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Systematic background selection with BasCoD enhances contrastive dimension reduction in single cell genomics
The moderating role of gender in the association between latent psychosocial profiles and myopia severity among adolescents
Atomic-scale strain waves for stronger and more ductile lightweight steels
SypC, a symbiont outer membrane vesicle protein, impacts the development of the squid–vibrio partnership
Bacterial outer membrane vesicles (OMVs) and the cargo they carry are increasingly recognized as a means of communication between microbial symbionts and the cells of their host. However, few studies have focused on the biochemical and molecular mechanisms underlying OMV signaling during symbiosis onset and development. We show here that SypC, an OMV protein of the bioluminescent symbiont Vibrio fischeri, is taken up by cells of the squid host Euprymna scolopes where it assumes a new function, i.e., the facilitation of symbiont-induced light-organ morphogenesis. SypC is a Wza-like outer membrane protein found in host-associated Vibrionaceae and is essential for V. fischeri biofilm formation. Colonization or direct treatment with V. fischeri OMVs triggers host development, which was reduced or delayed if the host is instead exposed to a ∆ sypC mutant or ∆ sypC OMVs. RNA-seq analyses comparing light organs colonized by either the mutant or its parent revealed differential expression of host genes associated with immune responses and tissue morphogenesis. In immunocytochemical imaging, SypC-bearing OMVs were taken up by the host’s macrophage-like cells near the light-organ crypts, revealing the mechanism by which SypC travels through tissue to trigger morphogenesis. Taken together, the data provide evidence that in addition to its role in biofilm formation and colonization, SypC has a second function promoting the induction of symbiotic-tissue development. These findings provide a critical piece of a puzzle whereby a rich array of host and symbiont molecules work in concert to orchestrate normal symbiont colonization and host development within the first hours to days of symbiosis.
Correction: Machine learning for prompt estimation of macroseismic intensity from seismometric data in Italy
Exploring electron spin dynamics in spin chains using defects as a quantum probe
Exploring the influence of locality on stakeholder behavioral intentions in industrial heritage tourism from a sense of place perspective
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning
Abstract Predicting crystal properties is essential for understanding structure-property relationships and accelerating material discovery. However, conventional approaches like experimental measurements or density functional theory calculations are resource-intensive, limiting their scalability. While machine learning offers a promising alternative by learning complex structure-property relationships from data, existing models often rely on labeled data, adopt representations insufficiently capturing essential structural characteristics, and lack integration of physics, limiting their generalizability and interpretability. Here, we introduce CLOUD (Crystal Language mOdel for Unified and Differentiable materials modeling), a transformer-based framework trained on a Symmetry-Consistent Ordered Parameter Encoding (SCOPE) that encodes crystal symmetry, Wyckoff positions, and composition in a compact, coordinate-free string representation. Pre-trained on over six million crystals, CLOUD is fine-tuned on downstream tasks and achieves competitive performance across diverse material properties, demonstrating strong scaling with respect to data and model size. Furthermore, as a proof-of-concept of differentiable materials modeling, CLOUD is applied to predict the phonon-related properties by integrating with the Debye model. This approach enforces thermodynamic consistency and enables temperature-dependent property prediction without requiring additional data. These results demonstrate CLOUD’s potential as a scalable and physics-informed foundation model for crystalline materials, unifying symmetry-consistent representations with physics-grounded learning for property prediction and materials discovery.
Conserved use of tetraspanin CD9 as an entry receptor by rhabdoviruses spanning multiple genera
Rhabdoviruses exhibit a broad host range, yet the cellular receptors underlying their cross-species tropism remain poorly defined. Here, we identified tetraspanin CD9 as a conserved functional entry receptor for diverse rhabdoviruses across genera, including viral hemorrhagic septicemia virus (VHSV) ( Novirhabdovirus ), Siniperca chuatsi rhabdovirus (SCRV) ( Siniperhavirus ), and vesicular stomatitis virus (VSV) ( Vesiculovirus ). We demonstrated that the domain IV of VHSV glycoprotein G directly interacted with the large extracellular loop domain of Lateolabrax japonicus CD9 (LjCD9). CD9 knockout, CD9 protein, or CD9 antibody significantly reduced VHSV infection in vitro and CD9 knockout zebrafish, while HEK293T cells, which are nonsusceptible but permissive to VHSV, become susceptible when expressing LjCD9, suggesting that LjCD9 is an entry receptor for VHSV. We further confirmed that LjCD9 functions as a functional receptor of SCRV. Importantly, the human CD9 orthologue can serve as a receptor of VSV. Our findings also revealed that LjCD9 mediated VHSV entry via clathrin- and caveolae-mediated endocytosis. Notably, nitazoxanide (NTZ) was identified as a broad-spectrum inhibitor of VHSV, SCRV, and VSV likely by interfering with the G protein–CD9 interaction. This study establishes CD9 as a cross-species receptor for rhabdoviruses and highlights NTZ as a promising broad-spectrum antiviral agent.
Altitude-resolved prediction of roadside air pollution using UAV measurements and machine learning
Neural circuit models for evidence accumulation through choice-selective sequences
Abstract Decision making is traditionally thought to be mediated by neurons that accumulate evidence through persistent activity. However, recent decision-making experiments in rodents have observed neurons across the brain that fire sequentially, rather than persistently, with the subset of neurons in the sequence depending on the animal’s choice. We developed two candidate circuit models in which neurons are active sequentially and transfer evidence faithfully to the next active population. One model encodes evidence in the relative firing of two competing chains of neurons, and the other in the network location of a stereotyped, bump-like pattern of neural activity. Neural recordings from four brain regions during an evidence accumulation task revealed that different regions displayed evidence tuning consistent with different candidate models. This work provides a mechanistic explanation for how graded information may be precisely accumulated within and transferred between neural populations, and suggests that different brain regions may accumulate evidence through different circuit mechanisms.
Quantum-inspired entanglement between collaborating brains during human memory encoding
The extent to which two brains align during information processing is thought to be central to collaborative memory encoding; however, the neural mechanisms that support such interpersonal alignment remain elusive. Traditional interbrain synchrony models based on phase-alignment metrics fail to distinguish true interbrain connectivity from spurious synchrony driven by shared stimulus processing. Here, we introduce a quantum-inspired framework to capture the connectivity between two collaborating brains. Using dual-brain Electroencephalogram (EEG) hyperscanning, we quantified interbrain coupling during collaborative (Colla)-memory and independent (Indep)-memory encoding in two experiments, including 70 dyads (N = 140) in Experiment 1 and 41 dyads (N = 82) in Experiment 2, which incorporated an empathy-enhancement training procedure. Treating Indep as a baseline state, we found that Colla without training deviated from this baseline by showing a higher probability of aligned states and a lower probability of misaligned states. Following empathy enhancement, Colla state probabilities returned toward the Indep baseline, accompanied by parallel normalization in memory retrieval performance and a shift in the cortical distribution of Colla-Indep differences toward regions implicated in socioemotional processing. Together, the Quantum Aligned-Misaligned Entanglement Model demonstrates that interbrain connectivity dynamics during memory encoding are context sensitive, dynamically evolving with cooperative engagement, and can be reshaped by empathic interaction in ways that systematically relate to subsequent retrieval performance. These findings suggest that quantum-inspired entanglement can be applied to modeling interbrain neural connectivity, offering a framework for understanding collaborative memory encoding.
In silico discovery of thioglycoside analogues as donor-site inhibitors of glycosyltransferase LgtC
Controllable assembly of sub-1 nm nanowires for the construction of aerogels
Abstract Aerogels exhibit excellent properties owing to their nano-sized building blocks and unique structures. With increasing application demands, traditional nanoscale building blocks have limitations in further optimizing the performance of aerogels; therefore, the development of novel, high-performance building blocks has become an urgent challenge in the field. Sub-1 nm nanowires (SNWs) exhibit polymer-like properties that make them superior to nanoscale nanowires, and are well-suited as new building blocks for aerogels. In this study, we achieved precise control over the aggregation state of GdOOH SNWs (Gd–SNWs) in three-dimensional space by regulating the interactions between SNWs as well as between SNWs and solvents, thereby obtaining SNW aerogels (SNWAs) with low density ( ~ 0.024 g cm −3 ) and high specific surface area (505 m 2 g −1 ). After silanization, the superhydrophobic SNWAs exhibited excellent fatigue resistance (50 cycles with a set strain of 50%). This innovative approach enriches the types of aerogels building blocks and opens up new avenues for high-performance aerogels.
Smooth-to-rough morphotype switching, a mechanism of phage resistance in <i> <i>Mycobacterium</i> abscessus </i>
Mycobacterium abscessus infections represent a growing global health concern due to their severe pathology and difficulty of treatment, largely driven by their intrinsic antimicrobial resistance. While phage therapy has emerged as a promising alternative approach, studies have predominantly focused on glycopeptidolipids (GPL)-deficient M. abscessus rough variants instead of the GPL-producing smooth variants predominant in Asia. Here, we aim to develop phage cocktails targeting both smooth and rough morphotypes. In the process, we found that phage treatment of smooth variants can select for rough morphotype switching from smooth-to-rough variants in vitro and in vivo, resulting in phage resistance associated with mutations within the GPL biosynthetic locus. We validated our findings in vitro and in vivo, suggesting a two-layered phage combination that surpasses single-phage treatments and potentially improves clinical phage cocktail strategies. This work underlines the need to better understand mechanisms of phage resistance in phage therapy and associated potential adverse effects and solutions. Phage resistance in M. abscessus through morphotype switching is clinically significant, as it may complicate treatment outcomes but could be averted with proper phage combinations.
All-digital aliasing-free PWM transmitter with reduced filtering requirements
Abstract The paper presents an All-Digital Aliasing-Free PWM (AF-PWM) transmitter, which combines multiphase band-limited PWM (MP-BLPWM) and accumulated N phase-shift pulse modulation (AN-PSPM), and its FPGA-implementation. As the architecture is based on MP-BLPWM, which generates finite harmonics PWM, this eliminates image and aliasing distortion, and improves spectral performance. However, finite harmonics PWM leads to large amplitude variation, which is converted to two voltage level signals using AN-PSPM, leading toward all-digital implementation. The transmitter’s performance is experimentally validated for 5G-NR and LTE signals, both with and without a switched-mode power amplifier (Class-D PA). Measurement results demonstrate that, when used with the PA, the transmitter achieves ACLR values of 37.9 dBc for 5G-NR and 42.2 dBc for LTE signals. Furthermore, the EVM of the proposed transmitter with the Class-D PA is measured at 1.3% for 5G-NR and 0.9% for LTE, highlighting its effectiveness for advanced wireless communication applications.
Calcium-mediated calreticulin-IRE1α interaction drives dynamic fluctuation of IRE1α activity under chronic endoplasmic reticulum stress
Personalized functional topography–based multisite brain age prediction modeling reveals divergent neurodevelopment in major depression
Major depressive disorder (MDD) is associated with widespread alterations in functional brain networks across the lifespan. However, heterogeneity in atypical brain development among patients with MDD remains largely uncharacterized. Using a multisite resting-state functional MRI dataset consisting of 1,105 MDD patients and 1,065 healthy controls, we constructed a harmonized multicenter brain age prediction model based on individualized functional topography and identified two patient subgroups with positive or negative brain age gaps (BAGs). In patients with a positive BAG (BAG+), expansion of the salience network (SAL) into the dorsolateral prefrontal and ventrolateral prefrontal cortices, in addition to contraction of the sensorimotor and dorsal attention networks (DAN), contributes to accelerated brain aging. Conversely, in the negative BAG (BAG−) group, SAL expansion into the orbitofrontal cortex (OFC) and contraction of the visual and sensorimotor networks (SMN) were linked to delayed brain development. These subgroups also exhibited distinct neurodevelopmental trajectories. Clinically, BAG+ patients showed stronger associations between higher-order network topography and mood symptoms, whereas BAG− patients exhibited links between visual/default mode network topography and insomnia. At the molecular level, both groups showed enrichment of genes related to synaptic signaling but displayed distinct expression patterns and divergent expression trajectories in key neurodevelopmental gene sets. Notably, antidepressant treatment modulated the brain in ways that were specific to each subgroup. These findings reveal heterogeneous neurodevelopmental profiles in MDD with distinct biological and clinical signatures, offering insights into personalized precision medicine for this disorder.
Design of electric and remote operating vehicles battery carrier by using small aluminum closed-cell foam blocks shielded by aluminum tubes
Abstract Aluminum closed-cell foam blocks (ACCFBs) are small blocks of foam shielded with small aluminum (Al) tubes developed to enhance the energy absorption of Al foam in limited volumes, such as one cubic inch. It is designed to overcome the problems of the high cost of production, maintenance, and heat insulation properties of foam sheets. Al blocks ideas quoted from human and animal bone parts, and it is designed to absorb energy laterally. This work presents the designs of remote operating vehicles (ROVs) and electric vehicles (EVs) battery carriers, constructed from a cube block of ACCFBs and two Al sheets. The carrier design is based on the properties of Al foam blocks. It is designed to withstand temperatures up to 120 °C. The carrier idea relies on replacing large sheets of Al foam with small, distributed blocks. It has good energy absorption, and at the same time, it helps solve the problems of harness design for crossing wires in narrow areas, such as in ROVs. The results show that the ROVs battery carrier made from the Al sandwich panel (AFS) needs 900 s to transfer 120 °C from the upper sheet to the lower sheet, while the carrier made from ACCFBs with the same volume needs 40 s only. It can also bear a load of up to 0.8 kN and has a working strength δ working : 1.093 MPa. The EVs battery carrier can bear a load of 117 kN (about 25 times the battery weight) at yield strength (0.45 MPa), and it has a δ working : 0.516 MPa. The calculated total time of cooling for the conduction and forced convection for both the ROVs and EVs carriers at a cooling temperature of 25 °C and at air velocity 1 m/s were 4:31 min and 32:25 min, and at 2 m/s were 3:15 min and 20:41 min, respectively, at a summer working temperature of 40 °C.