In situ click chemistry generation of cyclooxygenase-2 inhibitors

Structure-based protein and small molecule generation using EGNN and diffusion models: A comprehensive review

Recent breakthroughs in deep learning have revolutionized protein sequence and structure prediction. These advancements are built on decades of protein design efforts, and are overcoming traditional time and cost limitations. Diffusion models, at the forefront of these innovations, significantly enhance design efficiency by automating knowledge acquisition. In the field of de novo protein design, the goal is to create entirely novel proteins with predetermined structures. Given the arbitrary positions of proteins in 3-D space, graph representations and their properties are widely used in protein generation studies. A critical requirement in protein modelling is maintaining spatial relationships under transformations (rotations, translations, and reflections). This property, known as equivariance, ensures that predicted protein characteristics adapt seamlessly to changes in orientation or position. Equivariant graph neural networks offer a solution to this challenge. By incorporating equivariant graph neural networks to learn the score of the probability density function in diffusion models, one can generate proteins with robust 3-D structural representations. This review examines the latest deep learning advancements, specifically focusing on frameworks that combine diffusion models with equivariant graph neural networks for protein generation.

Synergistic powering of DNA walker movement by endogenous dual enzymes for constructing dual-mode biosensors

To achieve highly sensitive and reliable detection of apurinic/apyrimidinic endonuclease 1 (APE1), a critical cancer diagnostic biomarker, we designed a DNA walker-based dual-mode biosensor, utilizing cellular endogenous dual enzymes (APE 1 and Flap endonuclease 1 (FEN 1)) to collaborate in activating and propelling DNA walker motion on DNA-functionalized Au nanoparticles. Incorporating both fluorescence and electrochemical detection modes, this system leverages signal amplification from DNA walker movement and cascade amplification through tandem hybridization chain reactions (HCR), achieving highly sensitive detection of APE 1. In the fluorescence mode, continuous DNA walker movement, initiated by APE1 and driven by FEN1, generates a robust signal response within a concentration range of 0.01-500 U mL-1, presenting a good linearity in the concentration range of 0.01-10 U mL-1, with a detection limit of 0.01 U mL-1. In the electrochemical detection module, the cascade upstream DNA walker and downstream HCR dual signal amplification strategy further enhances the sensitivity of APE1 detection, extending the linear range to 0.01-50 U mL-1 and reducing the detection limit to 0.002 U mL-1. Rigorous validation demonstrates the biosensor's specificity and anti-interference capability against multiple enzymes. Moreover, it effectively distinguishes cancer cells from normal cell lysates, exhibiting excellent stability and consistency in the dual-modes. Overall, our findings underscore the efficacy of the developed dual-mode biosensor for detecting APE1 in serum and cell lysates samples, indicating its potential for clinical applications in disease diagnosis.

Design-build-test of recombinant Bacillus subtilis chassis cell by lifespan engineering for robust bioprocesses

Microbial cell factories utilize renewable raw materials for industrial chemical production, providing a promising path for sustainable development. Bacillus subtilis is widely used in industry for its food safety properties, but challenges remain in the limitations of microbial fermentation. This study proposes a novel strategy based on lifespan engineering to design robust B. subtilis chassis cells to supplement traditional metabolic modification strategies that can alleviate cell autolysis, tolerate toxic substrates, and get a higher mass transfer efficiency. The modified chassis cells could produce high levels of l-glutaminase, and tolerate hydroquinone to produce α-arbutin efficiently. In a 5 L bioreactor, the l-glutaminase enzyme activity of the final strain CRE15TG was increased to 2817.4 ± 21.7 U mL-1, about 1.98-fold compared with that of the wild type. The α-arbutin yield of strain CRE15A was increased to 134.7 g L-1, about 1.34-fold compared with that of the WT. To our knowledge, both of the products in this study performed the highest yields reported so far. The chassis modification strategy described in this study can Improve the utilization efficiency of chassis cells, mitigate the possible adverse effects caused by excessive metabolic modification of engineered strains, and provide a new idea for the future design of microbial cell factories.

Exploring the impact of circRNAs on cancer glycolysis: Insights into tumor progression and therapeutic strategies

Cancer cells exhibit altered metabolic pathways, prominently featuring enhanced glycolytic activity to sustain their rapid growth and proliferation. Dysregulation of glycolysis is a well-established hallmark of cancer and contributes to tumor progression and resistance to therapy. Increased glycolysis supplies the energy necessary for increased proliferation and creates an acidic milieu, which in turn encourages tumor cells' infiltration, metastasis, and chemoresistance. Circular RNAs (circRNAs) have emerged as pivotal players in diverse biological processes, including cancer development and metabolic reprogramming. The interplay between circRNAs and glycolysis is explored, illuminating how circRNAs regulate key glycolysis-associated genes and enzymes, thereby influencing tumor metabolic profiles. In this overview, we highlight the mechanisms by which circRNAs regulate glycolytic enzymes and modulate glycolysis. In addition, we discuss the clinical implications of dysregulated circRNAs in cancer glycolysis, including their potential use as diagnostic and prognostic biomarkers. All in all, in this overview, we provide the most recent findings on how circRNAs operate at the molecular level to control glycolysis in various types of cancer, including hepatocellular carcinoma (HCC), prostate cancer (PCa), colorectal cancer (CRC), cervical cancer (CC), glioma, non-small cell lung cancer (NSCLC), breast cancer, and gastric cancer (GC). In conclusion, this review provides a comprehensive overview of the significance of circRNAs in cancer glycolysis, shedding light on their intricate roles in tumor development and presenting innovative therapeutic avenues.

New Lead-free Hybrid Layered Double Perovskite Halides: Synthesis, Structural Transition and Ultralow Thermal Conductivity

Hybrid layered double perovskites (HLDPs), representing the two-dimensional manifestation of halide double perovskites, have elicited considerable interest owing to their intricate chemical bonding hierarchy and structural diversity. This intensified interest stems from the diverse options available for selecting alternating octahedral coordinated trivalent [M(III)] and monovalent metal centers [M(I)], along with the distinctive nature of the cationic organic amine located between the layers. Here, we have synthesized three new compounds with general formula (R'/R'')4/2M(III)M(I)Cl8; where R'=C3H7NH3 (i.e. 3N) and R''=NH3C4H8NH3 (i.e. 4N4); M(III)=In3+ or Ru3+; M(I)=Cu+ by simple solution-based acid precipitation method. The structural analysis reveals that (4N4)2CuInCl8 and (4N4)2CuRuCl8 adopt the layered Dion Jacobson (DJ) structure, whereas (3N)4CuInCl8 exhibits layered Ruddlesden Popper (RP) structure. The alternative octahedra within the inorganic layer display distortions and tilting. Three compounds show temperature-dependent structural phase transitions where changes in the staking of inorganic layer, extent of octahedral tilting and reorientation of organic spacers with temperature have been noticed. We have achieved ultralow lattice thermal conductivity (κL) in the HLDPs in the 2 to 300 K range, marking a distinctive feature within the realm of HLDP systems. The RP-HLDP compound, (3N)4CuInCl8, demonstrates anisotropy in κL while measured parallel and perpendicular to layer stacking, showcasing ultralow κL of 0.15 Wm-1K-1 at room temperature, which is one of the lowest values obtained among Pb-free metal halide perovskite. The observed ultralow κL in three new HLDPs is attributed to significant lattice anharmonicity arising from the chemical bonding heterogeneity and soft crystal structure, which resulted in low-energy localized optical phonon modes that suppress heat-carrying acoustic phonons.

Genome-wide analysis of MADS-box genes and their expression patterns in unisexual flower development in dioecious spinach

Evolution of unisexual flowers involves extreme changes in floral development. Spinach is one of the species to discern the formation and evolution of dioecy. MADS-box gene family is involved in regulation of floral organ identity and development and in many other plant developmental processes. However, there is no systematic analysis of MADS-box family genes in spinach. A comprehensive genome-wide analysis and transcriptome profiling of MADS-box genes were undertaken to understand their involvement in unisexual flower development at different stages in spinach. In total, 54 MADS-box genes found to be unevenly located across 6 chromosomes and can be divided into type I and type II genes. Twenty type I MADS-box genes are subdivided into Mα, Mβ and Mγ subgroups. While thirty-four type II SoMADSs consist of 3 MIKC*, and 31 MIKCC -type genes including sixteen floral homeotic MADS-box genes that are orthologous to the proposed Arabidopsis ABCDE model of floral organ identity determination, were identified in spinach. Gene structure, motif distribution, physiochemical properties, gene duplication and collinearity analyses for these genes are performed in detail. Promoters of both types of SoMADS genes contain mainly MeJA and ABA response elements. Expression profiling indicated that MIKCc genes exhibited more dynamic and intricate expression patterns compared to M-type genes and the majority of type-II genes AP1, SVP, and SOC1 sub-groups showed female flower-biased expression profiles, suggesting their role in carpel development, while PI showed male-biased expression throughout flower developmental stages, suggesting their role in stamen development. These results provide genomic resources and insights into spinach dioecious flower development and expedite spinach improvement.

Variability in interseismic strain accumulation rate and style along the Altyn Tagh Fault

Major strike-slip faults that develop between strong and weaker regions are thought to focus along narrow shear zones at the rheological boundary. Here we present the InSAR-derived velocity field spanning almost the entire length of one such fault, the 1600 km-long Altyn Tagh Fault (ATF), and analyse the strain distribution. We find that localisation of strain is actually variable, in contrast to other major strike-slip faults that show little variation, with strain concentrated at the fault for some sections and distributed over broad (>100 km) shear zones for others. Slip rate along the ATF is also variable, decreasing along the fault from 11.6 ± 1.6 mm/yr in the west to 7.2 ± 1.4 mm/yr in the central portion, before increasing again to 11.7  ± 0.9 mm/yr over the eastern portion. We show that the variable shear zone width may be linked to geological variability and the influence of heat flow, and the results imply that sub-parallel faults play an important role in the overall deformation field. This demonstrates the significance of accurately characterising strain rates over a broad region when assessing seismic hazard.

Metal ions-anchored bacterial outer membrane vesicles for enhanced ferroptosis induction and immune stimulation in targeted antitumor therapy

The activation of ferroptosis presents a versatile strategy for enhancing the antitumor immune responses in cancer therapy. However, developing ferroptosis inducers that combine high biocompatibility and therapeutic efficiency remains challenging. In this study, we propose a novel approach using biological nanoparticles derived from outer membrane vesicles (OMVs) of Escherichia coli for tumor treatment, aiming to activate ferroptosis and stimulate the immune responses. Specifically, we functionalize the OMVs by anchoring them with ferrous ions via electrostatic interactions and loading them with the STING agonist-4, followed by tumor-targeting DSPE-PEG-FA decoration, henceforth referred to as OMV/SaFeFA. The anchoring of ferrous ions endows the OMVs with peroxidase-like activity, capable of inducing cellular lipid peroxidation by catalyzing H2O2 to •OH. Furthermore, OMV/SaFeFA exhibits pH-responsive release of ferrous ions and the agonist, along with tumor-targeting capabilities, enabling tumor-specific therapy while minimizing side effects. Notably, the concurrent activation of the STING pathway and ferroptosis elicits robust antitumor responses in colon tumor-bearing mouse models, leading to exceptional therapeutic efficacy and prolonged survival. Importantly, no acute toxicity was observed in mice receiving OMV/SaFeFA treatments, underscoring its potential for future tumor therapy and clinical translation.

Full optimization of dynamic nuclear polarization on a 1 tesla benchtop polarizer with hyperpolarizing solids

Hyperpolarization by dissolution dynamic nuclear polarization (dDNP) provides the opportunity to dramatically increase the weak nuclear magnetic resonance (NMR) signal of liquid molecular targets using the high polarization of electron radicals. Unfortunately, the solution-state hyperpolarization can only be accessed once since freezing and melting of the hyperpolarized sample happen in an irreversible fashion. A way to expand the application horizon of dDNP can therefore be to find a recyclable DNP alternative. To pursue this ambitious goal, we recently introduced the concept of recyclable hyperpolarized flow (HypFlow) DNP where hyperpolarization happens in porous hyperpolarizing solids placed in a compact benchtop DNP polarizer at a magnetic field of 1 T and a temperature of 77 K. Here we aim to optimize the radical concentrations immobilized in hyperpolarizing solids with the objective of generating as much polarization as possible in a timeframe (<1 s) compatible with future recyclable DNP applications. To do so, the solid-state DNP enhancement factors, build-up rates and DNP spectra of different hyperpolarizing solids containing various nitroxide radical loadings (20-74 μmol cm-3) are compared against the DNP performance of varying nitroxide concentrations (10-100 mM) solvated in a glassy frozen solution. We demonstrate that in <1 s, polarization enhancement goes up to 56 and 102 with surface-bound and solvated radicals, respectively, under the optimized conditions. For the range of nitroxide concentrations used cross effect DNP seems to be the dominant mechanism under benchtop conditions. This was deduced from the electron paramagnetic resonance (EPR) lineshape of TEMPOL investigated using Q-band EPR measurements.

Infrared color-sorting metasurfaces

The process of sorting light based on colors (photon energy) is a prerequisite in broadband optical systems, typically achieved in the form of guiding incoming signals through a sequence of spectral filters. The assembly of filters often leads to lengthy optical trains and consequently, large system footprints. In this work, we address this issue by proposing a flat color-sorting device comprising a diffraction grating and a dielectric Huygens' metasurface. Upon the incidence of a broadband beam, the grating disperses wavelengths to a continuous range of angles in accordance with the law of diffraction. The following metasurface with multiple paired Huygens' resonances corrects the dispersion and binds wavelengths to the corresponding waveband with a designated output angle. We demonstrate the sorting efficacy by designing a device with a color-sorting metasurface with two discrete dispersion-compensated outputs (10.8 ± 0.3 μm and 11.9 ± 0.3 μm), based on the proposed approach. The optimized metasurface possesses an overall transmittance exceeding 57% and reduces lateral dispersion by 90% at the output. The proposed color-sorting mechanism provides a solution that benefits the designing of metasurfaces for miniature multi-band systems.

Chiral Diselenophosphoric Acids for Ion Pair Catalysis: A Novel Approach to Enhance Both Proton Donating and Proton Accepting Properties

The activation of poorly reactive substrates via strong chiral acids is a central topic in asymmetric ion pair catalysis these days. Despite highly successful scaffolds such as N-triflylphosphoramides, these catalysts either lack C2-symmetry or provide multiple H-bond acceptor sites, leading to lower ee values for certain reactions. We present BINOL-based diselenophosphoric acids (DSA) as an extremely promising alternative. Using an intertwined approach of synthesis and NMR studies, we developed a synthetic approach to DSA with up to 98 % NMR yield. The obtained acids provide both very high proton donor and proton acceptor properties, a bifunctionality, which is key to catalytic applications. Indeed, first reactivity test proved the much higher acidity of DSA and its ability to initiate Mukaiyama-Mannich reaction and protodesilylation of silyl ethers. Together with their C2-symmetry, the single donor and single acceptor situation, the decreased tendency of self-association, and the straightforward synthesis with potential 3,3'-substitution, the DSA provide all features ideal for the further development of ion pair catalysis.

From Plastic Waste to Green Hydrogen and Valuable Chemicals Using Sunlight and Water

Over 79 % of 6.3 billion tonnes of plastics produced from 1950 to 2015 have been disposed in landfills or found their way to the oceans, where they will reside for up to hundreds of years before being decomposed bringing upon significant dangers to our health and ecosystems. Plastic photoreforming offers an appealing alternative by using solar energy and water to transform plastic waste into value-added chemical commodities, while simultaneously producing green hydrogen via the hydrogen evolution reaction. This review aims to provide an overview of the underlying principles of emerging plastic photoreforming technologies, highlight the challenges associated with experimental protocols and performance assessments, discuss recent global breakthroughs on the photoreforming of plastics, and propose perspectives for future research. A critical assessment of current plastic photoreforming studies shows a lack of standardised conditions, hindering comparison amongst photocatalyst performance. Guidelines to establish a more accurate evaluation of materials and systems are proposed, with the aim to facilitate the translation of promising fundamental discovery in photocatalysts design.

Molecular Engineering of Porous Fe-N-C Catalyst with Sulfur Incorporation for Boosting CO2 Reduction and Zn-CO2 Battery

Transition metal-nitrogen-carbon (M-N-C) catalysts have emerged as promising candidates for electrocatalytic CO2 reduction reaction (CO2RR) due to their uniform active sites and high atomic utilization rate. However, poor efficiency at low overpotentials and unclear reaction mechanisms limit the application of M-N-C catalysts. In this study, Fe-N-C catalysts are developed by incorporating S atoms onto ordered hierarchical porous carbon substrates with a molecular iron thiophenoporphyrin. The well-prepared FeSNC catalyst exhibits superior CO2RR activity and stability, attributes to an optimized electronic environment, and enhances the adsorption of reaction intermediates. It displays the highest CO selectivity of 94.0% at -0.58 V (versus the reversible hydrogen electrode (RHE)) and achieves the highest partial current density of 13.64 mA cm-2 at -0.88 V. Furthermore, when employed as the cathode in a Zn-CO2 battery, FeSNC achieves a high-power density of 1.19 mW cm-2 and stable charge-discharge cycles. Density functional theory calculations demonstrate that the incorporation of S atoms into the hierarchical porous carbon substrate led to the iron center becoming more electron-rich, consequently improving the adsorption of the crucial reaction intermediate *COOH. This study underscores the significance of hierarchical porous structures and heteroatom doping for advancing electrocatalytic CO2RR and energy storage technologies.

Hydrogel forming microneedles loaded with VEGF and Ritlecitinib/polyhydroxyalkanoates nanoparticles for mini-invasive androgenetic alopecia treatment

Androgenetic alopecia (AGA), the most prevalent clinical hair loss, lacks safe and effective treatments due to downregulated angiogenic genes and insufficient vascularization in the perifollicular microenvironment of the bald scalp in AGA patients. In this study, a hyaluronic acid (HA) based hydrogel-formed microneedle (MN) was designed, referred to as V-R-MNs, which was simultaneously loaded with vascular endothelial growth factor (VEGF) and the novel hair loss drug Ritlecitinib, the latter is encapsulated in slowly biodegradable polyhydroxyalkanoates (PHAs) nanoparticles (R-PHA NPs) for minimally invasive AGA treatment. The integration of HA based hydrogel alongside PHA nanoparticles significantly bolstered the mechanical characteristics of microneedles and enhanced skin penetration efficiency. Due to the biosafety, mechanical strength, and controlled degradation properties of HA hydrogel formed microneedles, V-R-MNs can effectively penetrate the skin's stratum corneum, facilitating the direct delivery of VEGF and Ritlecitinib in a minimally invasive, painless and long-term sustained release manner. V-R-MNs not only promoted angiogenesis and improve the immune microenvironment around the hair follicle to promote the proliferation and development of hair follicle cells, but also the application of MNs to the skin to produce certain mechanical stimulation could also promote angiogenesis. In comparison to the clinical drug minoxidil for AGA treatment, the hair regeneration effect of V-R-MN in AGA model mice is characterized by a rapid onset of the anagen phase, improved hair quality, and greater coverage. This introduces a new, clinically safer, and more efficient strategy for AGA treatment, and serving as a reference for the treatment of other related diseases.

A Functional InDel in the WRKY10 Promoter Controls the Degree of Flesh Red Pigmentation in Apple

MYB transcription factors have been linked to anthocyanin synthesis and various color phenotypes in plants. In apple, MYB10 confers a red-flesh phenotype due to a minisatellite insertion in its R6 promoter, but R6:MYB10 genotypes exhibit various degrees of red pigmentation in the flesh, suggesting the involvement of other genetic factors. Here, it is shown that MdWRKY10, a transcription factor identified via DNA pull-down trapping, binds to the promoter of MdMYB10 and activates its transcription. MdWRKY10 specifically interacts with the WDR protein MdTTG1 to join the apple MYB-bHLH-WDR (MBW) complex, which significantly enhances its transcriptional activation activity. A 163-bp InDel detected in the promoter region of the alleles of MdWRKY10 in a hybrid population of identical heterozygous genotypes regarding R6 by structural variation analysis, contains a typical W-box element that MdWRKY10 binds to for transactivation. This leads to increased transcript levels of MdWRKY10 and MdMYB10 and enhanced anthocyanin synthesis in the flesh, largely accounting for the various degrees of flesh red pigmentation in the R6 background. These findings reveal a novel regulatory role of the WRKY-containing protein complex in the formation of red flesh apple phenotypes and provide broader insights into the molecular mechanism governing anthocyanin synthesis in plants.

Impact of preanalytical factors on liquid biopsy in the canine cancer model

While liquid biopsy has potential to transform cancer diagnostics through minimally-invasive detection and monitoring of tumors, the impact of preanalytical factors such as the timing and anatomical location of blood draw is not well understood. To address this gap, we leveraged pet dogs with spontaneous cancer as a model system, as their compressed disease timeline facilitates rapid diagnostic benchmarking. Key liquid biopsy metrics from dogs were consistent with existing reports from human patients. The tumor content of samples was higher from venipuncture sites closer to the tumor and from a central vein. Metrics also differed between lymphoma and non-hematopoietic cancers, urging cancer-type-specific interpretation. Liquid biopsy was highly sensitive to disease status, with changes identified soon after post chemotherapy administration, and trends of increased tumor fraction and other metrics observed prior to clinical relapse in dogs with lymphoma or osteosarcoma. These data support the utility of pet dogs with cancer as a relevant system for advancing liquid biopsy platforms.

Exploring the versatility of miRNA-128: a comprehensive review on its role as a biomarker and therapeutic target in clinical pathways

MicroRNAs (miRNAs/ miRs) are short, noncoding RNAs, usually consisting of 18 to 24 nucleotides, that control gene expression after the process of transcription and have crucial roles in several clinical processes. This article seeks to provide an in-depth review and evaluation of the many activities of miR-128, accentuating its potential as a versatile biomarker and target for therapy; The circulating miR-128 has garnered interest because of its substantial influence on gene regulation and its simplicity in extraction. Several miRNAs, such as miR-128, have been extracted from circulating blood cells, cerebrospinal fluid, and plasma/serum. The miR-128 molecule can specifically target a diverse range of genes, enabling it to have intricate physiological impacts by concurrently regulating many interrelated pathways. It has a vital function in several biological processes, such as modulating the immune system, regulating brain plasticity, organizing the cytoskeleton, and inducing neuronal death. In addition, miR-128 modulates genes associated with cell proliferation, the cell cycle, apoptosis, plasma LDL levels, and gene expression regulation in cardiac development. The dysregulation of miR-128 expression and activity is associated with the development of immunological responses, changes in neural plasticity, programmed cell death, cholesterol metabolism, and heightened vulnerability to autoimmune illnesses, neuroimmune disorders, cancer, and cardiac problems; The paper highlights the importance of studying the consequences of miR-128 dysregulation in these specific locations. By examining the implications of miRNA-128 dysregulation in these areas, the article underscores its significance in diagnosis and treatment, providing a foundation for research and clinical applications.

Visible light driven (VLD) reduced TiO2-x nanocatalysts designed by inorganic and organic reducing agent-mediated solvothermal methods for electrocatalytic and photocatalytic applications

This work presents a comparative study on the structural, optical and electrochemical characteristics of visible light driven (VLD) reduced titanium dioxide (TiO2-x ) nanocatalysts synthesized via inorganic and organic synthetic routes. X-ray diffraction (XRD) patterns, Raman spectra and X-ray absorption fine structure (XAFS) analyses reflected anatase phase titania. Whereas, the quantitative EXAFS fit and XANES analysis revealed structural distortion due to the presence of oxygen and titanium vacancies with low valent Ti states in anatase lattices of certain nanocatalysts, which subsequently leads to better electrochemical and photocatalytic activities. Moreover, owing to the large surface area and mesoporous structures, the Mg-TiO2-x nanocatalysts exhibited enhanced water adsorption and ultimately increased overall water splitting with an OER overpotential equal to 420 mV vs. RHE at a current density of 10 mA cm-2 (Tafel slope = 62 mV dec-1), extended visible light absorbance, decreased photoluminescence (PL) intensity and increased carrier lifetime in comparison with commercial titania.

The Genetic Architecture of the Human Corpus Callosum and its Subregions

The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.

Neural Representation of Valenced and Generic Probability and Uncertainty

Representing the probability and uncertainty of outcomes facilitates adaptive behavior by allowing organisms to prepare in advance and devote attention to relevant events. Probability and uncertainty are often studied only for valenced (appetitive or aversive) outcomes, raising the question of whether the identified neural machinery also processes the probability and uncertainty of motivationally neutral outcomes. Here, we aimed to dissociate valenced from valence-independent (i.e., generic) probability (p; maximum at p = 1) and uncertainty (maximum at p = 0.5) signals using human neuroimaging. In a Pavlovian task (n = 41; 19 females), different cues predicted appetitive, aversive, or neutral liquids with different probabilities (p = 0, p = 0.5, p = 1). Cue-elicited motor responses accelerated, and pupil sizes increased primarily for cues that predicted valenced liquids with higher probability. For neutral liquids, uncertainty rather than probability tended to accelerate cue-induced responding and decrease pupil size. At the neural level, generic uncertainty signals were limited to the occipital cortex, while generic probability also activated the anterior ventromedial prefrontal cortex. These generic probability and uncertainty signals contrasted with cue-induced responses that only encoded the probability and uncertainty of valenced liquids in medial prefrontal, insular, and occipital cortices. Our findings show a behavioral and neural dissociation of generic and valenced signals. Thus, some parts of the brain keep track of motivational charge while others do not, highlighting the need and usefulness of characterizing the exact nature of learned representations.

Alternating current electroluminescence devices: recent advances and functional applications

Wearable smart devices and visualisation sensors based on alternating current electroluminescence (ACEL) have received considerable attention in recent years. Due to the unique properties of ACEL devices, such as high mechanical strength, adaptability to complex environments, and no need for energy level matching, ACEL is suitable for multifunctional applications and visualisation sensing platforms. This review comprehensively outlines the latest developments in ACEL devices, starting with an analysis of the mechanism, classification, and optimisation strategies of ACEL. It introduces the functional applications of ACEL in multicolour displays, high-durability displays, stretchable and wearable displays, and autonomous function displays. Particularly, it emphasises the research progress of ACEL in sensory displays under interactive conditions such as liquid sensing, environmental factor sensing, kinetic energy sensing, and biosensing. Finally, it forecasts the challenges and new opportunities faced by future functional and interactive ACEL devices in fields such as artificial intelligence, smart robotics, and human-computer interaction.

Chrysophanol inhibits of colorectal cancer cell motility and energy metabolism by targeting the KITENIN/ErbB4 oncogenic complex

BACKGROUND

Expression of the KITENIN/ErbB4 oncogenic complex is associated with metastasis of colorectal cancer to distant organs and lymph nodes and is linked with poor prognosis and poor survival.

METHODS

Here, we used in vitro and in silico methods to test the ability of chrysophanol, a molecule of natural origin, to suppress the progression of colorectal cancer by targeting the KITENIN/ErbB4 complex.

RESULTS

Chrysophanol binds to ErbB4, disrupting the ErbB4/KITENIN complex and causing autophagic degradation of KITENIN. We demonstrated that chrysophanol binds to ErbB4 according to a molecular docking model. Chrysophanol reversed KITENIN-mediated effects on cell motility, aerobic glycolysis, and expression of downstream effector genes. Moreover, under conditions of KITENIN overexpression, chrysophanol suppressed the production of onco-metabolites.

CONCLUSION

Chrysophanol suppresses oncogenic activities by targeting the KITENIN/ErbB4 complex.

Dual Basicity and Nucleophilicity of Organosodium Reagents in Benzylic C-H Additions of Toluenes to Diarylethenes and Ketones

Profiting from the dual high basicity and nucleophilicity of organosodium complexes, here we report the stepwise lateral metalation of a wide range of alkyl arenes (MeAr), mediated by hydrocarbon-soluble NaCH2SiMe3 ⋅ PMDETA (PMDETA=N,N,N',N'',N''-pentamethyldiethylenetriamine), followed by nucleophilic addition to diarylethenes of the newly generated NaCH2Ar ⋅ PMDETA complexes. This method grants access to a range of functionalised hydrocarbons in excellent yields and can be upgraded to catalytic regimes when using trans-stilbene, a 10 mol% of the alkyl sodium base and toluene as a solvent. Extending this approach to aromatic ketones leads to the formation of stilbenes under mild reaction conditions, resulting from the deprotonative coupling of toluenes with ketones. Combining spectroscopic studies with the trapping and characterisation of key reaction intermediates, mechanistic insights have been gained, advancing the understanding of coordination effects in organosodium chemistry, and shedding light on their special reactivity profiles.

Chromosome X-Wide Common Variant Association Study (XWAS) in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) displays a notable male bias in prevalence. Research into rare (<0.1) genetic variants on the X chromosome has implicated over 20 genes in ASD pathogenesis, such as MECP2, DDX3X, and DMD. The "female protective effect" in ASD suggests that females may require a higher genetic burden to manifest similar symptoms as males, yet the mechanisms remain unclear. Despite technological advances in genomics, the complexity of the biological nature of sex chromosomes leave them underrepresented in genome-wide studies. Here, we conducted an X chromosome-wide association study (XWAS) using whole-genome sequencing data from 6,873 individuals with ASD (82% males) across Autism Speaks MSSNG, Simons Simplex Cohort SSC, and Simons Foundation Powering Autism Research SPARK, alongside 8,981 population controls (43% males). We analyzed 418,652 X-chromosome variants, identifying 59 associated with ASD (p-values 7.9×10-6 to 1.51×10-5), surpassing Bonferroni-corrected thresholds. Key findings include significant regions on chrXp22.2 (lead SNP=rs12687599, p=3.57×10-7) harboring ASB9/ASB11, and another encompassing DDX53/PTCHD1-AS long non-coding RNA (lead SNP=rs5926125, p=9.47×10-6). When mapping genes within 10kb of the 59 most significantly associated SNPs, 91 genes were found, 17 of which yielded association with ASD (GRPR, AP1S2, DDX53, HDAC8, PCDH19, PTCHD1, PCDH11X, PTCHD1-AS, DMD, SYAP1, CNKSR2, GLRA2, OFD1, CDKL5, GPRASP2, NXF5, SH3KBP1). FGF13 emerged as a novel X-linked ASD candidate gene, highlighted by sex-specific differences in minor allele frequencies. These results reveal significant new insights into X chromosome biology in ASD, confirming and nominating genes and pathways for further investigation.

From a distance: Shuttleworth revisited

The Shuttleworth equation: a linear stress-strain relation ubiquitously used in modeling the behavior of soft surfaces. Its validity in the realm of materials subject to large deformation is a topic of current debate. Here, we allow for large deformation by deriving the constitutive behavior of the surface from the general framework of finite kinematics. We distinguish cases of finite and infinitesimal surface relaxation preceding an infinitesimal applied deformation. The Shuttleworth equation identifies as the Cauchy stress measure in the fully linearized setting. We show that both in finite and linearized cases, measured elastic constants depend on the utilized stress measure. In addition, we discuss the physical implications of our results and analyze the impact of surface relaxation on the estimation of surface elastic moduli in the light of two different test cases.

Blue phosphorene on Au(111): theoretical, spectroscopic and diffraction analysis reveal the role of single Au adatoms

In investigating the monoatomic layers of P, several stable two-dimensional (2D) allotropes have been theoretically predicted. Among them, single-layer blue phosphorus (BlueP) appears to deliver promising properties. After initial success, where the structure of BlueP triangular patches on Au(111) was conceived on the basis of scanning tunneling microscopy (STM) and density functional theory (DFT), the surface structure model was revisited multiple times with increasing accuracy and insight of theoretical calculations and experimental datasets. Interestingly, the quest for a reliable atomic structure model of BlueP on Au(111) turned out to be very contentious and challenging, particularly considering the possible incorporation of Au atoms in the 2D sheet of P. This article proposes an extended report on theoretical findings that can be extracted from DFT calculations of the orbital projected band structure and employed for an efficient comparison protocol between the calculations and experimental datasets obtained from angle-resolved photoemission spectroscopy (ARPES). The findings, together with experimental and simulated data from STM imaging and surface X-ray diffraction (SXRD), show a clear way to verify the presence and characterize the stabilizing effect of foreign atoms in 2D materials.

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Noise Level of a Ring Laser Gyroscope in the Femto-Rad/s Range

Absolute angular rotation rate measurements with sensitivity better than prad/s would be beneficial for fundamental science investigations. In this regard, large frame Earth based ring laser gyroscopes are top instrumentation as far as bandwidth, long-term operation, and sensitivity are concerned. Here, we demonstrate that the GINGERINO active-ring laser upper limiting noise is close to 2×10^{-15}  rad/s for ∼2×10^{5}  s of integration time, as estimated by the Allan deviation evaluated in a differential measurement scheme. This result is more than a factor of 10 better than the theoretical prediction so far accounted for ideal ring lasers shot-noise with the two beams counterpropagating inside the cavity considered as two independent propagating modes. This feature is related to the peculiarity of real ring laser system dynamics that causes phase crosstalking among the two counterpropagating modes. In this context, the independent beam model is, then, not applicable, and the measured noise limit falls below the expected one.

Control of innate olfactory valence by segregated cortical amygdala circuits

Animals perform innate behaviors that are stereotyped responses to specific evolutionarily relevant stimuli in the absence of prior learning or experience. These behaviors can be reduced to an axis of valence, whereby specific odors evoke approach or avoidance. The cortical amygdala (plCoA) mediates innate attraction and aversion to odor. However, little is known about how this brain area gives rise to behaviors of opposing motivational valence. Here, we sought to define the circuit features of plCoA that give rise to innate olfactory behaviors of valence. We characterized the physiology, gene expression, and projections of this structure, identifying a divergent, topographic organization that selectively controls innate attraction and avoidance to odor. First, we examined odor-evoked responses in these areas and found sparse encoding of odor identity, but not valence. We next considered a topographic organization and found that optogenetic stimulation of the anterior and posterior domains of plCoA elicits attraction and avoidance, respectively, suggesting a functional axis for valence. Using single cell and spatial RNA sequencing, we identified the molecular cell types in plCoA, revealing an anteroposterior gradient in cell types, whereby anterior glutamatergic neurons preferentially express Slc17a6 and posterior neurons express Slc17a7. Activation of these respective cell types recapitulates appetitive and aversive valence behaviors, and chemogenetic inhibition reveals partial necessity for valence responses to innate appetitive or aversive odors. Finally, we identified topographically organized circuits defined by projections, whereby anterior neurons preferentially project to medial amygdala, and posterior neurons preferentially project to nucleus accumbens, which are respectively sufficient and necessary for innate negative and positive olfactory valence. Together, these data advance our understanding of how the olfactory system generates stereotypic, hardwired attraction and avoidance, and supports a model whereby distinct, topographically distributed plCoA populations direct innate olfactory valence responses by signaling to divergent valence-specific targets, linking upstream olfactory identity to downstream valence behaviors, through a population code. This represents a novel circuit motif in which valence encoding is represented not by the firing properties of individual neurons, but by population level identity encoding that is routed through divergent targets to mediate distinct valence.

Phase Electronic Structure Tuning via Pt, P-Doped Ni4Mo-Implanted Ti4O7 for Highly Efficient Water Splitting and Mg/Seawater Batteries

Fine-tuning nanoscale structures, morphologies, and electronic states are crucial for creating efficient water-splitting electrocatalysts. In this study, a method for electronic structure engineering to enhance overall water splitting in a corrosion-resistant electrocatalyst matrix by integrating Pt, P dual-doped Ni4Mo electrocatalysts onto a Ti4O7 nanorod grown on carbon cloth (Pt, P-Ni4Mo-Ti4O7/CC) is introduced. By optimizing platinum and phosphorus concentrations to 1.18% and 2.42%, respectively, low overpotentials are achieved remarkably: 24 mV at 10 mA cm-2 for the hydrogen evolution reaction and 290 mV at 20 mA cm-2 for the oxygen evolution reaction in 1.0 m KOH. These values approach or surpass those of benchmark Pt-C and IrO2 catalysts. Additionally, the Pt, P-Ni4Mo-Ti4O7/CC bifunctional electrocatalyst displays low cell potentials across various mediums, maintaining excellent current retention (96% stability after 40 h in mimic seawater at 20 mA cm-2) and demonstrating strong corrosion resistance and suitability for seawater  electrolysis. As a cathode in magnesium/seawater batteries, it achieves a power density of 7.2 mW cm-2 and maintains stability for 100 h. Density functional theory simulations confirm that P, Pt doping-assisted electronic structure modifications augment electrical conductivity and active sites in the hybrid electrocatalysts.

Exciton polaron formation and hot-carrier relaxation in rigid Dion-Jacobson-type two-dimensional perovskites

The efficiency of two-dimensional Dion-Jacobson-type materials relies on the complex interplay between electronic and lattice dynamics; however, questions remain about the functional role of exciton-phonon interactions. Here we establish the robust polaronic nature of the excitons in these materials at room temperature by combining ultrafast spectroscopy and electronic structure calculations. We show that polaronic distortion is associated with low-frequency (30-60 cm-1) lead iodide octahedral lattice motions. More importantly, we discover how targeted ligand modification of this two-dimensional perovskite structure manipulates exciton-phonon coupling, exciton polaron population and carrier cooling. At high excitation density, stronger exciton-phonon coupling increases the hot-carrier lifetime, forming a hot-phonon bottleneck. Our study provides detailed insight into the exciton-phonon coupling and its role in carrier cooling in two-dimensional perovskites relevant for developing emerging hybrid semiconductor materials with tailored properties.

Photostrictive Actuators Based on Freestanding Ferroelectric Membranes

Complex oxides offer a wide range of functional properties, and recent advances in the fabrication of freestanding membranes of these oxides are adding new mechanical degrees of freedom to this already rich functional ecosystem. Here, photoactuation is demonstrated in freestanding thin film resonators of ferroelectric Barium Titanate (BaTiO3) and paraelectric Strontium Titanate (SrTiO3). The free-standing films, transferred onto perforated supports, act as nano-drums, oscillating at their natural resonance frequency when illuminated by a frequency-modulated laser. The light-induced deflections in the ferroelectric BaTiO3 membranes are two orders of magnitude larger than in the paraelectric SrTiO3 ones. Time-resolved X-ray micro-diffraction under illumination and temperature-dependent holographic interferometry provide combined evidence for the photostrictive strain in BaTiO3 originating from a partial screening of ferroelectric polarization by photo-excited carriers, which decreases the tetragonality of the unit cell. These findings showcase the potential of photostrictive freestanding ferroelectric films as wireless actuators operated by light.

Deep generative spatiotemporal learning for integrating fracture mechanics in composite materials: inverse design, discovery, and optimization

The trade-off between strength and toughness presents a fundamental challenge in engineering material design. Composite materials (CMs) can strategically arrange different materials to enhance both strength and toughness by optimizing the distribution of loads and increasing resistance to crack propagation. However, current data-driven computational modeling approaches for CM configuration optimization suffer from limitations of "substantial computational cost" and "poor predictive power over extrapolation spaces", making it difficult to integrate with global optimization algorithms, and ultimately limiting the discovery of materials with optimal tradeoffs. As a breakthrough, we propose a data-driven design framework with a multi-task DL architecture capable of accurately predicting local fields' spatiotemporal behavior, including stress evolution and crack propagation, alongside homogenized mechanical properties. Our model, trained on datasets generated from crack phase fields simulations of random configurations, demonstrated exceptional predictive performance even for unseen configurations with well organized patterns exploiting nature-inspired morphological features. Importantly, solely from composite material (CM) configurations, our model effectively predicts long-term spatiotemporal fields with an accuracy comparable to FEM but with a substantial reduction in computational time. By coupling the model's predictive power with genetic optimization algorithms, we demonstrated the framework's applicability in two representative inverse design tasks: devising CM configurations with mechanical properties beyond the training set and guiding desired crack pattern formation. Our research highlights the potential of artificial intelligence as a feasible alternative to conventional computational approaches for straightforward configurational and structural optimization.

Understanding the influence of context on real-world walking energetics

Speeds that minimize energetic cost during steady-state walking have been observed during lab-based investigations of walking biomechanics and energetics. However, in real-world scenarios, humans walk in a variety of contexts that can elicit different walking strategies, and may not always prioritize minimizing energetic cost. To investigate whether individuals tend to select energetically optimal speeds in real-world situations and how contextual factors influence gait, we conducted a study combining data from lab and real-world experiments. Walking kinematics and context were measured during daily life over a week (N=17) using wearable sensors and a mobile phone. To determine context, we utilized self-reported activity logs, GPS data and follow-up exit interviews. Additionally, we estimated energetic cost using respirometry over a range of gait speeds in the lab. Gross and net cost of transport were calculated for each participant, and were used to identify energetically optimal walking speed ranges for each participant. The proportion of real-world steady-state stride speeds within these ranges (gross and net) were identified for all data and for each context. We found that energetically optimal speeds predicted by gross cost of transport were more predictive of walking speeds used during daily life than speeds that would minimize net cost of transport. On average, 82.2% of all steady-state stride speeds were energetically optimal for gross cost of transport for all contexts and participants, while only 45.6% were energetically optimal for net cost of transport. These results suggest that while energetic cost is a factor considered by humans when selecting gait speed in daily life, it is not the sole determining factor. Context contributes to the observed variability in movement parameters both within and between individuals.

Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications

Smart biosensors attract significant interest due to real-time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real-time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring) will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine-learning-based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone-based systems on current trends and challenges for future works in wearable health monitoring.

Unveiling microplastic distribution and interactions in the benthic layer of the Yangtze River Estuary and East China Sea

Microplastics (MPs), recognized as an emerging global environmental concern, have been extensively detected worldwide, with specific attention directed towards the Yangtze River Estuary (YRE) and East China Sea (ECS) regions. Despite their critical research significance, there remains a knowledge gap concerning the distribution of MPs in the benthic layer within this area, particularly regarding interactions governing their occurrence. Here we illuminate the distribution of MPs within the benthic layer and unravel the intricate interplay between bottom water and sediment in the YRE and ECS. We find that MPs are notably more abundant in bottom water, ranging from 8 to 175 times higher than in surface water. These MPs predominantly consist of polyester fibers, exhibit a size range between 0.5 and 5.0 mm, and display distinct coloration. Co-occurrence network analysis and Principal Coordinate Analysis confirm a robust correlation between MPs in bottom water and sediment, signifying the pivotal role of bottom water in mediating the distribution and transportation of MPs within the benthic layer. Furthermore, a positive correlation between MPs in sediment and bottom water turbidity underscores the impact of surface sediment resuspension and upwelling on MPs distribution. This study clarifies the intricate interactions within the benthic layer and highlights the crucial role of bottom water as a mediator in the vertical distribution of MPs, advancing our understanding of the "source-to-sink" transport processes governing MPs within water-sediment systems.

YTHDC1 m6A-dependent and m6A-independent functions converge to preserve the DNA damage response

Cells have evolved a robust and highly regulated DNA damage response to preserve their genomic integrity. Although increasing evidence highlights the relevance of RNA regulation, our understanding of its impact on a fully efficient DNA damage response remains limited. Here, through a targeted CRISPR-knockout screen, we identify RNA-binding proteins and modifiers that participate in the p53 response. Among the top hits, we find the m6A reader YTHDC1 as a master regulator of p53 expression. YTHDC1 binds to the transcription start sites of TP53 and other genes involved in the DNA damage response, promoting their transcriptional elongation. YTHDC1 deficiency also causes the retention of introns and therefore aberrant protein production of key DNA damage factors. While YTHDC1-mediated intron retention requires m6A, TP53 transcriptional pause-release is promoted by YTHDC1 independently of m6A. Depletion of YTHDC1 causes genomic instability and aberrant cancer cell proliferation mediated by genes regulated by YTHDC1. Our results uncover YTHDC1 as an orchestrator of the DNA damage response through distinct mechanisms of co-transcriptional mRNA regulation.

The Effects of Biomimetic Surface Topography on Vascular Cells: Implications for Vascular Conduits

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide and represent a pressing clinical need. Vascular occlusions are the predominant cause of CVD and necessitate surgical interventions such as bypass graft surgery to replace the damaged or obstructed blood vessel with a synthetic conduit. Synthetic small-diameter vascular grafts (sSDVGs) are desired to bypass blood vessels with an inner diameter <6 mm yet have limited use due to unacceptable patency rates. The incorporation of biophysical cues such as topography onto the sSDVG biointerface can be used to mimic the cellular microenvironment and improve outcomes. In this review, the utility of surface topography in sSDVG design is discussed. First, the primary challenges that sSDVGs face and the rationale for utilizing biomimetic topography are introduced. The current literature surrounding the effects of topographical cues on vascular cell behavior in vitro is reviewed, providing insight into which features are optimal for application in sSDVGs. The results of studies that have utilized topographically-enhanced sSDVGs in vivo are evaluated. Current challenges and barriers to clinical translation are discussed. Based on the wealth of evidence detailed here, substrate topography offers enormous potential to improve the outcome of sSDVGs and provide therapeutic solutions for CVDs.

Dual-additive-based electrolyte design for aqueous zinc ion batteries with high plating/stripping efficiency

A dual-additive-based aqueous electrolyte was designed with a pH-buffering additive (Zn(OAc)2) and an electrostatic shielding additive (TMAOAc) for high Zn plating/stripping efficiency. The buffering pair, OAc-/HOAc, can stabilize the pH value to suppress side hydrogen evolution reactions. Meanwhile, TMA+ acts as a competitive cation being preferentially adsorbed on the uneven surface of the Zn anode and exerts an electrostatic shielding effect to facilitate flat Zn deposition. Such a dual-additive-based electrolyte promotes an ultra-high Zn plating/stripping efficiency of 99.9% at 1 mA cm-2 and long-term cycling stability for 3600 h at 0.5 mA cm-2, offering valuable insights for advanced aqueous batteries.

The recent advancements in protein nanoparticles for immunotherapy

In recent years, the advancement of nanoparticle-based immunotherapy has introduced an innovative strategy for combatting diseases. Compared with other types of nanoparticles, protein nanoparticles have obtained substantial attention owing to their remarkable biocompatibility, biodegradability, ease of modification, and finely designed spatial structures. Nature provides several protein nanoparticle platforms, including viral capsids, ferritin, and albumin, which hold significant potential for disease treatment. These naturally occurring protein nanoparticles not only serve as effective drug delivery platforms but also augment antigen delivery and targeting capabilities through techniques like genetic modification and covalent conjugation. Motivated by nature's originality and driven by progress in computational methodologies, scientists have crafted numerous protein nanoparticles with intricate assembly structures, showing significant potential in the development of multivalent vaccines. Consequently, both naturally occurring and de novo designed protein nanoparticles are anticipated to enhance the effectiveness of immunotherapy. This review consolidates the advancements in protein nanoparticles for immunotherapy across diseases including cancer and other diseases like influenza, pneumonia, and hepatitis.

Dual-targeting of tumor cells and subcellular endoplasmic reticulum via AgPPIX-based Janus nanoparticles for photodynamic/immunotherapy against TNBC

Triple-negative breast cancer (TNBC) is known for its strong invasiveness, high recurrence rates, and poor prognosis. Heme oxygenase-1 (HO-1) is closely related to tumor invasion, metastasis, recurrence and formation of tumor immunosuppression. The expression of HO-1 is high in TNBC and low in normal tissues. In this study, AgPPIX was synthesized as a heme oxygenase-1 (HO-1) inhibitor and a photosensitizer for TNBC therapy. PDA nanoparticles were synthesized and modified with anti-CD24 and p-toluenesulfonamide (PTSC) on their both sides to obtain PTSC@AgPPIX/PDA@anti-CD24 Janus nanoparticles (PAPC) for AgPPIX-targeted delivery. Anti-CD24 is targeted to CD24 on tumor cells and the PTSC moiety is targeted to endoplasmic reticulum (ER), where HO-1 is located. The results indicated that PAPC Janus nanoparticles exhibited higher cytotoxicity in 4T1 cells than that of the mono-modified nanoparticles. PAPC not only inhibited the expression of HO-1 and VEGF but also reduced TrxR activity significantly. Furthermore, PAPC not only promoted intracellular ROS production under laser irradiation for tumor photodynamic therapy (PDT) but also polarized TAMs from M2-type to M1 for tumor immunotherapy. In vivo experiments confirmed that PAPC could remodel the tumor immune microenvironment and almost completely inhibit the tumor growth in mouse models. Therefore, PAPC Janus nanoparticles are a promising nanoplatform with a dual-targeting capacity for TNBC immune/PDT synergistic therapy.

Ion transport induced room-temperature insulator-metal transition in single-crystalline Cu2Se

Cu2Se is a superionic conductor above 414 K, with ionic conductivities reaching that of molten salts. The superionic behavior results from hopping Cu ions between different crystallographic sites within the Se scaffold. However, the properties of Cu2Se below 414 K are far less known due to experimental limitations imposed by the bulk or polycrystalline samples that have been available so far. Here, we report the synthesis of ultra-thin, large-area single crystalline Cu2Se samples using a chemical vapor deposition method. The as-synthesized Cu2Se crystals exhibit optically and electrically detectable and controllable robust phases at room temperature and above. We demonstrate that Cu ion vacancies can be manipulated to induce an insulator-metal transition, which exhibits 6 orders of magnitude change in the electrical resistance of two terminal devices, accompanied by an optical change in the phase configuration. Our experiments show that the high mobility of the liquid-like Cu ion vacancies in Cu2Se causes macroscopic ordering in the Cu vacancies. Consequently, phase distribution over the crystals is not dictated by the diffusive motion of the ions but by the local energy minima formed due to the phase transition. As a result, long-range vacancy ordering of the crystal below 414 K becomes optically observable at a micrometer scale. This work demonstrates that Cu2Se could be a prototypical system where long-range ordering properties can be studied via electrical and optical methods.

Analysis of the number of topological defects in active nematic fluids under applied shear flow

The number of topological defects in the shear flow of active nematic fluids is numerically investigated in this study. The evolution of the flow state of extensile active nematic fluids is explored by increasing the activity of active nematic fluids. Evidently, medium-activity active nematic fluids exhibit a highly ordered vortex lattice fluid state. However, high-activity active nematic fluids exhibit a meso-scale turbulent flow accompanied by topological defects. The number of topological defects (Ndef) increases with increasing shear Reynolds number (Res). Fluid viscosity strongly influences Ndef, while the influence of fluid density is relatively weak. Ndef decreases with increasing activity length scale (lζ) value. A small Res value strongly influences Ndef, whereas a large lζ value only weakly influences Ndef. As the activity increases, Ndef in contractile active nematic fluids becomes larger than that of extensile active nematic fluids.

High-Entropy Alloys and Their Affinity with Hydrogen: From Cantor to Platinum Group Elements Alloys

Properties of high-entropy alloys are currently in the spotlight due to their promising applications. One of the least investigated aspects is the affinity of these alloys to hydrogen, its diffusion, and reactions. In this study, high pressure is applied at ambient temperature and stress-induced diffusion of hydrogen is investigated into the structure of high-entropy alloys (HEA) including the famous Cantor alloy as well as less known, but nevertheless important platinum group (PGM) alloys. By applying X-ray diffraction to samples loaded into diamond anvil cells, a comparative investigation of transition element incorporating HEA alloys in Ne and H2 pressure-transmitting media is performed at ambient temperature. Even under stresses far exceeding conventional industrial processes, both Cantor and PGM alloys show exceptional resistance to hydride formation, on par with widely used industrial grade Cu-Be alloys. The observations inspire optimism for practical HEA applications in hydrogen-relevant industry and technology (e.g., coatings, etc), particularly those related to transport and storage.

Estrogen-induced chromatin looping changes identify a subset of functional regulatory elements

Transcriptional enhancers can regulate individual or multiple genes through long-range three-dimensional (3D) genome interactions, and these interactions are commonly altered in cancer. Yet, the functional relationship between changes in 3D interactions associated with regulatory regions and differential gene expression appears context-dependent. In this study, we used HiChiP to capture changes in 3D genome interactions between active regulatory regions of endometrial cancer cells in response to estrogen treatment and uncovered significant differential long-range interactions that are strongly enriched for estrogen receptor α (ER) bound sites (ERBS). The ERBS anchoring differential loops with either a gene's promoter or distal regions were correlated with larger transcriptional responses to estrogen compared to ERBS not involved in differential interactions. To functionally test this observation, CRISPR-based Enhancer-i was used to deactivate specific ERBS, which revealed a wide range of effects on the transcriptional response to estrogen. However, these effects are only subtly and not significantly stronger for ERBS in differential loops. In addition, we observed an enrichment of 3D interactions between the promoters of estrogen up-regulated genes and found that looped promoters can work together cooperatively. Overall, our work suggests that changes in 3D genome structure upon estrogen treatment identify some functionally important regulatory regions; however, these changes aren't required for a transcriptional response to E2 in endometrial cancer cells.

CryoEM reveals the structure of an archaeal pilus involved in twitching motility

Amongst the major types of archaeal filaments, several have been shown to closely resemble bacterial homologues of the Type IV pili (T4P). Within Sulfolobales, member species encode for three types of T4P, namely the archaellum, the UV-inducible pilus system (Ups) and the archaeal adhesive pilus (Aap). Whereas the archaellum functions primarily in swimming motility, and the Ups in UV-induced cell aggregation and DNA-exchange, the Aap plays an important role in adhesion and twitching motility. Here, we present a cryoEM structure of the Aap of the archaeal model organism Sulfolobus acidocaldarius. We identify the component subunit as AapB and find that while its structure follows the canonical T4P blueprint, it adopts three distinct conformations within the pilus. The tri-conformer Aap structure that we describe challenges our current understanding of pilus structure and sheds new light on the principles of twitching motility.

3D Puzzle at the Nanoscale-How do RNA Viruses Self-Assemble their Capsids into Perfectly Ordered Structures

The phenomenon of RNA virus self-organization, first observed in the mid-20th century in tobacco mosaic virus, is the subject of extensive research. Efforts to comprehend this process intensify due to its potential for producing vaccines or antiviral compounds as well as nanocarriers and nanotemplates. However, direct observation of the self-assembly is hindered by its prevalence within infected host cells. One of the approaches involves in vitro and in silico research using model viruses featuring a ssRNA(+) genome enclosed within a capsid made up of a single type protein. While various pathways are proposed based on these studies, their relevance in vivo remains uncertain. On the other hand, the development of advanced microscopic methods provide insights into the events within living cells, where following viral infection, specialized compartments form to facilitate the creation of nascent virions. Intriguingly, a growing body of evidence indicates that the primary function of packaging signals in viral RNA is to effectively initiate the virion self-assembly. This is in contrast to earlier opinions suggesting a role in marking RNA for encapsidation. Another noteworthy observation is that many viruses undergo self-assembly within membraneless liquid organelles, which are specifically induced by viral proteins.

Photocrosslinkable microgels derived from human platelet lysates: injectable biomaterials for cardiac cell culture

Cardiovascular diseases are a major global cause of morbidity and mortality, and they are often characterized by cardiomyocytes dead that ultimately leads to myocardial ischemia (MI). This condition replaces functional cardiac tissue with fibrotic scar tissue compromising heart function. Injectable systems for the in situ delivery of cells or molecules to assist during tissue repair have emerged as promising approaches for tissue engineering, particularly for myocardial repair. Methacryloyl platelet lysates (PLMA) have been employed for constructing full human-based 3D cell culture matrices and demonstrated potential for xeno-free applications. In this study, we propose using PLMA to produce microparticles (MPs) serving as anchors for cardiac and endothelial cells and ultimately as injectable systems for cardiac tissue repair. The herein reported PLMA MPs were produced by droplet microfluidics and showed great properties for cell attachment. More importantly, it is possible to show the capacity of PLMA MPs to serve as cell microcarriers even in the absence of animal-derived serum supplementation in the culture media.

Iterative Construction of Conserved Quantities in Dissipative Nearly Integrable Systems

Integrable systems offer rare examples of solvable many-body problems in the quantum world. Because of the fine-tuned structure, their realization in nature and experiment is never completely accurate, and therefore effects of integrability are observed only transiently. One way to overcome this limitation is to weakly couple nearly integrable systems to baths and driving: this will stabilize integrable effects up to arbitrary time and encode them in the stationary state approximated by a generalized Gibbs ensemble. However, the description of such driven dissipative nearly integrable models is challenging and no exact analytical methods have been proposed so far. Here, we develop an iterative scheme in which integrability breaking perturbations (baths) determine the conserved quantities that play the leading role in a highly efficient truncated generalized Gibbs ensemble description. Our scheme paves the way for easier calculations in thermodynamically large systems and can be used to construct unknown conserved quantities.

Systematic identification of structure-specific protein-protein interactions

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.