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With the introduction and implementation of core literacy, scientific thinking (ST) has become an essential goal and key dimension of science teaching. At present, there is no agreement on how to cultivate students' ST. This study took 238 sixth grade students from a public primary school in urban China as research sample, built a theoretical model of scientific thinking development based on the theory of the Bronfenbrenner' ecological systems theory, and used multiple data to explore and analyze the impact path of ST development of primary school students using the fuzzy sets of qualitative comparative analysis method (fsQCA). The development of urban primary school students' ST is the result of multiple factors at the level of individual drive, family environment, school teaching, and social resources. The result of data analysis showed that the influence path of ST development of urban primary school students driven by multiple factors includes three paths: parent participation leading, scientific practice leading, and home-school-community integration. We have interpreted the influence mechanism of each path in detail and put forward the enlightenment for science education policy and practice.

Purpose: The Program for the Education and Enrichment of Relational Skills (PEERS®) is a group-based social skills training program for adolescents on the autism spectrum. Although the program has been shown to be effective in improving social skills in autistic adolescents, evidence of its effectiveness from the Mandarin-speaking Chinese population is sparse. The present study used a non-randomized, pre- and post-intervention research design to investigate the feasibility and cultural validity of the program, as well as examine the moderators of intervention outcomes. Methods: Thirty-three autistic adolescents with intelligence quotient above 70 (M[subscript age] = 13.57, SD[subscript age] = 1.43; Male: Female 25:8) and their parents received 14 concurrent 90-minute sessions. Adolescents' autistic traits, challenging behaviors, emotional functioning, socio-cognitive process, social environment factors (school support), and caregivers' well-being were evaluated. Results: The findings suggest that with minor adjustments, the Mandarin version of PEERS® was generally acceptable and feasible for autistic adolescents and their parents. PEERS® may improve the social skills knowledge, reciprocal communication abilities, and emotional well-being of autistic adolescents. Also, participants with a higher level of school support, and parents with lower perceived subjective well-being at baseline may gain more benefits from PEERS®. The cultural adaptation and acceptability of the Mandarin Version of PEERS® were discussed. Conclusion: This feasibility study (Chinese Clinical Trial Registry: ChiCTR2200061417, 2022-06-23, retrospectively registered) provides a basis for further randomized control trials of the Mandarin version of PEERS®.

A method for the determination of 14 human milk oligosaccharides (HMOs) in infant formula milk powder was established by hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS). The sample was deproteinized by ethanol precipitation and degreased by freezing prior to separation by HILIC. The analytes were detected by multiple reaction monitoring (MRM) and quantified by an external standard method. Under optimized conditions, all HMOs showed good linear relationships within their respective concentration ranges, with determination coefficients (R2) greater than 0.994. The average recovery rates from blank goat’s and cow’s milk powders at three spiked levels ranged from 90.3% to 109.2%, with relative standard deviation (RSD) in the range of 0.7%–9.7% (n = 6), and the limit of detection (LOD) between 0.002 and 0.048 μg/mL. The developed method is characterized by fast analysis speed, high sensitivity and good accuracy, and meets the requirements for the rapid detection of the 14 HMOs in infant formula milk powder.

Background: Klebsiella pneumoniae is a Gram-negative bacterium that can cause infections, especially in individuals with diabetes. Recently, more hypervirulent strains have emerged, posing a threat even to healthy individuals. Understanding how K. pneumoniae regulates its virulence factors is crucial. Acetyl-phosphate (AcP) is essential for bacterial metabolism and can affect virulence factor expression. However, the role of the Pta-AckA pathway, which regulates AcP levels, in K. pneumoniae pathogenesis remains unclear. Methods: Deletion mutants lacking the pta and ackA, involved in AcP production and hydrolysis, were generated in K. pneumoniae CG43S3. Their effects on AcP levels, the patterns of global acetylated protein, capsular polysaccharide (CPS) amount, serum resistance, type 3 fimbriae expression, biofilm formation, and virulence in G. mellonella larva were assessed. Results: Deletion of ackA in K. pneumoniae CG43S3 led to AcP accumulation, while pta deletion abolished AcP synthesis when grown in TB7+1 % glucose. This pathway influenced global protein acetylation, with pta deletion decreasing acetylation and ackA deletion increasing it. Additionally, pta deletion decreased the CPS amount, serum resistance, and type 3 fimbriae expression, while ackA deletion increased these factors. Furthermore, deleting pta and ackA attenuated the infected larva's virulence and death rate. Conclusion: Our findings highlight the critical role of the Pta-AckA pathway in K. pneumoniae pathogenesis. This pathway regulates AcP levels, global protein acetylation, CPS production, serum resistance, and type 3 fimbriae expression, ultimately impacting virulence. The information provides insights into potential therapeutic targets for combating K. pneumoniae infection.

AIM: To elucidate the neuropathological mechanisms underlying diabetic vitreous hemorrhage (DVH) and its correlation with clinical characteristics. METHODS: Twenty-one individuals with DVH (male/female 12/9; mean age 52.29±11.66y) were selected, alongside 21 appropriately matched controls with diabetes mellitus (DM). Voxel-based morphometry (VBM) techniques were employed to identify aberrant functional regions in the brain. Receiver operating characteristic (ROC) curves were utilized for classification based on the average VBM values of the two groups, and Pearson correlation analysis was conducted to assess the relationship between average VBM values in distinct brain regions and clinical manifestations. RESULTS: Relative to the DM controls, DVH patients exhibited reduced VBM values in the right superior temporal pole, the right superior temporal gyrus, the right medial orbital frontal gyrus, and the left superior frontal gyrus. Furthermore, ROC curve analysis of these four brain regions in DVH patients demonstrated a high degree of accuracy, as indicated by the area under the curve. The average VBM value in each of these regions exhibited a negative correlation with both the duration of DVH and the score on the Hospital Anxiety and Depression Scale (HADS). CONCLUSION: Pathological alterations in four distinct brain regions are observed in patients with DVH, potentially reflecting neuropathological changes associated with this condition.

AIM: To analyze whether alterations of voxel mirror homology connectivity (VMHC) values, as determined by resting-state functional magnetic resonance imaging (rs-fMRI), occur in cerebral regions of patients with hypertensive retinopathy (HR) and to determine the relationship between VMHC values and clinical characteristics in patients with HR. METHODS: Twenty-one patients with HR and 21 age-matched healthy controls (HCs) were assessed by rs-fMRI scanning. The functional connectivity between the hemispheres of the cerebrum was assessed by measuring VMHC, with the ability of VMHC to distinguish between the HR and HC groups assessed using receiver operating characteristic (ROC) curve analysis. Differences in the demographic and clinical characteristics of the HR and HC groups were analyzed by independent sample t-tests. The relationship between average VMHC in several brain areas of HR patients and clinical features was determined using Pearson correlation analysis. RESULTS: Mean VMHC values of the bilateral cuneus gyrus (BA19), bilateral middle orbitofrontal gyrus (BA47), bilateral middle temporal gyrus (BA39) and bilateral superior medial frontal gyrus (BA9) were lower in the HR than in the HC group. CONCLUSION: VMHC values can predict the development of early HR, prevent the transformation of hypertensive microangiopathy, and provide useful information explaining the changes in neural mechanism associated with HR.

Deep learning methods have recently made substantial advances in polarimetric synthetic aperture radar (PolSAR) image classification. However, supervised training relying on massive labeled samples is one of its major limitations, especially for PolSAR images that are hard to manually annotate. Self-supervised learning (SSL) is an effective solution for insufficient labeled samples by mining supervised information from the data itself. Nevertheless, fully utilizing SSL in PolSAR classification tasks is still a great challenge due to the data complexity. Based on the abovementioned issues, we propose an SSL model with multibranch consistency (SSL-MBC) for few-shot PolSAR image classification. Specifically, the data augmentation technique used in the pretext task involves a combination of various spatial transformations and channel transformations achieved through scattering feature extraction. In addition, the distinct scattering features of PolSAR data are considered as its unique multimodal representations. It is observed that the different modal representations of the same instance exhibit similarity in the encoding space, with the hidden features of more modals being more prominent. Therefore, a multibranch contrastive SSL framework, without negative samples, is employed to efficiently achieve representation learning. The resulting abstract features are then fine-tuned to ensure generalization in downstream tasks, thereby enabling few-shot classification. Experimental results yielded from selected PolSAR datasets convincingly indicate that our method exhibits superior performance compared to other existing methodologies. The exhaustive ablation study shows that the model performance degrades when either the data augmentation or any branch is masked, and the classification result does not rely on the label amount.

In this study, molecularly imprinted membrane (MIM) was prepared using polydopamine (PDA)-modified polyvinylidene fluoride (PVDF) membrane as the base membrane, thidiazuron (TDZ) as the template, methacrylic acid (MAA) as the functional monomer, and ethylene glycol dimethacrylate (EGDMA) as the cross-linker. This adsorption material was applied to the highly selective simultaneous extraction of TDZ and its structural analogue forchlorfenuron (CPPU) from orange. Scanning electron microscope (SEM) characterization of the prepared samples showed that the surface of the three-dimensional network structure of the PDA@PVDF membrane was coated with dense molecularly imprinted polymers. The performance tests showed that the adsorption capacity of MIM for TDZ and CPPU was 1.80 and 1.89 times as high as that of the non-imprinted counterpart, reaching adsorption equilibrium after 20 and 30 min, respectively. The specificity parameters for the interfering substances coumarin and 3-tert butylphenol were determined to be 23.2 and 19.3, respectively. MIM was successfully applied for the simultaneous extraction of TDZ and CPPU from orange samples. At spiked concentrations of 2.0, 3.0 and 5.0 µmol/L, the spiked recoveries of MIM extraction combined with high performance liquid chromatography (HPLC) for TDZ and CPPU ranged from 90.3%–99.4% and 88.2%–98.1%, respectively, with relative standard deviations in the range of 0.9%–2.5% and 1.2%–3.0% (n = 3), respectively. The developed method had the advantages of simplicity, high sensitivity, precision and recoveries, and low cost and was suitable for the detection of TDZ and CPPU residues in fruits and vegetables.

In this study, we systematically investigated the regulatory effects of two hempseed peptides (APAM and RLPA) on pancreatic lipase (PL) and cholesterol esterase (CE) activities and the molecular binding mechanism using enzyme kinetics, synergistic inhibition, fluorescence spectroscopy, isothermal titration calorimetry and molecular docking. The results showed that RLPA had stronger inhibitory activity on PL and CE with half maximal inhibitory concentration (IC50) values of (79.62 ± 3.20) and (301.27 ± 14.40) μmol/L, respectively. Kinetic analysis indicated that the inhibition mechanism of APAM on the two enzymes was competitive inhibition, whereas RLPA was a mixed-type inhibitor. Both APAM and RLPA synergistically inhibited PL and CE with orlistat at low concentrations, but the synergistic effect was weakened or even antagonized at high concentrations. Fluorescence spectroscopy results showed that both peptides could produce static quenching by binding to PL and CE, which changed the hydrophobic environment of aliphatic amino acids in the enzymes. Isothermal titration calorimetry demonstrated that the binding process between the peptides and the enzymes was spontaneous and exothermic, which was achieved mainly through hydrogen bonding and electrostatic interaction. Further analysis using molecular docking simulations showed that hydrogen bonding, salt bridges, and cation-π interactions played crucial roles in peptide-enzyme binding. This study enriches our understanding of the interaction mechanism of peptides with PL and CE, and provides a scientific basis for the development of functional foods based on hempseed protein.

In this study, three enzymatic hydrolysis methods, alkaline protease (E1), pepsin + trypsin (E2), and alkaline protease + pepsin + trypsin (E3), were used to prepare hemoglobin hydrolysates from Ningxia beef cattle, which were screened for their antioxidant activity. Amino acid analysis and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to identify the amino acid compositions and sequences of the hydrolysates with molecular mass < 3 kDa. The potential antioxidant peptides were selected by computerized analysis and their activities were verified. Their action mechanism was studied by molecular simulation. The results showed that E3 exhibited the highest hydrolysis efficiency, and the < 3 kDa fraction obtained from the ultrafiltration of the resulting hydrolysate showed better antioxidant activity with half maximal inhibitory concentration (IC50) of (18.382 ± 0.023) mg/mL and (0.246 ± 0.012) mg/mL against 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) cationic radical, respectively. The < 3 kDa fraction was rich in hydrophobic and aromatic amino acids, and four peptides with the best antioxidant activity were selected and identified, whose amino acid sequences were DWGHSW, VFYPW, GTGW and TYFPHF, respectively. Among them, VFYPW showed the highest DPPH radical and ABTS cationic radical scavenging capacity with IC50 of (0.350 ± 0.013) mg/mL and (9.482 ± 0.122) µg/mL, followed by DWGHSW. DWGHSW and VFYPW were found to form stable complexes with Keap1 protein (PDB ID: 2FLU) through hydrogen bonds and hydrophobic interactions. In summary, this study provides a theoretical basis for the application of hemoglobin peptides from Ningxia beef cattle as natural antioxidant supplements and contributes to the high-value utilization of blood resources from Ningxia beef cattle.

Abstract Background The medical community has long been concerned about the cardiovascular disease risk in patients with type 2 diabetes. While liver fibrosis scores were originally designed for application in individuals with liver steatosis, an increasing number of studies have shown that they are also associated with cardiovascular disease risk. However, the association between Fibrosis-4 (Fib-4) in liver fibrosis scores and carotid atherosclerosis (CA) in patients with type 2 diabetes remains unclear. Objective The aim of this study is to investigate the association between the Fib-4 index and CA in patients with Type 2 diabetes. Additionally, it seeks to determine whether this relationship is influenced by factors including gender, age, body mass index (BMI), hypertension, and other variables. Methods Screening based on inclusion and exclusion criteria identified 2658 hospitalized patients with type 2 diabetes. Subsequently, patients were divided into three groups according to Fib-4 values (Fib-4 0.05). The results of the ROC curve analysis indicated that the AUC for Fib-4 predicting CA was 0.602 (P

Abstract Benign prostatic hyperplasia (BPH) is a prevalent urinary system disorder. Despite evidence of a significant genetic component from previous studies, the specific pathogenic genes and biological mechanisms are still largely unknown. The study utilized the FinnGen R10 dataset, encompassing 177,901 individuals (36,601 cases and 141,300 controls), and the GTEx v8 EQTLs files to conduct single-tissue and cross-tissue transcriptome-wide association studies (TWAS). FUSION method was utilized to validate the findings in specific tissues. Gene Analysis and Multi-marker Analysis of Genomic Annotation (MAGMA) were used to identify potential susceptibility genes. The intersection genes of the above results were analyzed by Mendelian randomization (MR), summary data-based MR (SMR) and colocalization studies. Fine-mapping of causal gene sets (FOCUS) software was employed to accurately locate risk genes. Gene Expression Omnibus (GEO) analysis explores the differential expression of genes. Finally, The GeneMANIA tool was utilized to further understand the functional roles of these susceptibility genes. The cross-tissue TWAS analysis revealed 28 genes associated with BPH susceptibility. Single-tissue TWAS and MAGMA further refined eight genes, and subsequent MR, SMR, FOCUS and colocalization analysis pinpointed INO80B as the key gene. The differential expression of this result was verified by GEO. INO80B may help prevent excessive prostatic cell proliferation by regulating cell cycle-related gene expression. Our research identified the INO80B gene, whose predicted expression is associated with BPH risk and hence provided a new insight into the genetic basis of this disease. However, further functional studies are necessary to elucidate the potential biological activity of these significant signals.

Abstract Direct resin restoration has been widely used to restore the tooth defect for its convenience and minimal invasion. However, the accuracy of the final contour of class II restoration is often unpredictable and quite technique-sensitive due to the limitation of traditional matrix band system. In this study, the authors developed a novel matrix band system using shape memory polymer (SMP), which possessed two reversible shapes including digitized permanent shape to reproduce anatomical proximal contour and programmable temporary shape for clinical practice and reservation. The permanent shape could be designed and customized in software or retrieved from imaging database collected from large general population. Only warm saline or water was needed to trigger the shape transformation without any auxiliary tools. The results of in vitro class II restoration showed the shape memory matrix bands brought the best proximal profile and contact point, compared to traditional metal matrix and sectional matrix. The novel shape memory matrix system represents the comfortable, precise, and minimally invasive trend of dentistry and has a broad industrialization prospect as a dental instrument.

Abstract One of the key advantages of perovskite light-emitting diodes (PeLEDs) is their potential to achieve high performance at much higher current densities compared to conventional solution-processed emitters. However, state-of-the-art PeLEDs have not yet reached this potential, often suffering from severe current-efficiency roll-off under intensive electrical excitations. Here, we demonstrate bright PeLEDs, with a peak radiance of 2409 W sr−1 m−2 and negligible current-efficiency roll-off, maintaining high external quantum efficiency over 20% even at current densities as high as 2270 mA cm−2. This significant improvement is achieved through the incorporation of electron-withdrawing trifluoroacetate anions into three-dimensional perovskite emitters, resulting in retarded Auger recombination due to a decoupled electron-hole wavefunction. Trifluoroacetate anions can additionally alter the crystallization dynamics and inhibit halide migration, facilitating charge injection balance and improving the tolerance of perovskites under high voltages. Our findings shed light on a promising future for perovskite emitters in high-power light-emitting applications, including laser diodes.

Abstract Aerial manipulators can manipulate objects while flying, allowing them to perform tasks in dangerous or inaccessible areas. Advanced aerial manipulation systems are often based on rigid-link mechanisms, but the balance between dexterity and payload capacity limits their broader application. Combining unmanned aerial vehicles with continuum manipulators emerges as a solution to this trade-off, but these systems face challenges with large actuation systems and unstable control. To address these challenges, we propose Aerial Elephant Trunk, an aerial continuum manipulator inspired by the elephant trunk, featuring a small-scale quadrotor and a dexterous, compliant tendon-driven continuum arm for versatile operation in both indoor and outdoor settings. We develop state estimation for the quadrotor using an Extended Kalman Filter, shape estimation for the continuum arm based on piecewise constant curvature, and whole-body motion planning using minimum jerk principles. Through comprehensive fundamental verifications, we demonstrate that our system can adapt to various constrained environments, such as navigating through narrow holes, tubes, or crevices, and can handle a range of objects, including slender, deformable, irregular, or heavy items. Our system can potentially be deployed in challenging conditions, such as pipeline maintenance or electricity line inspection at high altitudes.

Abstract Background Acute and critical neurological diseases are often accompanied with elevated intracranial pressure (ICP), leading to insufficient cerebral perfusion, which may cause severe secondary lesion. Existing ICP monitoring techniques often fail to effectively meet the demand for real-time noninvasive ICP monitoring and warning. This study aimed to explore the use of electrical impedance tomography (EIT) to provide real-time early warning of elevated ICP by observing cerebral perfusion. Methods An intracranial hypertension model was prepared by injecting autologous un-anticoagulated blood into the brain parenchyma of twelve Landrace swine. Invasive ICP monitoring was used as a control method, and a high-precision EIT system was used to acquire and analyze the changing patterns of cerebral perfusion EIT image parameters with respect to ICP. Four EIT parameters related to cerebral perfusion were extracted from the images, and their potential application in detecting ICP elevation was analyzed. Results When ICP increased, all EIT perfusion parameters decreased significantly (P 22 mmHg), the correlation between EIT perfusion parameters and ICP was more significant (P

Abstract The spatial role of M1 and M2 tumor-associated macrophages (M1/M2 TAMs) in precision medicine remains unclear. EGFR and TP53 are among the most frequently mutated genes in lung adenocarcinoma. We characterized the mutation status and density of M1/M2 TAMs within tumor islets and stroma in 117 lung adenocarcinomas using next-generation sequencing and immunohistochemistry, respectively. Stromal M1 TAMs were positively correlated with disease progression and smoking history. In contrast, islet M1/M2 TAMs were predominantly found in tumors with wild-type TP53 (wtp53) but not associated with EGFR status. The presence of wtp53 was associated with the spatial distribution of M1/M2 TAMs in tumor islets and stroma. Additionally, dominance of islet M1 TAMs and M1-signature were significantly associated with improved survival in patients with wtp53 lung adenocarcinoma, unlike in those with mutant TP53. Conditioned medium from M1 macrophages (M1 CM) induced apoptosis in wtp53 cells through increased p53 accumulation. We found that interferons in M1 CM activate JAK1/TYK2 via IFNARs, leading to enhanced STAT1 expression and Y701 phosphorylation. This activation facilitates p53-STAT1 interactions, reduces the interaction between p53 and MDM2, and subsequently decreases p53 ubiquitination. M1 CM inhibited tumorigenesis, and silencing p53 reduced the anti-tumor efficacy of polyinosinic:polycytidylic acid (poly I:C) in vivo. Furthermore, higher M1-signature was significantly associated with better responses and survival following anti-PD1 treatment in wtp53 melanomas. IFNs/STAT1/p53 signaling was critical for the anti-tumor activity of M1 macrophages. These findings suggest that p53 modulates the spatial balance of M1/M2 TAMs, and the tumoricidal effects of M1 TAMs depend on p53 status. Thus, p53 companion diagnostics could facilitate the development of M1-oriented therapies, which may be particularly beneficial for wtp53 patients when combined with immunotherapy.

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic placed a heavy strain on the United States healthcare system. Common hospital operational performances were impacted to varying degrees by the pandemic. This study examined the healthcare operational measures during COVID-19 pandemic. Methods This cross-sectional study examined the COVID-19 cases and death counts of 56 California counties and hospital-level utilization data of 397 hospitals in California from January 2019 to March 2021. Results A total of 56 California counties were analysed, of which 37 counties were urban and 19 counties were rural. Average patient length of stay was positively associated with the number of intensive care unit visits by COVID-19 patients for all counties, as well as urban and rural counties separately. However, average patient length of stay was negatively associated with the number of inpatient visits by COVID-19 patients for all counties and urban counties. Conclusions The findings suggest that, while the need for additional beds and nursing staff in intensive care units exceeded initial estimates, there were also opportunities to streamline the care process for improved efficiency in regular acute care units. The understanding of factors impacting average patient length of stay would be valuable for hospital administrators in optimizing resource allocation and utilization to balance patient outcomes with financial sustainability during disruptive events.

Abstract Amino acids are important bio-based products with a multi-billion-dollar market. The development of efficient high-throughput screening technologies utilizing biosensors is essential for the rapid identification of high-performance amino acid producers. However, there remains a pressing need for biosensors that specifically target certain critical amino acids, such as l-threonine and l-proline. In this study, a novel transcriptional regulator-based biosensor for l-threonine and l-proline was successfully developed, inspired by our new finding that SerE can export l-proline in addition to the previously known l-threonine and l-serine. Through directed evolution of SerR (the corresponding transcriptional regulator of SerE), the mutant SerRF104I which can recognize both l-threonine and l-proline as effectors and effectively distinguish strains with varying production levels was identified. Subsequently, the SerRF104I-based biosensor was employed for high-throughput screening of the superior enzyme mutants of l-homoserine dehydrogenase and γ-glutamyl kinase, which are critical enzymes in the biosynthesis of l-threonine and l-proline, respectively. A total of 25 and 13 novel mutants that increased the titers of l-threonine and l-proline by over 10% were successfully identified. Notably, six of the newly identified mutants exhibited similarities to the most effective mutants reported to date, indicating the promising application potential of the SerRF104I-based biosensor. This study illustrates an effective strategy for the development of transcriptional regulator-based biosensors for amino acids and other chemical compounds.

Abstract We present a novel approach to realize three-dimensional (3D) matter wave solitons (MWSs) transformation between different optical potential wells by manipulating their depths and centers. The 3D MWSs are obtained by the square operator method, and transformed to other types (elliptical/ring/necklace) by performing time evolution with the split-step Fourier method. The effectiveness and reliability of our approach is demonstrated by comparing the transformed solitons with those obtained iteratively using the square operator method. Redistribution of MWSs are observed due to the modulation of potentials. In certain complex optical potential wells, we demonstrate the generation of exotic MWSs, such as double gyration modes, through this transformation approach. Overall, the controllable soliton transformation provides an excellent opportunity for all-optical switching, optical information processing, and various other applications.

Abstract Separation of multi-component mixtures in an energy-efficient manner has important practical impact in chemical industry but is highly challenging. Especially, targeted simultaneous removal of multiple impurities to purify the desired product in one-step separation process is an extremely difficult task. We introduced a pore integration strategy of modularizing ordered pore structures with specific functions for on-demand assembly to deal with complex multi-component separation systems, which are unattainable by each individual pore. As a proof of concept, two ultramicroporous nanocrystals (one for C2H2-selective and the other for CO2-selective) as the shell pores were respectively grown on a C2H6-selective ordered porous material as the core pore. Both of the respective pore-integrated materials show excellent one-step ethylene production performance in dynamic breakthrough separation experiments of C2H2/C2H4/C2H6 and CO2/C2H4/C2H6 gas mixture, and even better than that from traditional tandem-packing processes originated from the optimized mass/heat transfer. Thermodynamic and dynamic simulation results explained that the pre-designed pore modules can perform specific target functions independently in the pore-integrated materials.

Abstract As batteries drive the transition to electrified transportation and energy systems, ensuring their quality, reliability, lifetime, and safety is crucial. While the solid electrolyte interphase (SEI) is known to govern these performance characteristics, its dynamic nature makes understanding its nucleation, growth, and composition an ambitious, yet elusive aspiration. This work employs chalcogenide fibres embedded in negative electrode materials for operando Infra-red Fibre-optic Evanescent Wave Spectroscopy (IR-FEWS), combined with Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) algorithms for spectra analysis. By establishing molecular fingerprints that can be used to identify reaction products, IR-FEWS combined with MCR-ALS enables improved understanding of SEI evolution during cell formation with notable differences stemming from electrolyte or anode material. For example, despite operating at an elevated potential, lithium titanate’s SEI has intrinsic instability, evidenced by continued carbonate formation. This approach leads the hunt for the SEI down a new path, giving empirical formulations theoretical roots.

Abstract Financial distress prediction (FDP) is a critical area of study for researchers, industry stakeholders, and regulatory authorities. However, FDP tasks present several challenges, including high-dimensional datasets, class imbalances, and the complexity of parameter optimization. These issues often hinder the predictive model’s ability to accurately identify companies at high risk of financial distress. To mitigate these challenges, we introduce FinMHSPE—a novel multi-heterogeneous self-paced ensemble (MHSPE) FDP learning framework. The proposed model uses pairwise comparisons of data from multiple time frames combined with the maximum relevance and minimum redundancy method to select an optimal subset of features, effectively resolving the high dimensionality issue. Furthermore, the proposed framework incorporates the MHSPE model to iteratively identify the most informative majority class data samples, effectively addressing the class imbalance issue. To optimize the model’s parameters, we leverage the particle swarm optimization algorithm. The robustness of our proposed model is validated through extensive experiments performed on a financial dataset of Chinese listed companies. The empirical results demonstrate that the proposed model outperforms existing competing models in the field of FDP. Specifically, our FinMHSPE framework achieves the highest performance, achieving an area under the curve (AUC) value of 0.9574, considerably surpassing all existing methods. A comparative analysis of AUC values further reveals that FinMHSPE outperforms state-of-the-art approaches that rely on financial features as inputs. Furthermore, our investigation identifies several valuable features for enhancing FDP model performance, notably those associated with a company’s information and growth potential.

Abstract Background Gliomas are the most common malignant primary tumors of the central nervous system. There is an urgent need for new convenient, targeted and specific imaging agents for gliomas. This study aimed to firstly evaluate the feasibility of 68Ga-NOTA-RM26 PET/CT imaging in glioma and analyze the relationship between the imaging characteristics and glioma grade, classification and molecular alterations. Results Twenty-two patients were confirmed as glioma by surgery or biopsy. All patients exhibited 68Ga-NOTA-RM26 uptake. SUVmax was chosen as the imaging marker for analysis. For all glioma patients, there were significant differences between grades (P = 0.047). For primary gliomas, SUVmax had good discrimination for both tumor classifications (P = 0.045) and grades (P = 0.03). There was a positive correlation (P

Abstract Background Advanced gastric cancer (GC) exhibits a high recurrence rate and a dismal prognosis. Myocyte enhancer factor 2c (MEF2C) was found to contribute to the development of various types of cancer. Therefore, our aim is to develop a prognostic model that predicts the prognosis of GC patients and initially explore the role of MEF2C in immunotherapy for GC. Methods Transcriptome sequence data of GC was obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and PRJEB25780 cohort for subsequent immune infiltration analysis, immune microenvironment analysis, consensus clustering analysis and feature selection for definition and classification of gene M and N. Principal component analysis (PCA) modeling was performed based on gene M and N for the calculation of immune checkpoint inhibitor (ICI) Score. Then, a Nomogram was constructed and evaluated for predicting the prognosis of GC patients, based on univariate and multivariate Cox regression. Functional enrichment analysis was performed to initially investigate the potential biological mechanisms. Through Genomics of Drug Sensitivity in Cancer (GDSC) dataset, the estimated IC50 values of several chemotherapeutic drugs were calculated. Tumor-related transcription factors (TFs) were retrieved from the Cistrome Cancer database and utilized our model to screen these TFs, and weighted correlation network analysis (WGCNA) was performed to identify transcription factors strongly associated with immunotherapy in GC. Finally, 10 patients with advanced GC were enrolled from Sun Yat-sen University Cancer Center, including paired tumor tissues, paracancerous tissues and peritoneal metastases, for preparing sequencing library, in order to perform external validation. Results Lower ICI Score was correlated with improved prognosis in both the training and validation cohorts. First, lower mutant-allele tumor heterogeneity (MATH) was associated with lower ICI Score, and those GC patients with lower MATH and lower ICI Score had the best prognosis. Second, regardless of the T or N staging, the low ICI Score group had significantly higher overall survival (OS) compared to the high ICI Score group. For its mechanisms, consistently, for Camptothecin, Doxorubicin, Mitomycin, Docetaxel, Cisplatin, Vinblastine, Sorafenib and Paclitaxel, all of the IC50 values were significantly lower in the low ICI Score group compared to the high ICI Score group. As a result, based on univariate and multivariate Cox regression, ICI Score was considered to be an independent prognostic factor for GC. And our Nomogram showed good agreement between predicted and actual probabilities. Based on CIBERSORT deconvolution analysis, there was difference of immune cell composition found between high and low ICI Score groups, probably affecting the efficacy of immunotherapy. Then, MEF2C, a tumor-related transcription factor, was screened out by WGCNA analysis. Higher MEF2C expression is significantly correlated with a worse OS. Moreover, its higher expression is also negatively correlated with tumor mutation burden (TMB) and microsatellite instability (MSI), but positively correlated with several immunosuppressive molecules, indicating MEF2C may exert its influence on tumor development by upregulating immunosuppressive molecules. Finally, based on transcriptome sequencing data on 10 paired tumor tissues from Sun Yat-sen University Cancer Center, MEF2C expression was significantly lower in paracancerous tissues compared to tumor tissues and peritoneal metastases, and it was also lower in tumor tissues compared to peritoneal metastases, indicating a potential positive association between MEF2C expression and tumor invasiveness. Conclusions Our prognostic model can effectively predict outcomes and facilitate stratification GC patients, offering valuable insights for clinical decision-making. The identified transcription factor MEF2C can serve as a biomarker for assessing the efficacy of immunotherapy for GC.

Objective: To delve deeper into the study of degenerative diseases, it becomes imperative to investigate whether deep-learning reconstruction (DLR) can improve the evaluation of white matter hyperintensity (WMH) on 3.0T scanners, and compare its lesion detection capabilities with conventional reconstruction (CR). Methods: A total of 131 participants (mean age, 46 years ±17; 46 men) were included in the study. The images of these participants were evaluated by readers blinded to clinical data. Two readers independently assessed subjective image indicators on a 4-point scale. The severity of WMH was assessed by four raters using the Fazekas scale. To evaluate the relative detection capabilities of each method, we employed the Wilcoxon signed rank test to compare scores between the DLR and the CR group. Additionally, we assessed interrater reliability using weighted k statistics and intraclass correlation coefficient to test consistency among the raters. Results: In terms of subjective image scoring, the DLR group exhibited significantly better scores compared to the CR group (P

CuW composites are widely used in high voltage transmission, electronic information, aerospace and other cutting-edge fields. At present, the preparation methods of CuW composites based on powder metallurgy have the defects of uneven microstructure and low density. Reducing the size of tungsten particles in the CuW composites can significantly improve the microstructure uniformity and density. In this paper, an innovative idea for regulating the microstructure of CuW composites by aluminothermic coupling with magnesiothermic reduction was proposed. The thermodynamics and dynamics of the reaction system for preparation of CuW composites by this method were studied, and the microstructure of CuW composites were systematically analysed and evaluation. The researches show that the inclusion in CuW prepared by aluminothermic reduction was Al2O3, and the inclusion in CuW prepared by aluminothermic coupling with magnesiothermic reduction was MgO·Al2O3. The addition of magnesium to the reducing agent had an obvious refining effect on the tungsten particles. The mechanism was that magnesium was converted into magnesium vapor during the rapid heating process of the system, and the gas-solid, gas-liquid-solid reaction occurred with tungsten oxide to generate smaller tungsten particles. With an increase of magnesium content, the average size of tungsten particles in the microstructure of CuW gradually decreased from 2.38 μm to 0.82 μm, and the microstructure uniformity increased from 56.26% to 76.96%.

Abstract Recent studies suggest the role of gut microbes in bile acid metabolism in the development and progression of colorectal cancer. However, the surveys of the association between fecal bile acid concentrations and colorectal cancer (CRC) have been inconsistent. We searched online to identify relevant cross-sectional and case-control studies published online in the major English language databases (Medline, Embase, Web of Science, AMED, and CINAHL) up to January 1, 2024. We selected studies according to inclusion and exclusion criteria and extracted data from them. RevMan 5.3 was used to perform the meta-analyses. In CRC risk meta-analysis, the effect size of CA (cholic acid), CDCA (chenodeoxycholic acid), DCA (deoxycholic acid), and UDCA (ursodeoxycholic acid) were significantly higher (CA: standardized mean difference [SMD] = 0.41, 95% confidence interval [CI]: 0.5–0.76, P = 0.02; CDCA: SMD = 0.35, 95% CI: 0.09–0.62, P = 0.009; DCA: SMD = 0.33,95% CI: 0.03–0.64, P = 0.03; UDCA: SMD = 0.46, 95% CI: 0.14–0.78, P = 0.005), and the combined effect size was significantly higher in the high-risk than the low-risk CRC group (SMD = 0.36, 95% CI: 0.21–0.51, P

Abstract Optical neural networks are considered next-generation physical implementations of artificial neural networks, but their capabilities are limited by on-chip integration scale and requirement for coherent light sources. This study proposes a spectral convolutional neural network (SCNN) with matter meta-imaging. The optical convolutional layer is implemented by integrating very large-scale and pixel-aligned spectral filters on CMOS image sensor. It facilitates highly parallel spectral vector-inner products of incident incoherent natural light i.e., the direct information carrier, which empowers in-sensor optical analog computing at extremely high energy efficiency. To the best of our knowledge, this is the first integrated optical computing utilizing natural light. We employ the same SCNN chip for completely different real-world complex tasks and achieve accuracies of over 96% for pathological diagnosis and almost 100% for face anti-spoofing at video rates. These results indicate a feasible and scalable in-sensor edge computing chip of natural light for various portable terminals.

Abstract The shortwave infrared (SWIR) region is an ideal spectral window for next-generation bioimaging to harness improved penetration and reduced phototoxicity. SWIR spectral activity may also be accessed via supramolecular dye aggregation. Unfortunately, development of dye aggregation remains challenging. We propose a crystal-aided aggregate synthesis (CAASH) approach to introduce a layer of rationality for the development of J-aggregate and the successful development of a water-soluble SWIR JV-aggregate with a bisbenzannulated silicon rhodamine scaffold (ESi5). The resulting SWIR-aggregates exhibit excellent stabilities toward organic solvents, pH, sonication, photobleaching, thiols, and endogenous oxidative species. Notably, the aggregates have a high structure-dependent melting temperature of ca. 330-335 K. In fact, the heating/annealing process can be exploited to reduce aggregation disorder. The aggregates are biocompatible and have broad potential in in vivo fluorescence and photoacoustic imaging and more.

Abstract Low-dimensional lead-free metal halide perovskites are highly attractive for cutting-edge optoelectronic applications. Herein, we report a class of scandium-based double perovskite crystals comprising antimony dopants that can generate multiexcitonic emissions in the ultraviolet, blue, and yellow spectral regions. Owing to the zero-dimensional nature of the crystal lattice that minimizes energy crosstalk, different excitonic states in the crystals can be selectively excited by ultraviolet light, X-ray irradiation, and mechanical action, enabling dynamic control of steady/transient-state spectral features by modulating the excitation modes. Remarkably, the transparent crystal exhibits highly efficient white photoluminescence (quantum yield >97%), X-ray excited blue emission with long afterglow (duration >9 h), and high-brightness self-reproducible violet-blue mechanoluminescence. These findings reveal the exceptional capability of low-dimensional perovskite crystals for integrating various excitonic luminescence, offering exciting opportunities for multi-level data encryption and all-in-one authentication technologies.

Objective: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used traditional methods such as multiple logistic regression (LR). Nowadays, machine learning (Mach-L) emerges as a new method and can be used in medical researches. In the present study, there were two goals: 1. Compare the accuracy of five alternative Mach-L techniques with that of conventional LR. 2. Use Mach-L to forecast PCOS and prioritize the risk factors. Materials and methods: Totally, 170 PCOS patients and 950 control participants were included. We collected information on demographics, biochemistry, and lifestyle. PCOS was identified using Rotterdam criteria. Random Forest (RF), stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), extreme gradient boosting (XGBoost), and gradient boosting with categorical features support (CatBoost) are five Mach-L algorithms that were used. Models with lower estimation errors were better. Results: By using t-test, we found subjects with PCOS were younger, glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT), γ-Glutamyl transferase (γ-GT), Triglyceride (TG), and educational levels were higher. All the five Mach-L methods had lower estimation errors compared to LR. The average of the AUC derived from Mach-L was mean AUC of 0.6669, higher than the that of LR (0.5908). Finally, age, TG, GPT, white blood cell count (WBC), uric acid (UA), and platelet (Plt) were the six most important risk factors selected by Mach-L. Conclusion: Mach-L methods overtook conventional LR and age was the most significant factor, followed by TG, GPT, WBC, UA, and Plt in a cohort of Chinese women.

Abstract. Background:. Without timely and effective rehabilitation, hearing loss may profoundly affect human life quality. China has a large population of hearing-impaired individuals, which imposes a heavy health burden on society. Moreover, this population is projected to increase rapidly owing to China’s aging society. Methods:. We used data from a population-representative epidemiological investigation of hearing loss and ear diseases in four Chinese provinces. We estimated the national prevalence using multiple linear regression of the age-group proportions and prevalence in 31 provinces with clustering analysis. We used years lived with disability (YLDs) to analyze the disease burden and forecasted the prevalence of hearing loss by 2060 in China. Results:. An estimated 115 million people had moderate-to-complete hearing loss in 2015 across the 31 provinces of China (8.4% of 1.37 billion people). Of these, 85.7% were older than age 50 years (99 million people) and 2.4% were younger than 20 years old (2.8 million people). Of all YLDs attributable to hearing loss, 68.9% were attributable to moderate-to-complete cases. By 2060, a projected 242 million people in China will have moderate-to-complete hearing loss, a 110.0% increase from 2015. Conclusions:. The hearing loss prevalence in China is high. Population aging and socioeconomic factors substantially affect the prevalence and severity of hearing loss and the disease burden. The prevalence and severity of hearing loss are unevenly distributed across different provinces. Future public health policies should take these trends and regional variations into account.

Background/Aims: Growing recognition identifies sessile serrated lesions (SSL) as colorectal cancer (CRC) precursors. However, the SSL detection rate remains debatable and lacks a definitive consensus. Additionally, understanding the influencing factors in SSL development is limited. We aim to retrospectively analyze the true prevalence and risk factors of SSL in China. Materials and Methods: This retrospective study collected medical data from patients who underwent colonoscopy at the Endoscopy Center of Shanghai East Hospital affiliated with Tongji University between March 1, 2019 and February 28, 2022. Data were sourced through the electronic medical record system and included information such as age, sex, lesion location, number, and pathology. This study predominantly focused on the detection rate and the clinical and endoscopic features of SSL. Results: Of 72 287 colonoscopies in 3 years, 3905 cases were histologically confirmed as SSL. Among them, 2290 (58.6%) were male, and 1615 (41.4%) were female. The overall SSL detection rate was 5.40%, slightly surpassing Asian/Chinese averages but lower than Western rates. Males had a higher SSL detection rate (6.1%) than females (4.6%). Univariate analysis revealed a significant association between SSL with dysplasia/adenocarcinoma (SSL-D/AD) and obesity (Body Mass Index, BMI ≥ 24), CRC family history, and hypertension. After multivariable logistic regression, only obesity (BMI ≥ 24) remained a statistically significant independent risk factor for SSL-D/AD. Conclusions: The SSL detection rate at our center is 5.4% and increases with age. Males have a significantly higher detection rate than females. Our findings suggest that endoscopists should consider risk factors for SSL-D/AD, such as obesity, CRC family history, and hypertension.

In semi-supervised object detection (SSOD), the methods based on dense pseudo-labeling bypass complex post-processing while maintaining competitive performance compared to the methods based on sparse pseudo-labeling. However, there are still relatively few researches focused on the dense pseudo-labeling paradigm. In this work, we first experimentally point out the shortcomings of current dense pseudo-labeling methods: 1) Low-quality sampling: the fixed threshold strategies can result in numerous false negatives and false positives. 2) Inconsistency between classification scores and localization quality: classification scores cannot represent localization quality, resulting in poor quality of predicted bounding boxes for sampled positive samples. 3) Suboptimal training approach: current training methods only utilize its knowledge from the perspective of final dense pseudo-labels, failing to fully exploit the teacher model. To address these issues, we propose a method called Dense-Label Refinement and Cross Optimization (DRCO) based on dense pseudo-labels. Specifically, to tackle the issue of low-quality sampling, we introduce the Adaptive Sampling Approach (ASA), which achieves high-quality sampling at the image level and dynamic sampling ratios without introducing any additional hyperparameters. For the inconsistency between classification scores and localization quality, Comprehensive FRS (cFRS) is proposed to jointly optimize the classification and localization branches more efficiently, thereby obtaining a more comprehensive score. Finally, for the suboptimal training approach, we introduce Cross Prediction Optimization (CPO). CPO efficiently leverages the knowledge of the teacher model through a Cross-Head operation, thereby achieving more effective teacher-student interaction. DRCO achieves 27.31% mAP with only 1% COCO labeled data, which is approximately 1.24% mAP higher than the previous state-of-the-art. Based on MS COCO and PASCAL VOC benchmarks, further comprehensive experiments demonstrate that our method alleviates the aforementioned shortcomings and achieves competitive performance.

Abstract Regenerating periodontal bone defect surrounding periodontal tissue is crucial for orthodontic or dental implant treatment. The declined osteogenic ability of periodontal ligament stem cells (PDLSCs) induced by inflammation stimulus contributes to reduced capacity to regenerate periodontal bone, which brings about a huge challenge for treating periodontitis. Here, inspired by the adhesive property of mussels, we have created adhesive and mineralized hydrogel microspheres loaded with traditional compound cordycepin (MMS-CY). MMS-CY could adhere to the surface of alveolar bone, then promote the migration capacity of PDLSCs and thus recruit them to inflammatory periodontal tissues. Furthermore, MMS-CY rescued the impaired osteogenesis and ligament-forming capacity of PDLSCs, which were suppressed by the inflammation stimulus. Moreover, MMS-CY also displayed the excellent inhibitory effect on the osteoclastic activity. Mechanistically, MMS-CY inhibited the premature senescence induced by the inflammation stimulus through the nuclear factor erythroid 2-related factor (NRF2) pathway and reducing the DNA injury. Utilizing in vivo rat periodontitis model, MMS-CY was demonstrated to enhance the periodontal bone regeneration by improving osteogenesis and inhibiting the osteoclastic activity. Altogether, our study indicated that the multi-pronged approach is promising to promote the periodontal bone regeneration in periodontitis condition by reducing the inflammation-induced stem cell senescence and maintaining bone homeostasis.

Abstract Background Calcification of the radial artery is one of the main causes of anastomotic stenosis in autogenous arteriovenous fistulas in uremic patients. However, the pathogenesis of calcification is still unknown. This study attempted to screen and validate the risk factors for vascular calcification in patients with uremia. Methods Serum of blood were collected and tissue samples from radial artery were obtained from 60 uremia patients with or without hemodialysis. General biochemical indicators and calcification-related molecules were collected and detected via ELISA or correlation analysis. In addition, pathological changes and calcification-related molecules in the radial artery were evaluated by HE or immunohistochemical staining. Results There were differences in total calcium, calcium-phosphorus products, allograft inflammatory factor 1 (AIF-1), intact parathyroid hormone (iPTH), vitamin D (VD), fibroblast growth factor 23 (FGF23) and soluble klotho (sKlotho) in the blood of uremic patients with or without hemodialysis. Furthermore, these factors are related to calcification of the radial artery. The expression of AIF-1, PTHR1, VDR, FGF23 and sKlotho was also increased in the calcified radial artery. Conclusions The levels of AIF-1, PTH, VDR, FGF23 and sKlotho in serum were associated with calcification of the radial artery in patients with uremia. Furthermore, calcification of the radial artery was further aggravated by abnormalities in calcium and phosphorus in maintenance hemodialysis patients.

Abstract Dissection of the physiological interactomes of histone post-translational modifications (hPTMs) is crucial for understanding epigenetic regulatory pathways. Peptide- or protein-based histone photoaffinity tools expanded the ability to probe the epigenetic interactome, but in situ profiling in native cells remains challenging. Here, we develop a nucleus-targeting histone-tail-based photoaffinity probe capable of profiling the hPTM-mediated interactomes in native cells, by integrating cell-permeable and nuclear localization peptide modules into an hPTM peptide equipped with a photoreactive moiety. These types of probes, such as histone H3 lysine 4 trimethylation and histone H3 Lysine 9 crotonylation probes, enable the probing of epigenetic interactomes both in HeLa cell and hard-to-transfect RAW264.7 cells, resulting in the discovery of distinct interactors in different cell lines. The utility of this probe is further exemplified by characterizing interactome of emerging hPTM, such as AF9 was detected as a binder of histone H3 Lysine 9 lactylation, thus expanding the toolbox for profiling of hPTM-mediated PPIs in live cells.

Abstract Halorhodospira (Hlr.) halophila strain BN9622 is an extremely halophilic and alkaliphilic purple phototrophic bacterium and has been widely used as a model for exploring the osmoadaptive and photosynthetic strategies employed by phototrophic extreme halophiles that enable them to thrive in hypersaline environments. Here we present the cryo-EM structures of (1) a unique native Hlr. halophila triple-complex formed from light-harvesting (LH1), the reaction center (RC), and high-potential iron–sulfur protein (HiPIP) at 2.44 Å resolution, and (2) a HiPIP-free LH1–RC complex at 2.64 Å resolution. Differing from the LH1 in the Hlr. halophila LH1–LH2 co-complex where LH1 encircles LH2, the RC-associated LH1 complex consists of 16 (rather than 18) αβ-subunits circularly surrounding the RC. These distinct forms of LH1 indicate that the number of subunits in a Hlr. halophila LH1 complex is flexible and its size is a function of the photocomplex it encircles. Like LH1 in the LH1–LH2 co-complex, the RC-associated LH1 complex also contained two forms of αβ-polypeptides and both dimeric and monomeric molecules of bacteriochlorophyll a. The majority of the isolated Hlr. halophila LH1–RC complexes contained the electron donor HiPIP bound to the surface of the RC cytochrome subunit near the heme-1 group. The bound HiPIP consisted of an N-terminal functional domain and a long C-terminal extension firmly attached to the cytochrome subunit. Despite overall highly negative surface-charge distributions for both the cytochrome subunit and HiPIP, the interface between the two proteins was relatively uncharged and neutral, forming a pathway for electron tunneling. The structure of the Hlr. halophila LH1–RC–HiPIP complex provides insights into the mechanism of light energy acquisition coupled with a long-distance electron donating process toward the charge separation site in a multi-extremophilic phototroph.

Abstract Background Acute pulmonary embolism represents the third most prevalent cardiovascular pathology, following coronary heart disease and hypertension. Its untreated mortality rate is as high as 20–30%, which represents a significant threat to patient survival. In view of the current lack of real-time monitoring techniques for acute pulmonary embolism, this study primarily investigates the potential of the pulsatility electrical impedance tomography (EIT) technique for the detection and real-time monitoring of acute pulmonary embolism through the collection and imaging of the pulsatile signal of pulmonary blood flow. Methods A before-and-after self-control experiment was conducted on anaesthetised domestic pigs (N = 12, 20.75 ± 2.56 kg). The changes in pulmonary perfusion caused by an acute pulmonary embolism (artificially induced) were monitored in real time using the pulsation method. This enabled the extraction of indicators such as Amplitude, Forward (Negative) Slope, and S ARC , which were used to assess the local pulmonary blood flow perfusion state. Furthermore, the degree of ventilation/perfusion matching in the lungs was evaluated concurrently with the analysis of the pulmonary ventilation area. Subsequently, a control verification was conducted utilising the conventional invasive hypertonic saline (5 ml 10% NaCl) contrast technique. Results The perfusion alterations subsequent to embolism in the pulsatility method are highly concordant with those observed in the hypertonic saline method, as evidenced by the imaging and indicator data. In particular, the perfusion area on the side of the embolism is markedly diminished, and the absolute values of all perfusion indicators are significantly reduced. Among these, Amplitude (P

Abstract Background With the aging of society, cognitive impairment in elderly people is becoming increasingly common and has caused major public health problems. The screening of cognitive impairment in elderly people and its related influencing factors can aid in the development of relevant intervention and improvement strategies. Methods In this study, stratified random cluster sampling was used to conduct a cross-sectional survey of elderly individuals aged 65 years in Chengdu, Sichuan Province, through an electronic questionnaire from November 2022 to November 2023. Descriptive analysis and logistic regression analysis were used to investigate cognitive impairment and its relevant influencing factors. Results Among the 16,609 elderly people, 7524 (45.3%) were males and 9085 (54.7%) were females, with an average age of 73.6 ± 6.5 years (age range 65–101 years). The average years of education was 5.9 ± 6.2 years, and the proportion of individuals with cognitive impairment was 13.1%. With increasing age, the risk of cognitive impairment increased significantly. The risk factors for cognitive impairment in elderly individuals included advanced age, hypertension, heart disease, diabetes, cerebrovascular disease, depressive symptoms, and anxiety symptoms, while the protective factors included higher education level, married status, and greater life satisfaction. Conclusion Cognitive impairment in elderly individuals in Chengdu is serious. We can intervene in and improve cognitive impairment in elderly people by controlling blood pressure and blood sugar, treating depressive and anxiety symptoms and developing community colleges for elderly people and increasing satisfaction with life.