performance.

Electrolytic hydrogen production via water splitting holds significant promise for the future of the energy revolution. The design of efficient and abundant catalysts, coupled with a comprehensive understanding of the hydrogen evolution reaction (HER) mechanism, is of paramount importance. In this study, we propose a strategy to craft an atomically precise cluster catalyst with superior HER performance by cocoupling a Mo2O4 structural unit and a Cu(I) alkynyl cluster into a structured framework. The resulting bimetallic cluster, Mo2Cu17, encapsulates a distinctive structure [Mo2O4Cu17(TC4A)4(PhC≡C)6], comprising a binuclear Mo2O4 subunit and a {Cu17(TC4A)2(PhC≡C)6} cluster, both shielded by thiacalix[4]arene (TC4A) and phenylacetylene (PhC≡CH). Expanding our exploration, we synthesized two homoleptic CuI alkynyl clusters coprotected by the TC4A and PhC≡C- ligands: Cu13 and Cu22. Remarkably, Mo2Cu17 demonstrates superior HER efficiency compared to its counterparts, achieving a current density of 10 mA cm-2 in alkaline solution with an overpotential as low as 120 mV, significantly outperforming Cu13 (178 mV) and Cu22 (214 mV) nanoclusters. DFT calculations illuminate the catalytic mechanism and indicate that the intrinsically higher activity of Mo2Cu17 may be attributed to the synergistic Mo2O4-Cu(I) coupling.

Systematic investigation on the rational design and optimization of bi-based metal oxide semiconductors in photocatalytic applications.

To address the global energy shortage and mitigate greenhouse gas emissions on a massive scale, it is critical to explore novel and efficient photocatalysts for the utilization of renewable resources. Bi-based metal oxide (BixMOy) semiconductors composed of bismuth, transition metal, and oxygen atoms have demonstrated improved photocatalytic activity and product selectivity. The vast number of element combinations available for BixMOymaterials provides a huge compositional space for the rational design and isolation of promising photocatalysts for specific applications. In this study, we have systematically investigated the electronic and optical properties over Bi2O3and a series of selected BixMOygroup materials (BiVO4, BiFeO3, BiCoO3, and BiCrO3) by calculating band structure, basic optical property features, mobility and separation of charge carriers. It is clearly noted that the band gap and band edge position of the BixMOygroup materials can be tuned in a wide range in comparison to Bi2O3. Similarly, the light response of BixMOyalso can be broadened from the ultraviolet to the visible light region by adjusting the selection of transition metals. Additionally, the analysis of the effective mass of charge carriers of these materials further confirms their possibility in photocatalytic reaction applications because of the appropriate separation efficiency and mobility of carriers. A selection of experimental investigations on the crystal structure, composition, and optical properties of Bi2O3, BiVO4, and BiFeO3as well as their catalytic performance in the degradation of methylene blue over was also conducted, which agree well with the theoretical predictions.

Construction and validation of a dynamic nomogram using Lasso-logistic regression for predicting the severity of severe fever with thrombocytopenia syndrome patients at admission.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a highly fatal infectious disease caused by the SFTS virus (SFTSV), posing a significant public health threat. This study aimed to construct a dynamic model for the early identification of SFTS patients at high risk of disease progression. METHODS: All eligible patients enrolled between April 2014 and July 2023 were divided into training and validation sets. Thirty-four clinical variables in the training set underwent analysis using least absolute shrinkage and selection operator (LASSO) logistic regression. Selected variables were then input into the multivariate logistic regression model to construct a dynamic nomogram. The model's performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) in both training and validation sets. Kaplan-Meier survival analysis was utilized to evaluate prognostic performance. RESULTS: 299 SFTS patients entered the final investigation, with 208 patients in the training set and 90 patients in the validation set. LASSO and the multivariate logistic regression identified six significant prediction factors: age (OR, 1.060; 95% CI, 1.017-1.109; P = 0.007), CREA (OR, 1.017; 95% CI, 1.003-1.031; P = 0.019), PT (OR, 1.765; 95% CI, 1.175-2.752; P = 0.008), D-dimer (OR, 1.039; 95% CI, 1.005-1.078; P = 0.032), nervous system symptoms (OR, 8.244; 95% CI, 3.035-26.858; P < 0.001) and hemorrhage symptoms (OR, 3.414; 95% CI, 1.096-10.974; P = 0.035). The AUC-ROC, C-index, calibration plots, and DCA demonstrated the robust performance of the nomogram in predicting severity at admission, and Kaplan-Meier survival analysis indicated its utility in predicting 28-day mortality among SFTS patients. The dynamic nomogram is accessible at https://sfts.shinyapps.io/SFTS_severity_nomogram/ . CONCLUSION: This study provided a practical and readily applicable tool for the early identification of high-risk SFTS patients, enabling the timely initiation of intensified treatments and protocol adjustments to mitigate disease progression.

Renal damage and old age: risk factors for thrombosis in patients with ANCA-associated vasculitis.

INTRODUCTION: Thrombosis in ANCA-associated vasculitis (AAV) was prevalent and has been neglected in Chinese patients. This study tried to describe the clinical characteristics, identify the risk factors, and investigate the causal relationship between AAV and venous thromboembolism (VTE) by two-sample Mendelian randomization (MR) analysis. METHODS: In this retrospective, observational study, we included all hospitalized AAV patients from Jan 2013 to Apr 2022 in Peking Union Medical College Hospital. We collected their clinical data for multivariate regression analysis to determine the risk factors for thrombosis. The nomogram was constructed by applying these risk factors to predict thrombosis in AAV patients. As for MR analysis, we selected single nucleotide polymorphisms (SNPs) related to AAV from published genome-wide association studies and extracted the outcome data containing deep vein thrombosis (DVT) and pulmonary embolism (PE) from the UK biobank. RESULTS: 1203 primary AAV patients were enrolled, and thrombosis occurred in 11.3%. Multivariate regression suggested that older than 65 years, EGPA, neurological involvement, lung involvement, significantly elevated serum creatinine (> 500µmol/L), and elevated D-dimer were associated with thrombosis in AAV patients. The model demonstrated satisfied discrimination with an AUC of 0.769 (95% CI, 0.726-0.812). MR analysis showed that EGPA could increase the risk of developing DVT and PE (OR = 1.0038, 95%CI = 1.0035-1.0041, P = 0.009). CONCLUSION: Thrombosis was not rare in Chinese patients with AAV. Renal damage and old age emerged as critical risk factors for thrombosis. EGPA might have a potential causal relationship with DVT and PE.

Mechanism of N2O formation in catalytic after-treatment systems of ammonia/hydrogen-fuelled engines.

The combustion processes and catalytic after-treatment of ammonia/hydrogen-fueled engines, including NOx storage and reduction (NSR) and noble-metal selective catalytic reduction (SCR), can produce the byproduct N2O, a potent greenhouse gas that weakens the zero-carbon attribute of these fuels. Currently, the mechanism of N2O formation on DeNOx catalysts remains unclear due to limited research on catalytic after-treatment for such engines and the complexity of surface catalytic reactions. To elucidate the formation of N2O on the DeNOx catalysts of ammonia/hydrogen fuel engines, the impact factors on N2O formation on platinum catalysts (typical catalysts in NSR and noble-metal SCR) were investigated using first-principles molecular dynamics (FPMD). By employing the blue-moon ensemble enhanced sampling method and the slow-growth approach for free energy surface exploration, together with density functional theory (DFT) for electronic structure analysis, a linear relationship between the spin splitting of the d states of Pt clusters and N2O formation energy barriers was revealed, along with the increased structural sensitivity of Pt clusters with fewer atoms. It is highlighted that the energy barrier for N2O formation is determined by the matching degree of energy levels between molecules and surfaces. These findings provide atomic-scale insights into N2O formation on DeNOx catalysts for ammonia/hydrogen-fueled engines, facilitating N2O emission control for carbon-free engines.

Hydrothermal carbonization of Chinese medicine residue from licorice: Effects of pore and chemical structures on chromium migration.

The Chinese medicine residue (CMR) is composed of wet substances, so using hydrothermal carbonization (HTC) to recover renewable energy from the residue is a suitable treatment method. Chromium (Cr), a kind of heavy metal element, is enriched in hydrochar and severely restricts its effective utilization. An in-depth analysis of the migration path and mechanism of Cr in hydrochar is helpful in promoting energy utilization for CMR. Here, licorice, a significant Chinese medicine, was selected as the example to analyze the evolutions of its pore and chemical structures and their effects on the migration mechanism of Cr during the HTC process. The products obtained under various HTC conditions were analyzed using nitrogen adsorption, FTIR, and 13C NMR. The results show that, considering reaction time and relevant reactions as the primary factors during the HTC process, the migration pathway of Cr in hydrochar undergoes two stages, and they are the accompanying migration stage and the recovery aggregation stage. Active adsorption sites for Cr may exist within the pore structure of hydrochar. In the HTC process, hydrolysis, decarboxylation, and decarbonylation reactions are the direct drivers of Cr migration, while aromatization is the underlying cause of Cr recovery and aggregation. It is hypothesized that Cr catalyzes the acetylene cyclotrimerization reaction, thereby promoting the formation of aromatic structures in hydrochar and integrating into the hydrochar carbon skeleton.

Semisupervised white matter hyperintensities segmentation on MRI.

This study proposed a semisupervised loss function named level-set loss (LSLoss) for cerebral white matter hyperintensities (WMHs) segmentation on fluid-attenuated inversion recovery images. The training procedure did not require manually labeled WMH masks. Our image preprocessing steps included biased field correction, skull stripping, and white matter segmentation. With the proposed LSLoss, we trained a V-Net using the MRI images from both local and public databases. Local databases were the small vessel disease cohort (HKU-SVD, n = 360) and the multiple sclerosis cohort (HKU-MS, n = 20) from our institutional imaging center. Public databases were the Medical Image Computing Computer-assisted Intervention (MICCAI) WMH challenge database (MICCAI-WMH, n = 60) and the normal control cohort of the Alzheimer's Disease Neuroimaging Initiative database (ADNI-CN, n = 15). We achieved an overall dice similarity coefficient (DSC) of 0.81 on the HKU-SVD testing set (n = 20), DSC = 0.77 on the HKU-MS testing set (n = 5), and DSC = 0.78 on MICCAI-WMH testing set (n = 30). The segmentation results obtained by our semisupervised V-Net were comparable with the supervised methods and outperformed the unsupervised methods in the literature.