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A novel hybrid attention based deep learning framework for textual emotion recognition using natural language processing technologies for disabled persons

Driving forces of RNA condensation revealed through coarse-grained modeling with explicit Mg ²⁺

RNAs are major drivers of phase separation in the formation of biomolecular condensates and can undergo protein-free phase separation in the presence of divalent ions or crowding agents. Much remains to be understood regarding how the complex interplay of base stacking, base pairing, electrostatics, ion interactions, and particularly structural propensities governs RNA phase behavior. Here, we develop an intermediate resolution model for condensates of RNAs (iConRNA) that can capture key local and long-range structural features of dynamic RNAs and simulate their spontaneous phase transitions with Mg 2+ . Representing each nucleotide using 6 to 7 beads, iConRNA accurately captures base stacking and pairing and includes explicit Mg 2+ . The model not only reproduces major conformational properties of poly(rA) and poly(rU) but also correctly folds small structured RNAs and predicts their melting temperatures. With an effective model of explicit Mg 2+ , iConRNA successfully recapitulates experimentally observed lower critical solution temperature phase separation of poly(rA) and triplet repeats, and critically, the nontrivial dependence of phase transitions on RNA sequence, length, concentration, and Mg 2+ level. Further mechanistic analysis reveals a key role of RNA folding in modulating phase separation as well as its temperature and ion dependence, besides other driving forces such as Mg 2+ –phosphate interactions, base stacking, and base pairing. These studies also support iConRNA as a powerful tool for direct simulation of RNA-driven phase transitions, enabling molecular studies of how RNA conformational dynamics and its response to complex condensate environments control the phase behavior and condensate material properties.

Genome-wide identification, phylogenetic analysis and expression pattern study of trihelix transcription factors in Pisum sativum L.

On the scale of heterogeneity in composite electrodes of batteries

An electrode in cylindrical or pouch cell batteries contains millions of active particles embedded in a conductive network. Battery performance, such as voltage, capacity, and cyclic efficiency, is a collective response of the particle network. We use optical microscopy to measure the local, heterogeneous state of charge of individual particles upon charging and discharging. The optical reflectivity is proportional to Li composition in the ternary oxide LiNi x Mn y Co z O 2 (NMC) cathode. Through clustering analysis, we determine the scale of heterogeneity where a representative volume in the composite electrode contains 100 to 1,000 particles. The heterogeneous activity in the particle network can be described by Weibull defect population at the particle interface with the conductive matrix.

Advancing sustainable aviation by integrating renewable solar energy into unconventional airport spaces using a spherical fuzzy CRITIC–RATGOS approach

Morphological specializations of mosquito CO ₂ -sensing olfactory receptor neurons

Hematophagous mosquitoes use CO 2 as a key arousal signal that gates behavioral responses to host-derived cues. In Aedes aegypti , CO 2 is detected by olfactory receptor neurons (ORNs) housed in the sensory hairs (sensilla) on the maxillary palp. While the molecular mechanism and behavioral significance of CO 2 sensing have been well studied in mosquitoes, the nanoscale three-dimensional structures of their CO 2 -sensing ORNs and associated cells have remained unclear. Using serial block-face scanning electron microscopy, we characterize the CO 2 -sensing cpA neuron and its odor-sensitive neighbors, cpB and cpC, within the capitate sensilla of A. aegypti. Notably, cpA neurons are significantly larger, with an outer dendritic surface area 8 to 12 times greater than that of cpB and cpC neurons. This expanded CO 2 -sensing surface arises from its unique architecture, consisting of numerous flattened dendritic sheets folded into intricate lamellae. In contrast, cpB and cpC dendrites exhibit sparse, narrow cylindrical branches. Moreover, the cpA axon displays a prominent pearls-on-a-string morphology, with numerous mitochondria-rich, nonsynaptic varicosities connected by thin cables. Remarkably, a glial cell and an auxiliary cell together ensheathe the cpA soma but not cpB or cpC, suggesting a specialized role in supporting cpA function. Compared to Drosophila CO 2 -sensitive ORNs, a larger portion of the cpA outer dendrite is embedded within the sensillum cuticle, potentially improving access to environmental CO 2 . These findings reveal key morphological specializations of cpA neurons, thereby advancing our understanding of mosquito sensory biology and laying the groundwork for future studies on the molecular basis and functional ramifications of these anatomical adaptations.

A 2D omnidirectional inertial switch with multiple thresholds

Rewarding touch limits lifespan through neural to intestinal signaling

In multicellular organisms, sensory perception affects many aspects of behavior and physiology. Perception of environmental stressors like food scarcity often leads to physiological changes that promote survival and slow aging. However, recent work shows that perception of attractive food smells can block the health benefits of dietary restriction in multiple model organisms. While it is known that sensory perception and cell nonautonomous signaling can modulate health and longevity, our knowledge of the specific sensory cues and mechanistic pathways that define this signaling is still limited. Here we find that the sense of touch interacts with nutritional state to modulate lifespan in Caenorhabditis elegans . Worms subjected to dietary restriction are shorter-lived when they perceive tactile stimuli that mimic bacterial food and/or protective soil. Touch modulation of dietary restriction requires putative mechanoreceptor proteins, the neurotransmitters dopamine and tyramine/adrenaline, and the neuropeptides INS-11 and GnRH. Ultimately, the touch circuit regulates the longevity effectors DAF-2/IGF1R and FMO-2/FMO5. These results establish a physiological touch circuit and connect neural reward pathways to the growth and reproductive axes. Finding that texture mechanosensation can modulate longevity suggests a role for touch in lifespan.

Prognostic model for early-onset colorectal cancer with liver metastasis after primary tumor resection and chemotherapy

A universal thermal performance curve arises in biology and ecology

Temperature has strong impacts on all biological and ecological processes, and thermal performance curves (TPCs) have been employed recurrently to assess them. TPCs almost always take a particular asymmetric shape across the biological hierarchy, with many different competing mechanisms and models doing a similarly good job of trying to explain the TPC phenomenon. Here, we reveal that the ubiquitous exponential scaling of biological processes with temperature creates a mechanistic tendency for TPC data and models to collapse onto a single curve (which we call the Universal TPC, UTPC), explaining mathematically why biological systems respond to temperature in such a consistent way. We illustrate that many seemingly different TPCs actually approximate rescaled versions of the same curve, even when thermal performance estimates vary widely across organisms, systems, and contexts. We demonstrate remarkable UTPC collapse across the tree of life, with diverse datasets spanning microbes to vertebrates, and individual physiology to population growth. UTPC phenomena also provide a strong theoretical basis for predicting performance of warm-adapted organisms will be more sensitive to- and less tolerant of- temperature fluctuations; an important consideration in the context of climate change.

Addressing the serotonin hypothesis of depression through analyses of genetics, methylation and metabolite variations in glioma patients

Abstract Serotonin and serotonin metabolism has for decades been understood as playing a critical role in mood disorders and has more recently also been implicated in brain tumour biology. However, in part due to the lack of direct investigation of genetic and epigenetic variation affecting serotonin pathways within human brain tissue this understanding has recently been challenged. We analysed genetic and epigenetic variation in the Monoamine oxidase A ( MAOA) and serotonin transporter ( 5HTT) genes using 232 biobanked glioma tissue samples from 216 adult patients. We further examined the association between use of antidepressants (targeting serotonergic pathways), serotonin levels and methylation. In male patients, genetic variation in the MAOA gene was significantly associated with tissue serotonin levels. Further analysis identified five single nucleotide variants (SNVs) that may contribute to this association. In contrast, 5HTT variants were not statistically associated with serotonin pathway metabolites, nor were MAOA variants in females. Increased methylation at several 5HTT CpG sites was positively correlated with serotonin levels and negatively correlated with 5-HIAA levels. In males, one CpG site in the MAOA gene was negatively associated with the 5-HIAA/serotonin ratio, suggesting reduced enzymatic degradation of serotonin due to lower MAOA activity. Patients using antidepressants had lower tissue serotonin levels. In males, genetic variation in the MAOA gene was significantly associated with tissue serotonin levels, although this association was not mediated by methylation. Our result supports the notion that the MAOA and 5HTT genes are related to serotonin metabolism and that such metabolism is related to antidepressant use.

Outrunning protein diffusion to the air–water interface in cryoEM

Here, we report a series of measurements indicating that it is physically possible to thin and vitrify a specimen for electron cryomicroscopy (cryoEM) faster than proteins diffuse to the air–water interface. We achieved this by spraying picoliter volume droplets at speeds of hundreds of meters per second into a thin layer of liquid ethane coating the surface of a precooled specimen support. The droplets simultaneously collapsed and froze in microseconds into the amorphous phase as they landed on the surface. The atomic structure of the proteins was preserved and tomographic reconstructions of the vitrified specimens indicated adhesion to the interfaces was eliminated. Improved control of the final thickness of the specimen and the orientation distribution of the particles are now the limiting factors. This demonstration provides a basis for the development of specimen preparation methods and instruments that eliminate the detrimental effects of the air–water interface in cryoEM.

Adsorption of sodium lauryl sulfate onto calcium-phosphate hydroxyl@clay hybrid adsorbents

Intracellular pH regulates ubiquitin-mediated degradation of the MAP kinase ERK3

Intracellular pH (pHi) influences diverse cellular processes, including cell proliferation, metabolism, and migration, and is linked to metabolic diseases and cancer. Protonation alters protein charge and conformation, modulating different aspects of protein function. How pHi fluctuations are sensed by signaling proteins and translated into cellular responses remains incompletely understood. Here, we reveal that pHi plays a key role in regulating the stability of the mitogen-activated protein kinase Extracellular signal-regulated kinase 3 (ERK3). Intracellular acidification markedly increases the half-life of ERK3, whereas alkalinization accelerates its degradation. The pH-dependent regulation of ERK3 is rapid, reversible, and consistent across cell types. Mechanistically, we identified a region in the C-terminus of ERK3 that contains pH-sensing motifs. We further show by quantitative proteomics that short-term acidification or alkalinization globally affects the cellular proteome. Our findings underscore the critical role of pHi in ERK3 turnover and suggest a broader role for pH in regulating protein stability and cell signaling.

Cold stress resilience in rice: genotypic variation, yield traits, and GGE biplot insights

Correction for Yu et al., Tetraphenylethene-based highly emissive metallacage as a component of theranostic supramolecular nanoparticles

A dual-channel hyperspectral classification method based on NAS and transformer

Theta-nested gamma oscillations balance prediction and vigilance in spatial navigation

Recent experimental findings challenge the traditional belief that vigilance is solely attributed to the sensorimotor system, suggesting instead that hippocampal activity, coupled with locomotor processes, enhances environmental sampling and planning. Here, we propose that hippocampal theta-nested gamma oscillations (TGOs), widely observed in experiments, play essential roles in both prediction and vigilance, in terms of recalling reward sites and avoiding unexpected dangers through synfire chains (SFCs). Despite the recognized importance of TGOs in navigation, their precise functional roles remain unclear. By building a biologically plausible spiking neuronal network model and reproducing experimental results, we leverage SFC properties-length and separation-to reveal that the positive correlation between theta frequency and motion velocity optimally balances planning for predictable events and staying alert to unexpected ones. Based on this adaptive mechanism, we further explain the distinct functional contributions of TGOs consistent with experimental findings: Theta oscillations facilitate self-location awareness, gamma oscillations enhance predictive capabilities, and their coupling ensures sufficient time windows for prediction. Our study provides insights into the functional roles of TGOs in the hippocampus, highlighting their importance in achieving both planning and vigilance during goal-directed navigation.

Experimental investigation on deformation behavior and failure modes of limestone under coupled effects of water content and end friction

Hierarchical self-assembly for high-yield addressable complexity at fixed conditions

There is evidence that the self-assembly of complex molecular systems often proceeds hierarchically, by first building subunits that later assemble in larger entities, in a process that can repeat multiple times. Yet, our understanding of this phenomenon and its performance is limited. Here, we introduce a simple model for hierarchical addressable self-assembly, where interactions between particles can be optimized to maximize the fraction of a well-formed target structure, or yield. We find that a hierarchical strategy leads to an impressive yield up to at least five generations of the hierarchy and does not require a cycle of temperatures as used in previous methods. High yield is obtained when the microscopic interaction decreases with the scale of units considered, such that the total interaction between intermediate structures remains identical at all scales. We provide thermodynamic and dynamical arguments constraining the interaction strengths where this strategy is effective. Overall, our work characterizes an alternative strategy for addressable self-assembly at a fixed temperature, and provides insight into the mechanisms sustaining hierarchical assembly in biological systems.