Search

Successful recognition is generally thought to be based on both recollection and familiarity of studied information. Recent studies found that making judgments of learning (JOLs) can reactively facilitate recognition performance, a form of reactivity effect on memory. The current study aimed to explore the roles of recollection and familiarity in the "reactivity effect" on recognition performance. Experiment 1 replicated the positive reactivity effect on recognition performance. Experiment 2 used the sequential remember/know (R/K) procedure, Experiment 3 utilized the simultaneous R/K procedure, and Experiment 4 inserted a long study-test interval (i.e., 24-h) to determine the roles of recollection and familiarity in the reactivity effect. These three experiments converged in demonstrating that making JOLs reactively facilitated recognition performance through enhancing both recollection and familiarity. Furthermore, there was minimal difference between the reactive influences on recollection and familiarity. The documented findings imply that the JOL reactivity effect on recognition is supported by two underlying mechanisms: greater recollection induced by enhanced distinctiveness, and superior familiarity induced by enhanced learning engagement.

Employment of appropriate study strategies is crucial for academic success. Previous findings on whether use of specific strategies is related to academic performance in real educational settings were inconsistent, and their participant samples were largely restricted to undergraduate students. The current study recruited a large sample (i.e., 4,331 participants) of elementary school students to explore the association between use of specific strategies and academic performance by using multilevel linear regression models, in which two potential confounding variables (i.e., SES and gender) are controlled for. The results showed that after controlling for SES, gender and other study strategies, use of spaced study, rereading and help-seeking positively related to academic performance in elementary school students. However, use of self-testing, highlighting/underlining, note-taking, summarizing, making diagrams, making study plans and studying with friends did not positively correlate with academic performance in elementary school children. Instructors and parents are suggested to encourage children to study by using the effective study strategies, and teach them how to maximize the benefits of these strategies.

Recent research has suggested that students prefer restudying over retrieval practice when learning difficult materials, despite the latter being a more effective learning strategy. The current study investigated whether an instructional intervention can improve the use of retrieval practice for both easy and difficult materials. In Experiment 1, after initial learning of each item, participants rated their perceived mental effort (PME) and judgment of learning (JOL) for each item. Then, participants chose whether to restudy or take retrieval practice for that item. The results showed that participants chose to take retrieval practice less frequently for difficult items compared to easy ones. Furthermore, participants' ratings of PME and JOL sequentially mediated the relationship between item difficulty and their learning strategy choices. Specifically, difficult items resulted in higher levels of PME, which in turn led to lower JOL, ultimately reducing the likelihood of choosing retrieval practice. In Experiment 2, half of the participants received an instructional intervention, which revealed that while students prefer restudying for difficult items, retrieval practice benefits both easy and difficult items in long-term retention. The remaining half did not receive such intervention and were designated as the control group. The results indicated that, compared to the control group, students who received the intervention increased the odds of choosing retrieval practice for both types of materials after the intervention. The findings of this study suggest that students can be supported to use retrieval practice regardless of item difficulty.

IntroductionUrinary incontinence (UI) significantly impairs women’s quality of life. Identifying its risk factors is essential for developing effective interventions. Sarcopenia, characterized by the accelerated loss of muscle mass and function, is an emerging concern often linked to obesity and abnormal metabolic status, exacerbating various adverse health outcomes. This population-based study aimed to explore the independent and joint associations of sarcopenia, obesity, and metabolic health with UI risk, as well as to evaluate the mediating role of metabolic indicators in these associationsMethodsA total of 3,557 women aged ≥20 years from the National Health and Nutrition Examination Survey were included. Sarcopenia was assessed using the appendicular lean mass index (ALMI), and obesity was defined by body mass index and waist circumference. Metabolic health was evaluated using revised criteria from the National Cholesterol Education Program-Adult Treatment Panel III. UI was identified through responses to the “Kidney Conditions-Urology” questionnaire and classified into stress UI (SUI), urgency UI (UUI), and mixed UI (MUI). Multivariable logistic regression and restricted cubic spline models were used to evaluate the associations and visualize the relationship between ALMI and UI. Mediation models were constructed to assess the mediating role of metabolic indicators.ResultsWe found that sarcopenia was significantly associated with an increased risk of MUI in the general population. Age-specific analysis revealed that sarcopenia is an independent risk factor for SUI in women aged ≥60, and for MUI in women aged 40–59 years. Sarcopenic obesity, particularly under central obesity criteria, further elevated the risk of UI. Notably, women with the metabolically unhealthy obese phenotype with sarcopenia were at the highest risk for both SUI and MUI. Metabolically unhealthy status, glycohemoglobin, vitamin D, and serum albumin levels were partial mediators of these associations.ConclusionOur findings elucidated the complex interactions between sarcopenia, obesity, and metabolic health, underscoring the critical need for integrated therapeutic strategies that address both metabolic health and targeted nutritional interventions, aiming to enhance muscular health and effectively manage and prevent UI.

Objective: Huazhi Rougan granules (HRGs) are a promising drug to improve alcoholic liver disease (ALD), but its mechanism remains unclear. Materials and Methods: Network pharmacology, molecular docking, and animal experiments were used to reveal the potential mechanism of HRG against ALD. Results: A total of 245 potential targets of HRG against ALD were obtained. Functional enrichment analysis suggests that HRG could synergistically regulate various biological pathways to exert therapeutic effects on ALD. Molecular docking showed that the key targets exhibited the good binding ability with the key compounds. The in vivo experiments showed that HRG can effectively alleviate pathological changes in liver tissue, improve blood lipid levels, antioxidant stress ability, and liver function, and reduce the release of inflammatory cytokines in the liver. Conclusions: This study reflects that HRG is an effective strategy for treating ALD, providing a basis for revealing the prevention and treatment mechanisms of ALD.

The reactivity effect of metacognitive judgments on first-order task performance has received increased research attention. Previous studies showed that soliciting retrospective confidence ratings (CRs) reactively enhances task performance itself, such as performance in decision making and reasoning tasks, especially for those with high self-confidence. It remains unknown whether CRs can improve students’ academic assessment performance in real educational settings. The current study recruited 795 fourth-grade elementary school children to explore if making CRs reactively affects students’ academic assessment performance in two main subjects (i.e., Chinese Language and Mathematics). The data were collected across six waves with half-year intervals. From Wave 2, children either provided (CR group) or did not provide CRs (no-CR group) when completing standardized academic assessments. The results showed Bayesian evidence supporting the claim that making CRs does not influence children’s academic assessment performance (both the average performance across waves 2–6 and the performance in each wave) in both subjects. Furthermore, children’s self-confidence did not moderate the reactive influence of CRs. The results from multilevel regression analyses re-confirmed the above conclusions. Possible explanations for the absence of the reactivity effect of CRs on children’s academic assessment performance are discussed.

Abstract Background Cornelia de Lange syndrome (CdLS) is a multisystem genetic disorder, and cases caused by variants in the structural maintenance of chromosomes protein 3 (SMC3) gene are uncommon. Here, we report two cases of CdLS associated with novel pathogenic variants in SMC3 from two Chinese families. Methods Clinical presentations of two patients with CdLS were evaluated, and specimens from the patients and other family members were collected for Trio‐based whole‐exome sequencing. Pyrosequencing, chip‐based digital PCR, minigene splicing assay, and in silico analysis were carried out to elucidate the impact of novel variants. Results Novel heterozygous variants in SMC3 were identified in each proband. One harbored a novel splicing and mosaic variant (c.2535+1G>A) in SMC3. The mutated allele G>A conversion was approximately 23.1% by digital PCR, which indicated that 46.2% of peripheral blood cells had this variant. Additionally, in vitro minigene splicing analysis validated that the c.2535+1G>A variant led to an exon skipping in messenger RNA splicing. The other carried a heterozygous variant (c.435C>A), which was predicted to be pathogenic as well as significantly altered in local electrical potential. The former showed multiple abnormalities and marked clinical severity, and the latter mainly exhibited a speech developmental disorder and slightly facial anomalies. Conclusion Both patients were clinically diagnosed with Cornelia de Lange syndrome 3 (CdLS3). The newly identified SMC3 gene variants can expand the understanding of CdLS3 and provide reliable evidence for genetic counseling to the affected family.

Objective: To investigate the mechanism of Renshen Guben oral liquid (RSGB) enhancing immune function. Materials and Methods: Network pharmacology and molecular docking were used to intuitively demonstrate the mechanism of immune regulation of RSGB. Results: A total of 112 active compounds of RSGB were found, and 501 targets were predicted. Furthermore, 2974 immune targets were obtained from UniProt and NCBI Gene databases, and 111 common targets of RSGB and immunity were obtained. Among them, interleukin (IL) 6, tumor necrosis factor, AKT1, VEGFA, STAT3, MAPK1, SRC, EGFR, IL1B, and PTGS2 might be the key targets for RSGB to improve immunity. ClueGO and Kyoto Encyclopedia of Genes and Genomes analysis showed that the immunoregulatory mechanism of RSGB may find a relation with the B cell receptor signaling pathway and T cell receptor signaling pathway. Furthermore, this study preliminarily explored the mechanism of RSGB improving menopausal syndrome, polycystic ovary syndrome, and cancer-related fatigue by enhancing immunity. Conclusions: RSGB can improve the body's immunity through multicomponent, multitarget, and multipathway. In addition, RSGB can also improve the immune capacity of the body to assist in the treatment of diseases, which has great potential as an immunomodulator.

By allocating each object to one of the predefined categories, image classification deeply understands the attributes and features of the data on each object in the scene, and further mines the potential features and internal connections of the data, supporting the subsequent application decision-making with necessary structured data. One of the key challenges to image classification is how to accurately classify sparse data, when there is an imbalance between different categories of data, i.e., how to identify small objects in images. Recognizing a person in satellite images is such a challenging task. These objects are sparse either globally or in each recognizable local segment. Therefore, they are often overlooked by the classifier, or removed as noises. During deep learning, feature sparsity means the samples contain too much useless information, which suppresses the generalization and accuracy of the model. To solve the problem, this paper presents a spatial distance-based spatial clustering algorithm for sparse image data (SDBSCA-SID). Firstly, the imaging range of the image sensor constitutes a two-dimensional (2D) constraint space. Under the constraint, spatial clustering was carried out based on the features of each sample to aggregate dense data into primary categories, and aggregate sparse data and noises into secondary categories. Referring to the 2D constrained space, multiple spatial classification surfaces were constructed to aggregate the sparse data to the two sides of these surfaces as much as possible. If the error is minimized, then the sparse data belong to these classification surfaces. To shorten the convergence time of the clustering algorithm on imbalanced data, the original sample set was cut into slices, and assigned to several calculation units for separate clustering. Next, the same-class clusters were merged through reduction. Finally, the obtained class labels were compared with the preset class labels, wrapping up the semantic segmentation of images. The stability and accuracy of our algorithm were demonstrated through tests on image samples.

Abstract Background I-125 seeds brachytherapy (ISB) has been used to improve the clinical effectiveness of transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC). We aim to appraise the safety and clinical efficacy of combined ISB and TACE for the treatment of subcapsular HCC. Materials and methods A retrospective investigative study extending from January 2017 to December 2020, involved individuals suffering from subcapsular HCC, who were subjected to TACE treatment with or without ISB in our center. The clinical effectiveness was compared between 2 groups. Results Sixty-four patients, in total, with subcapsular HCC had to undergo TACE with (n = 32) or without (n = 32) ISB in our center. After CT-guided ISB, only 2 (6.3%) patients experienced a self-limited pneumothorax. Combined treatment resulted in a significantly higher complete response (56.3% vs. 18.8%, P = 0.002) and total response (90.7% vs. 59.4%, P = 0.004) rates than that of TACE alone. In comparison to the TACE alone group, the median progression-free survival was substantially longer in the combined treatment group (11 months vs. 5 months, P = 0.016). Further, 15 and 28 patients in combined and TACE alone groups respectively died within the follow-up. The median OS was comparable between combined and TACE alone groups (22 months vs. 18 months, P = 0.529). Conclusions Combined TACE and ISB therapy is a safe treatment method for individuals suffering from subcapsular HCC. When compared, combined treatment had significantly enhanced clinical efficacy as a subcapsular HCC therapy, in comparison to TACE alone.

The trajectory planning of multiple unmanned aerial vehicles (UAVs) is the core of efficient UAV mission execution. Existing studies have mainly transformed this problem into a single-objective optimization problem using a single metric to evaluate multi-UAV trajectory planning methods. However, multi-UAV trajectory planning evolves into a many-objective optimization problem due to the complexity of the demand and the environment. Therefore, a multi-UAV cooperative trajectory planning model based on many-objective optimization is proposed to optimize trajectory distance, trajectory time, trajectory threat, and trajectory coordination distance costs of UAVs. The NSGA-III algorithm, which overcomes the problems of traditional trajectory planning, is used to solve the model. This paper also designs a segmented crossover strategy and introduces dynamic crossover probability in the crossover operator to improve the solving efficiency of the model and accelerate the convergence speed of the algorithm. Experimental results prove the effectiveness of the multi-UAV cooperative trajectory planning algorithm, thereby addressing different actual needs.

ObjectiveTo analyze the feasibility， reliability and validity of the disability assessment for dementia scale for the elderly.MethodsA total of 290 dementia patients from 17 survey sites in 13 districts and counties of Chengdu were enrolled by convenient sampling method， and they were assessed using demographic data inventory， Mini-Mental State Examination （MMSE）， Neuropsychiatric Inventory （NPI）， Physical Self-Maintenance Scale （PSMS） and disability assessment for dementia scale for the elderly. Cronbach's α coefficient， Spearman-Brown coefficient， Guttman split-half coefficient and test-retest reliability were used to evaluate the internal consistency of above scales. Criterion-related validity of the scale was analyzed based on MMSE， NPI and PSMS.ResultsA total of 276 patients （95.17%） completed valid questionnaires. The intraclass correlation coefficient of the total score and each dimension were between 0.828~0.976， the Spearman-Brown coefficient were between 0.790~0.917， the Guttman split-half coefficient were between 0.812~0.857， and the Cronbach’s α coefficient were between 0.737~0.886. The cognitive function dimension score was positively correlated with the MMSE score （r=0.948， P

Wavelet transformation is a widely used method in high-frequency sequence stratigraphic analysis. However, the application is problematic since different wavelets always return the same sequence analysis results. To address this issue, we applied five commonly used wavelets to theoretical sequence models to document some application criteria. Five gradual scale-change sequence models were simplified from the glutenite succession deposition by gravity flows to form the fining-upwards cycle sequences (FUCS) and coarsening-upwards cycle sequences (CUCS). After conducting theoretical sequence model tests, the optimal wavelet (sym4) was selected and successfully used with actual data to identify the sequence boundaries. We also proposed a new method to optimize the scale of continuous wavelet transformation (CWT) for sequence boundary determination. We found that the balloon-like marks in scalograms of db4, sym4, and coif4 wavelet determine, respectively, the fourth-order sequence boundary, the thick succession sequence boundaries in FUCS, and the thick succession sequence in FUCS and CUCS. Comparing the sequence identification results shows that the asymmetric wavelets had an advantage in high-frequency sequence boundary determination and sedimentary cycle discrimination through the amplitude trend of the coefficient, in which the sym4 wavelet is the most effective. In conclusion, the asymmetry of wavelets is the first selection principle, of which asymmetric wavelets are more sensitive to sediment deposition by flood flows. The match of the wavelet between the sequence is the second selection principle, in which the correlation of time-frequency impacts the accuracy of sequence surface localization. However, the waveform of the wavelet is a visual and abstract parameter for sequence boundary detection. The appropriate wavelet for lacustrine sequence analysis is the asymmetric wavelet with a weak number of side lobes. The depositional flows, depositional process, and autogenic are three sedimentary factors that influence the sequence analysis results. [ABSTRACT FROM AUTHOR]

In this work, a new treatment method combining ultrasonic vibration with FeCoNiCrCu high entropy alloy (HEA) coating was used to prepared Al/Mg bimetal through the lost foam compound casting. The effects of composite treatment involving ultrasonic vibration and HEA coating on interfacial microstructure and mechanical properties of Al/Mg bimetal were studied. Results demonstrate that the interface thickness of the Al/Mg bimetal with composite treatment significantly decreases to only 26.99% of the thickness observed in the untreated Al/Mg bimetal. The HEA coating hinders the diffusion between Al and Mg, resulting the significant reduction in Al/Mg intermetallic compounds in the interface. The Al/Mg bimetal interface with composite treatment is composed of Al3Mg2 and Mg2Si/AlxFeCoNiCrCu+FeCoNiCrCu/δ-Mg+Al12Mg17 eutectic structures. The interface resulting from the composite treatment has a lower hardness than that without treatment. The acoustic cavitation and acoustic streaming effects generated by ultrasonic vibration promote the diffusion of Al elements within the HEA coating, resulting in a significant improvement in the metallurgical bonding quality on the Mg side. The fracture position shifts from the Mg side of the Al/Mg bimetal only with HEA coating to the Al side with composite treatment. The shear strength of the Al/Mg bimetal increases from 32.16 MPa without treatment to 63.44 MPa with ultrasonic vibration and HEA coating, increasing by 97.26%. [ABSTRACT FROM AUTHOR]

Inorganic binder used in casting process has the advantages of low odor, labor-friendly conditions, and relatively low cost, which is one of the main development directions for casting molding materials in the future. However, compared to organic binders (such as resin binders), inorganic binders exhibit lower bonding strength and are more sensitive to environmental humidity. This sensitivity poses challenges, particularly in the reclamation of used sand, thus limiting their broader application. In this paper, the research and application status of inorganic binders (mainly silicate inorganic binders) and their curing methods are summarized. In addition, the research and application of phosphate inorganic binders and 3D printing inorganic binders that are being developed are introduced. Meanwhile, a detailed comparative analysis is conducted on the challenging issue of "reclamation for used sand" in the application of inorganic binders. Finally, the development direction of inorganic binders is clarified. [ABSTRACT FROM AUTHOR]

BackgroundNeurofilament light chain (NfL) is a novel biomarker for the assessment of neurological function after cardiac arrest (CA). Although meta-analysis has confirmed its predictive value, it has not conducted a more detailed analysis of its research. We conducted a meta-analysis to evaluate the relationship between serum NfL level and neurological prognosis in patients with spontaneous circulation recovery after CA, and subgroup analysis was conducted according to sample collection time, time to assess neurological function, study design, whether TTM was received, the method of specimen determination, and the presence of neurological disease in patients. To analyze the influence of these factors on the predictive value of serum NfL.MethodsPublished Cochrane reviews and an updated, extended search of MEDLINE, Cochrane Library, Embase, Scopus, ClinicalKey, CINAHL, and Web of Science for relevant studies until March 2022 were assessed through inclusion and exclusion criteria. The standard mean difference and 95% confidence interval were calculated using the random-effects model or fixed-effects model to assess the association between one variable factor NfL level and the outcome of CA patients. Subgroup analysis according to sample collection time was performed. The prognosis analysis and publication bias were also assessed using Egger's and Begg's tests.ResultsAmong 1209 related articles for screening, 6 studies (1360 patients) met the inclusion criteria and were selected for meta-analysis. The level of serum NfL in the good prognosis group (CPC1-2, CPC: cerebral performance category score) was significantly lower than that in the poor prognosis group (CPC3-5)SMD(standardized mean difference) = 0.553, 95%CI(confidence interval) = 0.418-0.687, I2 = 65.5% PConclusionNfL may play a potential neuroprognostication role in postcardiac arrest patients with spontaneous circulation, regardless of when the sample was collected after CA.

IQM, a plant-specific calmodulin-binding protein, plays multiple roles in plant growth and development. Although a comprehensive analysis has been carried out on the IQM family genes in Arabidopsis and rice, the number and functions of IQM genes in other species have not been explored. In this study, we identified 15 members of the soybean (Glycine max) IQM gene family using BLASTP tools. These members were distributed on 12 soybean chromosomes and constitute six pairs caused by fragment duplication events. According to phylogeny, the 15 genes were divided into three subfamilies (I, II, and III), and members of the same subfamily had similar gene and protein structures. Yeast two-hybrid experiments revealed that the IQ motif is critical for the binding of GmIQM proteins to GmCaM, and its function is conserved in soybean, Arabidopsis, and rice. Based on real-time PCR, the soybean IQM genes were strongly induced by PEG and NaCl, suggesting their important biological functions in abiotic stress responses. Overall, this genome-wide analysis of the soybean IQM gene family lays a solid theoretical foundation for further research on the functions of GmIQM genes and could serve as a reference for the improvement and breeding of soybean stress resistance traits.

Abstract Background Compound kushen injection (CKI), a Chinese patent drug, is widely used in the treatment of various cancers, especially neoplasms of the digestive system. However, the underlying mechanism of CKI in pancreatic cancer (PC) treatment has not been totally elucidated. Methods Here, to overcome the limitation of conventional network pharmacology methods with a weak combination with clinical information, this study proposes a network pharmacology approach of integrated bioinformatics that applies a weighted gene co-expression network analysis (WGCNA) to conventional network pharmacology, and then integrates molecular docking technology and biological experiments to verify the results of this network pharmacology analysis. Results The WGCNA analysis revealed 2 gene modules closely associated with classification, staging and survival status of PC. Further CytoHubba analysis revealed 10 hub genes (NCAPG, BUB1, CDK1, TPX2, DLGAP5, INAVA, MST1R, TMPRSS4, TMEM92 and SFN) associated with the development of PC, and survival analysis found 5 genes (TSPOAP1, ADGRG6, GPR87, FAM111B and MMP28) associated with the prognosis and survival of PC. By integrating these results into the conventional network pharmacology study of CKI treating PC, we found that the mechanism of CKI for PC treatment was related to cell cycle, JAK-STAT, ErbB, PI3K-Akt and mTOR signalling pathways. Finally, we found that CDK1 , JAK1 , EGFR , MAPK1 and MAPK3 served as core genes regulated by CKI in PC treatment, and were further verified by molecular docking, cell proliferation assay, RT-qPCR and western blot analysis. Conclusions Overall, this study suggests that the optimized network pharmacology approach is suitable to explore the molecular mechanism of CKI in the treatment of PC, which provides a reference for further investigating biomarkers for diagnosis and prognosis of PC and even the clinical rational application of CKI.