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In the fields of wind power, and other industries, the Al2O3/TiO2 coating is prepared and ground on the bearing ring, in order to obtain the insulation resisting the electrical erosion for the motors at high voltage. A novel wet chemical mechanical grinding (WCMG) method is proposed to finish this hard-brittle composite material, utilizing the structured diamond abrasives pad and the NaOH solution. The softened workpiece's surface under the chemical reaction was demonstrated by means of Raman spectrum, indentation and scratching tests. The analytical model of surface roughness and fracture cracks is established based on the synthesis of geometry and kinematics, contact mechanics, material removal and indentation fracture mechanics. The surface roughness of coating was reduced from initial Sa 3.293 μm down to final Sa 0.049 μm in the WCMG process with grain size 3 μm and pH 12.01, mostly attributed to the ductile removal of chemically softened coating surface.

Abstract The ATP-binding cassette (ABC) transporter, MsbA, plays a pivotal role in lipopolysaccharide (LPS) biogenesis by facilitating the transport of the LPS precursor lipooligosaccharide (LOS) from the cytoplasmic to the periplasmic leaflet of the inner membrane. Despite multiple studies shedding light on MsbA, the role of lipids in modulating MsbA-nucleotide interactions remains poorly understood. Here we use native mass spectrometry (MS) to investigate and resolve nucleotide and lipid binding to MsbA, demonstrating that the transporter has a higher affinity for adenosine 5’-diphosphate (ADP). Moreover, native MS shows the LPS-precursor 3-deoxy-D-manno-oct-2-ulosonic acid (Kdo)2-lipid A (KDL) can tune the selectivity of MsbA for adenosine 5’-triphosphate (ATP) over ADP. Guided by these studies, four open, inward-facing structures of MsbA are determined that vary in their openness. We also report a 2.7 Å-resolution structure of MsbA in an open, outward-facing conformation that is not only bound to KDL at the exterior site, but with the nucleotide binding domains (NBDs) adopting a distinct nucleotide-free structure. The results obtained from this study offer valuable insight and snapshots of MsbA during the transport cycle.

Abstract The “hologenome” concept is an increasingly popular way of thinking about microbiome-host for marine organisms. However, it is challenging to track hologenome dynamics because of the large amount of material, with tracking itself usually resulting in damage or death of the research object. Here we show the simple and efficient holo-2bRAD approach for the tracking of hologenome dynamics in marine invertebrates (i.e., scallop and shrimp) from one holo-2bRAD library. The stable performance of our approach was shown with high genotyping accuracy of 99.91% and a high correlation of r > 0.99 for the species-level profiling of microorganisms. To explore the host-microbe association underlying mass mortality events of bivalve larvae, core microbial species changed with the stages were found, and two potentially associated host SNPs were identified. Overall, our research provides a powerful tool with various advantages (e.g., cost-effective, simple, and applicable for challenging samples) in genetic, ecological, and evolutionary studies.

Abstract Previous studies have reported that the significant association between serum calcium and mortality substantially in patients, especially among those with intensive care unit (ICU). And In diabetes mellitus, congestive heart failure (CHF) is a significant comorbidity. We aim to evaluate the association between serum calcium levels and in-hospital mortality among patients with diabetes and congestive heart failure. The participants in this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. To scrutinize potential associations between serum calcium levels and in-hospital mortality, a comprehensive analysis encompassing multivariate logistic regression, cubic spline function model, threshold effect analysis, and subgroup analysis was performed. This retrospective cohort study encompassed 7063 patients, among whom the in-hospital mortality stood at 12.2%. In the multivariate logistic regression, adjusted odds ratios (ORs) were contrasted with the reference category Q6 (8.8–9.1 mg/dL) for serum calcium levels and in-hospital mortality. The adjusted ORs for Q1 (≤ 7.7 mg/dL), Q2 (7.7–8 mg/dL), and Q7 (≥ 9.1 mg/dL) were 1.69 (95% CI 1.17–2.44, p = 0.005), 1.62 (95% CI 1.11–2.36, p = 0.013), and 1.57 (95% CI 1.1–2.24, p = 0.012) respectively. The dose–response analysis uncovered a U-shaped relationship between serum calcium levels and in-hospital mortality in diabetic patients with heart failure. Subgroup analyses confirmed result stability notwithstanding the influence of diverse factors. Our investigation revealed a U-shaped correlation between serum calcium levels and in-hospital mortality in diabetes patients with congestive heart failure, pinpointing a significant inflection point at 9.05 mg/dL.

Highlights Synergistic passivation mechanism of the dual functional compound of potassium bromide for metal halide perovskite films, that is through chemical bonding and physical screening towards the various types of defects. Metal-ion additives can simultaneously passivate the defects of halide vacancies with bromine anions and dangling bond defects with metal cations. Achieve the maximum external quantum efficiency of ~21% and maximum luminance of ~60,000 cd m−2.

Abstract Arylamines, serving as crucial building blocks in natural products and finding applications in multifunctional materials, are synthesized on a large scale via an electrophilic nitration/reduction sequence. However, the current methods for aromatic C–H amination have not yet attained the same level of versatility as electrophilic nitration. Here we show an extensively investigated transition metal-free and regioselective strategy for the amination of nitrobenzenes, enabling the synthesis of 4-nitro-N-arylamines through C(sp2)-H/N-H cross-coupling between electron-deficient nitroarenes and amines. Mechanistic studies have elucidated that the crucial aspects of these reactions encompass the generation of nitrogen radicals and recombination of nitrobenzene complex radicals. The C(sp2)-N bond formation is demonstrated to be highly effective for primary and secondary arylamines as well as aliphatic amines under mild conditions, exhibiting exceptional tolerance towards diverse functional groups in both nitroarenes and amines (>100 examples with yields up to 96%). Notably, this C(sp2)-H/N-H cross-coupling exhibits exclusive para-selectivity.

Summary: Cardiovascular diseases (CVDs) pose a significant global health threat, responsible for a considerable portion of worldwide mortality. Flexible electronics enable continuous, noninvasive, real-time, and portable monitoring, providing an ideal platform for personalized healthcare. Nevertheless, challenges persist in sustaining stable adherence across diverse and intricate skin environments, hindering further advancement toward clinical applications. Strategies such as structural design and chemical modification can significantly enhance the environmental adaptability and monitoring performance of flexible electronics. This review delineates processing techniques, including structural design and chemical modification, to mitigate signal interference from sebaceous skin, motion artifacts from the skin in motion, and infection risks from fragile skin, thereby enabling the accurate monitoring of key cardiovascular indicators in complex physiological environments. Moreover, it delves into the potential for the strategic development and improvement of flexible electronics to ensure their alignment with complex physiological environment requirements, facilitating their transition to clinical applications.

The recent years have witnessed the rapid advancement of clustered regularly interspaced short palindromic repeats/associated protein 9 (CRISPR/Cas9)-mediated gene editing in cancer therapy. The success of cancer gene therapy relies heavily on the development of safe and effective delivery vectors. We focus on organic nanocarriers because of their flexible customizability, which permits them to accomplish excellent delivery efficiency and performance. In this review, the pharmacokinetic behavior of CRISPR/Cas9 nanocarriers serves as a guide to outline the strategies for improving the bioavailability of nanocarriers through physical, chemical, and biological means. Furthermore, the potential of organic nanocarriers for simultaneous delivery of therapeutic agents and gene editing tools is highlighted. Finally, we discuss future directions for the development of cancer therapeutic nanosystems, paving the way for the construction of effective CRISPR/Cas9 delivery systems.

In backlighting systems for liquid crystal displays, conventional red, green, and blue (RGB) light sources that lack polarization properties can result in a significant optical loss of up to 50% when passing through a polarizer. To address this inefficiency and optimize energy utilization, this study presents a high-performance device designed for RGB polarized emissions. The device employs an array of semipolar blue µLEDs with inherent polarization capabilities, coupled with mechanically stretched films of green-emitting CsPbBr3 nanorods and red-emitting CsPbI3-Cs4PbI6 hybrid nanocrystals. The CsPbBr3 nanorods in the polymer film offer intrinsic polarization emission, while the aligned-wire structures formed by the stable CsPbI3-Cs4PbI6 hybrid nanocrystals contribute to substantial anisotropic emissions, due to their high dielectric constant. The resulting device achieved RGB polarization degrees of 0.26, 0.48, and 0.38, respectively, and exhibited a broad color gamut, reaching 137.2% of the NTSC standard and 102.5% of the Rec. 2020 standard. When compared to a device utilizing c-plane LEDs for excitation, the current approach increased the intensity of light transmitted through the polarizer by 73.6%. This novel fabrication approach for polarized devices containing RGB components holds considerable promise for advancing next-generation display technologies.

Urinary tract infections (UTI) caused by uropathogenic Escherichia coli (UPEC) are a significant global health challenge. The UPEC biofilm lifestyle is believed to play an important role in infection recurrency and treatment resistance, but our understanding of how the extracellular matrix (ECM) components curli and cellulose contribute to biofilm formation and pathogenicity is limited. Here, we study the spatial and temporal development of native UPEC biofilm using agar-based detection methods where the non-toxic, optically active fluorescent tracer EbbaBiolight 680 reports the expression and structural location of curli in real-time. An in vitro screen of the biofilm capacity of common UPEC strains reveals significant strain variability and identifies UPEC No. 12 (UPEC12) as a strong biofilm former at 28 °C and 37 °C. Non-interventional microscopy, including time-lapse and 2-photon, reveal significant horizontal and vertical heterogeneity in the UPEC12 biofilm structure. We identify region-specific expression of curli, with a shift in localization from the bottom of the flat central regions of the biofilm to the upper surface in the topographically dramatic intermediate region. When investigating if the rdar morphotype affects wettability of the biofilm surface, we found that the nano-architecture of curli guided by cellulose, rather than the rdar macrostructures, leads to increased hydrophobicity of the biofilm. By providing new insights at exceptional temporal and spatial resolution, we demonstrate how non-interventional analysis of native biofilms will facilitate the next generation of understanding into the roles of ECM components during growth of UPEC biofilms and their contribution to the pathogenesis of UTI.

BackgroundRehabilitation therapists often perform physically demanding treatments that may result in work-related injuries, yet related studies are scarce. This study aimed to investigate the work-related injuries of rehabilitation therapists and provide feasible preventive measures.MethodsA cross-sectional study was carried out in 34 regions across China using an online questionnaire. The survey gathered responses primarily from 1,198 rehabilitative therapists working in 120 health institutes. Following data collection, descriptive analysis, chi-square tests, logistic regression, and receiver operating characteristic (ROC) curves were employed to analyze the data.ResultsIn this study, the incidence of work-related injuries was reported to be 87% (n = 1,041). The top three musculoskeletal issues reported were low back pain (12%), neck pain (10%), and shoulder pain (9%). Logistic regression and ROC curve analysis identified that working as a physiotherapist and years of work experience (OR [95% CI]: 1.03 [0.99–1.07]) were significant contributors to the incidence of work-related injuries. Specifically, neuro-physiotherapists (OR [95% CI]: 3.04 [1.56–5.92]), musculoskeletal physiotherapists (OR [95% CI]: 2.46 [1.16–5.18]), and intensive care physiotherapists (OR [95% CI]: 4.70 [1.24–17.88]) were at higher risk. Furthermore, five factors were proven to be associated with injury prevention as reported by therapists: patient engagement (OR [95% CI]: 0.38 [0.23–0.62]), improving techniques (OR [95% CI]: 0.59 [0.39–0.90]), maintaining exercise habits (OR [95% CI]: 0.59 [0.40–0.86]), utilizing instruments (OR [95% CI]: 0.80 [0.53–1.19]), and strengthening education (OR [95% CI]: 0.43 [0.21–0.90]).ConclusionThe present study investigated the factors contributing to work-related injuries among rehabilitation therapists, with a focus on identifying both risk and preventive measures. These findings offer new perspectives on decreasing injury risk.

Ischemia‒reperfusion (I/R) injury is a frequently observed complication after flap surgery, and it affects skin flap survival and patient prognosis. Currently, there are no proven safe and effective treatment options to treat skin flap I/R injury. Herein, the potential efficacies of the bioactive peptide from maggots (BPM), as well as its underlying mechanisms, were explored in a rat model of skin flap I/R injury and LPS- or H2O2-elicited RAW 264.7 cells. We demonstrated that BPM significantly ameliorated the area of flap survival, and histological changes in skin tissue in vivo. Furthermore, BPM could markedly restore or enhance Nrf2 and HO-1 levels, and suppress the expression of pro-inflammatory cytokines, including TLR4, p-IκB, NFκB p65, p-p65, IL-6, and TNF-α in I/R-injured skin flaps. In addition, BPM treatment exhibited excellent biocompatibility with an adequate safety profile, while it exhibited superior ROS-scavenging ability and the upregulation of antioxidant enzymes in vitro. Mechanistically, the above benefits related to BPM involved the activation of Nrf2/HO-1 and suppression of TLR4/NF-κB pathway. Taken together, this study may provide a scientific basis for the potential therapeutic effect of BPM in the prevention of skin flap I/R injury and other related diseases.

Abstract Adipocytes play a significant role in breast cancer due to the unique histological structure of the breast. These have not only been detected adjacent to breast cancer cells but they have also been implicated in cancer development. Adipocytes in obese individuals and tumor microenvironment (TME) have a common feature, that is, hypoxia. The increased expression of hypoxia-inducible factor (HIF)-1α is known to alter the metabolism and functions of adipocytes. In this study, we described the mechanism linking the hypoxia-sensing pathway manifested by HIF to adipocytes and breast cancer and discussed the mechanism underlying the role of hypoxic adipocytes in breast cancer development from the perspective of metabolic remodeling. The processes and pathways in hypoxic adipocytes could be a promising target in breast cancer therapy.

Abstract Ground heat flux (G0) is a key component of the land‐surface energy balance of high‐latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G0 data (measured or modeled) for snow‐free period as a reference. When observed G0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state‐of‐the‐art uncertainty quantification methods, the developed G0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.

The process-based water system models have been transitioning from single-functional to integrated multi-objective and multi-functional since the worldwide digital upgrade of urban water system management. The proliferation of model complexity results in more significant uncertainty and computational requirements. However, conventional model calibration methods are insufficient in dealing with extensive computational time and limited monitoring samples. Here we introduce a novel machine learning system designed to expedite parameter optimization with limited data and boost efficiency in parameter search. MLPS, termed the machine learning parallel system for fast parameter search of integrated process-based models, aims to enhance both the performance and efficiency of the integrated model by ensuring its comprehensiveness, accuracy, and stability. MLPS was constructed upon the concept of model surrogation + algorithm optimization using Ant Colony Optimization (ACO) coupled with Long Short-Term Memory (LSTM). The optimization results of the Integrated sewer network and urban river model demonstrate that the average relative percentage difference of the predicted river pollutant concentrations increases from 1.1 to 6.0, and the average absolute percent bias decreases from 124.3% to 8.8%. The model outputs closely align with the monitoring data, and parameter calibration time is reduced by 89.94%. MLPS enables the efficient optimization of integrated process-based models, facilitating the application of highly precise complex models in environmental management. The design of MLPS also presents valuable insights for optimizing complex models in other fields.

Abstract Native mass spectrometry (MS) is a powerful technique for interrogating membrane protein complexes and their interactions with other molecules. A key aspect of the technique is the ability to preserve native-like structures and noncovalent interactions, which can be challenging depending on the choice of detergent. Different strategies have been employed to reduce charge on protein complexes to minimize activation and preserve non-covalent interactions. Here, we report the synthesis of a class of polyamine detergents tailored for native MS studies of membrane proteins. These detergents, a series of spermine covalently attached to various alkyl tails, are exceptional charge-reducing molecules, exhibiting a ten-fold enhanced potency over spermine. Addition of polyamine detergents to proteins solubilized in maltoside detergents results in improved, charge-reduced native mass spectra and reduced dissociation of subunits. Polyamine detergents open new opportunities to investigate membrane proteins in different detergent environments that have thwarted previous native MS studies.

With the improvement of people's living standards and health awareness, the safety of animal-derived food has attracted worldwide attention. Chemical contamination (melamine, veterinary drug residues, food additive residues, etc.) and pathogenic microorganisms are the primary causes of food safety issues in animal-derived food products, potentially threatening human health and socioeconomic development. Therefore, it is essential to establish rapid detection methods for animal-derived food safety. Surface-enhanced Raman spectroscopy (SERS) has the advantages of rapid detection, good selectivity, and high sensitivity. It has shown great application potential in food safety, which has become one of the research hotspots. This paper reviews the application of SERS in the safety of animal-derived food detection and comprehensively introduces the use of SERS to detect melamine, foodborne pathogens, pesticide and veterinary drug residues, and food additives. Furthermore, it prospects the application of SERS technology in rapid residue detection, which would be believed to provide valuable insights into the field of SERS-based food safety evaluation.

Abstract Boreal forest heights are associated with global carbon stocks and energy budgets. The launch of the Advanced Topographic Laser Altimeter System (ATLAS) onboard the NASA's Ice, Cloud and Land Elevation Satellite (ICESat‐2) enables canopy vertical structure measurement at a global scale. However, with a photon‐counting laser system, ICESat‐2 contains high uncertainties in the estimated canopy heights, requiring appropriate quality control before being applied to canopy height modelling. We adopted a multivariate quality control approach (i.e. the Cook's distance) to improve the quality of ICESat‐2 samples. The controlled ICESat‐2 data were then input as the response variable for predicting boreal forest heights based on spatially continuous satellite data and machine learning (ML) regression models. The examined ML regressors include artificial neural networks (ANN), gradient boosting machine (GBM), random forest (RF) and support vector regression (SVR). The proposed quality control effectively removes low‐quality ICESat‐2 samples and enhances the correlations between ICESat‐2 and airborne laser scanning (ALS) observations. Moreover, the controlled ICESat‐2 samples help achieve a trade‐off between sample quality and quantity for all ML regressors, generating close canopy heights to ALS‐derived counterparts. Overall, RF and GBM make better canopy height predictions than ANN and SVR. Of all explanatory variables, the normalized difference vegetation index calculated based on the first red edge band of Sentinel‐2 (NDVIredEdge1) is considered the most important. The proposed quality control on ICESat‐2 sample selection and canopy height model (CHM) development workflow will greatly benefit forest structure investigations in the Arctic community.

Micro light-emitting diodes (micro-LEDs) are considered crucial for the next-generation display technology. However, the high cost of large-scale transfer technology and the lack of maturity in full-color technology have hindered the availability of mature products. The perovskite quantum dot (PQD) material offers a promising solution for achieving full-color capabilities in micro-LED displays. This review article aims to provide an overview on the latest progresses on PQD full-color technology for micro-LEDs. The review covers a variety of patterning techniques, including photolithography, inkjet printing, microfluidic processing, and laser processing, as well as the research on intrinsic stability of PQDs. Finally, the current drawbacks and solutions of PQD color conversion micro-LEDs are discussed, and the future research prospects in this field are anticipated.

Structural and functional studies of the ATP-binding cassette transporter MsbA have revealed two distinct lipopolysaccharide (LPS) binding sites: one located in the central cavity and the other at a membrane-facing, exterior site. Although these binding sites are known to be important for MsbA function, the thermodynamic basis for these specific MsbA-LPS interactions is not well understood. Here, we use native mass spectrometry to determine the thermodynamics of MsbA interacting with the LPS-precursor 3-deoxy-D-manno-oct-2-ulosonic acid (Kdo)2-lipid A (KDL). The binding of KDL is solely driven by entropy, despite the transporter adopting an inward-facing conformation or trapped in an outward-facing conformation with adenosine 5’-diphosphate and vanadate. An extension of the mutant cycle approach is employed to probe basic residues that interact with KDL. We find the molecular recognition of KDL is driven by a positive coupling entropy (as large as –100 kJ/mol at 298 K) that outweighs unfavorable coupling enthalpy. These findings indicate that alterations in solvent reorganization and conformational entropy can contribute significantly to the free energy of protein-lipid association. The results presented herein showcase the advantage of native MS to obtain thermodynamic insight into protein-lipid interactions that would otherwise be intractable using traditional approaches, and this enabling technology will be instrumental in the life sciences and drug discovery.

Indium phosphide (InP) quantum‐dot light‐emitting diodes (QLEDs) are considered as one of the most promising candidates for emerging displays owing to their good luminous performance and environmentally friendly properties. The operation of green InP QLEDs relies on the radiative recombination of electrically generated excitons, as in most QLEDs; however, the electrons injected into green InP QLEDs can easily pass through the quantum‐dot (QD) layer, resulting in a carrier imbalance and low external quantum efficiency (EQE). Herein, the mechanism of electron leakage in green InP QLEDs is revealed. Based on comparative experiments and simulations of the carrier concentration distribution, the path of electron leakage is determined and it is found that the root cause is the large Fermi energy difference between green InP QDs and indium tin oxide (ITO). To solve this problem, an ultrathin LiF layer is applied to modify the work function of the ITO, which simultaneously hinders electron leakage and enhances hole injection. Benefiting from a more balanced carrier injection, the maximum EQE of green InP QLEDs improves from 4.70% to 9.14%. In these findings, a universal mechanism is provided for hindering electron leakage in green InP QLEDs, indicating the feasibility of developing highly efficient green InP QLEDs.

Hydrogels are networked hydrophilic polymers with enriched polar groups and confined water but are relatively less explored as electrocatalysts. Here, the authors demonstrate that insulative polymeric hydrogels can be an underlying catalogue of metal-free oxygen evolution electrocatalyst with huge extension potentials.

Abstract Background No study has evaluated the impact of regimen on recurrence, metastasis and survival in patients with adenoid cystic carcinoma (ACC). The present study aimed to compare the efficacy of radioactive seed implantation and other regimens in treating ACC, so as to investigate the clinical applicability of radioactive seed implantation and determine the indications for this regimen. Methods A total of 188 patients with ACC in oromaxillofacial region were allocated to four groups according to the treatment regimen: group 1 was treated with a combination of surgery and 125I seed therapy, group 2 with a combination of surgery and external radiotherapy, group 3 with surgery, whereas group 4 was untreated. The Kaplan–Meier method was used to assess the survival rates, and the Cox regression analyses were used to identify the associated prognostic factors. Results The overall survival rates of 188 patients and groups 1, 2, 3 and 4 were 85.7%, 75%, 68.2% and 37.5%, respectively. Cox regression analysis revealed that age, T stage, N stage and regimen were independent prognostic factors of survival. Amongst patients with primary ACC, the efficacy of radioactive seed implantation was higher in those with perineural invasion than in those without. Conclusion Patient age, T stage, N stage and regimen are independent prognostic factors of survival in patients with ACC. Patients treated with surgery combined with postoperative 125I seed radiotherapy have a higher overall survival rate, and those with perineural invasion are more suitable for radioactive seed implantation therapy.

Recent mechanistic studies have indicated that combinations of radiotherapy (RT) plus immunotherapy (via CSF-1R inhibition) can serve as a strategy to overcome RT resistance and improve the survival of glioma mice. Given the high mortality rate for glioma, including low-grade glioma (LGG) patients, it is of critical importance to investigate the mechanism of the combination of RT and immunotherapy and further translate the mechanism from mouse studies to improve survival of RT-treated human glioma patients. Using the RNA-seq data from a glioma mouse study, 874 differentially expressed genes (DEGs) between the group of RT-treated mice at glioma recurrence and the group of mice with combination treatment (RT plus CSF-1R inhibition) were translated to the human genome to identify significant molecular pathways using the KEGG enrichment analysis. The enrichment analysis yields statistically significant signaling pathways, including the phosphoinositide 3-kinase (PI3K)/AKT pathway, Hippo pathway, and Notch pathway. Within each pathway, a candidate gene set was selected by Cox regression models as genetic biomarkers for resistance to RT and response to the combination of RT plus immunotherapies. Each Cox model is trained using a cohort of 295 RT-treated LGG patients from The Cancer Genome Atlas (TCGA) database and validated using a cohort of 127 RT-treated LGG patients from the Chinese Glioma Genome Atlas (CGGA) database. A four-DEG signature (ITGB8, COL9A3, TGFB2, JAG1) was identified from the significant genes within the three pathways and yielded the area under time-dependent ROC curve AUC = 0.86 for 5-year survival in the validation set, which indicates that the selected DEGs have strong prognostic value and are potential intervention targets for combination therapies. These findings may facilitate future trial designs for developing combination therapies for glioma patients.

Cardiovascular diseases (CVDs) are one of the most urgent threats to humans worldwide, which are responsible for almost one-third of global mortality. Over the last decade, research on flexible electronics for monitoring and treatment of CVDs has attracted tremendous attention. In contrast to conventional medical instruments in hospitals that are usually bulky, hard to move, monofunctional, and time-consuming, flexible electronics are capable of continuous, noninvasive, real-time, and portable monitoring. Notable progress has been made in this emerging field, and thus a number of significant achievements and concomitant research prospects deserve attention for practical implementation. Here, we comprehensively review the latest progress of flexible electronics for CVDs, focusing on new functions provided by flexible electronics. First, the characteristics of CVDs and flexible electronics and the foundation of their combination are briefly reviewed. Then, four representative applications of flexible electronics for CVDs are elaborated: blood pressure (BP) monitoring, electrocardiogram (ECG) monitoring, echocardiogram monitoring, and direct epicardium monitoring. Their operational principles, progress, merits and demerits, and future efforts are discussed. Finally, the remaining challenges and opportunities for flexible electronics for cardiovascular healthcare are outlined.

The high-value-added compounds of sea cucumber (Stichopus japonicus) intestine have not been exploited in sea cucumber processing. Here, low molecular weight peptides from the sea cucumber intestine (SCIP) were prepared using papain, and the effect of SCIP on promoting cartilage callus formation and their underlying mechanisms were studied. The results exhibited that the SCIP supplement markedly increased the area of the cartilage callus and ameliorated the early inflammatory environment at the fracture site by modulating the levels of inflammatory factors. Furthermore, SCIP promoted the polarization of M1 to M2 macrophages and finally promoted the differentiation of mesenchymal stem cells into chondrocytes at the fracture site through M2-like macrophage-mediated TGF-family factors and secretion of exosomes. This is the first report that SCIP can promote cartilage callus formation in mice with tibial fractures by promoting the polarization of M1 to M2 macrophages. SCIP might be considered raw material for developing nutraceutical additives.

The bacterial ABC transporter MsbA is essential for lipopolysaccharide biogenesis. Here, the authors apply native mass spectrometry, X-ray crystallography, cryo-EM and biochemical approaches to characterize the structural basis and functional roles of MsbA binding to copper and specific lipids.

This study tried to explore the ground movement induced by triple stacked tunneling (TST) with different construction sequences. A case study in Tianjin, China was used to investigate the ground movement during the TST (upper tunneling (UT)). For this, a modified Peck formula was proposed to predict the surface settlement induced by TST. Next, three sets of finite element analyses (FEA) were used to compare the effects of construction sequences (i.e. UT, middle tunneling (MT), and lower tunneling (LT)) on vertical and lateral ground displacements. The results of Tianjin case and UT reveal that compared to a Gaussian distribution for a single tunnel, the surface settlement curve of triple stacked tunnels is a bimodal distribution. It seems that the proposed modified Peck formula can effectively predict the surface settlement induced by TST. The results of the three sets of FEA demonstrate that the construction sequence has a significant influence on the ground movement. Among the three construction sequences, the largest lateral displacement is observed in the MT and the smallest one in UT. The existing tunnel has an inhibitory effect on the vertical displacement. The maximum value of the lateral displacement occurs at the depth of the new tunnel in each construction sequence.

In this study, the extraction process of fennel essential oil was optimized by response surface methodology. Fennel essential oil was used as oil phase, Tween 80+40 as surfactant and glycerol as cosurfactant to prepare fennel essential oil microemulsion system. The structure, particle size, total reducing power and storage property of fennel essential oil microemulsion were investigated by rheology, particle size analyzer and reduction reaction. The results showed that the yield of essential oil of fennel was as high as 15.99%±0.10% when the ratio of material to liquid was 1:8.40 g/mL, the extraction time was 4.09 h, the particle size was 80 mesh, and the extraction temperature 80 ℃. The diameter of fennel essential oil microemulsion was 30.92±0.13 nm, and when the moisture content was higher than 60%, it was a stable O/W microemulsion. The emulsification of fennel essential oil significantly improved the total reducing power of fennel essential oil. According to the principle of chemical reaction kinetics, the Arrhenius equation was established as k=2518.85·e−35583.09/RT. The model predicted that the fennel essential oil microemulsion could store 1899.18, 932.03, 492.94 and 271.51 h at 20, 35, 50 and 65 ℃, the maximum relative error was 8.73%, and the error was small, which could accurately predict the shelf life of the microemulsion.

Background Type 2 diabetes mellitus (T2DM) is known to be associated with cognitive decline and brain structural changes. This study systematically reviews and estimates human brain volumetric differences and atrophy associated with T2DM. Methods PubMed, PsycInfo and Cochrane Library were searched for brain imaging studies reporting on brain volume differences between individuals with T2DM and healthy controls. Data were examined using meta-analysis, and association between age, sex, diabetes characteristics and brain volumes were tested using meta-regression. Results A total of 14,605 entries were identified; after title, abstract and full-text screening applying inclusion and exclusion criteria, 64 studies were included and 42 studies with compatible data contributed to the meta-analysis (n=31,630; mean age 71.0 years; 44.4% male; 26,942 control; 4,688 diabetes). Individuals with T2DM had significantly smaller total brain volume, total grey matter volume, total white matter volume and hippocampal volume (approximately 1% to 4%); meta-analyses of smaller samples focusing on other brain regions and brain atrophy rate in longitudinal investigations also indicated smaller brain volumes and greater brain atrophy associated with T2DM. Meta-regression suggests that diabetes-related brain volume differences start occurring in early adulthood, decreases with age and increases with diabetes duration. Conclusion T2DM is associated with smaller total and regional brain volume and greater atrophy over time. These effects are substantial and highlight an urgent need to develop interventions to reduce the risk of T2DM for brain health.

BackgroundAbnormally changed steroid hormones during pregnancy are closely related to the pathological process of gestational diabetes mellitus (GDM). Our aim was to systematically profile the metabolic alteration of circulating steroid hormones in GDM women and screen for risk factors.MethodsThis study was a case-control study with data measured from 40 GDM women and 70 healthy pregnant women during their 24-28 gestational weeks. 36 kinds of steroid hormones, including 3 kinds of corticosteroids, 2 kinds of progestins, 5 kinds of androgens and 26 kinds of downstream estrogens in serum were systematically measured using a combined sensitive UPLC-MS/MS method. The flux of different metabolic pathways of steroid hormones was analyzed. Logistic regression and ROC curve model analyses were performed to identify potential steroid markers closely associated with GDM development.ResultsSerum corticosteroids, progestins and almost all the estrogen metabolites via 16-pathway from parent estrogens were higher in GDM women compared with healthy controls. Most of the estrogen metabolites via 4-pathway and more than half of the metabolites via 2-pathway were not significantly different. 16α-hydroxyestrone (16OHE1), estrone-glucuronide/sulfate (E1-G/S) and the ratio of total 2-pathway estrogens to total estrogens were screened as three indicators closely related to the risk of GDM development. The adjusted odds ratios of GDM for the highest quartile compared with the lowest were 72.22 (95% CI 11.27-462.71, Ptrend

The hydrodynamic model, based on the strict conservation of momentum and continuity equations, can accurately simulate the distribution of a flow field. However, significant computing time and storage space requirements limit real-time prediction. Machine learning is well known for its fast computing speed and powerful learning ability, but its accuracy depends on an abundance of training data, hindering its wider use in locations without sufficient measurements. Application restrictions in data-deficient areas can be addressed through transfer learning, provided that two areas share common characteristics. In this study, a machine learning method based on a deep super-resolution convolutional neural network (DSRCNN) and transfer learning is proposed, validated, and applied to model two bend flows and one realistic test case. Firstly, the hydrodynamic model was established and validated against measured data. The validated model was considered to have the ability to generate real data and was used to generate a comprehensive data set for training and validating the machine learning model. Three different methods were compared and tested, with Realizable k-ε performing better than the others in predicting the outer bank flow distribution. DSRCNN was compared to a plain SRCNN (PSRCNN), as well as Bilinear, Nearest, and Bicubic methods, and the results showed that DSRCNN had the best performance. We compared Raw, RT, and TL methods, finding that the TL method performed the best overall. Therefore, the research results showed that the developed super-resolution convolutional neural network can provide more reliable predications and serve as an ideal tool for simulating flow field distribution in bends.

Water quality prediction, a well-established field with broad implications across various sectors, is thoroughly examined in this comprehensive review. Through an exhaustive analysis of over 170 studies conducted in the last five years, we focus on the application of machine learning for predicting water quality. The review begins by presenting the latest methodologies for acquiring water quality data. Categorizing machine learning-based predictions for water quality into two primary segments—indicator prediction and water quality index prediction—further distinguishes between single-indicator and multi-indicator predictions. A meticulous examination of each method’s technical details follows. This article explores current cutting-edge research trends in machine learning algorithms, providing a technical perspective on their application in water quality prediction. It investigates the utilization of algorithms in predicting water quality and concludes by highlighting significant challenges and future research directions. Emphasis is placed on key areas such as hydrodynamic water quality coupling, effective data processing and acquisition, and mitigating model uncertainty. The paper provides a detailed perspective on the present state of application and the principal characteristics of emerging technologies in water quality prediction.

Recent years have witnessed growing research interest in dual-wavelength mode-locked fiber lasers for their pivotal role in diverse applications and the exploration of nonlinear dynamics. Despite notable progress in their development, achieving reliable mode-locked dual-wavelength operation typically necessitates intricate manual adjustments of the cavity’s polarization components. In this article, we present the realization of automatic mode-locking in a dual-wavelength soliton fiber laser. To provide guidance for the algorithm design, we systematically investigated the impact of polarization configurations and initial states on the laser’s operation through numerical simulations and linear scan experiments. The results indicate that operational regimes can be finely adjusted around the wave plate position supporting the mode-locked dual-wavelength solution. Furthermore, the laser exhibits multiple stable states at the mode-locked dual-wavelength point, with critical dependence on the initial conditions. Accordingly, we developed a two-stage genetic algorithm that was demonstrated to be effective for realizing automatic dual-wavelength mode-locking. To further improve the performance of the algorithm, a feedforward neural network was trained and integrated into the algorithm, enabling accurate identification of the dual-wavelength states. This study provides valuable insights into understanding how polarization configurations and initial conditions impact the operational regimes of dual-wavelength mode-locked fiber lasers. The algorithm developed can be extended to optimize other systems with multiple stable states supported at the same parameter point.

The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with transposed convolutions. This study designed synthetic experiments to downscale daily reference evapotranspiration (ET0) data, which are a key indicator for climate change, from low resolutions (2°, 1°, and 0.5°) to a fine resolution (0.25°). The entire time period was divided into two major parts, i.e., training–validation (80%) and test periods (20%), and the training–validation period was further divided into training (80%) and validation (20%) parts. In the comparison of the downscaling performance between the SRCTN and Q-M models, the root-mean-squared error (RMSE) values indicated the accuracy of the models. For the SRCTN model, the RMSE values were reported for different scaling ratios: 0.239 for a ratio of 8, 0.077 for a ratio of 4, and 0.015 for a ratio of 2. In contrast, the RMSE values for the Q-M method were 0.334, 0.208, and 0.109 for scaling ratios of 8, 4, and 2, respectively. Notably, the RMSE values in the SRCTN model were consistently lower than those in the Q-M method across all scaling ratios, suggesting that the SRCTN model exhibited better downscaling performance in this evaluation. The results exhibited that the SRCTN method could reproduce the spatiotemporal distributions and extremes for the testing period very well. The trained SRCTN model in one study area performed remarkably well in a different area via transfer learning without re-training or calibration, and it outperformed the classic downscaling approach. The good performance of the SRCTN algorithm can be primarily attributed to the incorporation of transposed convolutions, which can be partially seen as trainable upsampling operations. Therefore, the proposed SRCTN method is a promising candidate tool for downscaling daily ET0 and can potentially be employed to conduct downscaling operations for other variables.

Crosslinking is a promising method to modulate the gel properties of food-grade starch gels. Still, the poor crosslinking effect of a single type of crosslinker limits the application of this method in starch gel modification. In this study, an Ca2+ synergistic multiple crosslinking modification method was proposed to prepare crosslinked starches with good gel properties and setting. The rheological properties of the samples were tested. The modified sample (SC-Ca-N3, G′ = 1347 ± 27) showed a 79% improvement compared to the starch without synergistic crosslinking modification (SC-N, G′ = 752 ± 6). The elastic modulus of starch gels can be adjusted by changing the degree of the crosslinking reaction. The results of nonlinear rheological Lissajous curve analysis showed that the synergistically crosslinked gel system strongly resisted deformation. In addition, the microstructure of the modified samples was characterized using scanning electron microscopy. The XPS, FTIR, and XRD results indicated that multiple molecular forces participate in the synergistic crosslinking reaction.

Gurney flaps can enhance the hydrodynamic efficiency of airfoils, and they are currently used in several applications, including racing cars and wind turbines. However, there is a lack of studies in the literature on the application of Gurney flaps on the Horizontal Axis Ocean Current Turbine (HAOCT). The influence of Gurney flaps on the hydrodynamic efficiency of the HAOCT is evaluated through numerical analysis. The effect of the Gurney flaps on the turbine is evaluated after the validation of the utilized numerical method is completed using the wind tunnel experimental data of the two-dimensional NACA 63415 airfoil and the water tunnel experimental data of the NACA 638xx series rotor on the clean blade. By calculating the velocity and pressure fields of the 2D airfoil by CFD, it was possible to analyze the lift improvement with the addition of the Gurney flaps by evaluating the pressure difference between the pressure surface and the negative pressure surface, and the drag improvement was due to the Gurney flaps obstructing the chordal flow of the fluid in the wake. For the 2D NACA-63415 airfoil, the drag coefficient increases with the increase in the head angle, while the lift coefficient increases and then decreases. The flap height divided by the local chord length of the Gurney flaps is 0.01, and the lift-to-drag ratio is the highest when the head angle is 4°. For the NACA-638xx turbine, the addition of Gurney flaps significantly increases the axial thrust coefficient. At lower tip speed ratios, the effect of the Gurney flaps on the rotor’s power coefficient is limited, with the greatest increase in the power coefficient at a tip speed ratio of 6 and a decrease in the power coefficient increase as the tip speed ratio increases. Increasing the height of the Gurney flaps can increase the peak power coefficient, but the power performance decreases at high tip speed ratios. The Gurney flaps distributed at the root of the rotor have less effect on the power performance. A 0.4 local radius spread of the Gurney flaps increases the peak turbine power coefficient by only 0.34%, while full-length Gurney flaps can increase the peaked blade power coefficient by 10.68%, indicating that Gurney flaps can be used to design a new HAOCT.

Targeted genotyping is an extremely powerful approach for the detection of known genetic variations that are biologically or clinically important. However, for non-model organisms, large-scale target genotyping in a cost-effective manner remains a major challenge. To address this issue, we present an ultrahigh-multiplex, in-solution probe array-based high-throughput diverse marker genotyping (HD-Marker) approach that is capable of targeted genotyping of up to 86 000 loci, with coverage of the whole gene repertoire, in what is a 27-fold and six-fold multiplex increase in comparison with the conventional Illumina GoldenGate and original HD-Marker assays, respectively. We perform extensive analyses of various ultrahigh-multiplex levels of HD-Marker (30 k-plex, 56 k-plex, and 86 k-plex) and show the power and excellent performance of the proposed method with an extremely high capture rate (about 96%) and genotyping accuracy (about 96%). With great advantages in terms of cost (as low as 0.0006 USD per genotype) and high technical flexibility, HD-Marker is a highly efficient and powerful tool with broad application potential for genetic, ecological, and evolutionary studies of non-model organisms.

Nd3+-doped YVO4 nanotheranostic agent with blood-brain-barrier permeability could achieve NIR-II imaging/MRI and efficient SDT of orthotopic gliomas.

The unprecedented rate of metro construction has led to a highly complex network of metro lines. Tunnels are being overlapped to an ever-increasing degree. This paper investigates the deformation response of double-track overlapped tunnels in Tianjin, China using finite element analysis (FEA) and field monitoring, considering the attributes of different tunneling forms. With respect to the upper tunneling, the results of the FEA and field monitoring showed that the maximum vertical displacements of the ground surface during the tail passage were 2.06 mm, 2.25 mm and 2.39 mm obtained by the FEA, field monitoring and Peck calculation, respectively; the heaves on the vertical displacement curve were observed at 8 m (1.25D, where D is the diameter of the tunnel) away from the center of the tunnel and the curve at both sides was asymmetrical. Furthermore, the crown and bottom produce approximately 0.38 mm and 1.26 mm of contraction, respectively. The results of the FEA of the upper and lower sections demonstrated that the tunneling form has an obvious influence on the deformation response of the double-track overlapped tunnel. Compared with the upper tunneling, the lower tunneling exerted significantly less influence on the deformation response, which manifested as a smaller displacement of the strata and deformation of the existing tunnel. The results of this study on overlapped tunnels can provide a reference for similar projects in the future.

With the rapid development of urban rail transit and underground space construction, the advantages of the concealed excavation method are gradually highlighted in the urban center area affected by a complex engineering environment. At present, the pipe curtain method with a flexible section and wide application of the soil layer is being widely used in engineering, but the research on the stability of the excavation face during the construction of the pipe curtain method in soft soil areas still has not formed a complete system. Therefore, this paper analyzes the stability of the excavation face under different reinforcement conditions and the influence of different spacing, numbers, and strength of MJS (metro jet system) zones on the stability of the excavation face of the pipe curtain method based on the actual project of the Guiqiao Road Station of the Shanghai Metro, China, and gives a reference for the reinforcement of the palm face in the excavation process of the pipe curtain method in soft soil areas. The study shows that the safety coefficient of the excavation face decreases with the increase in the slope angle of the excavation face, with the increase in spacing of the MJS zone, and with the increase in height of the MJS zone arrangement, while the safety coefficient of the excavation face increases with the increase in strength of the MJS zones themselves and the increase in the strength of the soil between the MJS zones. Further, the machine learning model is applied to predict the stability of the excavation face under different cases, and the relevant fitting accuracy is above 0.9, which can predict the stability of the excavation better.

Depression is a mental disorder characterized by low mood, lack of motivation, negative cognitive outlook, and sleep problems. Suicide may occur in severe cases, although suicidal thoughts are not seen in all cases. Globally, an estimated 350 million individuals grapple with depression, as reported by the World Health Organization. At present, drug and psychological treatments are the main treatments, but they produce insufficient responses in many patients and fail to work at all in many others. Consequently, treating depression has long been an important topic in society. Given the escalating prevalence of depression, a comprehensive strategy for managing its symptoms and impacts has garnered significant attention. In this context, nutritional psychiatry emerges as a promising avenue. Extensive research has underscored the potential benefits of a well-rounded diet rich in fruits, vegetables, fish, and meat in alleviating depressive symptoms. However, the intricate mechanisms linking dietary interventions to brain function alterations remain largely unexplored. This review delves into the intricate relationship between dietary patterns and depression, while exploring the plausible mechanisms underlying the impact of dietary interventions on depression management. As we endeavor to unveil the pathways through which nutrition influences mental well-being, a holistic perspective that encompasses multidisciplinary strategies gains prominence, potentially reshaping how we approach and address depression.

Sulfur is an essential element for plant growth, development and resistance to environmental stresses. Glucosinolates (GSLs), a group of sulfur rich secondary metabolites found in Brassicaceae plants, are known for their defensive properties against pathogens and herbivores. Due to their integration of a large proportion of total sulfur, their biosynthesis and degradation are closely linked to sulfur metabolism. It has been demonstrated that GSLs can be broken down to release sulfur and facilitate the production of other thio-metabolites when the plant is under stress. However, the regulation of this process is still not fully understood. In this study, we constructed two broccoli LSU (low sulfur responsive) gene overexpressing lines, 35S::BoLSU1 and 35S::BoLSU2, to detect changes in GSL metabolism after sulfur deficiency treatment. The results showed that BoLSU1 and BoLSU2 inhibit the biosynthesis of aliphatic GSLs, while also promoting their degradation and increasing the content of glutathione (GSH), leading to the reallocation of sulfur from the GSL pool to other thio-metabolites such as GSH. Furthermore, this regulation of GSL metabolism mediated by BoLSU1 and BoLSU2 is found to be dependent on myrosinases BGLU28 and BGLU30. Our study provides insight into the physiological role of LSU proteins and their regulation of sulfur metabolism.

The horizontal axis tidal turbine (HATT) is a device that harnesses the energy of ocean currents and converts it into electrical energy. The blade plays a crucial role in the efficiency of power generation in HATTs. This study focuses on the use of slotted blades to enhance the efficiency of HATTs and investigates the flow control mechanism of these slots using computational fluid dynamics (CFD) methods. Initially, CFD simulations were conducted to analyze the impact of the slot’s geometry parameters on a two-dimensional (2-D) slot and to demonstrate its passive fluid control mechanism. Subsequently, the slot was implemented on three-dimensional (3-D) blades to examine its effect on the hydrodynamic performance of the blades. The results of the 2-D simulation indicate that the width and position of the slots have a significant influence on the lift-to-drag ratio of the hydrofoils, resulting in a maximum increase of 166%. For the 3-D blades, the simulation results reveal that the slot can enhance the power coefficient of the blades, particularly at low tip-speed ratios, with a maximum increase of 7.8%.

Abstract Gliomas are common and refractory primary tumors closely associated with the fine structures of the brain. Photothermal therapy (PTT) has recently shown promise as an effective treatment for gliomas. However, nonspecific accumulation of photothermal agents may affect adjacent normal brain structures, and the inflammatory response induced during PTT may result in an increased risk of brain tumor recurrence or metastasis. Here, the design and fabrication of an intelligent nanomachine is reported based on Gd2O3@Ir/TMB‐RVG29 (G@IT‐R) hybrid nanomaterials. These nanomaterials enable tumor‐specific PTT and eliminate inflammation to protect normal brain tissue. The mechanism involves the rabies virus glycopeptide‐29 peptide (RVG29) passing through the blood–brain barrier (BBB) and targeting gliomas. In the tumor microenvironment, Ir nanozymes can act as logic control systems to trigger chromogenic reaction amplification of 3,3′,5,5′‐tetramethylbenzidine (TMB) for tumor‐specific PTT, whereas in normal brain tissues, they scavenge reactive oxygen species (ROS) generated by poor therapy and function as protective agents. Autophagy inhibition of Gd2O3 enables excellent photothermal therapeutic effects on orthotopic gliomas and protection against inflammation in normal cells. The results of this study may prove useful in developing highly efficient nanomedicines for glioma treatment.

Background: Persistent pathological cardiac hypertrophy has been associated with increased risk of heart failure and even sudden death. Multiple Chinese patent medicines (CPMs) have gained attention as alternative and complementary remedies due to their high efficiency and few side effects. However, the effects of CPM-related treatment regimens for cardiac hypertrophy had not been systematically evaluated.Aim: The objective of this study was to estimate and compare the effectiveness of different mechanisms of CPMs to improve clinical outcomes, including clinical efficacy and echocardiographic indices, in the treatment of cardiac hypertrophy patents.Methods: A network meta-analysis was conducted on CPM-related randomized controlled trials (RCTs) published between 2012 and 2022 involving cardiac hypertrophy patients from four foreign and four Chinese databases. The outcomes concerned efficacy and related indicators, including echocardiographic indices, cardiac biomarkers, and functional exercise capacity, which were evaluated as odds ratios, mean differences, and 95% credible intervals. Network plots, league tables, surface-under-the-cumulative ranking (SUCRA), and funnel plots were created for each outcome, and all analyses were conducted using Stata 16.0 software.Results: A total of 25 RCTs were evaluated; these involved 2395 patients in a network meta-analysis (NMA). The results from existing evidence indicate that blood-activating and stasis-removing Chinese patent medicine (BASR-CPM) + Western medicine (WM) showed a good improvement in clinical efficacy (OR = 8.27; 95%CI = 0.97, 70.73). A combined treatment regimen of CPM with a function of qi-replenishing, blood-activating and stasis-removing, and Western medicine was an effective treatment regimen for echocardiographic indices such as decreasing left ventricular end-systolic dimension (LVESD) (SMD = −2.35; 95%CI = −3.09, −1.62) and left ventricular mass index (LVMI) (SMD = −1.73; 95%CI = −2.92, −0.54). Furthermore, KWYR-CPM + WM and BASR-CPM also showed good improvement for echocardiographic indices of LVEDD (SMD = −1.84; 95%CI = −3.46, −0.22) and left ventricular ejection fraction (SMD = 1.90; 95%CI = −0.46, −3.35), respectively.Conclusion: The study showed that BASR-CPM + WM may be the potentially superior treatment regimen for improving clinical efficacy among cardiac hypertrophy patients. QR&BASR-CPM + WM might be the optimal treatment for decreasing LVESD and LVMI. However, due to potential risks from bias and limited RCTs, further studies with larger samples and high-quality RCTs are needed to support these findings.Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329589],identifier [CRD42022329589].

The burden of cancer is increasing, being widely recognized as one of the main reasons for deaths among humans. Despite the tremendous efforts that have been made worldwide to stem the progression and metastasis of cancer, morbidity and mortality in malignant tumors have been clearly rising and threatening human health. In recent years, nanomedicine has come to occupy an increasingly important position in precision oncotherapy, which improves the diagnosis, treatment, and long-term prognosis of cancer. In particular, LDNs with distinctive physicochemical capabilities have provided great potential for advanced biomedical applications, attributed to their large surface area, abundant surface binding sites, and good cellular permeation properties. In addition, LDNs can integrate CT/MR/US/PAI and PTT/PDT/CDT/NDDS into a multimodal theranostic nanoplatform, enabling targeted therapy and efficacy assessments for cancer. This review attempts to concisely summarize the classification and major properties of LDNs. Simultaneously, we particularly emphasize their applications in the imaging, diagnosis, and treatment of cancerous diseases.

As the dominant shrub community plant in the Mu Us Sandy Land, S. vulgaris is the key factor of ecological environment restoration in the Mu Us Sandy Land, It is of great significance to explore the estimation and inversion of content based on spectrum for ecological environment evaluation and intervention in Mu Us Sandy Land. The SVC HR-1024 portable feature spectrometer and SPAD 502 chlorophyll meter were used to study Mu Us Sandy Land of S. vulgaris. The best band is screened by correlation matrix method, the best vegetation index is screened by Structural Equation Modeling model, and then the best inversion model is established by different mathematical modeling methods. Results revealed that the vegetation indices and chlorophyll content were correlated, combining the six vegetation indices revealed that 610–690nm and 700–940 nm were the bands with the highest correlation. In the selection of optimal vegetation index, NDVI, ratio vegetation index and mNDVI perform best and are suitable for subsequent modeling. Of the four models, the partial least squares model had the best fitting effect (R2 > 0.91). The univariate linear regression model had the simplest processing procedure, but its accuracy was unstable (R2 = 0.1–0.9). multivariate stepwise regression accuracy is also appropriate (R2 > 0.8). The stability of BP neural network modeling is not high. Compare the four methods, PLS and multivariate stepwise regression have their own advantages, and the accuracy is higher, you can make a choice according to the demand as the late modeling method.

Abstract Low‐value, renewable, carbon‐rich resources, with different biomass feedstocks and their derivatives as typical examples, represent virtually inexhaustive carbon sources and carbon‐related energy on Earth. Upon conversion to higher‐value forms (referred to as “up‐carbonization” here), these abundant feedstocks provide viable opportunities for energy‐rich fuels and sustainable platform chemicals production. However, many of the current methods for such up‐carbonization still lack sufficient energy, cost, and material efficiency, which affect their economics and carbon‐emissions footprint. With external electricity precisely delivered, discharge plasmas enable many stubborn reactions to occur under mild conditions, by creating locally intensified and highly reactive environments. This technology emerges as a novel, versatile technology platform for integrated or stand‐alone conversion of carbon‐rich resources. The plasma‐based processes are compatible for integration with increasingly abundant and cost‐effective renewable electricity, making the whole conversion carbon‐neutral and further paving the plasma‐electrified up‐carbonization to be performance‐, environment‐, and economics‐viable. Despite the chief interest in this emerging area, no review article brings together the state‐of‐the‐art results from diverse disciplines and underlies basic mechanisms and chemistry underpinned. As such, this review aims to fill this gap and provide basic guidelines for future research and transformation, by providing an overview of the application of plasma techniques for carbon‐rich resource conversion, with particular focus on the perspective of discharge plasmas, the fundamentals of why plasmas are particularly suited for up‐carbonization, and featured examples of plasma‐enabled resource valorization. With parallels drawn and specificity highlighted, we also discuss the technique shortcomings, current challenges, and research needs for future work.