Single-Atom palladium engineered cobalt nanocomposite for selective aerobic oxidation of sulfides to sulfoxides.

Developing efficient catalysts for the selective oxidation of sulfides to sulfoxides using molecular oxygen as the oxidant is a challenging task. Here, we report a novel catalyst comprising a single atom palladium engineered cobalt nanocomposite (denoted as PdCo@NC-800-0.01) for this reaction. The incorporation of single atom palladium effectively transforms an originally inactive cobalt nanocomposite into a highly efficient and selective catalyst for the oxidation of sulfides. This catalyst PdCo@NC-800-0.01 exhibited outstanding performance in the selective oxidation of sulfides to sulfoxides using O2 as the oxidant in the presence of isobutyraldehyde (IBA) under mild conditions, demonstrating high activity and excellent selectivity for a broad spectrum of sulfides with good tolerance toward various functional groups, including those susceptible to oxidation. Furthermore, the catalyst could be easily recovered and reused up to 10 times without any significant loss in activity and selectivity. Comprehensive characterizations and theoretical calculations revealed that the engineering of cobalt nanocomposite with single atom Pd greatly enhanced the ability to adsorb and activate IBA, leading to the generation of the key acyl radical. This radical then reacted with singlet oxygen 1O2 derived from molecular oxygen, producing reactive oxygen species peroxy radical, which ultimately promoted the catalytic performance.

Deciphering and integrating invariants for neural operator learning with various physical mechanisms.

Neural operators have been explored as surrogate models for simulating physical systems to overcome the limitations of traditional partial differential equation (PDE) solvers. However, most existing operator learning methods assume that the data originate from a single physical mechanism, limiting their applicability and performance in more realistic scenarios. To this end, we propose the physical invariant attention neural operator (PIANO) to decipher and integrate the physical invariants for operator learning from the PDE series with various physical mechanisms. PIANO employs self-supervised learning to extract physical knowledge and attention mechanisms to integrate them into dynamic convolutional layers. Compared to existing techniques, PIANO can reduce the relative error by 13.6%-82.2% on PDE forecasting tasks across varying coefficients, forces or boundary conditions. Additionally, varied downstream tasks reveal that the PI embeddings deciphered by PIANO align well with the underlying invariants in the PDE systems, verifying the physical significance of PIANO.

[Retracted] MicroRNA­203 inhibits the proliferation and invasion of U251 glioblastoma cells by directly targeting PLD2.

Following the publication of this paper, it was drawn to the Editors' attention by a concerned reader that the PLD2 western blotting data shown in Fig. 3A and the Transwell invasion assay data shown in Fig. 6 were strikingly similar to data appearing in different form in other articles written by different authors at different research institutes that had either already been published elsewhere prior to the submission of this paper to Molecular Medicine Reports, or were under consideration for publication at around the same time. In view of the fact that certain of these data had already apparently been published previously, the Editor of Molecular Medicine Reports has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Molecular Medicine Reports 9: 503­508, 2014; 10.3892/mmr.2013.1814].

Complex-valued neural-operator-assisted soliton identification.

The numerical determination of solitary states is an important topic for such research areas as Bose-Einstein condensates, nonlinear optics, plasma physics, and so on. In this paper, we propose a data-driven approach for identifying solitons based on dynamical solutions of real-time differential equations. Our approach combines a machine-learning architecture called the complex-valued neural operator (CNO) with an energy-restricted gradient optimization. The CNO serves as a generalization of the traditional neural operator to the complex domain, and constructs a smooth mapping between the initial and final states; the energy-restricted optimization facilitates the search for solitons by constraining the energy space. We concretely demonstrate this approach on the quasi-one-dimensional Bose-Einstein condensate with homogeneous and inhomogeneous nonlinearities. Our work offers an idea for data-driven effective modeling and studies of solitary waves in nonlinear physical systems.

Balanced callose and cellulose biosynthesis in Arabidopsis quorum-sensing signaling and pattern-triggered immunity.

The plant cell wall (CW) is one of the most important physical barriers that phytopathogens must conquer to invade their hosts. This barrier is a dynamic structure that responds to pathogen infection through a complex network of immune receptors, together with CW-synthesizing and CW-degrading enzymes. Callose deposition in the primary CW is a well-known physical response to pathogen infection. Notably, callose and cellulose biosynthesis share an initial substrate, UDP-glucose, which is the main load-bearing component of the CW. However, how these 2 critical biosynthetic processes are balanced during plant-pathogen interactions remains unclear. Here, using 2 different pathogen-derived molecules, bacterial flagellin (flg22) and the diffusible signal factor (DSF) produced by Xanthomonas campestris pv. campestris, we show a negative correlation between cellulose and callose biosynthesis in Arabidopsis (Arabidopsis thaliana). By quantifying the abundance of callose and cellulose under DSF or flg22 elicitation and characterizing the dynamics of the enzymes involved in the biosynthesis and degradation of these 2 polymers, we show that the balance of these 2 CW components is mediated by the activity of a ß-1,3-glucanase (BG2). Our data demonstrate balanced cellulose and callose biosynthesis during plant immune responses.

Optimization Design of MK-GGBS Based Geopolymer Repairing Mortar Based on Response Surface Methodology.

There are several influencing factors in the preparation of MK (metakaolin)-GGBS (ground granulated blast furnace slag)-based geopolymer repair mortars, including the MK-GGBS ratio, the alkalinity of the alkali activator solution, the modulus of the alkali activator solution, and the water-to-solid ratio. There are interactions between these factors, such as the different alkaline and modulus requirements of MK and GGBS, the interaction between the alkaline and modulus of the alkali activator solution, and the influence of water throughout the process. The effect of these interactions on the geopolymer repair mortar is not fully understood, making optimization of the MK-GGBS repair mortar ratio difficult. Therefore, in this paper, the response surface methodology (RSM) was used to optimize the preparation of the repair mortar, with GGBS content, SiO2/Na2O molar ratio, Na2O/binder ratio, and water/binder ratio as influencing factors and 1 d compressive strength, 1 d flexural strength, and 1 d bond strength as evaluation indices. Additionally, the repair mortar's overall performance was assessed in terms of setting time, long-term compressive and bond strength, shrinkage, water absorption, and efflorescence. The results show that RSM was successful in establishing a relationship between the repair mortar's properties and the factors. The recommended values of the GGBS content, Na2O/binder ratio, SiO2/Na2O molar ratio, and water/binder ratio are 60%, 10.1%, 1.19, and 0.41, respectively. The optimized mortar meets the standard's requirements for set time, water absorption, shrinkage values, and mechanical strength, with minimal visual efflorescence. The back-scattered electron (BSE) images and energy dispersive spectroscopy (EDS) analysis show that the geopolymer and cement have good interfacial adhesion, and a denser interfacial transition zone exists in the optimized proportion.

Molecular condensation and mechanoregulation of plant class I formin, an integrin-like actin nucleator.

The actin cytoskeleton (AC) undergoes rapid remodelling to coordinate cellular processes during signal transduction, including changes in actin nucleation, crosslinking, and depolymerization in a time- and space-dependent manner. Switching the initial actin nucleation often provides timely control of the entire actin network formation. Located at the cell surface, the plant class I formin family is a major class of actin nucleators that rapidly respond to exterior chemical and environmental cues. Plant class I formins are structurally integrated within the plant cell wall-plasma membrane-actin cytoskeleton (CW-PM-AC) continuum, sharing similar biophysical properties to mammalian integrins that are embedded within the extracellular matrix-PM-AC continuum. In plants, perturbation of structural components of the CW-PM-AC continuum changes the biophysical properties of two dimensional-scaffolding structures, which results in uncontrolled molecular diffusion and interactions of class I formins, as well as their clustering and activities in the nucleation of the AC. Emerging studies have shown that the PM-integrated formins are highly responsive to the mechanical perturbation of CW and AC integrity changes that tune the oligomerization and condensation of formin on the cell surface. However, during diverse signalling transductions, the molecular mechanisms that spatiotemporally underlie the mechanosensing and mechanoregulation of formin for remodelling actin remain unclear. Here, the emphasis will be placed on recent developments in understanding how the molecular condensation of class I formin regulates the biochemical activities in tuning actin polymerization during plant immune signalling, as well as how the plant structural components of the CW-PM-AC continuum control formin condensation at a nanometre scale.

Identification of immune subtypes and their prognosis and molecular implications in colorectal cancer.

Immune composition is commonly heterogeneous and varies among colorectal cancer (CRC) patients. A comprehensive immune classification may act as important characteristics to predict CRC prognosis. Thus, we aimed to identify novel immune specific subtypes to guide future therapies. Unsupervised clustering was used to classify CRC samples into different immune subtypes based on abundances of immune cell populations, during which TCGA and GSE17536 datasets were used as training and validation sets, respectively. The associations between the immune subtypes and patient prognosis were investigated. Further, we identified differentially expressed genes (DEGs) between immune high and low subtypes, followed by functional enrichment analyses of DEGs. The expression levels of 74 immunomodulators (IMs) across immune subtypes were analyzed. As a result, we clustered CRC samples into three distinct immune subtypes (immune high, moderate, and low). Patients with immune-high subtype showed the best prognosis, and patients with immune-low subtype had the worst survival in both TCGA and GSE17536 cohorts. A group of 2735 up-regulated DEGs were identified across immune high and low subtypes. The main DEGs were the members of complement components, chemokines, immunoglobulins, and immunosuppressive genes that are involved in immune modulation-related pathways (e.g., cytokine-cytokine receptor interaction) or GO terms (e.g., adaptive immune response and T cell activation). The expression levels of 63 IMs were significantly varied across immune subtypes. In conclusion, this study provides a conceptual framework and molecular characteristics of CRC immune subtypes, which may accurately predict prognosis and offer novel targets for personalized immunotherapy through modifying subtype-specific tumor immune microenvironment.

Stochastic Lag Time Parameterization for Markov State Models of Protein Dynamics.

Markov state models (MSMs) play a key role in studying protein conformational dynamics. A sliding count window with a fixed lag time is widely used to sample sub-trajectories for transition counting and MSM construction. However, sub-trajectories sampled with a fixed lag time may not perform well under different selections of lag time, which requires strong prior practice and leads to less robust estimation. To alleviate it, we propose a novel stochastic method from a Poisson process to generate perturbative lag time for sub-trajectory sampling and utilize it to construct a Markov chain. Comprehensive evaluations on the double-well system, WW domain, BPTI, and RBD-ACE2 complex of SARS-CoV-2 reveal that our algorithm significantly increases the robustness and power of a constructed MSM without disturbing the Markovian properties. Furthermore, the superiority of our algorithm is amplified for slow dynamic modes in complex biological processes.

Perineural invasion-associated biomarkers for tumor development.

Perineural invasion (PNI) is the process of neoplastic invasion of peripheral nerves and is considered to be the fifth mode of cancer metastasis. PNI has been detected in head and neck tumors and pancreatic, prostate, bile duct, gastric, and colorectal cancers. It leads to poor prognostic outcomes and high local recurrence rates. Despite the increasing number of studies on PNI, targeted therapeutic modalities have not been proposed. The identification of PNI-related biomarkers would facilitate the non-invasive and early diagnosis of cancers, the establishment of prognostic panels, and the development of targeted therapeutic approaches. In this review, we compile information on the molecular mediators involved in PNI-associated cancers. The expression and prognostic significance of molecular mediators and their receptors in PNI-associated cancers are analyzed, and the possible mechanisms of action of these mediators in PNI are explored, as well as the association of cells in the microenvironment where PNI occurs.

Dual control of formin-nucleated actin assembly by the chromatin and ER in mouse oocytes.

The first asymmetric meiotic cell divisions in mouse oocytes are driven by formin 2 (FMN2)-nucleated actin polymerization around the spindle. In this study, we investigated how FMN2 is recruited to the spindle peripheral ER and how its activity is regulated in mouse meiosis I (MI) oocytes. We show that this process is regulated by the Ran GTPase, a conserved mediator of chromatin signal, and the ER-associated protein VAPA. FMN2 contains a nuclear localization sequence (NLS) within a domain (SLD) previously shown to be required for FMN2 localization to the spindle periphery. FMN2 NLS is bound to the importin α1/ß complex, and the disruption of this interaction by RanGTP is required for FMN2 accumulation in the area proximal to the chromatin and the MI spindle. The importin-free FMN2 is then recruited to the surface of ER around the spindle through the binding of the SLD with the ER-membrane protein VAPA. We further show that FMN2 is autoinhibited through an intramolecular interaction between the SLD with the C-terminal formin homology 2 (FH2) domain that nucleates actin filaments. VAPA binding to SLD relieves the autoinhibition of FMN2, leading to localized actin polymerization. This dual control of formin-mediated actin assembly allows actin polymerization to initiate the movement of the meiotic spindle toward the cortex, an essential step in the maturation of the mammalian female gamete.

Biomarker Assessment of Homologous Recombination Deficiency in Epithelial Ovarian Cancer: Association With Progression-Free Survival After Surgery.

Identifying BRCA mutations and homologous recombination deficiency (HRD) is the key to choosing patients for poly (ADP-ribose) polymerase inhibitor (PARPi) therapy. At present, a large amount of research focuses on the application of HRD detection in ovarian cancer. However, few studies have discussed the relationship between HRD detection and postoperative survival in patients with epithelial ovarian cancer (EOC). This study included 38 consecutive patients with EOC who underwent cytoreduction surgery. Owing to tissue availability, only 29 patients underwent molecular profiling and survival analysis. Overall, 21 (72.4%) tumors had HRD scores of ≥42. Mutations in BRCA were observed in 5/29 (17.2%) patients. In this cohort, an HRD score of ≥42 was more common in serous ovarian tumors. We found no statistically significant association between homologous recombination repair (HRR) genes and HRD scores except for tumor protein P53 (TP53) mutation. We also found a strong positive association between HRD scores and chromosomal instability (CIN). In the survival analysis, an HRD score of >23 was correlated with better postoperative progression-free survival (pPFS). With increased depth of research, an appropriate HRD score threshold may serve as a prognostic tool and should be assessed in future studies to predict the clinical value of PARPi.

[Retracted] MicroRNA­663 inhibits the proliferation, migration and invasion of glioblastoma cells via targeting TGF­ß1.

Subsequently to the publication of the above article, an interested reader drew to the Editor's attention that they had identified several instances of overlapping data panels comparing between the scratch­wound assay data ('36 h' experiments) portrayed in Figs. 3 and 8; furthermore, there appeared to be an overlap in a pair of the data panels shown for the Transwell assay experiments with U87 cells in Fig. 9 (albeit with an inversion of one of the panels), such that these data may have been derived from the same original source, even though they were purportedly intended to show the results from differently performed experiments. Given the multiple instances of overlapping data panels that have been identified in the compilation of the figures in this article, the Editor of Oncology Reports has decided that this article should be retracted from the publication on account of a lack of overall confidence in the presented data. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive any reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 35: 1125­1134, 2016; DOI: 10.3892/or.2015.4432].

Coassembly of a New Insect Cuticular Protein and Chitosan via Liquid-Liquid Phase Separation.

Insect cuticle is a fiber-reinforced composite material that consists of polysaccharide chitin fibers and a protein matrix. The molecular interactions between insect cuticle proteins and chitin that govern the assembly and evolution of cuticles are still not well understood. Herein, we report that Ostrinia furnacalis cuticular protein hypothetical-1 (OfCPH-1), a newly discovered and most abundant cuticular protein from Asian corn borer O. furnacalis, can form coacervates in the presence of chitosan. The OfCPH-1-chitosan coacervate microdroplets are initially liquid-like but become gel-like with increasing time or salt concentration. The liquid-to-gel transition is driven by hydrogen-bonding interactions, during which an induced ß-sheet structure of OfCPH-1 is observed. Given the abundance of OfCPH-1 in the cuticle of O. furnacalis, this liquid-liquid phase separation process and its aging behavior could play critical roles in the formation of the cuticle.

Antifungal effects of alantolactone on Candida albicans: An in vitro study.

The human fungal pathogen Candida albicans can cause many kinds of infections, including biofilm infections on medical devices, while the available antifungal drugs are limited to only a few. In this study, alantolactone (Ala) demonstrated antifungal activities against C. albicans, as well as other Candida species, with a MIC of 72 µg/mL. Ala could also inhibit the adhesion, yeast-to-hyphal transition, biofilm formation and development of C. albicans. The exopolysaccharide of biofilm matrix and extracellular phospholipase production could also be reduced by Ala treatment. Ala could increase permeability of C. albicans cell membrane and ROS contribute to the anti-biofilm activity of Ala. Overall, the present study suggests that Ala may provide a promising candidate for developing antifungal drugs against C. albicans infections.

Mutation profiling of circulating tumor DNA identifies distinct mutation patterns in non-Hodgkin lymphoma.

OBJECTIVE: Circulating tumor DNA (ctDNA) is emerging as a versatile biomarker for noninvasive genotyping and response monitoring in specific B-cell lymphomas; however, few studies have been conducted to explore ctDNA-based mutation profiling across non-Hodgkin lymphomas (NHLs) and genomic changes after initiation of chemotherapy. METHODS: A targeted sequencing of 362 genes was performed to detect the mutation profiles in paired blood and tissue samples from 42 NHL patients. Genomic alterations were explored in 11 diffuse large B-cell lymphoma (DLBCL) patients using paired blood samples collected pre- and post-R-CHOP chemotherapy. RESULTS: The frequencies of PIM1, MYD88, MYC, ZNF292, JAK, and MAF mutations were higher in aggressive than in indolent B-cell lymphoma and NK/T subtypes. Tumor mutation burden in blood samples was higher in aggressive than in indolent B-cell lymphomas and higher in patients who progressed than in those who responded to treatments. Our data also revealed significant enhance of concordance index through integrating mutated genes that were significantly associated with prognosis into International Prognostic Index-based prognostic model. Moreover, acquisition of mutations such as PCLO_p.L1220Tfs*3 was associated with resistance to R-CHOP in DLBCL patients. CONCLUSIONS: Our findings illustrated distinct mutation patterns across various NHL subtypes and suggested the association of genomic alterations in ctDNA with treatment outcomes.

Potentiation of plant defense by bacterial outer membrane vesicles is mediated by membrane nanodomains.

Outer membrane vesicles (OMVs) are released from the outer membranes of Gram-negative bacteria during infection and modulate host immunity during host-pathogen interactions. The mechanisms by which OMVs are perceived by plants and affect host immunity are unclear. Here, we used the pathogen Xanthomonas campestris pv. campestris to demonstrate that OMV-plant interactions at the Arabidopsis thaliana plasma membrane (PM) modulate various host processes, including endocytosis, innate immune responses, and suppression of pathogenesis by phytobacteria. The lipid phase of OMVs is highly ordered and OMVs directly insert into the Arabidopsis PM, thereby enhancing the plant PM's lipid order; this also resulted in strengthened plant defenses. Strikingly, the integration of OMVs into the plant PM is host nanodomain- and remorin-dependent. Using coarse-grained simulations of molecular dynamics, we demonstrated that OMV integration into the plant PM depends on the membrane lipid order. Our computational simulations further showed that the saturation level of the OMV lipids could fine-tune the enhancement of host lipid order. Our work unraveled the mechanisms underlying the ability of OMVs produced by a plant pathogen to insert into the host PM, alter host membrane properties, and modulate plant immune responses.

Membrane nanodomains modulate formin condensation for actin remodeling in Arabidopsis innate immune responses.

The assembly of macromolecules on the plasma membrane concentrates cell surface biomolecules into nanometer- to micrometer-scale clusters (nano- or microdomains) that help the cell initiate or respond to signals. In plant-microbe interactions, the actin cytoskeleton undergoes rapid remodeling during pathogen-associated molecular pattern-triggered immunity (PTI). The nanoclustering of formin-actin nucleator proteins at the cell surface has been identified as underlying actin nucleation during plant innate immune responses. Here, we show that the condensation of nanodomain constituents and the self-assembly of remorin proteins enables this mechanism of controlling formin condensation and activity during innate immunity in Arabidopsis thaliana. Through intrinsically disordered region-mediated remorin oligomerization and formin interaction, remorin gradually recruits and condenses formins upon PTI activation in lipid bilayers, consequently increasing actin nucleation in a time-dependent manner postinfection. Such nanodomain- and remorin-mediated regulation of plant surface biomolecules is expected to be a general feature of plant innate immune responses that creates spatially separated biochemical compartments and fine tunes membrane physicochemical properties for transduction of immune signals in the host.