<p>Correlation between ACTA2, TAGLN, and TPM2 expression and drug sensitivity of selected compounds of drug screening</p>

<p>Distribution of clinical and pathological features in the validation cohort BR1301a</p>

Abstract Solar‐driven high‐efficiency and direct conversion of methane into high‐value‐added liquid oxygenates against overoxidation remains a great challenge. Herein, facile and mass fabrication of low‐cost tungsten single‐atom photocatalysts is achieved by directly calcining urea and sodium tungstate under atmosphere (W‐SA‐PCN‐ m , urea amount m = 7.5, 15, 30, and 150 g). The single‐atom photocatalysts can manage H 2 O 2 in situ generation and decomposition into ·OH, thus achieving highly efficient CH 4 photooxidation in water vapor under mild conditions. Systematic investigations demonstrate that integration of multifunctions of methane activation, H 2 O 2 generation, and decomposition into one photocatalyst can dramatically promote methane conversion to C1 oxygenates with a yield as high as 4956 µmol g cat −1 , superior to that of the most reported non‐precious photocatalysts. Liquid–solid phase transition can induce the products to facilely switch in from HCOOH to CH 3 OH by pulling the catalyst above water with CH 3 OH/HCOOH ratio from 10% (in H 2 O) to 80% (above H 2 O).

<p>Immunohistochemical validation of basal markers in TNBC samples</p>

Shape-memory polymers (SMP) are a class of materials that are better known as smart materials. The smartness of the SMP comes from their tunability properties allowing them to tweak into various shapes and orientations as per the desired applications. Many animals can change the stiffness of their skin, adopt the colors from the environment, change their appearance according to needs and in case of approaching danger, etc. Inspired by these above natural phenomena, many smart materials have been developed by researchers over the last decade and SMP is one of them. SMP polymers can easily be manipulated to the desired shape by changing their physical and chemical parameters such as temperature, light, ultrasound, chemical cross-linkage, crystallization, etc. SMP is a suitable candidate for designing novel metamaterials or programmable metamaterials in which the temporary shape can be retained and also imposed and controlled through programming such that the initial shape of the material can be recovered by an application of an external stimulus. The best characteristic of these polymers is the retain-ability of original or temporary shape in different stimuli fields prompting this material to have a memory effect for shape retainability. Due to such exceptional properties of the SMP, these smart materials find wide applications in Aerospace, Biomedical micro-devices, Robotics, Acoustics, Electronics, Textiles, Bionics engineering, and many other contemporary fields.This chapter discusses some fundamentals related to the fabrication strategies, emerging application aspects, and memory retention/ programming aspects of the shape memory polymers. The current state of the art and future directions has also been outlined to provide a roadmap for smart memory polymers-based technologies.

<p>Expression of BaC-associated genes in murine mammary epithelial subpopulations</p>

BACKGROUND: Spatial transcriptomics (ST) technologies are reshaping our understanding of tissue organization and cellular context in health and disease. However, technical benchmarking across platforms remains limited, particularly in formalin-fixed, paraffin-embedded (FFPE) clinical samples, which represent the most common tissue format in oncology. RESULTS: Here, we systematically benchmark five commercial ST platforms (Visium v1, Visium v2/CytAssist, Visium HD, Xenium, and CosMx) using matched FFPE human tumor sections from six cancer types. Uniquely, our study includes both sequencing-based and imaging-based platforms profiled on the same samples, enabling direct technical comparisons across spatial capture modalities. We evaluate platform performance across multiple dimensions, including transcript and UMI detection, gene-histology concordance, cell type recovery, and integration with a targeted protein panel (Visium v2, 30 proteins), enabling spatial multi-omics. We also quantify the impact of sampling strategies and area coverage on cell type estimation, revealing trade-offs in spatial resolution versus tissue context. Notably, we present the first same-sample comparison of Xenium Multi-Tissue (377 genes) and Xenium Prime (5,000 genes), highlighting key differences in transcript recovery and spatial signal despite shared chemistry and imaging infrastructure. Finally, we integrate Visium targeted protein data with matched RNA profiles, uncovering widespread RNA-protein decoupling and spatial heterogeneity in concordance. CONCLUSIONS: Collectively, this work provides a harmonized dataset and technical reference for the spatial transcriptomics community, offering insight into the relative strengths, limitations, and design considerations associated with high-throughput spatial profiling of FFPE tumors.

<p>Functional validation of TAGLN-KO cells</p>

<p>Evaluation of dasatinib sensitivity in tB-TNBC models <i>in vitro</i> and <i>in vivo</i>. <b>A,</b> Dose–response curves showing cell viability of indicated cell lines treated with increasing concentrations of dasatinib for 72 hours. Solid lines represent the mean of three biological replicates performed in technical replicates normalized to untreated controls, and IC<sub>50</sub> values are indicated. <b>B,</b> Representative IHC images of tB-TNBC PDXs (PDX_01 and PDX_02) showing expression of SMA, TAGL, and TPM2. Scale bars, 100 μm. <b>C,</b> Quantification of positive tumor cells for each tB-marker in PDX_01 and PDX_02. Data are shown as mean ± SEM of different tumor areas. <b>D,</b> Schematic representation of the dasatinib treatment protocol. <b>E,</b> Tumor growth curves of the tB-TNBC PDXs treated with vehicle (black) or dasatinib (red). Error bars, ± SEM. <i>P</i> values calculated by Wilcoxon test. <b>F,</b> Bar plot showing tumor weight at the end point. Data are shown as mean ± SEM. <i>P</i> values calculated by two-tailed Student <i>t</i> test. **, <i>P</i> < 0.01. <b>D,</b> Created in BioRender. Rodilla, V. (2026) <a href="https://BioRender.com/qpb7bux" target="_blank">https://BioRender.com/qpb7bux</a>.</p>

<p>Histological distribution of SMA, TAGL and TPM2 in the validation cohorts of TNBC</p>

<p>Secondary antibodies used for IHC, IF, and WB assays</p>

The proposed work enumerates a hybrid thin, deep-subwavelength (2 cm) acoustic metamaterials acting as a completely new type of sound absorber, showing multiple broadband sound absorption effects. Based on the fractal distribution of Helmholtz resonator (HRs) structures, integrated with careful design and construct hybrid cross micro-perforated panel (CMPP) that demonstrate broad banding approximately one-octave low-frequency sound absorption behavior. To determine the sound absorption coefficient of this novel type of metamaterial, the equivalent impedance model for the fractal cavity and the micro-perforated Maa's model for CMPP are both used. We validate these novel material designs through numerical, theoretical, and experimental data. It is demonstrated that the material design possesses superior sound absorption which is primarily due to the frictional losses of the structure imposed on acoustic wave energy. The peaks of different sound absorption phenomena show tunability by adjusting the geometric parameters of the fractal structures like cavity thickness 't', cross perforation diameter of micro perforated panel, etc. The fractal structures and their perforation panel are optimized dimensionally for maximum broadband sound absorption which is estimated numerically. This new kind of fractals cavity integrated with CMPP acoustic metamaterial has many applications as in multiple functional materials with broad-band absorption behavior etc.

In today’s digital age, people make use of digital media platforms to interact and ‘influence’ each other on social media (Brown and Hayes, 2007). Social media influencers (SMI) are such users who have attained a celebrity-like status and secured a considerable network of followers by developing engaging content based on expertise in a specific domain, and who directly influence the behavior of their followers (Hearn and Schonhoff, 2016; De Veriman et al., 2017; Ge and Gretzel, 2018). VI, also termed as a virtual celebrity, digital personality, CGI influencer (Mrad et al., 2022), or AI influencer (Thomas and Fowler, 2021) refer to fictional personalities created through computer imagery (Miao et al., 2022). They possess human- like characteristics (Burden and Savin-Baden, 2019), physical features and personality (Moustakas et al., 2020), and indulge in online activity (Hudders et al., 2021; Moustakas et al., 2020). VI exhibit anthropomorphism (Moustakas et al., 2020), ranging from anime-like to almost human-like appearance (Kim et al., 2023), and akin to human influencers, can be effective as they can look and behave like human influencers (Sands et al., 2020). In the case of human SMIs, scholars have adopted the opinion leadership framework to analyze the persuasive traits of an endorser. Katz and Lazersfeld (1955) have highlighted the significant role played by the media spokesperson in persuading audience into use sponsors’ product or services, which they termed as the ‘opinion leader’. Thus, trust in an endorser is of utmost importance. Consumer segments are heterogeneous and factors which contribute or detract viewer trust in VI can also differ. VI phenomena are at the introductory stage in emerging economies like India, and we aim to gain insight on viewers perception of VI as new endorser.

BACKGROUND: Accurate locoregional staging is critical in the management of T1 rectal cancer and guides organ-preserving strategies. Despite guideline recommendations, the real-world performance of magnetic resonance imaging (MRI) and endoscopic ultrasound (EUS) remains unclear. This study aims to evaluate the use and accuracy of locoregional staging in T1 rectal cancer. METHODS: Retrospective analysis was performed from a nationwide multicentre T1 colorectal cancer cohort (EpiT1 Consortium) between 2007 and 2018 with a 5-year follow-up. Locoregional staging methods included MRI and EUS. Multivariable logistic regression identified factors associated with locoregional imaging. The accuracy of each technique and their combination for T and N staging was assessed. RESULTS: Among 3161 patients with T1 colorectal cancer, 681 had rectal cancer, of which 424 (62.3%) underwent locoregional staging: 234 (55.2%) with MRI only, 131 (30.9%) with both MRI and EUS, and 59 (13.9%) with EUS only. Factors associated with imaging (MRI and EUS) included management at a referral centre (odds ratio 2.9, 95% confidence interval 1.5 to 5.7), tumour location in the low/middle rectum (odds ratio 3.2, 1.8 to 5.7), suspicion of invasive carcinoma at colonoscopy (odds ratio 2.4, 1.3 to 4.5), and high-risk histological features (odds ratio 3.7, 1.8 to 7.4). MRI accurately staged T in 28.3%, whereas EUS achieved an accuracy of 59% for T staging. Combining modalities overstaged 67.1% of tumours for T staging. N staging was detected with ≤ 16% sensitivity across all strategies; in the surgical group (MRI and/or EUS), overall accuracy was 78%. CONCLUSION: Locoregional staging varied widely and was influenced by non-tumour-related factors. MRI and EUS showed modest accuracy, overstaging T, and low sensitivity for N. These findings highlight the need to improve pretreatment evaluation of T1 rectal cancer.

<p>Integration of three scRNA-seq datasets from healthy human mammary gland</p>

<p>Integration of three scRNA-seq datasets from adult murine mammary gland</p>