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Background Autism spectrum disorder (ASD) negatively impacts mental health, particularly in mothers of autistic children who experience heightened stress. Applied behaviour analysis (ABA) and music therapy are recognised interventions for improving ASD symptoms. However, the specific benefits of parent–child music therapy and ABA for autistic children and their mothers remain uncertain. This study evaluated the effects of parent–child music therapy on preschool autistic children and their mothers. Method A randomised controlled trial was conducted with 100 mother–child pairs assigned to either the control group receiving ABA or the intervention group receiving both music therapy and ABA. Qualitative interviews were conducted post-intervention for 12 mothers. Results Children in the intervention group exhibited lower scores for ASD symptoms than those in the control group. Moreover, mothers in the intervention group demonstrated reduced dysfunctional parent–child interaction, lower overall parental stress, significantly improved family functioning, and increased levels of hope compared with those in the control group. Mothers held positive views regarding music therapy. Conclusions Combining ABA with parent–child music therapy can alleviate ASD symptoms in children and reduce stress in mothers. Improved parent–child interaction and enhanced family functioning further support the benefits of this combined approach. Parent–child music therapy, combined with ABA demonstrated positive outcomes for autistic children, including reduced ASD symptoms, improved parent–child interaction, decreased parental stress, enhanced family functioning, and increased hope. These findings highlight the potential of incorporating music therapy as a valuable component in the comprehensive treatment of ASD. Trial registration This study was registered in the Chinese Clinical Trial registry (05/07/2021, ChiCTR2100048261, https://www.chictr.org.cn/showproj.html?proj=128957 ). Ethical approval was obtained from the Research Ethics Committee of Fujian Medical University and the study hospital (Fujian Provincial Maternity and Child Health Hospital; 2017 − 105), and informed consent was obtained from all subjects and/or their legal guardian(s).

The isothermal enzyme‐free nucleic acid amplification method plays an indispensable role in biosensing by virtue of its simple, robust, and highly efficient properties without the assistance of temperature cycling or/and enzymatic biocatalysis. Up to now, enzyme‐free nucleic acid amplification has been extensively utilized for biological assays and has achieved the highly sensitive detection of various biological targets, including DNAs, RNAs, small molecules, proteins, and even cells. In this Review, the mechanisms of entropy‐driven reaction, hybridization chain reaction, catalytic hairpin assembly and DNAzyme are concisely described and their recent application as biosensors is comprehensively summarized. Furthermore, the current problems and the developments of these DNA circuits are also discussed.

The interfacial structure between the inorganic filler and epoxy resin matrix in epoxy resin (EP) composites has a great influence on the mechanical properties, thermal conductivity, and electrical properties. In this paper, two micro@nanostructured Al2O3 fillers and their epoxy resin composites were prepared, and their morphology, interfacial bond strength, mechanical properties, thermal conductivity, and electrical properties systematically tested and analyzed. The experimental results show that modification by a nano-Al2O3 coating on the surface of micro-Al2O3 can effectively improve the infiltration of Al2O3 filler and epoxy resin, reduce the interfacial defects caused by weak bonding of Al2O3 filler and epoxy resin, and thus synergistically improve the mechanical properties, thermal conductivity, and electrical properties of epoxy resin composites. The thermal conductivity was improved by 22.5% compared with 22.65% when using micro-Al2O3/EP, the tensile and flexural strength were improved by 36.67% and 20.82%, and the alternating-current breakdown strength was improved by 12.88%. In addition, thermally stimulated current experiments were carried out to study the electron transport properties of micro@nano-Al2O3 epoxy resin composites, revealing that filler nanomodification could improve the trap depth, suppress the carrier transport, and improve the dielectric properties of the composites.Graphic Abstract

Chalcogenide perovskites have gained attention as alternative semiconductor materials, yet their experimental investigation remains limited. This study investigates the synthesis and characterization of a series of chalcogenide perovskite powder samples via the sulfurization of oxide precursors at different temperatures. Zr- and Hf-based chalcogenide perovskites adopted a perovskite structure with a Pnma space group, while Ti-based chalcogenides formed hexagonal phases. The minimum synthesis temperature varied among materials and was correlated with the strength of the A cation–oxygen bonds. The synthesized chalcogenide perovskites exhibit bandgaps suitable for solar cell absorption layers, and the photoluminescence (PL) results indicate that SrZrS3, SrHfS3, CaZrS3, and CaHfS3 are promising candidates for light-emitting semiconductors.

Epsilon-poly-l-lysine (ε-PL) is a potent antimicrobial agent, but strategies to enhance its biosynthesis remain limited due to insufficient understanding of its physiological regulation. This study explores the interaction between Streptomyces albulus and heterogeneous microbial extracts, with a focus on actinomycete-derived signals. The S. gilvosporeus extract induces the highest ε-PL production (3.4 g/L), exceeding the control by 2.6-fold and outperforming B. cinerea by 1.8-fold. Multi-omics analyses combined with morphological and biochemical profiling reveal that the induced state is characterized by intensified central carbon flux, enhanced lipid turnover, elevated respiratory activity, and cofactor regeneration, alongside suppression of competing secondary pathways. Morphological alterations, including denser mycelial aggregation and compact colony structures, accompany these metabolic shifts. Compared to B. cinerea, S. gilvosporeus elicits more pronounced stress adaptation and metabolic reprogramming in S. albulus. These findings suggest that interspecies interactions can activate intrinsic aggression resistance mechanisms, thereby driving ε-PL biosynthesis through a previously unrecognized physiological route.

Background Cancer originates from dysregulated cell proliferation driven by driver gene mutations. Despite numerous algorithms developed to identify genomic mutational signatures, they often suffer from high computational complexity and limited clinical applicability. Methods Here, we presented ProgModule, an advanced computational framework designed to identify mutation driver modules for cancer prognosis and immunotherapy response prediction. In ProgModule, we introduced the Prognosis-Related Mutually Exclusive Mutation (PRMEM) score, which optimizes the balance between exclusive mutation coverage and the incorporation of mutation combination mechanisms critical for cancer prognosis. Results Applying to BLCA and HNSC cohorts, ProgModule successfully identified driver modules that stratify patients into distinct prognostic subgroups, and the combination of these modules could serve as an effective prognostic biomarker. Extending our method to diverse cancers, ProgModule presented robust prognostic performance and stability across model parameters, including stopping criteria and network topology. Moreover, our analysis suggested that driver modules can predict immunotherapeutic benefit more effectively than existing signatures. Further analyses based on published CRISPR data indicated that genes within these modules may serve as potential therapeutic targets. Conclusions Altogether, ProgModule emerges as a powerful tool for identifying mutation driver modules as prognostic and immunotherapy response biomarkers, and genes within these modules may be used as potential therapeutic targets for cancer, offering new insights into precision oncology.

Cataracts are associated with a decline in both cognitive and visual functions. This study examines postoperative changes in cognitive and visual functions in patients with age-related cataracts, focusing on the differential effects of unilateral and bilateral cataract surgeries on these functions. Additionally, the study evaluates changes in cognitive function following cataract surgery in individuals with mild cognitive impairment (MCI). A cohort of patients (n = 35, 59 eyes) aged 60 years and older (69.9 ± 7.0 years) with age-related cataracts who underwent unilateral or bilateral cataract surgery between May and June 2024 was selected. Cognitive and visual functions were evaluated preoperatively and at 1 week, 1 month, and 3 months postoperatively. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA). Visual function was assessed using a binocular visual function testing system based on virtual reality (VR) technology, which evaluated low spatial frequency suppression, simultaneous vision, stereopsis, and perceptual eye position under 3D viewing conditions without glasses. Based on preoperative MoCA scores, patients were classified into cognitively normal and mild cognitive impairment (MCI) groups. Patients with age-related cataracts demonstrated significant improvements in both cognitive and visual functions at 1 week, 1 month, and 3 months postoperatively, compared to preoperative assessments (  < 0.05). Specifically, both the bilateral surgery group and the MCI group exhibited substantial improvements in cognitive function at these time points (  < 0.05). Additionally, the bilateral surgery group outperformed the unilateral surgery group in cognitive function throughout the follow-up period (  < 0.05). In terms of visual function, the bilateral surgery group showed significant improvements in low spatial frequency suppression, simultaneous vision, and stereopsis at 1 week, 1 month, and 3 months postoperatively, compared to preoperative measurements (  < 0.05). Both cognitive and visual functions significantly improved after cataract surgery. Bilateral cataract surgery is more effective in increasing the cognitive functions than unilateral surgery. Additionally, cataract surgery plays a critical role in facilitating cognitive recovery in patients with mild cognitive impairment (MCI).

We evaluated the performance of three global evapotranspiration (ET) models at local, regional, and global scales using the multiple sets of leaf area index (LAI) and meteorological data from 1982 to 2017 and investigated the uncertainty in ET simulations from the model structure and forcing data. The three ET models were the Simple Terrestrial Hydrosphere model (SiTH) developed by our team, the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), and the MODerate Resolution Imaging Spectroradiometer (MODIS) ET algorithm (MOD16). Comparing the observed with simulated monthly ET by the three models over 43 Fluxnet sites, we found that SiTH overestimated ET for forests with mean slope from 1.25 to 1.67, but it performed better than the other two models over short vegetation. MOD16 and PT-JPL models simulated well for forests but poorly in dryland biomes (slope = 0.25~0.55; R2 = 0.02~0.46). At the catchment scale, all models performed well, except for some tropical and high latitudinal catchments, with NSE values lower than 0 and RMSE and MAE values far beyond their mean values. At the global scale, SiTH highly overestimated ET in tropics, while PT-JPL slightly underestimated ET between 30°N and 60°N and MOD16 underestimated ET between 15°S and 30°S. Generally, the PT-JPL provided the better performance than SiTH and MOD16 models. This study also revealed that the estimated ET by SiTH and especially PT-JPL model were influenced by the uncertainty in meteorological data, and the estimated ET was performed better using MERRA-2 datasets for PT-JPL and using ERA5 datasets for SiTH. While the estimated ET by MOD16 were relatively sensitive to LAI data. In addition, our results suggested that the GLOBMAP and GIMMS datasets were more suitable for long-term ET simulations than the GLASS dataset.

Cotton, one of the most important economic crops worldwide, has long been bred mainly for improvements in yield and quality, with relatively little focus on salt-alkali resistance. In this study, transcriptomic and metabolomic sequencing were performed on exposed to alkaline stress for different durations. The results of sample clustering, principal component analysis (PCA), and the number of differentially expressed genes (DEGs) revealed that 12 hours and 24 hours were the periods during which upland cotton presented the strongest response to salt stress, with flavonoid biosynthesis and alpha-linolenic acid metabolism playing significant roles during this time. A total of 6,610 DEGs were identified via comparison to the 0 h time point, including 579 transcription factors (TFs) that were significantly enriched in pathways such as flavonoid biosynthesis, the cell cycle, the cytochrome P450 pathway, phenylalanine metabolism, phototransduction, and alpha-linolenic acid metabolism. Through ultrahigh-performance liquid chromatography-MS (UPLC-MS), 4,225 metabolites were identified, and 1,684 differentially accumulated metabolites (DAMs) were identified by comparison to the levels at 0 h. A joint analysis of RNA-seq and metabolomic data revealed that the flavonoid biosynthesis and alpha-linolenic acid metabolism pathways play key roles in the response of to alkaline stress, and the key genes in these pathways were identified. The weighted gene correlation network analysis (WGCNA) revealed 15 candidate genes associated with alkali tolerance in cotton, including 4 TFs and 4 genes related to flavonoid and anthocyanin biosynthesis. In conclusion, our study provides a theoretical foundation for understanding the molecular mechanisms underlying alkali tolerance in cotton and offers new gene resources for future research.

The tumor microenvironment (TME) cells interact with each other and play a pivotal role in tumor progression and treatment response. A comprehensive characterization of cell and intercellular crosstalk in the TME is essential for understanding tumor biology and developing effective therapies. However, current cell infiltration analysis methods only partially describe the TME's cellular landscape and overlook cell‐cell crosstalk. Here, this approach, CITMIC, can infer the cell infiltration of TME by simultaneously measuring 86 different cell types, constructing an individualized cell‐cell crosstalk network based on functional similarities between cells, and using only gene transcription data. This is a novel approach to estimating the relative cell infiltration levels, which are shown to be superior to the current methods. The TME cell‐based features generated by analyzing melanoma data are effective in predicting prognosis and treatment response. Interestingly, these features are found to be particularly effective in assessing the prognosis of high‐stage patients, and this method is applied to multiple high‐stage adenocarcinomas, where more significant prognostic performance is also observed. In conclusion, CITMIC offers a more comprehensive description of TME cell composition by considering cell‐cell crosstalk, providing an important reference for the discovery of predictive biomarkers and the development of new therapeutic strategies. CITMIC is a novel method for assessing the extent of cell infiltration in the TME by considering the cell‐cell crosstalk. It can simultaneously infer 86 different cell types and its performance is superior to other methods through comparing cytometry immunophenotyping. The cell infiltration levels can be used to predict cancer patient prognosis, especially in highly staged adenocarcinomas.