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Cerebral amyloid β-peptide (Aβ) accumulation resulting from an imbalance between Aβ production and clearance is one of the most important causes in the formation of Alzheimer’s disease (AD). In order to preserve the maintenance of Aβ homeostasis and have a notable AD therapy, achieving a method to clear up Aβ plaques becomes an emerging task. Herein, we describe a self-destructive nanosweeper based on multifunctional peptide-polymers that is capable of capturing and clearing Aβ for the effective treatment of AD. The nanosweeper recognize and bind Aβ via co-assembly through hydrogen bonding interactions. The Aβ-loaded nanosweeper enters cells and upregulates autophagy thus promoting the degradation of Aβ. As a result, the nanosweeper decreases the cytotoxicity of Aβ and rescues memory deficits of AD transgenic mice. We believe that this resourceful and synergistic approach has valuable potential as an AD treatment strategy. Cerebral amyloid β-peptide accumulation is a causative factor in Alzheimer’s Disease. Here the authors design a 'nanosweeper' that binds amyloid β-peptide and induces autophagy to clear the accumulated plagues.

Fast radio bursts (FRBs) are millisecond-duration radio transients with extremely high brightness temperatures at cosmological distances, and the physical origin and the radiation mechanism of FRBs are still unknown. The observed spectral bandwidth of some FRBs appeared narrow compared with their peak frequencies, which could be used to constrain the radiation mechanism and the astrophysical environment of FRBs. In this work, we investigate some of the possible physical origins of the narrow spectra from the perspectives of intrinsic radiation mechanisms, coherent processes, radiative transfers, and interference processes. We find that: (1) If the observed narrow spectra of FRBs are attributed to the intrinsic radiation mechanism by a single charged particle, the particle’s deflection angle should be much smaller than the radiation beaming angle. (2) Coherent process can cause narrow spectra. For the bunching mechanism, the narrow spectra might arise from the radiating bunches with a quasiperiodic distribution. For the maser mechanism, the negative absorption process can naturally cause a narrow spectrum. (3) Most absorption and scattering processes seem not to significantly change the observed spectra based on the current observation of some FRB repeaters. (4) Scintillation and plasma lensing in the FRB source environment can modulate the spectra, leading to the narrow spectra and the burst-to-burst variation of spectra. A planet-like object can generate the spectral modulation via gravitational lensing at the gigahertz band, but the observed burst-to-burst variation of the spectra does not support this scenario.

Self-assembling peptides have shown tremendous potential in the fields of material sciences, nanoscience, and medicine. Because of the vast combinatorial space of even short peptides, identification of self-assembling sequences remains a challenge. Herein, we develop an experimental method to rapidly screen a huge array of peptide sequences for self-assembling property, using the one-bead one-compound (OBOC) combinatorial library method. In this approach, peptides on beads are N-terminally capped with nitro-1,2,3-benzoxadiazole, a hydrophobicity-sensitive fluorescence molecule. Beads displaying self-assembling peptides would fluoresce under aqueous environment. Using this approach, we identify eight pentapeptides, all of which are able to self-assemble into nanoparticles or nanofibers. Some of them are able to interact with and are taken up efficiently by HeLa cells. Intracellular distribution varied among these non-toxic peptidic nanoparticles. This simple screening strategy has enabled rapid identification of self-assembling peptides suitable for the development of nanostructures for various biomedical and material applications. Self-assembling peptides have a range of potential applications but developing self-assembling sequences can be challenging. Here, the authors report on a one-bead one-compound combinatorial library where fluorescence is used to detect the potential for self-assembly and identified candidates are evaluated.

This study investigates the impact of HelloTalk, a mobile-assisted language learning (MALL) platform, on the development of intercultural competence (IC) in Chinese English as a Foreign Language (EFL) students. A mixed-methods approach was employed, involving both quantitative surveys and qualitative interviews. Results indicate that the HelloTalk-based intervention significantly improved students’ IC, with the most notable gains observed in their knowledge of other cultures and intercultural communication skills. These findings suggest that mobile-assisted intercultural exchange offers a more effective approach to developing IC compared to traditional classroom learning. Qualitative data further highlight students’ positive perceptions of HelloTalk’s accessibility, flexibility, and the reduced communication anxiety it fosters. However, challenges such as difficulties in making connections and the potential for deception on mobile platforms were also identified. The study underscores the value of incorporating mobile technologies in EFL curricula to facilitate meaningful intercultural exchanges and improve students’ intercultural competence.

We report the observations of FRB 20220912A using the Five-hundred-meter Aperture Spherical radio Telescope. We conducted 17 observations totaling 8.67 hr and detected a total of 1076 bursts with an event rate up to 390 hr−1. The cumulative energy distribution can be well described using a broken power-law function with the lower- and higher-energy slopes of −0.38 ± 0.02 and −2.07 ± 0.07, respectively. We also report the L-band (1–1.5 GHz) spectral index of the synthetic spectrum of FRB 20220912A bursts, which is −2.6 ± 0.21. The average rotation measure value of the bursts from FRB 20220912A is −0.08 ± 5.39 rad m−2, close to 0 rad m−2 and was relatively stable over 2 months. Most bursts have nearly 100% linear polarization. About 45% of the bursts have circular polarization with Signal-to-Noise ratio > 3, and the highest circular polarization degree can reach 70%. Our observations suggest that FRB 20220912A is located in a relatively clean local environment with complex circular polarization characteristics. These various behaviors imply that the mechanism of circular polarization of FRBs likely originates from an intrinsic radiation mechanism, such as coherent curvature radiation or inverse Compton scattering inside the magnetosphere of the FRB engine source (e.g., a magnetar).

Variations in the Faraday rotation measure (RM) of repeating fast radio bursts (FRBs) provide critical diagnostics of the dynamically evolving magnetoionic environments surrounding their progenitors. Sudden, transient “RM flares” can trace the passage of discrete magnetoionic structures, such as stellar coronal mass ejections from the companion or other dense plasma clumps, across the line of sight. However, identifying these rare events is difficult because RM evolution manifests a wide range of complex behaviors, from smooth, long-term trends to chaotic stochasticity, further complicated by highly nonuniform temporal sampling. This complexity makes it a nontrivial challenge to distinguish localized “flares” from intrinsic environmental volatility. We present a generalized algorithmic framework that establishes a robust methodology for the automated detection and characterization of RM flares. By isolating discrete transient perturbations from quiescent backgrounds, this pipeline enables the uniform census of environmental variability across the FRB population. Applying this framework to 15 repeating FRBs, we find that distinct RM flares are rare, with FRB 20220529A being the only source to exhibit an algorithmic detection under standardized parameters. Most other active repeaters instead display high-level intrinsic fluctuations or secular evolution. This work provides a rigorous foundation for distinguishing between different modes of local plasma dynamics, offering a crucial diagnostic tool for identifying the diverse progenitor systems and local environments of FRBs.

Simulation and empirical studies of genomic selection (GS) show accuracies sufficient to generate rapid genetic gains. However, with the increased popularity of GS approaches, numerous models have been proposed and no comparative analysis is available to identify the most promising ones. Using eight wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), Arabidopsis thaliana (L.) Heynh., and maize (Zea mays L.) datasets, the predictive ability of currently available GS models along with several machine learning methods was evaluated by comparing accuracies, the genomic estimated breeding values (GEBVs), and the marker effects for each model. While a similar level of accuracy was observed for many models, the level of overfitting varied widely as did the computation time and the distribution of marker effect estimates. Our comparisons suggested that GS in plant breeding programs could be based on a reduced set of models such as the Bayesian Lasso, weighted Bayesian shrinkage regression (wBSR, a fast version of BayesB), and random forest (RF) (a machine learning method that could capture nonadditive effects). Linear combinations of different models were tested as well as bagging and boosting methods, but they did not improve accuracy. This study also showed large differences in accuracy between subpopulations within a dataset that could not always be explained by differences in phenotypic variance and size. The broad diversity of empirical datasets tested here adds evidence that GS could increase genetic gain per unit of time and cost.

Research probing the clinical utility of immune checkpoint inhibitors (ICIs) supports the development of novel, efficacious approaches to treating colorectal cancer (CRC) patients without chemotherapy. Therapeutic innovations, however, need to be evaluated in light of real-world economic considerations. This study compared the cost-effectiveness of first-line dual-immunotherapies, single immunotherapy, and chemotherapies in the treatment of microsatellite-instability-high/mismatch repair deficient (MSI-H/dMMR) advanced CRC from the perspective of American healthcare systems. Individual patient data (IPD) from the KEYNOTE-177 and CheckMate-8HW trials were collected with IPDfromKM and used to develop a Markov model with a 30-year duration and three mutually exclusive health states, providing a framework for the evaluation of the cost-effectiveness of first-line nivolumab together with ipilimumab, pembrolizumab, and chemotherapy for treating MSI-H/dMMR advanced CRC. Primary outcomes consisted of total costs, life years (LYs), quality-adjusted LYs (QALYs), incremental cost-effectiveness ratio (ICER) values, and incremental net-health benefits (INHB) at willingness-to-pay (WTP) thresholds of $100,000/QALY in the USA. Nivolumab plus ipilimumab ($482,416 [18.72 QALYs]) and pembrolizumab ($336,617 [12.21 QALYs]) increased cost (effectiveness) by $145,800 (5.30 QALYs) than chemotherapy ($374,728 [10.07 QALYs]), respectively. The corresponding ICER was $13,670/QALY and -$14,768/QALY, with INHB of 2.52 and 6.80 QALYs, respectively. It was further found that the ICER and INHB of nivolumab plus ipilimumab versus pembrolizumab were $22,386/QALY and 3.84 QALYs, respectively. In addition, the established model is stable. First-line immunotherapeutic treatments for MSI-H/dMMR advanced CRC cases in the USA appears to be cost-effective, with a dual-immunotherapeutic regimen consisting of nivolumab plus ipilimumab being preferable.

Background Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive type of pancreatic cancer, with a five-year survival rate below 8%. Its high mortality is largely due to late diagnosis, metastatic potential, and resistance to therapy. Epithelial-mesenchymal transition (EMT) plays a key role in metastasis, enabling cancer cells to become mobile. Partial EMT, where cells maintain both epithelial and mesenchymal traits, is more frequent in tumors than complete EMT and contributes to cancer progression. The long non-coding RNA MIR31 host gene ( MIR31HG ) has recently emerged as a critical factor in PDAC oncogenesis. This study aimed to investigate MIR31HG ’s role in partial EMT and its association with the basal-like PDAC subtype. Methods We analyzed the relationship between MIR31HG expression, partial EMT, and the basal-like subtype of PDAC by integrating data from public databases. We reanalyzed public data from PDAC patient-derived organoids to assess MIR31HG expression and gene signatures under hypoxic and normoxic conditions. RNA sequencing and bioinformatics analyses, including gene set enrichment analysis (GSEA), were used to investigate differentially expressed genes and pathway enrichments. EMT, partial EMT, and hypoxia scores were calculated based on the expression levels of specific gene sets. Results We observed that MIR31HG overexpression strongly correlates with higher partial EMT scores and the stabilization of the epithelial phenotype in PDAC. MIR31HG is highly expressed in the basal-like subtype of PDAC, which exhibits partial EMT traits. Hypoxia, a hallmark of basal-like PDAC, was shown to significantly induce MIR31HG expression, thereby promoting the basal-like phenotype and partial EMT. In patient-derived organoids, hypoxic conditions increased MIR31HG expression and enhanced basal-like and partial EMT gene signatures, while normoxia reduced these expressions. These findings suggest that hypoxia-induced MIR31HG expression plays a crucial role in driving the aggressive basal-like subtype of PDAC. Conclusions Our results indicate that MIR31HG is crucial in regulating PDAC progression, particularly in the aggressive basal-like subtype associated with hypoxia and partial EMT. Targeting the MIR31HG -mediated network may offer a novel therapeutic approach to combat hypoxia-driven PDAC.

The applications of hydrogels in biomedical field has been since multiple decades. Discoveries in biology and chemistry render this platform endowed with much engineering potentials and growing continuously. Novel approaches in constructing these materials have led to the production of complex hybrid hydrogels systems that can incorporate both natural and synthetic polymers and other functional moieties for mediated cell response, tunable release kinetic profiles, thus they are used and research for diverse biomedical applications. Recent advancement in this field has established promising techniques for the development of biorelevant materials for construction of hybrid hydrogels with potential applications in the delivery of cancer therapeutics, drug discovery, and re-generative medicines. In this review, recent trends in advanced hybrid hydrogels systems incorporating nano/microstructures, their synthesis, and their potential applications in tissue engineering and anticancer drug delivery has been discussed. Examples of some new approaches including click reactions implementation, 3D printing, and photopatterning for the development of these materials has been briefly discussed. In addition, the application of biomolecules and motifs for desired outcomes, and tailoring of their transport and kinetic behavior for achieving desired outcomes in hybrid nanogels has also been reviewed.