Browse Articles
Discover research articles across all indexed journals
Epithelial cell extrusion underlies starvation-induced cell loss in a sea anemone
Abstract Epithelia likely predate the last common animal ancestor, yet the evolutionary origin and nutritional regulation of epithelial remodelling remain poorly understood. Here, we show that extensive, starvation-induced cell loss in the sea anemone Nematostella vectensis is associated with epidermal cell extrusion. This process involves formation of a rosette-like arrangement in which an apoptotic, extruding cell is surrounded by a phospho-ERK1/2-positive ring of cells, accompanied by basal translocation of adherens junction components. Combining chemical perturbations with computational quantification of extrusion and cell density, we show that apoptosis is necessary but not sufficient for rosette formation, and that ERK1/2 signalling limits epidermal extrusion density. Furthermore, we find increased extrusion activity during starvation, and potential nutrient recycling via phagocytosis of extruded cells. Together, our findings indicate that epithelial cell extrusion has physiological roles in sea anemones and that its key hallmarks are likely evolutionarily ancient, predating the last common cnidarian-bilaterian ancestor.
Direct Access to Inherently Chiral Phosphines via an Enantioselective Palladium-Catalyzed Hirao Reaction
Metabolomic properties of the fluid from the surgical ligation after breast-conserving therapy and intraoperative radiotherapy
Non-invasive in vivo acoustoelectric neuromodulation and its contribution to ultrasound stimulation
Abstract Non-invasive brain stimulation offers therapeutic potential without surgery, yet existing electrical approaches lack spatial precision due to the long wavelengths of electric fields. Here we demonstrate acoustoelectric neuromodulation, a nonlinear interaction between applied acoustic and electric fields that generates spatially localised, low-frequency electric fields at the ultrasound focus. Using in vitro and in vivo mouse electrophysiology, we show motor-evoked responses that depend on both the amplitude and frequency of the acoustoelectric field, with controls excluding purely acoustic or electrical origins. In vivo measurements show acoustoelectric potentials of ≈9 mV, corresponding to estimated focal electric fields of ~6 V/m at 500 kHz and 1 MPa acoustic pressure, with ~1.5 mm extrema spacing demonstrated in phantom experiments. Importantly, we identify an acoustoelectric contribution to conventional ultrasound stimulation, arising from interactions between ultrasound-induced electrical signals and propagating acoustic waves, establishing acoustoelectric neuromodulation as a distinct mechanism influencing ultrasound-based brain stimulation.
Comparative genomics reveals population structure and functional differentiation in Limosilactobacillus fermentum
Sequence redesign of glycosyltransferases for enhanced heterologous expression and glycosylation efficiency in Escherichia coli
Zwitterionic Bioinspired Acceptor–Acceptor (A <sub>1</sub> –A <sub>2</sub> ) Type Interlayers for Organic Solar Cells
Statistical approach to analyze wear parameters and worn surface morphology of aluminum – silicon carbide (13%) – graphite composites with and without cryogenic treatment
Abstract Recent technology requires materials with unusual combinations of properties to meet specific needs. Composite materials are gaining more importance due to high toughness, stiffness, specific strength, strength to weight ratio etc. Hybrid composite materials are in more demand with varying reinforcement which enhances mechanical properties. The present work is aimed at reinforcing AL6061 alloy with 13% Silicon carbide and varying % of graphite (1%, 2% and 3%). The hybrid composites are fabricated using bottom pouring stir casting machine. The fabrication of specimens is done as per ASTM standards. The wear characteristics of Al–SiC (13%)-Graphite composites, with and without cryogenic treatment, were investigated using a statistical optimization approach based on the Taguchi method. The multiple regression equation obtained using ANOVA correlates the evaluation of the wear of the HYBRID combination of both untreated and cryogenically treated (CT) specimens with a reasonable degree of approximation. Cryogenic treatment resulted in a reduction in wear scar depth and coefficient of friction under the tested conditions. The Al 6061/13%SiC/2%Gr is best among all the combinations studied.
Molecular diffusion enhanced performance evaluation of metal-organic frameworks for CO2 capture
Abstract Molecular diffusion is a fundamental property that limits the performance of solid sorbents in carbon dioxide capture and separation applications. Unique to each sorbent, gas diffusion is determined by the physical and chemical interactions that occur between the gas molecules and a sorbent’s surface atoms. At the process level where carbon dioxide capture performance is validated, however, simulations are typically carried out using generalized parameters that omit the structure-specific, molecular kinetics occurring in each sorbent. Here, we report process-scale simulations of carbon dioxide capture performance in metal-organic frameworks (MOF) informed by molecular adsorption predictions that represent the unique structural properties of each MOF. By evaluating a total of 10,143 MOFs for post-combustion carbon dioxide capture, we demonstrate how the inclusion of the material-specific, molecular diffusion dynamics alters their simulated, process-level performance. The method could be applied to evaluate a broader class of solid sorbents, including covalent organic frameworks and zeolites.
Artificial intelligence facilitates urban green transition in the Yangtze River Delta urban agglomeration
Abstract This study examines the pivotal role of artificial intelligence (AI) in advancing the urban green transition (UGT), with a particular focus on the Yangtze River Delta (YRD) Urban Agglomeration. Drawing on panel data from 40 cities in the YRD between 2012 and 2024, the research utilizes benchmark regression, non-linear effect analysis, and spatial econometric models to investigate how AI influences UGT through production, consumption, and agglomeration channels. The main findings are as follows: (1) AI exerts a significant positive effect on UGT. (2) UGT exhibits strong spatial autocorrelation, whereas AI’s impact is characterized by robust local promotion but limited spatial spillover. (3) The influence of AI displays marked heterogeneity, varying by urban hierarchy, geographic location, resource endowment, and levels of institutional and market development. (4) The effects of AI on UGT are mediated by fixed capital stock, industrial structure upgrading, and consumption levels. Additionally, digital infrastructure, green consumption awareness, and digital industry agglomeration serve as moderating factors. AI’s influence also exhibits nonlinear diminishing marginal effects at specific thresholds in productive services and agricultural agglomeration. These results highlight the multifaceted mechanisms through which AI drives sustainable urban development and offer policy implications for fostering green transformation in metropolitan regions.
Transfer-printed yellow and red InGaN micro-LEDs on diamond for ultra-low-power high-speed optical interconnects
Simulation of CRISPR/Cas9-mediated gene editing for the Vitellogenin gene in Apis mellifera
Abstract CRISPR/Cas9 genome editing provides a powerful framework for interrogating gene function in Apis mellifera . Yet, empirical application remains challenging due to biological constraints, including haplodiploid genetics, narrow embryonic injection window, and the social rearing requirements that complicate functional validation. These constraints necessitate in silico pre-screening to maximize editing success before resource-intensive wet-lab implementation. Within the omnigenic framework, which distinguishes core regulatory genes from peripheral loci buffered by network effects, vitellogenin ( Vg ) represents an optimal target which is ancestrally dedicated to yolk provisioning; it has been co-opted to orchestrate diverse non-reproductive functions including longevity, stress resistance, immunity, and social behavior. We developed a computational pipeline to design a list of 57 and 56 candidate guide RNAs (gRNA) for targeted Vg knockout, evaluating candidate sites in both functional exons 2 and 3 based on structural accessibility and frameshift efficiency. Comparative analysis revealed complementary strengths in two top-best candidates from initial target pool of predicted gRNAs. The gRNA targeting exon 2 exhibits weaker secondary structure (ΔG = –0.25 kcal/mol versus –2.10 kcal/mol for exon 3), aligning with empirical evidence that sites with ΔG > –1.0 kcal/mol achieve 2–5 × higher Cas9 binding efficiency. This site yielded moderate frameshift frequency (77.8%; 61.9 percentile). Conversely, the predicted editing outcome for the gRNA targeting exon 3, despite stronger structural constraints, demonstrated superior functional disruption metrics demonstrating very high frameshift frequency (88.3%; 95.2 percentile), high in silico editing precision, minimal microhomology-mediated repair bias, and reproducible outcomes wherein nearly all predicted indels disrupt the coding sequence. Protein structure and domain analyses further predict that frameshift edits will generate a truncated protein missing all downstream functional domains. We recommend parallel empirical validation of both exon 2 and exon 3 targets to resolve the trade-off between structural accessibility (favoring higher editing rates) and frameshift efficacy (favoring complete loss-of-function). This dual-target strategy accommodates uncertainty in in vivo performance while maximizing the probability of generating informative phenotypes. Our in silico framework enables rational CRISPR design in non-model organisms by computationally balancing biophysical accessibility with functional impact, accelerating functional genomics in species where empirical optimization faces substantial biological constraints.
Induced pluripotent stem cell–derived models of malignant nerve sheath tumor progression mimic glial to neuro-mesenchymal transition and uncover therapeutic opportunities
Correction: Factors associated with reduction in quality of life after SARS-CoV-2 infection
Reverse engineering of BNIP3 identifies a mitochondrial protective peptide
Abstract Recent advances in mitochondrial network dynamic and signalling highlight mitochondria as key therapeutic targets across diverse diseases. Yet, high drug development failure rates reflect an incomplete understanding of upstream molecular regulators of mitochondrial fate. Here, we address this gap by reverse engineering of the BH3-only protein BNIP3. Structural modelling and sequence–function analyses of its N-terminus identify a critical functional domain and amino acid hotspots that directly activate BCL-2 executioner proteins, triggering mitochondrial cell death. Leveraging these insights, we develop a BNIP3 antagonist peptide (B-017) that disrupts interactions between BNIP3 and BCL-2 executioner proteins, preserving mitochondrial integrity. B-017 demonstrates target specificity, a favourable safety profile, and robust suppression of cell death signalling in human cells. In clinically relevant animal models, it reduces tissue damage in the heart, brain, and liver. Together, these findings position B-017 as a promising therapeutic candidate targeting mitochondrial dysfunction.