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Salt water is ubiquitous, playing crucial roles in geological and physiological processes. Despite centuries of investigations, whether or not water’s structure is drastically changed by dissolved ions is still debated. Based on density functional theory, we employ machine learning based molecular dynamics to model sodium chloride, potassium chloride, and sodium bromide solutions at different concentrations. The resulting reciprocal-space structure factors agree quantitatively with neutron diffraction data. Here we provide clear evidence that the ions in salt water do not distort the structure of water in the same way as neat water responds to elevated pressure. Rather, the computed structural changes are restricted to the ionic first solvation shells intruding into the hydrogen bond network, beyond which the oxygen radial-distribution function does not undergo major change relative to neat water. Our findings suggest that the widely cited pressure-like effect on the solvent in Hofmeister series ionic solutions should be carefully revisited. By advanced machine learning techniques, first-principles simulations find that dissolving salt in water does not change water structure drastically. It is contrary to the notion of “pressure effect” which has been widely applied over past 25 years.

The electrical double layer (EDL) at metal oxide-electrolyte interfaces critically affects fundamental processes in water splitting, batteries, and corrosion. However, limitations in the microscopic-level understanding of the EDL have been a major bottleneck in controlling these interfacial processes. Herein, we use ab initio-based machine learning potential simulations incorporating long-range electrostatics to unravel the molecular-scale picture of the EDL at the prototypical anatase TiO 2 -electrolyte interface under various pH conditions. Our large-scale simulations, capable of capturing interfacial water dissociation/recombination reactions and electrolytic proton transport, provide unprecedented insights into the detailed structure of the EDL. Moreover, the larger capacitance of the EDL under basic relative to acidic conditions, originating from the higher affinity of the cations for the oxide surface, is found to give rise to distinct charging mechanisms on negative and positive surfaces. Our results are validated by the agreement between the computed EDL capacitance and experimental data. Microscopic understanding of the electrical double layer (EDL) is key to optimizing interfacial processes in water splitting and batteries. Here, the authors report the insight of EDL at oxide-electrolyte interfaces with ab initio machine learning simulations that agrees with available experiments.

Ending all forms of hunger by 2030, as set forward in the UN-Sustainable Development Goal 2 (UN-SDG2), is a daunting but essential task, given the limited timeline ahead and the negative global health and socio-economic impact of hunger. Malnutrition or hidden hunger due to micronutrient deficiencies affects about one third of the world population and severely jeopardizes economic development. Staple crop biofortification through gene stacking, using a rational combination of conventional breeding and metabolic engineering strategies, should enable a leap forward within the coming decade. A number of specific actions and policy interventions are proposed to reach this goal. Biofortification is an effective means to reduce micronutrient malnutrition. Here, the authors review recent advances in biofortification and propose stacking multiple micronutrient traits into high-yielding varieties through the combination of conventional breeding and genetic engineering approaches.

Objective To investigate the efficacy and safety of belimumab in the treatment of systemic lupus erythematosus (SLE) in a real-world setting and provide a valuable reference for clinical treatment. Methods In this retrospective study, 101 patients with SLE who came to our hospital from March 2020 to September 2022, 56 of whom with lupus nephritis (LN), were selected. All patients received belimumab in combination with standard of care(SoC)therapy regimen for more than 52 weeks and their clinical/laboratory data, assessment of disease activity, glucocorticoids dosage and occurrence of adverse events were recorded. Lupus Low Disease Activity State (LLDAS) and DORIS remission as a primary goal in the treatment of SLE. The groups were classified according to the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2 K): SLEDAI-2 K < 6 was categorized as the mild group (mild activity) and SLEDAI-2 K ≥ 6 was categorized as the active group (moderate-severe activity). The disease of the two groups mentioned above were assessed using the SELENA-SLEDAI Flare Index (SFI) and the SLE Responder Index-4 (SRI-4), respectively. Furthermore, we used complete remission (CR) and partial remission (PR) in the kidney as the standard for efficacy evaluation for LN patients. Results After 52 weeks of treatment with belimumab, patients’ complement levels increased significantly ( p  < 0.05); Other indicators such as 24-hour urine protein quantification and daily glucocorticoids dose decreased compared to pretreatment ( p  < 0.05). At 52 weeks, (i) after evaluation, the whole group of patients showed significant improvement in their condition; (ii) 55.4% of patients achieved LLDAS and 23.8% achieved DORIS remission; (iii) 73.2% of patients with LN achieved CR, 16.1% achieved PR. Adverse reactions were observed in 15 patients (14.9%), all of which normalized after symptomatic treatment. Conclusions In general, during treatment with belimumab, immunological and biochemical indices improved in SLE patients, urinary protein levels were reduced in LN patients, and the rate of renal function remission was effectively increased; At the same time, the use of belimumab is associated with a low frequency of side effects, good overall tolerability and a favorable safety profile.

In practical industrial applications, the operating conditions of bearings frequently change, posing significant challenges for reliable fault diagnosis. Traditional machine learning methods, which rely on the assumption of independent and identically distributed samples, often experience a significant decline in diagnostic accuracy under such variable conditions. To address this issue, this paper proposes a bearing fault transfer diagnosis method that combines the Balanced Distribution Adaptation (BDA) algorithm with a Back Propagation neural network (BPNN) classification algorithm. Firstly, time-domain features of the bearing signals are extracted to comprehensively reflect the operational state of the bearings. Principal Component Analysis (PCA) is then utilized to reduce the dimensionality of the high-dimensional features, preserving the main information while reducing computational complexity. Subsequently, the BDA algorithm is employed to align the features of the source and target domains, balancing distribution differences and achieving effective feature space transfer. Finally, the BP neural network classification algorithm is used to classify the transferred features, thereby diagnosing bearing faults. Experimental results demonstrate that, compared to traditional fault diagnosis methods, the proposed approach achieves higher diagnostic accuracy and robustness under different working conditions. This method not only addresses the challenges posed by changing operating conditions but also holds significant practical value, providing a robust and efficient solution for real-world industrial applications such as predictive maintenance and condition monitoring in critical engineering systems.

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease that can affect multiple systems. Pulmonary arterial hypertension (PAH) has a close linkage with SLE. However, the inter-relational mechanisms between them are still unclear. This article aimed to explore the shared gene signatures and potential molecular mechanisms in SLE and PAH.MethodsThe microarray data of SLE and PAH in the Gene Expression Omnibus (GEO) database were downloaded. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify the co-expression modules related to SLE and PAH. The shared genes existing in the SLE and PAH were performed an enrichment analysis by ClueGO software, and their unique genes were also performed with biological processes analyses using the DAVID website. The results were validated in another cohort by differential gene analysis. Moreover, the common microRNAs (miRNAs) in SLE and PAH were obtained from the Human microRNA Disease Database (HMDD) and the target genes of whom were predicted through the miRTarbase. Finally, we constructed the common miRNAs–mRNAs network with the overlapped genes in target and shared genes.ResultsUsing WGCNA, four modules and one module were identified as the significant modules with SLE and PAH, respectively. A ClueGO enrichment analysis of shared genes reported that highly activated type I IFN response was a common feature in the pathophysiology of SLE and PAH. The results of differential analysis in another cohort were extremely similar to them. We also proposed a disease road model for the possible mechanism of PAH secondary to SLE according to the shared and unique gene signatures in SLE and PAH. The miRNA–mRNA network showed that hsa-miR-146a might regulate the shared IFN-induced genes, which might play an important role in PAH secondary to SLE.ConclusionOur work firstly revealed the high IFN response in SLE patients might be a crucial susceptible factor for PAH and identified novel gene candidates that could be used as biomarkers or potential therapeutic targets.

Objectives DM–associated rapidly progressive interstitial lung disease (DM-RP-ILD) has been the clinical conundrum. We assess the serum levels of tumor markers (TMs) in different types of ILD, and explore the diagnostic utility of TMs for DM/ADM-RP-ILD. Methods This was a retrospective cohort study, data including clinical and laboratory records were collected from the first affiliated hospital of Zhengzhou University from December 2015, to June 2020. Tumor markers (TMs) include CEA, CA153, CA724, CA125, and CA199. Spearman analysis, ROC, and Kaplan–Meier curve were used for data analysis. Results Total 272 patients (149 DM and 123 ADM) were enrolled, 152 (55.88%) with ILD (116 with chronic ILD, 36 with RP-ILD) and 120 (44.12%) without ILD among them. The serum levels of CEA and ferritin were significantly higher in patients with RP-ILD than in the other two groups. Serum CA125, CA199, and CA153 levels in patients with RP-ILD were higher than those without ILD. CEA levels were associated with the ferritin, KL-6 and anti-MDA5 levels, and CEA concentration was significantly negatively correlated with DLco ( P  = 0.016, R 2  =  − 0.281). CEA [AUC = 0.7, 95% CI = (0.594, 0.806)] and ferritin [AUC = 0.737, 95% CI = (0.614, 0.860)] had diagnosed value for patients developing RP-ILD. Patients with high serum CEA levels had higher mortality rate within the DM-ILD population. Conclusions TMs and ferritin were increased in DM/ADM-RP-ILD, and serum CEA and CA153 levels can evaluate disease severity of DM. And CEA and ferritin can be used as noninvasive diagnostic biomarkers for patients with DM-RP-ILD. Key Points • Interstitial lung disease (ILD) is a serious complication of DM, and is a leading cause of mortality, especially rapidly progressive ILD. • Tumor markers as a kind of noninvasive detection can reflect the disease severity of DM, and CEA and ferritin can be used to identify patients with RP-ILD.

To enhance the accuracy and efficiency of reliability analyses for an aero-engine vectoring exhaust nozzle (VEN), a dual-stochastic extreme response surface method based on the genetic algorithm (DSERSM-GA) is developed by integrating the genetic algorithm, the random extremum response surface method, and the dual response surface method in the paper. In the proposed method, a limited set of Monte Carlo samples is strategically utilized to construct and optimize a population-based response surface model, forming a robust mathematical framework for reliability prediction. The uncertainty sources considered include aerodynamic loads acting on the vector nozzle, material densities of the expansion plate and triangular link, as well as the elastic moduli of these components. Stress and deformation responses of both the expansion plate and triangular link are employed as the performance metrics. The proposed DSERSM-GA methodology is validated through dynamic reliability simulations applied to a vector nozzle system, yielding distributions and corresponding reliability indices of critical responses. Comparative analyses against traditional Monte Carlo Simulation (MCS) and conventional Extreme Response Surface Methods (ERSM) demonstrate that the DSERSM-GA significantly reduces computational costs while preserving high predictive accuracy.

Background Lupus nephritis (LN) is one of the most severe complications of systemic lupus erythematosus (SLE). Circular RNAs (circRNAs) can act as competitive endogenous RNAs (ceRNAs) to regulate gene transcription, which is involved in mechanism of many diseases. However, the role of circRNA in lupus nephritis has been rarely reported. In this study, we aim to investigate the clinical value of circRNAs and explore the mechanism of circRNA involvement in the pathogenesis of LN. Methods Renal tissues from three untreated LN patients and three normal controls (NCs) were used to identify differently expressed circRNAs by next-generation sequencing (NGS). Validated assays were used by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The interactions between circRNA and miRNA, or miRNA and mRNA were further determined by luciferase reporter assay. The extent of renal fibrosis between the two groups was assessed by Masson-trichome staining and immunohistochemistry (IHC) staining. Results 159 circRNAs were significantly dysregulated in LN patients compared with NCs. The expression of hsa_circ_0123190 was significantly decreased in the renal tissues of patients with LN ( P  = 0.014). Bio-informatics analysis and luciferase reporter assay illustrated that hsa_circ_0123190 can act as a sponge for hsa-miR-483-3p, which was also validated to interact with APLNR. APLNR mRNA expression was related with chronicity index (CI) of LN ( P  = 0.033, R 2  = 0.452). Moreover, the fibrotic-related protein, transforming growth factor-β1 (TGF-β1), which was regulated by APLNR, was more pronounced in the LN group ( P  = 0.018). Conclusion Hsa_circ_0123190 may function as a ceRNA to regulate APLNR expression by sponging hsa-miR-483-3p in LN.