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Immersive technology plays an increasingly important role in design education, supporting digital literacy and experiential learning in higher education, particularly in the post-COVID-19 context. Many design disciplines, such as Architecture and Landscape Design, which used to rely heavily on physical field trips, and dialogic studios as signature pedagogies, had to adapt to the proliferation of innovative educational technologies due to the suspension of face-to-face teaching and learning. Augmented reality and virtual reality are now extensively used in technology and design education to support a more interactive, collaborative, and student-centred approach to learning. This paper expands on a pilot research study on the transition from traditional signature pedagogies of studio-based design education to technology-enhanced collaborative learning to support experiential learning. Based on Kolb's experiential learning framework concerning four learning modes, namely, concrete experience (CE), reflective observation (RO), abstract conceptualisation (AC), and active experimentation (AE), this paper analyses data from 75 undergraduate students across four cohorts in three different higher education institutions in Hong Kong. They were surveyed on their experiences of synchronous hybrid virtual experiential learning with design and technology curricula. Furthermore, six students were interviewed about their experiences. The research findings confirm two research hypotheses showing that immersive experiential learning could constructively align RO and AE, thus bringing an overall positive impact on the experiential learning process, but shows no conclusive influence on promoting CE, especially AC. The quantitative findings and qualitative results gave new insights into the discussion of the theoretical and practical implications of the study.

Purpose: This study builds upon an established effective training method to investigate the advantages of high variability phonetic identification training for enhancing lexical tone perception and production in Mandarin-speaking pediatric cochlear implant (CI) recipients, who typically face ongoing challenges in these areas. Method: Thirty-two Mandarin-speaking children with CIs were quasirandomly assigned into the training group (TG) and the control group (CG). The 16 TG participants received five sessions of high variability phonetic training (HVPT) within a period of 3 weeks. The CG participants did not receive the training. Perception and production of Mandarin tones were administered before (pretest) and immediately after (posttest) the completion of HVPT via lexical tone recognition task and picture naming task. Both groups participated in the identical pretest and posttest with the same time frame between the two test sessions. Results: TG showed significant improvement from pretest to posttest in identifying Mandarin tones for both trained and untrained speech stimuli. Moreover, perceptual learning of HVPT significantly facilitated trainees' production of T1 and T2 as rated by a cohort of 10 Mandarin-speaking adults with normal hearing, which was corroborated by acoustic analyses revealing improved fundamental frequency (F0) median for T1 and T2 production and enlarged F0 movement for T2 production. In contrast, TG children's production of T3 and T4 showed nonsignificant changes across two test sessions. Meanwhile, CG did not exhibit significant changes in either perception or production. Conclusions: The results suggest a limited and inconsistent transfer of perceptual learning to lexical tone production in children with CIs, which challenges the notion of a robust transfer and highlights the complexity of the interaction between perceptual training and production outcomes. Further research on individual differences with a longitudinal design is needed to optimize the training protocol or tailor interventions to better meet the diverse needs of learners.

In order to study the horizontal well multi-segment multi-cluster fracture extension in the deep coal reservoir where the cleat fissures are developed, a multi-segment multi-cluster fracture extension model is created based on the extended finite element and taking into account the inter-seam interference and the induced stress field. With the secondary development of pre-processing in Python language, a large number of approximately orthogonal cleat fissures were added into the model. The effects of cluster spacing, fracturing sequence and segment spacing on multi-fracture extension were analyzed, and the advantages and disadvantages of fracturing effect were verified by querying the number of fracture-communicating cutting groups. The simulation results show that when the cluster spacing is 20 m and the segment spacing is 40-45 m, the number of fracture communication cutting groups is relatively high, and the fracture length is optimal due to the small influence of inter-seam interference and induced stress field; at the aspect of the influence of different fracturing sequences on the extension of multi-fractures, the fracturing effects are ranked from excellent to poor: sequential fracturing > alternating fracturing > synchronous fracturing. The results of modeling and field application are in good agreement, with 96.5% for the second fracturing section and 93.4% for the third fracturing section.

Abstract Background Immunoglobulin A nephropathy (IgAN) is a complex renal disease with a highly variable clinical course. Identifying reliable prognostic markers is crucial for risk stratification and treatment decisions. This study aimed to understand the influence of different proportions of crescents (Cs) on the progression of IgAN. Methods Four databases (PubMed, Web of Science, Embase, and Cochrane Library) were searched until September 25, 2023. The study encompassed IgAN patients, focusing on kidney outcomes and end-stage kidney disease (ESKD). Statistical analysis included calculating hazard ratios (HR) for binary outcomes and examining publication bias. Results The meta-analysis involved thirteen studies comprising 11,849 patients. For kidney outcomes, crescent formation may be linked to an elevated risk (HR = 2.01, 95%CI 1.40–2.87, P 10 (HR = 1.8, 95%CI 1.32–2.45, P 25%(HR = 2.11, 95% CI 1.47–3.02, P 25% also displayed an elevated risk (HR = 1.70, 95% CI 1.18–2.44, P = 0.004). However, a proportion > 10% (including > 25%) did not show a significant association with ESKD (HR = 1.12, 95% CI 0.36–3.47, P = 0.842) versus less. Conclusions This systematic review and meta-analysis established a strong association between crescent proportions and the progression of IgAN. Higher proportions, notably exceeding 25%, were reliable prognostic markers, indicating a greater risk of adverse kidney outcomes and ESKD. These findings have significant clinical implications, offering the potential for more precise risk stratification in IgAN patients.

Abstract Orthopedic implants have faced challenges in treating bone defects due to various factors, including inadequate osseointegration, oxidative stress, bacterial infection, immunological rejection, and poor individualized treatment. These challenges profoundly affect both the results of treatment and patients' daily lives. There is great promise for the layer-by-layer (LbL) assembly method in tissue engineering. The method primarily relies on electrostatic attraction and entails the consecutive deposition of electrolyte complexes with opposite charges onto a substrate, leading to the formation of homogeneous single layers that can be quickly deposited to produce nanolayer films. LbL has attracted considerable interest as a coating technology because of its ease of production, cost-effectiveness, and capability to apply diverse biomaterial coatings without compromising the primary bio-functional properties of the substrate materials. This review will look into the fundamentals and evolution of LbL in orthopedics, provide an analysis of the chemical strategy used to prepare bone implants with LbL and introduce the application of LbL bone implants in orthopedics over recent years. Among the many potential uses of LbL, such as the implementation of sustained-release and programmed drug delivery, which in turn promotes the osseointegration and the development of new blood vessels, as well as antibacterial, antioxidant, and other similar applications. In addition, we offer a thorough examination of cell behavior and biomaterial interaction to facilitate the advancement of next-generation LbL films for tissue engineering.

Abstract This study investigated the effect of dietary interventions targeting gut microbiota on exercise performance in mice. Analysis of the gut microbiota of individuals with varying levels of physical activity revealed enrichment of Eubacterium rectale and Faecalibacterium prausnitzii in the active population. Through in vitro fecal fermentation experiments, dietary factor combinations that promote the abundance of these bacteria were identified. Dietary interventions, including E. rectale supplementation, FAG combination (gavage of Fructus Arctii extract, Agaricus blazei Murrill polysaccharides, and galactooligosaccharides mixture), and CFG combination (gavage of curcumin, Fructus Arctii extract, and galactooligosaccharides mixture), significantly improved mouse exercise performance, increased glycogen accumulation, regulated serum biochemical parameters, and increased short‐chain fatty acid and fatty acid amide levels in feces. Metagenomic sequencing revealed alterations in the composition of the gut microbiota. Fecal metabolome analysis highlighted changes in metabolites related to lipids, organic acids, nucleic acids, and carbohydrates. These findings suggest that E. rectale and dietary interventions positively affect exercise performance by modulating the gut microbiota and associated metabolites.

In this study, we investigated the evolution of grain structures and second phases of a Mg-9.5Gd-4Y–2Zn-0.3Zr alloy during two-stage deformation that took place in the metal during hot extrusion, as well as their effects on its mechanical properties. We found that the alloy exhibited a bimodal grain structure consisting of equiaxed dynamic recrystallized (DRXed) grains and elongated unDRXed grains. As the extrusion process progressed, DRX occurred on a large scale, resulting in an increase in the proportion of DRXed grains from 17.8% to 93.2%, and a reduction in average grain size from 80.3 μm to 9.41 μm. The grain orientation also underwent a transition from a single orientation of an extrusion direction (ED) parallel to (i.e. ED//) to mixed orientations of ED// and ED//. The primary mechanism of dynamic recrystallization (DRX) during extrusion involved particle-stimulated nucleation (PSN) accompanied by both continuous and discontinuous DRX. The Mg-9.5Gd-4Y–2Zn-0.3Zr alloy mainly contained intergranular 18R-long period stacking order (LPSO) phases and intragranular 14H-LPSO. As the extrusion process progressed, 18R-LPSO changed from blocky to lamellar to accommodate deformation, and β-Mg5(Gd,Y) phase particles dynamically precipitated along DRXed grain boundaries. The 14H-LPSO phase was found to be primarily distributed within coarse unDRXed grains. As deformation via extrusion progressed, the quantity of 14H-LPSO gradually decreased. Ultimately, with the gradual dissolution of Mg5(Gd,Y), 14H-LPSO reprecipitated within the recrystallized grain boundaries. As the extrusion process progressed, both the yield strength (YS) and elongation (EL) increased from 132.6 MPa to 287.6 MPa and from 10.8% to 15.5%, respectively. This was mainly attributed to the significant reduction in grain size and second phase size.

Laser powder bed fusion (LPBF) fabricated Al–Mn–Mg-Sc-Zr alloy generally possesses a bi-modal microstructure of columnar grains and equiaxed grains. Such an anisotropic microstructure would introduce varied tensile performance in different orientations. To date, few study on the microstructure and tensile property anisotropy have been reported for LPBF fabricated Al–Mn–Mg-Sc-Zr alloys built at different layer thicknesses, which limits the exploration in mechanical property optimization. In this work, the microstructure anisotropy and room-temperature tensile properties of LPBF produced and peak-aged Al–Mn–Mg-Sc-Zr alloys built at 30 and 60 μm layer thicknesses were systematically investigated by scanning electron microscope, transmission electron microscope, and tensile testing. A higher layer thickness of 60 μm resulted in coarser grains with the precipitates size remained similarly compared to the 30 μm specimens. This led to a reduced yield strength in 60 μm specimens (492–509 MPa) comparing to those in 30 μm specimens at 502 MPa–510 MPa. In addition, the existence of columnar grains within melt pools contributed to a larger effective slip length in the vertical direction than that in the horizontal orientation. Such difference in effective slip length in the loading direction contributed to a lower strength in vertical orientations. For ductility, the slightly higher defect level in 60 μm specimens (0.58%) resulted in reduced elongations of 3%–6% compared to those of 30 μm specimens (0.10%). The ductility anisotropy was attributed to the preferential distribution of gas pores and keyhole defects at melt pool boundaries.

ObjectiveTo address the problem of ultra-short baseline (USBL) relative navigation and positioning during the dynamic docking of an autonomous underwater vehicle (AUV) in shallow water, a compensated unscented particle filter (CUPF) algorithm based on a disturbance observer is proposed. MethodsThe CUPF algorithm compensates for missing values in the USBL data based on the dead reckoning model, estimates the unknown disturbances in the dynamic docking of the AUV using observer technology and filters outliers in the USBL data combined with the unscented particle filter to realize the estimation of the AUV's state. Results The lake trial data shows that the proposed CUPF algorithm can effectively remove outliers and fill in missing values for USBL positioning with a speed estimation error of less than 15% and computation time reduced by 57% compared with traditional methods. ConclusionsThe CUPF algorithm can improve the positioning accuracy of USBL while smoothing the AUV motion trajectory and state estimation by fully utilizing relative measurement information for AUV docking.

Abstract Background Alcohol dehydrogenase (ADH) is an enzyme that binds to zinc, facilitating the interconversion of ethanol and acetaldehyde or other corresponding alcohols/aldehydes in the pathway of ethanol fermentation. It plays a pivotal role in responding to environmental stress. However, the response of the ADH family to abiotic stress remains unknown in rapeseed. Result In this study, we conducted a comprehensive genome-wide investigation of the ADH family in rapeseed, encompassing analysis of their gene structure, replication patterns, conserved motifs, cis-acting elements, and response to stress. A total of 47 ADH genes were identified within the rapeseed genome. Through phylogenetic analysis, BnADHs were classified into four distinct clades (I, II, IV, V). Prediction of protein domains revealed that all BnADH members possessed a GroES-like (ADH_N) domain and a zinc-bound (ADH_zinc_N) domain. Analysis of promoter sequences demonstrated that BnADHs contained numerous cis-acting elements associated with hormone and stress responses, indicating their widespread involvement in various biological regulatory processes. Expression profiling under different concentrations of salt stress treatments (0%, 0.4%, 0.8%, 1.0% NaCl) further highlighted the significant role played by the BnADH family in abiotic stress response mechanisms. Overexpression of BnADH36 in rapeseed significantly improved the salt tolerance of rapeseed. Conclusion The features of the BnADH family in rapeseed was comprehensively characterized in this study, which could provide reference to the research of BnADHs in abiotic stress response.

Abstract Background In clinical oncology practice, patient-reported outcomes (PROs) are essential for assessing the symptom burden, quality of life, and psychological status of patients. However, there remains a gap between the use of PROs in an oncologic setting and its implementation. Furthermore, numerous reviews in PRO implementation are often based on one particular technology, setting, or health condition, making it difficult to obtain a comprehensive and coherent summary of available evidence to help plan and undertake implementation. This systematic review aims to identify and integrate enablers and barriers to PRO implementation through the comprehensive framework for implementation research (CFIR) to provide a reference for implementing patient-reported outcomes management in oncology settings. Methods This review strictly observed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed, Web of Science, CINAHL, Embase, and PsycINFO databases were systematically searched using a three-step search strategy. The search was limited from the inception of each database to April 2024. Articles describing facilitators and barriers to implementing PROs in clinical oncology practice were included. Two researchers screened the literature independently, and the quality assessment of cross-sectional, qualitative, and mixed studies was completed using the critical appraisal tools recommended by Joanna Briggs Institute (JBI) and the mixed methods assessment tool, respectively. Basic information about the included studies and determinants affecting PRO implementation was extracted, and coding categorization of facilitators and barriers was completed based on the 48 constructs provided by the CFIR framework. Results We included 30 studies from 5,649 search results, including 25 original and 5 review studies. The quality of the literature for qualitative studies was generally good, and the quality for quantitative and mixed studies was assessed as fair. We identified 52 facilitators and 50 barriers in the included literature, covering the domains used in the CFIR framework and 39 constructs, mainly including "Innovation Evidence-Base", "Innovation Complexity", "Innovation Design", "Structural Characteristics", "Compatibility", "Incentive Systems", "Access to Knowledge & Information", "Innovation Deliverers", "Innovation Recipients", and "Planning". Conclusions This systematic review integrated facilitators and barriers affecting PRO implementation in routine oncology clinical practice settings and categorized them through the CFIR framework. These influencing factors should be fully considered in future clinical practice to ensure the successful implementation of PROs. Trial registration It has been registered prospectively in PROSPERO under the registration number 42024532983.

Abstract The intricate balance among cost, output, and quality has substantially hindered the practical application of graphene within the downstream industry chain. Here we present a scalable and green supercritical CO2-assisted mechano-exfoliation (SCME) process that omits the use of organic solvents and oxidants throughout the production lifecycle, including exfoliation, separation, and purification. The SCME process achieves graphene powder space-time yields exceeding 40 kg/(m³·day) at laboratory (0.06–0.2 kg) and pilot scales ( > 4 kg), with resultant free-standing films showing conductivities up to 5.26 × 10⁵ S/m. Further kinetic investigations propose general guidelines for grinding-assisted exfoliation: (1) the macroscopic optimizing ability of mechanotechnics for mass transfer frequency and stress distribution and (2) the microscopic multiplication ability of exfoliation medium for shear-delamination. The comprehensive techno-economic analysis also underscores the economic viability of the SCME process for large-scale production.

Abstract This retrospective study used cone-beam computed tomography to investigated the crown-root morphology and alveolar bone structure in incisors region in subjects with closed deep overbite and comparison the difference between gender and age. The CBCT images for 40 subjects (group C) with Angle II division 2 were selected from patients of the HeFei Stomatological Hospital from November 2023 to March 2024.20 individual normal occlusion subjects (group A),20 patients with Angle II division 1(group B) were included. The crown-root ratio of the maxillary and mandibular anterior teeth, crown-root angle and alveolar bone structure were measured on the CBCT images, the data were statistically analyzed. In addition to mandibular lateral incisor, the crown-root ratio of maxillary and mandibular anterior teeth in the Class II division 2 group was higher than that in the individual normal occlusion group and the Class II division 1 (P

Abstract Thyroid cancer (TC) represents one of the most prevalent endocrine malignancies, with a rising incidence worldwide. Epigenetic alterations, which modify gene expression without altering the underlying DNA sequence, have garnered significant attention in recent years. Increasing evidence underscores the pivotal role of epigenetic modifications, including DNA methylation, RNA methylation, and histone methylation, in the pathogenesis of TC. This review provides a comprehensive overview of these reversible and environmentally influenced epigenetic modifications, highlighting their molecular mechanisms and functional roles in TC. Additionally, the clinical implications, challenges associated with studying these epigenetic modifications, and potential future research directions are explored. Graphical Abstract

Abstract Carboxy-terminus of Hsc70-interacting protein (CHIP), an E3 ligase, modulates the stability of its targeted proteins to alleviate various pathological perturbations in various organ systems. Cisplatin is a widely used chemotherapeutic agent, but it is also known for its alarming renal toxicity. The role of CHIP in the pathogenesis of cisplatin-induced acute kidney injury (AKI) has not been adequately investigated. Herein, we demonstrated that CHIP was abundantly expressed in the renal proximal tubular epithelia, and its expression was downregulated in cisplatin-induced AKI. Further investigation revealed that CHIP overexpression or activation alleviated, while its gene disruption promoted, oxidative stress and apoptosis in renal proximal tubular epithelia induced by cisplatin. In terms of mechanism, CHIP interacted with and ubiquitinated NUR77 to promote its degradation, which consequently shielded BCL2 to maintain mitochondrial permeability of renal proximal tubular cells in the presence of cisplatin. Also, we demonstrated that CHIP interacted with NUR77 via its central coiled-coil (CC) domain, a non-canonical interactive pattern. In conclusion, these findings indicated that CHIP ubiquitinated and degraded its substrate NUR77 to attenuate intrinsic apoptosis in cisplatin-treated renal proximal tubular epithelia, thus providing a novel insight for the pathogenesis of cisplatin-induced AKI.

Abstract Computer holography is a prominent technique for reconstructing customized three-dimensional (3D) diffraction fields. However, the quality of optical reconstruction remains a fundamental challenge in 3D computer holography, especially for the 3D diffraction fields with physically continuous and extensive depth range. Here, we propose a 3D computer-generated hologram (CGH) optimization framework with phase space tailoring. Based on phase space analysis of the space and frequency properties in both lateral and axial directions, the intensity of the 3D diffraction field is adequately sampled across a large depth range. This sampling ensures the reconstructed intensity distribution to be comprehensively constrained with physical consistency. A physics-informed loss function is constructed based on the phase space tailoring to optimize the CGH with suppression of vortex stagnation. Numerical and optical experiments demonstrate the proposed method significantly enhances the 3D optical reconstructions with suppressed speckle noise across a continuous and extensive depth range.

Abstract Clinical evidence supports the notion that T cell exhaustion and terminal differentiation pose challenges to the persistence and effectiveness of chimeric antigen receptor-T (CAR-T) cells. MEK1/2 inhibitors (MEKIs), widely used in cancer treatment due to their ability to inhibit aberrant MAPK signaling, have shown potential synergistic effects when combined with immunotherapy. However, the impact and mechanisms of MEKIs on CAR-T cells remain uncertain and controversial. To address this, we conducted a comprehensive investigation to determine whether MEKIs enhance or impair the efficacy of CAR-T cells. Our findings revealed that MEKIs attenuated CAR-T cell exhaustion and terminal differentiation induced by tonic signaling and antigen stimulation, thereby improving CAR-T cell efficacy against hematological and solid tumors. Remarkably, these effects were independent of the specific scFvs and costimulatory domains utilized in CARs. Mechanistically, analysis of bulk and single-cell transcriptional profiles demonstrates that the effect of MEK inhibition was related to diminish anabolic metabolism and downregulation of c-Fos and JunB. Additionally, the overexpression of c-Fos or JunB in CAR-T cells counteracted the effects of MEK inhibition. Furthermore, our Cut-and-Tag assay revealed that MEK inhibition downregulated the JunB-driven gene profiles associated with exhaustion, differentiation, anergy, glycolysis, and apoptosis. In summary, our research unveil the critical role of the MAPK-c-Fos-JunB axis in driving CAR-T cell exhaustion and terminal differentiation. These mechanistic insights significantly broaden the potential application of MEKIs to enhance the effectiveness of CAR-T therapy.

Abstract In recent years, deep learning models have dramatically influenced image inpainting. However, many existing studies still suffer from over‐smoothed or blurred textures when missing regions are large or contain rich visual details. To restore textures at a fine‐grained level, a multi‐stage inpainting approach is proposed, which applies a series of partial inpainting modules as well as a progressive inpainting module to inpaint missing areas from their boundaries to the centre successively. Some improvements are made on the partial convolutions to reduce artifacts like blurriness, which require a convolution kernel to contain known pixels more than a certain proportion. Towards photorealistic inpainting results, the intermediate outputs from each stage are used to compute the loss. Finally, to facilitate the training process, a multi‐step training is designed that progressively adds inpainting modules to optimize the model. Experiments show that this method outperforms the current excellent techniques on the publicly available datasets: CelebA, Places2 and Paris StreetView.

Abstract Alternative splicing is an important process that contributes to highly diverse transcripts and protein products, which can affect the development of disease in various organisms. Cardiovascular disease (CVD) represents one of the greatest global threats to humans, particularly acute myocardial infarction (MI) and subsequent ischemic reperfusion (IR) injury, which involve complex transcriptomic changes in heart tissues associated with metabolic reshaping and immunological response. In this study, we used a newly developed ONT full-length transcriptomic approach and performed transcript-resolved differential expression profiling in murine models of MI and IR. We built an analytical pipeline to reliably identify and quantify alternative splicing products (isoforms), expanding on the currently available catalog of isoforms described in mice. The updated alternative splicing landscape included transcripts, genes, and pathways that were differentially regulated during IR and MI. Our study establishes a pipeline to profile highly diverse isoforms using state-of-the-art long-read sequencing, builds a landscape of alternative splicing in the mouse heart during MI and IR.

Abstract The industrial internet acts as a crucial accelerator for driving enterprise digital transformation and plays a vital role in enhancing performance and competitiveness. However, our understanding of how small and medium-sized enterprises (SMEs) leverage the industrial internet to improve their performance and competitiveness remains limited. This study developed a “Digital transformation paths chain” framework to shed light on the key factors that drive SMEs to adopt the industrial internet and its influence on performance and competitiveness. Data from 314 Chinese SMEs were collected and analyzed using fsQCA and PLS-SEM to examine this model. Our findings highlight the positive impact of industrial internet adoption on enterprise performance and competitive advantage. The results highlight that technology, organization, and environment (TOE) drive industrial internet adoption. Industrial internet adoption positively impacts enterprise performance and competitive advantage through integration, application, and drive. This study offers valuable insights for businesses, policymakers, and other stakeholders engaged in digital transformation initiatives through the industrial internet.

A series of star-shaped multi-arm styrene-butadiene copolymers (S-g-SSB-6) were synthesized by living anionic polymerization, with n-butyllithium as initiator, styrene and butadiene as monomers, 2,2-di(tetra-hydrofuran-2-yl) propane as polar structure regulator and hexachlorodisilane as coupling agent. The molecular weight and its distribution, coupling arm number and coupling efficiency of S-g-SSB-6 were characterized by gel permeation chromatogram. The rheological properties of S-g-SSB-6, star-shaped multi-arm styrene-butadiene copolymer with SiCl4 as coupling agent, and linear styrene-butadiene copolymer (L-SSB) were characterized by rotational rheometer, and the effects of branched chain length and branched chain flexibility on the rheological properties of S-g-SSB-6 were also investigated. The results showed that the coupling arm numbers of S-g-SSB-6 reached 4.1, and the coupling efficiency was greater than 80%. S-g-SSB had lower melt viscosity and better fluid flow than those of L-SSB under the same weight-average molecular weight. When the branching degree was the same, the melt viscosity of S-g-SSB-6 increased with the increase of single arm molecular weight and molecular chain rigidity.

Reservoir characterization is a vital task within the oil and gas industry, with the identification of lithofacies in subsurface formations being a fundamental aspect of this process. However, lithofacies identification in complex geological environments with high dimensions, such as the Lower Indus Basin in Pakistan, poses a notable challenge, especially when dealing with limited data. To address this issue, we propose four common data-driven machine learning approaches: multi-resolution graph-based clustering (MRGC), artificial neural networks (ANN), K-nearest neighbors (KNN), and self-organizing map (SOM). We utilized these proposed approaches to assess their performance in scenarios with varying core sample availability, specifically evaluating their effectiveness in identifying lithofacies within the Lower Goru formation of the middle Indus Basin. The study reveals that in scenarios with a limited number of core samples, MRGC is the preferred choice, while KNN or MRGC is more suitable for larger datasets. The results demonstrate the superior performance of MRGC and KNN in lithofacies identification within the specified geological environment, with SOM following closely behind, and ANN exhibiting comparatively lower efficacy. The accurate identification of lithofacies from the selected model is complemented by the application of the truncated Gaussian simulation method for facies modeling. Comparative results confirm the excellent agreement between the model identification of lithofacies from well logs and electro-facies obtained from the truncated Gaussian simulation electro-facies volume. This study highlights the crucial role of selecting the right machine learning approach for precise lithofacies identification and modeling in complex geological environments. The comparative analysis provides practitioners in the petroleum industry with insights into the strengths and limitations of each method, enhancing existing knowledge. In conclusion, this research emphasizes the significance of comprehensive research and method selection for advancing lithofacies identification in diverse formations or study areas, ultimately benefiting the broader field of subsurface characterization in the petroleum industry.

Abstract The intratumoral microbiome (TM) refers to the microorganisms in the tumor tissues, including bacteria, fungi, viruses, and so on, and is distinct from the gut microbiome and circulating microbiota. TM is strongly associated with tumorigenesis, progression, metastasis, and response to therapy. This paper highlights the current status of TM. Tract sources, adjacent normal tissue, circulatory system, and concomitant tumor co‐metastasis are the main origin of TM. The advanced techniques in TM analysis are comprehensively summarized. Besides, TM is involved in tumor progression through several mechanisms, including DNA damage, activation of oncogenic signaling pathways (phosphoinositide 3‐kinase [PI3K], signal transducer and activator of transcription [STAT], WNT/β‐catenin, and extracellular regulated protein kinases [ERK]), influence of cytokines and induce inflammatory responses, and interaction with the tumor microenvironment (anti‐tumor immunity, pro‐tumor immunity, and microbial‐derived metabolites). Moreover, promising directions of TM in tumor therapy include immunotherapy, chemotherapy, radiotherapy, the application of probiotics/prebiotics/synbiotics, fecal microbiome transplantation, engineered microbiota, phage therapy, and oncolytic virus therapy. The inherent challenges of clinical application are also summarized. This review provides a comprehensive landscape for analyzing TM, especially the TM‐related mechanisms and TM‐based treatment in cancer.

Abstract Engineering Kondo lattice with tailored functionality is desirable for elucidating the heavy fermion physics. We realize the construction of an artificial Kondo lattice/superconductor heterojunction by growing monolayer VSe2 on bulk 2H-NbSe2 with molecular beam epitaxy. Spectroscopic imaging scanning tunneling microscopy measurements show the emergence of a new charge density wave (CDW) phase with $$\sqrt{3}\times$$ 3 × $$\sqrt{3}$$ 3 periodicity on the monolayer VSe2. Unexpectedly, a pronounced Kondo resonance appears around the Fermi level, and distributes uniformly over the entire film, evidencing the formation of Kondo lattice. Density functional theory calculations suggest the existence of magnetic interstitial V atoms in VSe2/NbSe2, which play a key role in forming the CDW phase along with the Kondo lattice observed in VSe2. The Kondo origin is verified from both the magnetic field and temperature dependences of the resonance peak, yielding a Kondo temperature of ~ 44 K. Moreover, a superconducting proximity gap opens on monolayer VSe2, whose shape deviates from the function of one-band BCS superconductor, but is reproduced by model calculations with heavy electrons participating the pairing condensate. Our work lays the experimental foundation for studying interactions between the heavy fermion liquids and the superconducting condensate.

Abstract Quantitatively probing the ultimate limit of near-field enhancement around plasmonic nanostructures remains elusive, despite more than five decades since the discovery of surface-enhanced Raman scattering. Theoretical calculations have predicted an ultimate near-field enhancement exceeding 1000 using the best plasmonic material silver, but experimental estimations disperse by orders of magnitude. Here, we design a high-quality silver plasmonic nanocavity with atomic precision and precisely quantify the upper limit of near-field enhancement in ~1 nm junctions. A hot-spot averaged Raman enhancement of 4.27 × 1010 is recorded with a small fluctuation, corresponding to an averaged electric field enhancement larger than 1000 times. This result quantitatively delineates the ultimate limit of plasmonic field enhancement around plasmonic nanostructures, establishing a foundation for diverse plasmon-enhanced processes and strong light-matter interactions at the atomic scale.

Highlights The introduction of MoS2 generates a “kill three birds with one stone” effect to the original binary MXene/ANF system: lubrication toughening mechanical performance; reduction in secondary reflection pollution of electromagnetic wave; and improvement in the performance of photothermal conversion. After the introduction of MoS2 into MXene/ANF (60:40), the strain and toughness were increased by 53.5% (from 18.3% to 28.1%) and 61.7% (from 8.9 to 14.5 MJ m−3), respectively. Fortunately, the SER decreases by 22.4%, and the photothermal conversion performance was increased by 22.2% from ~ 45 to ~ 55 °C.

Abstract To address challenges in screening for chronic kidney disease (CKD), we devised a deep learning-based CKD screening model named UWF-CKDS. It utilizes ultra-wide-field (UWF) fundus images to predict the presence of CKD. We validated the model with data from 23 tertiary hospitals across China. Retinal vessels and retinal microvascular parameters (RMPs) were extracted to enhance model interpretability, which revealed a significant correlation between renal function and RMPs. UWF-CKDS, utilizing UWF images, RMPs, and relevant medical history, can accurately determine CKD status. Importantly, UWF-CKDS exhibited superior performance compared to CTR-CKDS, a model developed using the central region (CTR) cropped from UWF images, underscoring the contribution of the peripheral retina in predicting renal function. The study presents UWF-CKDS as a highly implementable method for large-scale and accurate CKD screening at the population level.

Abstract Background In recent years, radiomics has been shown to be an effective tool for the diagnosis and prediction of diseases. Existing evidence suggests that imaging features play a key role in predicting the recurrence of lumbar disk herniation (rLDH). Thus, this study aimed to evaluate the risk of rLDH in patients undergoing percutaneous endoscopic lumbar discectomy (PELD) using radiomics to facilitate the development of more rational surgical and perioperative management strategies. Method This was a retrospective case-control study involving 487 patients who underwent PELD at the L4/5 level. The rLDH and negative groups were matched using propensity score matching (PSM). A total of 1409 radiomic features were extracted from preoperative lumbar MRI images using intraclass correlation coefficient (ICC) analysis, t-test, and LASSO analysis. Afterward, 6 predictive models were constructed and evaluated using ROC curve analysis, AUC, specificity, sensitivity, confusion matrix, and 2 repeated 3-fold cross-validations. Lastly, the Shapley Additive Explanation (SHAP) analysis provided visual explanations for the models. Results Following screening and matching, 128 patients were included in both the recurrence and control groups. Moreover, 18 of the extracted radiomic features were selected for generating six models, which achieved an AUC of 0.551–0.859 for predicting rLDH. Among these models, SVM, RF, and XG Boost exhibited superior performances. Finally, cross-validation revealed that their accuracy was 0.674–0.791, 0.647–0.729, and 0.674–0.718. Conclusion Radiomics based on MRI can be used to predict the risk of rLDH, offering more comprehensive guidance for perioperative treatment by extracting imaging information that cannot be visualized with the naked eye. Meanwhile, the accuracy and generalizability of the model can be improved in the future by incorporating more data and conducting multicenter studies.

Abstract Ecolinguistics explores the interplay between language and the environment, offering insights into how linguistic elements adapt and evolve. This study examines five cement-related English loanwords in Chinese to uncover the evolutionary mechanisms governing the adaptation of these loanwords by analyzing their ecological dynamics. The research quantitatively evaluates the ecology of these loanwords using two indicators: lexical niche breadth and overlap. The results are as follows: (1) The emergence of English loanwords in Chinese is intricately linked to specific social environments. As new concepts and items are introduced from abroad, the masses initially coin new loanwords, which are later standardized by authoritative bodies. (2) The vitality of the loanwords correlates with their niche breadth. The competition among lexical variants is influenced by niche overlap. The loanwords for cement are ranked by vitality values in descending order—ShuiNi (水泥/water mud): 3.221, YangHui (洋灰/foreign ash): 2.350, ShuiMenTing (水门汀/water-gate concrete): 1.385, HongMaoNi (红毛泥/red-hair clay): 1.202, and ShiMinTu (士敏土/sticky soil): 0.879. (3) The endangerment of the loanwords results from the synergistic interaction between external (nature, society, culture, psychology) and internal (sound, form, meaning, grammar) environments. Intense competition arises due to multiple synonyms for the same entity, and adaptation challenges occur when the loanwords do not precisely fit the entity. Among the five loanwords for cement, the first two exhibit higher vitality and continue to develop sustainably, while the last three show lower vitality and are gradually becoming endangered. As these loanwords undergo continuous evolution, a lexical ecocontinuum emerges: (i) extinct in the wild—ShiMinTu; (ii) critically endangered—HongMaoNi; (iii) endangered—ShuiMenTing; (iv) vulnerable—YangHui; (v) least concerned—ShuiNi.

Abstract Increasing the molecular weight while maintaining mono-dispersity has been proved crucial in innovating high-performance photovoltaic materials in giant oligomeric acceptors. However, developing efficient giant oligomeric donors to replace the batch-varied polymers remains challenging due to a lack of design principles. Here, by designing two unique isomeric rhodanine-based linkers, we successfully regulate the assembly behaviors of giant dimeric donors (G-Dimer-Ds) and fabricate the first all-giant-oligomer OSCs pairing with giant dimeric acceptor DY. Multiple characterizations demonstrate the small homo-molecular interaction with strong thermal-driven assembly capability in G-Dimer-D2 simultaneously facilitates reducing energetic disorder, improving charge transport and obtaining stable morphology, resulting in a satisfactory efficiency of 15.70% and long-term photostability with an extrapolated T 80 of ca.10,000 hours, and further enhancing thermal-driven assembly promotes efficiency of 16.05%. Our results provide construction approaches on efficient giant donors, and propose a promising type of OSC with completely definite structures, high efficiency and superior stability.

Abstract LncRNAs are highly implicated in oxidative stress (OS) during the growth of mammalian follicles. TAK1 binding protein 2 gene (TAB2) has been suggested to involve in the normal apoptosis and proliferation of granulosa cells (GCs), the main supporting cells in ovarian follicles. In this study, we found that TAB2 increased the expressions of SOD1, P50, and P65 to suppress the OS, thereby inhibiting the apoptosis and promoting the proliferation in GCs. Notably, DNMTs appeared to mediate the expression of TAB2 without the changes of DNA methylation at TAB2’s promoter. We identified an antisense lncRNA of TAB2, discovered that DNA methylation regulated the transcription of TAB2-AS in GCs, and found TAB2-AS medicated the follicular growth of ovaries in vivo. Mechanistically, the hypomethylation of the CpG site (−1759/−1760) activated the transcription of TAB2-AS, and the 1–155 nt and 156-241 nt of TAB2-AS were respectively complementary to 4368–4534 nt and 4215–4300 nt of TAB2’s mRNA to increase the expression of TAB2. Moreover, TAB2-AS inhibited the OS and apoptosis of GCs, while promoted the proliferation of GCs to expedite the follicular growth, which was in line with that of TAB2. Collectively, these findings revealed the antisense lncRNA mechanism mediated by DNA methylation, and TAB2-AS might be the target to control OS during follicular growth in mammals.

Spaceborne Synthetic Aperture Radar (SAR) systems are often subject to strong electromagnetic interference, resulting in imaging quality degradation. However, existing image domain-based interference suppression methods are prone to image distortion and loss of texture detail information, among other difficulties. To address these problems, this paper proposes a method for suppressing active suppression interferences inspaceborne SAR images based on perceptual learning of regional feature refinement. First, an active suppression interference signal and image model is established in the spaceborne SAR image domain. Second, a high-precision interference recognition network based on regional feature perception is designed to extract the active suppression interference pattern features of the involved SAR image using an efficient channel attention mechanism, consequently resulting in effective recognition of the interference region of the SAR image. Third, a multivariate regional feature refinement interference suppression network is constructed based on the joint learning of the SAR image and suppression interference features, which are combined to form the SAR image and suppression interference pattern. A feature refinement interference suppression network is then constructed based on the joint learning of the SAR image and suppression interference feature. The network slices the SAR image into multivariate regions, and adopts multi-module collaborative processing of suppression interference features on the multivariate regions to realize refined suppression of the active suppression interference of the SAR image under complex conditions. Finally, a simulation dataset of SAR image active suppression interference is constructed, and the evaluated Sentinel-1 data are used for experimental verification and analysis. The experimental results show that the proposed method can effectively recognize and suppress various typical active suppression interferences in spaceborne SAR images.

Invasive tumors are difficult to be completely resected in clinical surgery due to the lack of clear resection margins, which greatly increases the risk of postoperative recurrence. However, chemotherapy and radiotherapy as the traditional means of postoperative adjuvant therapy, are limited in postoperative applications, such as multi-drug resistance and low sensitivity, etc. Therefore, an engineered magnesium alloy rod is designed as a postoperative implant to completely remove postoperative residual tumor tissue and inhibit tumor recurrence by gas and mild magnetic hyperthermia therapy (MMHT). As a reactive metal, magnesium alloy responds to the acidic tumor microenvironment by continuously generating hydrogen. The in-situ generation of hydrogen not only protects the surrounding normal tissue, but also enables the magnesium alloy to achieve MMHT under low-intensity alternating magnetic field (AMF). Furthermore, the numerous reactive oxygen species (ROS) produced by heat stress will combine with nitric oxide (NO) generated in situ, to produce more toxic reactive nitrogen species (RNS) storm. In summary, engineered magnesium alloy can completely remove residual tumor tissue and inhibit tumor recurrence by MMHT and RNS storm under low-intensity AMF, and the biodegradability of magnesium alloy makes great potential for clinical application.

This study aimed to study the effects of sterilization temperature and time on the quality of canned Antarctic krill pretreated with L-lysine (Lys) at the same sterilization intensity. Pretreatment with either water or the water-retaining agent sodium tripolyphosphate (STPP) served as control. Four combinations of sterilization temperature and time were established as follows: 115 ℃ for 60 min, 117 ℃ for 38 min, 119 ℃ for 24 min, and 121 ℃ for 15 min. After sterilization at 115 ℃ for 60 min, the Lys-treated group had lower hardness and chewiness and the lowest degree of lipid oxidation. Low-field nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) analysis indicated the largest peak area of immobilized water and the highest signal intensity in the pseudo-color image. The microstructure analysis showed that the muscle tissue treated with Lys had a more regular and complete structure with uniformly distributed pores. The sensory evaluation results showed that Antarctic krill meat treated with Lys and sterilized at 115 ℃ for 60 min had better flavor and texture, and scored highest in acceptability. In conclusion, Lys could be a substitute for phosphate to improve the quality of canned Antarctic krill, and sterilization at 115 ℃ for 60 min was the optimal sterilization conditions to maintain the quality of canned Antarctic krill. Lys pretreatment combined with this sterilization process has good applicability in actual production.

Abstract Background The reference values of eNO have certain differences among people of different countries and races. We aimed to obtain the reference value of eNO in healthy children and adolescents (6–18 years old) in China and to explore the associations between the reference values with ages, gender, heights, BMI, and regions. Methods We measured FeNO50 levels in 5949 healthy Chinese children and adolescents, FeNO200 and CaNO levels in 658 participants from 16 provinces of 7 administrative areas in China aged 6–18. All persons were studied after obtaining informed consent from children and their parents. Results The mean FeNO50 of 5949 Chinese children and adolescents aged 6–18 years was 14.1 ppb, with a 95% confidence interval of 1-38.1 ppb. The mean FeNO200 of 658 persons was 6.9 ppb with a 95% upper confidence interval of 15.0 ppb, and the mean CaNO was 3.0 ppb with a 95% upper confidence interval of 11.2 ppb. In the 6–11 age group, age and height were correlated with the logarithm of FeNO50 (P 0.05). The logarithm of CaNO was correlated with gender (P

Abstract Background Acute kidney injury (AKI) is a major complication following cardiac surgery. We explored the clinical utility of iron metabolism indexes for identification of patients at risk for AKI after cardiac surgery. Methods This prospective observational study included patients who underwent cardiac surgery between March 2023 and June 2023. Iron metabolism indexes were measured upon admission to the intensive care unit. Multivariable logistic regression analyses were performed to explore the relationship between iron metabolism indexes and cardiac surgery-associated AKI (CSA-AKI). Receiver operating characteristic (ROC) curve was used to assess the predictive ability of iron, APACHE II score and the combination of the two indicators. Restricted cubic splines (RCS) was used to further confirm the linear relationship between iron and CSA-AKI. Results Among the 112 recruited patients, 38 (33.9%) were diagnosed with AKI. Multivariable logistic regression analysis indicated that APACHE II score (odds ratio [OR], 1.208; 95% confidence interval [CI], 1.003–1.455, P = 0.036) and iron (OR 1.069; 95% CI 1.009–1.133, P = 0.036) could be used as independent risk factors to predict CSA-AKI. ROC curve analysis showed that iron (area under curve [AUC] = 0.669, 95% CI 0.572–0.757), APACHE II score (AUC = 0.655, 95% CI 0.557–0.744) and iron and APACHE II score combination (AUC = 0.726, 95% CI 0.632–0.807) were predictive indicators for CSA-AKI. RCS further confirmed the linear relationship between iron and CSA-AKI. Conclusions Elevated iron levels were independently associated with higher risk of CSA-AKI, and there was a linear relationship between iron and CSA-AKI.

Abstract Recent advances in cancer research have highlighted the pivotal role of tertiary lymphoid structures (TLSs) in modulating immune responses, particularly in breast cancer (BRCA). Here, we performed an integrated analysis of bulk transcriptome data from over 6000 BRCA samples using biological network-based computational strategies and machine learning (ML) methods, and identified LGALS2 as a key marker within TLSs. Single-cell sequencing and spatial transcriptomics uncover the role of LGALS2 in TLS-associated dendritic cells (DCs) stimulation and reveal the complexity of the tumor microenvironment (TME) at both the macro and micro levels. Elevated LGALS2 expression correlates with prolonged survival, which is associated with a robust immune response marked by diverse immune cell infiltration and active anti-tumor pathways leading to a ‘hot’ tumor microenvironment. The colocalization of LGALS2 with TLS-associated DCs and its role in immune activation in BRCA were confirmed by hematoxylin-eosin (HE), immunohistochemistry (IHC), and in vivo validation analyses. The identification of LGALS2 as a key factor in BRCA not only highlights its therapeutic potential in novel TLS-directed immunotherapy but also opens new avenues in patient stratification and treatment selection, ultimately improving clinical management.

Abstract The olfactory system can generate unique sensory memories of various odorous molecules, guiding emotional and cognitive decisions. However, most existing electronic noses remain constrained to momentary concentration, failing to trigger specific memories for different smells. Here, we report an artificial olfactory memory system utilizing conductive metal-organic frameworks (Ce-HHTP) that integrates sensing and memory and exhibits short- and long-term memory responses to alcohols and aldehydes. Experiments and theoretical calculations show that distinct memories are derived from the specific combinations of Ce-HHTP with O atoms in different guest. An unmanned aircraft equipped with this system realized the sensory memories in established areas. Moreover, the fusion of portable detection boxes and wearable flexible electrodes demonstrated the immense potential in off-site pollution monitoring and health management. This work represents an artificial olfactory memory system with two specific sensory memories under simultaneous conditions, laying the foundation for bionic design with qualities of human olfactory memory.

Highlights Comprehensively reviewed the progress in research on graphene electrode-based triboelectric nanogenerators (TENGs) from two dimensions, including precision processing methods of graphene electrodes and applications of TENGs. Discussed the various applications of graphene electrode-based TENGs in different scenarios, as well as the ways in which graphene electrodes enhance the performance of TENGs. Offered a prospective discussion on the future development of graphene electrode-based TENGs, with the aim of promoting continuous advancements in this field.

The present study systematically investigated the influence of forging strategies on the microstructures and deformation behaviors of a Ti–5Al–5Mo–5V–1Cr–1Fe (Ti-55511) near β-titanium alloy. Microstructure analysis revealed that the as-cast alloy exhibited a basket-weave structure predominantly comprised of lamellar α phase. Three different forging methods were used to adjust the morphology of the primary α phase during the final two forging steps: 1) dual-phase (825 °C) + dual-phase forging (DD sample), 2) dual-phase + β single-phase (900 °C) forging (DS sample), and 3) β single-phase + dual-phase forging (SD sample). After standard heat treatment, the DD samples exhibited equiaxed αp due to sufficient deformation in dual-phase region, while DS samples transformed into lamellar shape due to αp reforming during the cooling process of the final β single-phase forging. In contrast, the SD samples displayed short-rod αp due to reforming in the single-phase region and insufficient deformation in the dual-phase region. All these αp and βt phases can hinder dislocation motion to enhance the strength. The DS sample exhibited the best combination of strength, ductility, and impact toughness. During tensile deformation, planar dislocation slip and {101‾1} twinning were dominant in the αp, while wave slip occurred in the βt phase. The fracture behavior transitioned from brittle to ductile after forging and heat treatment. Overall, this study offers a practical and effective method for optimizing the mechanical properties of the Ti-55511 alloy.

The traditional method of screening plants for disease resistance phenotype is both time-consuming and costly. Genomic selection offers a potential solution to improve efficiency, but accurately predicting plant disease resistance remains a challenge. In this study, we evaluated eight different machine learning (ML) methods, including random forest classification (RFC), support vector classifier (SVC), light gradient boosting machine (lightGBM), random forest classification plus kinship (RFC_K), support vector classification plus kinship (SVC_K), light gradient boosting machine plus kinship (lightGBM_K), deep neural network genomic prediction (DNNGP), and densely connected convolutional networks (DenseNet), for predicting plant disease resistance. Our results demonstrate that the three plus kinship (K) methods developed in this study achieved high prediction accuracy. Specifically, these methods achieved accuracies of up to 95% for rice blast (RB), 85% for rice black-streaked dwarf virus (RBSDV), and 85% for rice sheath blight (RSB) when trained and applied to the rice diversity panel I (RDPI). Furthermore, the plus K models performed well in predicting wheat blast (WB) and wheat stripe rust (WSR) diseases, with mean accuracies of up to 90% and 93%, respectively. To assess the generalizability of our models, we applied the trained plus K methods to predict RB disease resistance in an independent population, rice diversity panel II (RDPII). Concurrently, we evaluated the RB resistance of RDPII cultivars using spray inoculation. Comparing the predictions with the spray inoculation results, we found that the accuracy of the plus K methods reached 91%. These findings highlight the effectiveness of the plus K methods (RFC_K, SVC_K, and lightGBM_K) in accurately predicting plant disease resistance for RB, RBSDV, RSB, WB, and WSR. The methods developed in this study not only provide valuable strategies for predicting disease resistance, but also pave the way for using machine learning to streamline genome-based crop breeding.

Abstract Background Esophageal squamous cell carcinoma (ESCC) is often diagnosed at advanced stages due to the inherent limitations of current screening methodologies. Central to evaluating tumor invasion and prognostic assessment in ESCC is the integrity of the basement membrane (BM). However, current research on the implications of BM-related genes (BMRGs) in diagnosing ESCC remains sparse. Methods We performed a comprehensive analysis using single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, alongside gene expression profiles acquired from GEO and The Cancer Genome Atlas (TCGA) databases. This identified differentially expressed BMRGs in ESCC. Employing LASSO, RF, and SVM-RFE, we selected potential BM biomarkers and crafted a diagnostic nomogram for ESCC, validated by ROC curves and AUC values. We also explored immune infiltration and biological mechanisms through consensus clustering and GSVA, and utilized single cell trajectory analysis and GSCALite to study gene distributions and pathways. In vitro experiments further elucidated the role of these genes in ESCC carcinogenesis. Results Here, we discovered that ESCC cell types exhibited markedly elevated BM-related scores. Our analysis pinpointed seven BM genes upregulated and linked to immune infiltration, showcasing unique gene expression profiles and varying immune cell densities across the BM-related subtypes. Furthermore, a robust positive correlation was observed between these genes expression and EMT activity. The knockdown of BGN significantly suppressed cell proliferation, migration, invasion, while also augmenting cell viability following chemotherapy drug treatment. Conclusion Our study identified seven key BMRGs (BGN, LAMB3, SPARC, MMP1, LUM, COL4A1, and NELL2) and established a diagnostic nomogram for ESCC. Of noteworthy significance is the discovery of BGN as a promising drug target, indicating a novel strategy for future clinical combination therapies in ESCC.

Abstract Psychiatric disorders are severe health challenges that exert a heavy public burden. Air pollution has been widely reported as related to psychiatric disorder risk, but their casual association and pathological mechanism remained unclear. Herein, we systematically investigated the large genome-wide association studies (6 cohorts with 1,357,645 samples), single-cell RNA (26 samples with 157,488 cells), and bulk-RNAseq (1595 samples) datasets to reveal the genetic causality and biological link between four air pollutants and nine psychiatric disorders. As a result, we identified ten positive genetic correlations between air pollution and psychiatric disorders. Besides, PM2.5 and NO2 presented significant causal effects on schizophrenia risk which was robust with adjustment of potential confounders. Besides, transcriptome-wide association studies identified the shared genes between PM2.5/NO2 and schizophrenia. We then discovered a schizophrenia-derived inhibitory neuron subtype with highly expressed shared genes and abnormal synaptic and metabolic pathways by scRNA analyses and confirmed their abnormal level and correlations with the shared genes in schizophrenia patients in a large RNA-seq cohort. Comprehensively, we discovered robust genetic causality between PM2.5, NO2, and schizophrenia and identified an abnormal inhibitory neuron subtype that links schizophrenia pathology and PM2.5/NO2 exposure. These discoveries highlight the schizophrenia risk under air pollutants exposure and provide novel mechanical insights into schizophrenia pathology, contributing to pollutant-related schizophrenia risk control and therapeutic strategies development. Graphical Abstract

Abstract Wearable ultrasound imaging technology has become an emerging modality for the continuous monitoring of deep-tissue physiology, providing crucial health and disease information. Fast volumetric imaging that can provide a full spatiotemporal view of intrinsic 3D targets is desirable for interpreting internal organ dynamics. However, existing 1D ultrasound transducer arrays provide 2D images, making it challenging to overcome the trade-off between the temporal resolution and volumetric coverage. In addition, the high driving voltage limits their implementation in wearable settings. With the use of microelectromechanical system (MEMS) technology, we report an ultrasonic phased-array transducer, i.e., a 2D piezoelectric micromachined ultrasound transducer (pMUT) array, which is driven by a low voltage and is chip-compatible for fast 3D volumetric imaging. By grouping multiple pMUT cells into one single drive channel/element, we propose an innovative cell–element–array design and operation of a pMUT array that can be used to quantitatively characterize the key coupling effects between each pMUT cell, allowing 3D imaging with 5-V actuation. The pMUT array demonstrates fast volumetric imaging covering a range of 40 mm × 40 mm × 70 mm in wire phantom and vascular phantom experiments, achieving a high temporal frame rate of 11 kHz. The proposed solution offers a full volumetric view of deep-tissue disorders in a fast manner, paving the way for long-term wearable imaging technology for various organs in deep tissues.