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Genetic and pharmacological inactivation of peptidoglycan remodeling increases antibiotic susceptibility of vancomycin-resistant Enterococcus faecium
Longitudinal changes and cumulative exposure of estimated glucose disposal rate and all-cause mortality in middle-aged and older Chinese adults
SRP orchestrates protein biogenesis beyond initial ER membrane targeting
Abstract The Signal Recognition Particle (SRP) targets nascent proteins to the Sec61 translocon for import into the endoplasmic reticulum (ER). However, its range of substrates, point of engagement during targeting, and hence full biological impact remain unclear. Here, we examined SRP interactions with the nascent proteome of S. cerevisiae during translation and membrane targeting. SRP binds effectively to transmembrane domains (TMDs) as they emerge from the ribosomal tunnel, but only to a minority of cleavable signal peptides. We identify nascent chain features that promote SRP binding, allowing to develop a predictive algorithm. We show SRP performs a role in triaging nascent ER proteins into distinct targeting routes and downstream maturation processes. Furthermore, ribosomes frequently dissociate from the membrane before completing translocation, allowing the chaperone Ssb to assist folding of emerging cytosolic domains. Ribosomes translating multipass membrane proteins are retargeted to the translocon through repeated SRP interactions with internal TMDs, emphasizing collaboration between SRP and chaperones in membrane protein biogenesis.
AgriTrack framework for AI-based tracking of pest migration through farmers’ helpline data
Whole blood epigenomic and transcriptomic characterization identifies vulnerable molecular subtypes of chronic coronary disease
BCAFL: a secure and efficient blockchain framework for asynchronous federated learning
Abstract Traditional synchronous Federated Learning (FL) is subject to the waiting latency inherent to synchronization mechanisms. Consequently, its convergence rate is constrained by straggler nodes within heterogeneous environments. Asynchronous Federated Learning (AFL) improves execution efficiency by removing global synchronization barriers. However, when integrated with blockchain for decentralized deployment, it still encounters challenges such as on-chain storage overhead arising from model parameters, convergence perturbations induced by stale gradients, and Byzantine security threats. To this end, this paper proposes BCAFL, a decentralized blockchain framework tailored for semi-asynchronous federated learning. BCAFL utilizes the InterPlanetary File System (IPFS) to implement off-chain storage for global model parameters. By integrating Model-Agnostic Meta-Learning (MAML) and PowerSGD, the framework enhances the model’s local adaptation capability on non-IID data while concurrently reducing communication overhead. To safeguard model security and convergence stability in asynchronous environments, this study develops a Mutual Information and Delay-Aware (MIDA) dynamic aggregation mechanism. This mechanism leverages Mutual Information (MI) to perform model verification for defense against poisoning attacks, while simultaneously modulating aggregation weights via a dynamic aggregation factor to effectively mitigate model oscillations inherent in asynchronous convergence. Additionally, this study develops a dynamic stake-based Verifiable Random Function (VRF) committee consensus mechanism. By quantifying election weights based on node contributions, this approach enhances consensus efficiency and resistance to Sybil attacks. Simulation results demonstrate that, compared with various existing baseline schemes, BCAFL maintains the convergence accuracy of the global model while reducing communication overhead. It effectively suppresses convergence oscillations caused by asynchronous delays and defends against poisoning and Byzantine attacks. Furthermore, when the network scale is expanded to 300 nodes, the consensus latency does not show a significant increase.
Catchment lithology controls net carbon balance along the Antarctic Peninsula
Predictive networks generate motion-induced color illusions
Post-release tuberculosis risk among formerly incarcerated populations in Lima Peru
Correction: Anticarcinogenic effects of miR-199a-loaded gold nanoparticles on hepatocellular carcinoma: in vitro study
Electron pressure drives THz phonons in metal–metal superlattices
Abstract Ultrafast control of lattice motion in metals is a central challenge for high-frequency strain engineering and spintronic applications. Coherent strain control at terahertz (THz) frequencies in metals has remained elusive because free electrons are expected to delocalize energy beyond the optical penetration depth, preventing rapid and efficient stress generation. Here we show that robust and cost-effective metal–metal superlattices (SLs), where periodic repetitions of bilayers — each layer a few atoms thick — are deposited by sputtering, constitute thermoacoustic metamaterials that overcome this limitation. We combine femtosecond X-ray diffraction with mode-resolved density-functional theory and two-temperature modeling to show that electron pressure, rather than phonon stress, drives a large-amplitude coherent terahertz (1 THz) lattice oscillation in sputtered Pt/Cu superlattices. We establish electron pressure as an engineerable, dominant actuation mechanism in metallic metamaterials which can be tailored by the pitch and the constituent materials of the sputtered SL structure, enabling applications such as ultrafast strain-mediated antiferromagnetic spintronic devices.
Integrated computational and experimental benchmarking of Bacillus phage endolysins reveals the relationship between peptidoglycan-fragment recognition descriptors and antibacterial performance
The bacteroidal metabolite O-LysoPE facilitates hepatocyte-mediated immunosuppression in autoimmune hepatitis
In-situ SEM evaluation of single-nanowire response in CuO–Cu₂O–ZnO nanowire arrays for infrared energy harvesting
Meiotic pairing through barcode-like satellite DNA repeats
Abstract During meiosis, chromosomes must find, pair, and synapse with their homologous partners in the crowded milieu of the nucleus. Although homology detection generally relies on recombination, pairing can occur in its absence, suggesting alternative mechanisms. Here, we show that the barcode-like arrangement of non-coding satellite DNA repeats facilitates homologue pairing during meiosis. Using satellite DNA deletion, duplication, and translocation strains, we demonstrate that repeat mismatches perturb meiotic pairing, particularly at centromeres and pericentromeres. Notably, pairing defects are also observed in the progeny of D. melanogaster natural populations that have diverged in their satellite DNA content. In the absence of satellite DNA homology, pairing is antagonised by the HORMAD protein, Mad2, while a Pachytene checkpoint 2 (Pch2)-dependent meiotic delay restores pairing. In addition, compromised meiotic pairing is strongly correlated with mid-oogenesis cell death, a quality control mechanism that likely culls defective oocytes to prevent chromosome mis-segregation and aneuploidy. Taken together, our findings reveal an important role for satellite DNA repeats during meiotic homology detection. We propose that this repeat-based pairing mechanism exerts an underappreciated selective pressure, constraining the divergence of rapidly evolving satellite DNA within interbreeding natural populations.
Association between obesity and outcomes of first-line CDK4/6 inhibitor therapy in metastatic breast cancer: a multicenter real-world study
High responsivity IR sensing based on reflectometric RF MEMS
Abstract Radiofrequency microelectromechanical systems (RF MEMS) integrated with metasurfaces are promising platforms for spectrally selective infrared (IR) sensing. Conventional devices detect IR radiation by tracking resonance frequency shifts. Here, we introduce a reflectometric approach that instead monitors changes in the RF MEMS input impedance and analytically links them to sensing metrics. By coupling a reconfigurable matching network to an RF MEMS resonator, the detector achieves IR responsivities governed by its phase-slope quality factor and tunable to exceptionally high values. Using contour-mode resonators at ambient conditions, we demonstrate responsivities exceeding 11,400 V/W in a 50-Ω readout (>200 A/W), spectral selectivity with a full-width at half-maximum (FWHM) of 0.54 μm at 5.94 μm, noise-equivalent power (NEP) of $$\sim 450\ {{{\rm{pW}}}}/\sqrt{{{{\rm{Hz}}}}}$$ ~ 450 pW / Hz , a ~ 552-μs time constant, and resolve IR power levels down to ~ 740 pW. Reflectometric RF MEMS detectors provide a reconfigurable, spectrally selective, and scalable platform for high-performance on-chip IR spectroscopy and sensing.