Interference of ATP-Adenosine Axis by Engineered Biohybrid for Amplifying Immunogenic Cell Death-Mediated Antitumor Immunotherapy.

Immunogenic cell death (ICD) often results in the production and accumulation of adenosine (ADO), a byproduct that negatively impacts the therapeutic effect as well as facilitates tumor development and metastasis. Here, an innovative strategy is elaborately developed to effectively activate ICD while avoiding the generation of immunosuppressive adenosine. Specifically, ZIF-90, an ATP-responsive consumer, is synthesized as the core carrier to encapsulate AB680 (CD73 inhibitor) and then coated with an iron-polyphenol layer to prepare the ICD inducer (AZTF), which is further grafted onto prebiotic bacteria via the esterification reaction to obtain the engineered biohybrid (Bc@AZTF). Particularly, the designed Bc@AZTF can actively enrich in tumor sites and respond to the acidic tumor microenvironment to offload AZTF nanoparticles, which can consume intracellular ATP (iATP) content and simultaneously inhibit the ATP-adenosine axis to reduce the accumulation of adenosine, thereby alleviating adenosine-mediated immunosuppression and strikingly amplifying ICD effect. Importantly, the synergy of anti-PD-1 (αPD-1) with Bc@AZTF not only establishes a collaborative antitumor immune network to potentiate effective tumoricidal immunity but also activates long-lasting immune memory effects to manage tumor recurrence and rechallenge, presenting a new paradigm for ICD treatment combined with adenosine metabolism.

Exact Analytical Algorithm for the Solvent-Accessible Surface Area and Derivatives in Implicit Solvent Molecular Simulations on GPUs.

In this paper, we present differentiable solvent-accessible surface area (dSASA), an exact geometric method to calculate SASA analytically along with atomic derivatives on GPUs. The atoms in a molecule are first assigned to tetrahedra in groups of four atoms by Delaunay tetrahedralization adapted for efficient GPU implementation, and the SASA values for atoms and molecules are calculated based on the tetrahedralization information and inclusion-exclusion method. The SASA values from the numerical icosahedral-based method can be reproduced with >98% accuracy for both proteins and RNAs. Having been implemented on GPUs and incorporated into AMBER, we can apply dSASA to implicit solvent molecular dynamics simulations with the inclusion of this nonpolar term. The current GPU version of GB/SA simulations has been accelerated up to nearly 20-fold compared to the CPU version, outperforming LCPO, a commonly used, fast algorithm for calculating SASA, as the system size increases. While we focus on the accuracy of the SASA calculations for proteins and nucleic acids, we also demonstrate stable GB/SA MD mini-protein simulations.

In Situ Formed Microalgae-Integrated Living Hydrogel for Enhanced Tumor Starvation Therapy and Immunotherapy through Photosynthetic Oxygenation.

The effectiveness of various cancer therapies for solid tumors is substantially limited by the highly hypoxic tumor microenvironment (TME). Here, a microalgae-integrated living hydrogel (ACG gel) is developed to concurrently enhance hypoxia-constrained tumor starvation therapy and immunotherapy. The ACG gel is formed in situ following intratumoral injection of a biohybrid fluid composed of alginate, Chlorella sorokiniana, and glucose oxidase, facilitated by the crossing-linking between divalent ions within tumors and alginate. The microalgae Chlorella sorokiniana embedded in ACG gel generate abundant oxygen through photosynthesis, enhancing glucose oxidase-catalyzed glucose consumption and shifting the TME from immunosuppressive to immunopermissive status, thus reducing the tumor cell energy supply and boosting antitumor immunity. In murine 4T1 tumor models, the ACG gel significantly suppresses tumor growth and effectively prevents postoperative tumor recurrence. This study, leveraging microalgae as natural oxygenerators, provides a versatile and universal strategy for the development of oxygen-dependent tumor therapies.

Exact analytical algorithm for solvent accessible surface area and derivatives in implicit solvent molecular simulations on GPUs.

In this paper, we present dSASA (differentiable SASA), an exact geometric method to calculate solvent accessible surface area (SASA) analytically along with atomic derivatives on GPUs. The atoms in a molecule are first assigned to tetrahedra in groups of four atoms by Delaunay tetrahedrization adapted for efficient GPU implementation and the SASA values for atoms and molecules are calculated based on the tetrahedrization information and inclusion-exclusion method. The SASA values from the numerical icosahedral-based method can be reproduced with more than 98% accuracy for both proteins and RNAs. Having been implemented on GPUs and incorporated into the software Amber, we can apply dSASA to implicit solvent molecular dynamics simulations with inclusion of this nonpolar term. The current GPU version of GB/SA simulations has been accelerated up to nearly 20-fold compared to the CPU version, outperforming LCPO, a commonly used, fast algorithm for calculating SASA, as the system size increases. While we focus on the accuracy of the SASA calculations for proteins and nucleic acids, we also demonstrate stable GB/SA MD mini-protein simulations.

Relationship between ankle pain, range of motion, strength and balance in individuals with functional ankle instability: a cross-sectional study.

BACKGROUND: About 15-60% of individuals with ankle sprains may develop functional ankle instability (FAI), which is characterised by ankle pain, decreased muscle strength, limited range of motion, and impaired balance, causing a decline in social activity and quality of life. However, the relationship between those characters is still unclear. This study aimed to investigate whether a relationship existed between ankle pain, active range of motion (AROM), strength and balance and if ankle pain, AROM and strength can predict balance in individuals with FAI. METHODS: Seventy-seven subjects (46 males; 31 females) with unilateral FAI participated in this study. Ankle pain was measured by the visual analogue scale (VAS), ankle AROM was measured using a universal goniometer, ankle strength was measured using a handheld dynamometer, the static balance was measured by the Time in Balance Test (TBT) and the dynamic balance was measured by the modified Star Excursion Balance Test (mSEBT). Pearson product-moment correlations were used to determine the correlations between ankle pain, AROM, strength and balance. Multiple linear regressions were used to investigate if ankle pain, AROM and strength can predict balance in individuals with FAI. RESULTS: VAS and AROM-plantarflexion predicted 25.6% of the TBT (f2 = 0.344, P < 0.001). AROM-dorsiflexion predicted 24.6% of the mSEBT-anterior reach (f2 = 0.326, P < 0.001). VAS, AROM-plantarflexion and strength-plantarflexion predicted 33.5% of the mSEBT-posteromedial reach (f2 = 0.504, P < 0.001). AROM-plantarflexion and strength-plantarflexion predicted 28.2% of the mSEBT-posterolateral reach (f2 = 0.393, P < 0.001). CONCLUSION: This study shows that ankle plantarflexion strength, AROM of dorsiflexion and plantarflexion and pain are predictors of balance in individuals with FAI. These factors could be considered in the rehabilitation of FAI. TRIAL REGISTRATION: Trial registration number: ChiCTR2200063532.

Adaptability of water resources development and utilization to social-economy system in Hunan province, China.

The interplay of water resources with social-economy spheres involves a reciprocal feedback mechanism. With the acceleration of the construction process of modernized water networks in Hunan Province, investigating the adaptation status of the "Water-Social-Economy " composite system (WSE) is crucial for promoting sustainability. This study clarifies the connotation of the adaptability of WSE, and the quantitative analyses were conducted through coupling coordinative degree, harmonious development capacity, and the evolution of development lag types among the 14 cities of Hunan Province from 2005 to 2020. The results show that: (1) The development index of the water resources subsystem (WRS) showed a "downward-fluctuation-upward" trend, while the development index of the social-economy subsystem (SES) showed signs of great improvement, the former didn't catch up with the latter. (2) The coupling coordination degree of WSE developed well, and reached the coordinative development stage by 2020, but the unbalanced spatial pattern between north to south and east to west still exists and is further intensified. (3) The development ability of WSE improved while the harmony ability reduced, and the development rate of WRS and SES hasn't achieved dynamic synchronization. Finally, the policies and suggestions to improve the adaptability are put forward, which is of instructive significance for the sustainable development of water suitability.

Scanning Probe Lithography: State-of-the-Art and Future Perspectives.

High-throughput and high-accuracy nanofabrication methods are required for the ever-increasing demand for nanoelectronics, high-density data storage devices, nanophotonics, quantum computing, molecular circuitry, and scaffolds in bioengineering used for cell proliferation applications. The scanning probe lithography (SPL) nanofabrication technique is a critical nanofabrication method with great potential to evolve into a disruptive atomic-scale fabrication technology to meet these demands. Through this timely review, we aspire to provide an overview of the SPL fabrication mechanism and the state-the-art research in this area, and detail the applications and characteristics of this technique, including the effects of thermal aspects and chemical aspects, and the influence of electric and magnetic fields in governing the mechanics of the functionalized tip interacting with the substrate during SPL. Alongside this, the review also sheds light on comparing various fabrication capabilities, throughput, and attainable resolution. Finally, the paper alludes to the fact that a majority of the reported literature suggests that SPL has yet to achieve its full commercial potential and is currently largely a laboratory-based nanofabrication technique used for prototyping of nanostructures and nanodevices.

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket.

The SARS-CoV-2 coronavirus is an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell and is the primary target of neutralizing antibodies. The receptor binding domain (RBD) of the spike samples multiple conformations in a compromise between evading immune recognition and searching for the host-cell surface receptor. Using atomistic simulations of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we map the free energy landscape for RBD opening and identify interactions in an allosteric pocket that influence RBD dynamics. The results provide an explanation for experimental observation of increased antibody binding for a clinical variant with a substitution in this pocket. Our results also suggest the possibility of allosteric targeting of the RBD equilibrium to favor open states via binding of small molecules to the hinge pocket. In addition to potential value as experimental probes to quantify RBD conformational heterogeneity, small molecules that modulate the RBD equilibrium could help explore the relationship between RBD opening and S1 shedding.

The flexibility of ACE2 in the context of SARS-CoV-2 infection.

The coronavirus disease 2019 (COVID-19) pandemic has swept over the world in the past months, causing significant loss of life and consequences to human health. Although numerous drug and vaccine development efforts are underway, there are many outstanding questions on the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral association to angiotensin-converting enzyme 2 (ACE2), its main host receptor, and host cell entry. Structural and biophysical studies indicate some degree of flexibility in the viral extracellular spike glycoprotein and at the receptor-binding domain (RBD)-receptor interface, suggesting a role in infection. Here, we perform explicitly solvated, all-atom, molecular dynamics simulations of the glycosylated, full-length, membrane-bound ACE2 receptor in both an apo and spike RBD-bound state to probe the intrinsic dynamics of the ACE2 receptor in the context of the cell surface. A large degree of fluctuation in the full-length structure is observed, indicating hinge bending motions at the linker region connecting the head to the transmembrane helix while still not disrupting the ACE2 homodimer or ACE2-RBD interfaces. This flexibility translates into an ensemble of ACE2 homodimer conformations that could sterically accommodate binding of the spike trimer to more than one ACE2 homodimer and suggests a mechanical contribution of the host receptor toward the large spike conformational changes required for cell fusion. This work presents further structural and functional insights into the role of ACE2 in viral infection that can potentially be exploited for the rational design of effective SARS-CoV-2 therapeutics.

ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution.

Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.

Recognition of polymer configurations by unsupervised learning.

Unsupervised learning as an important branch of machine learning is commonly adopted to discover patterns, with the purpose of conducting data clustering without being labeled in advance. In this study, we elucidate the striking ability of unsupervised learning techniques in exploring the phase transitions of polymer configurations. In order to extract the low-dimensional representation of polymer configurations, principal component analysis and diffusion map are applied to distinguish the coiled state and collapsed states and further detect the delicate distinction among collapsed states, respectively. These dimensionality reduction techniques not only identify the distinct states in the feature space, but also offer significant insights to understand the relation between salient features and order parameters in physics. In addition, a hybrid neural network scheme combining the supervised learning and unsupervised learning is utilized to precisely detect the critical point of phase transition between polymer configurations. Our study demonstrates a promising strategy based on the unsupervised learning, particularly in the exploration of phase transition in polymeric systems.

A novel AFM-based 5-axis nanoscale machine tool for fabrication of nanostructures on a micro ball.

This paper presents a novel atomic force microscopy (AFM)-based 5-axis nanoscale machine tool developed to fabricate nanostructures on different annuli of the micro ball. Different nanostructures can be obtained by combining the scratching trajectory of the AFM tip with the movement of the high precision air-bearing spindle. The center of the micro ball is aligned to be coincided with the gyration center of the high precision to guarantee the machining process during the rotating of the air-bearing spindle. Processing on different annuli of the micro ball is achieved by controlling the distance between the center of the micro ball and the rotation center of the AFM head. Nanostructures including square cavities, circular cavities, triangular cavities, and an annular nanochannel are machined successfully on the three different circumferences of a micro ball with a diameter of 1500 µm. Moreover, the influences of the error motions of the high precision air-bearing spindle and the eccentric between the micro ball and the gyration center of the high precision air-bearing spindle on the processing position error on the micro ball are also investigated. This proposed machining method has the potential to prepare the inertial confinement fusion target with the expected dimension defects, which would advance the application of the AFM tip-based nanomachining approach.

Leaf patterning of Clivia miniata var. variegata is associated with differential DNA methylation.

KEY MESSAGE: Leaf patterns (yellow, green and striped) of Clivia miniata var. variegata might be caused by differential DNA methylation in CCGG sites in response to heterogeneous environmental pressure. Clivia miniata is an important ornamental plant.Clivia miniata var. variegata (Cmvv) is a variegated leaf mutant of C. miniata. Typical Cmvv has attractive green and yellow-stripped leaves. The study has revealed that an explant of Cmvv, even a full-green explant, could regenerate plants of three different types: yellow, green, ands triped; normal-appearing chloroplasts were found in guard cells but not in mesophyll cells of all the three types of Cmvv using confocal laser scanning microscopy (CLSM).Thus, we speculated that cells of the three types of Cmvv had an identical mutation and the mutation might disturb mesophyll cell chloroplast biogenesis after symplastic isolation of guard cells. Using CLSM and methylation sensitive amplification polymorphism (MSAP), we found that (a) striped leaves of Cmvv are due to sectorial decreases in chlorophyll levels and the decreases are associated with CG hypermethylation; (b) extent of epigenetic divergence among the three types of Cmvv leaves is positively correlated with intensity of leaf-color difference; and (c) green stripes of two plants are clustered in one group based on the MSAP profiles, but green and yellow stripes of a plant are not. Sequencing analysis indicated that CG hypermethylation in gene bodies of CPSAR1 and ycf2 might lead to gene silencing and yellow leaves/stripes of Cmvv. All together, it is possible that cytosine methylation involved regulating leaf color of Cmvv, also striped pattern of Cmvv might be caused by differential DNA methylation in response to heterogeneous environmental pressure. Furthermore, a novel leaf-color epigenetic hypothesis was proposed in this article.

Direct and indirect organogenesis of Clivia miniata and assessment of DNA methylation changes in various regenerated plantlets.

UNLABELLED: Clivia miniata is an important indoor ornamental plant and has been reported to have medicinal value. We developed an efficient in vitro micropropagation protocol from young leaves (indirect organogenesis), young petals (indirect organogenesis) and shoot tips (direct organogenesis) of this plant. Using young leaves and shoot tips as explants, the regeneration frequencies were much higher than those in previous investigation and the regeneration was dependent upon less nutrition. We speculated that the leaf-derived callus can generate amino acids necessary for protein synthesis by itself. We employed the methylation-sensitive amplified polymorphism (MSAP) method to assess cytosine methylation variation in various regenerated plantlets and between organs. The MSAP profiles indicated that the frequency of somaclonal variation in the form of cytosine methylation was highest in petal-derived plantlets followed by secondary leaf-derived, primary leaf-derived and shoot tip-derived plantlets, but the methylation variation in petal-derived plantlets was lower than between petals and leaves of a single plant. The results indicated that the methylation variation in regenerated plantlets was related to the types of explants, regeneration pathways and number of regeneration generations. Two possible factors for the highest somaclonal variation rate in petal-derived plantlets are the callus phase and petal-specific set of epigenetic regulators. The property of meristem integrity can account for the lowest variation rate in shoot tip-derived plantlets. Moreover, the secondary plantlets underwent a longer total period of in vitro culture, which can explain why the methylation variation rate in the secondary plantlets is higher than in the primary ones. KEY MESSAGE: Methylation variation in regenerated plantlets of C. miniata was found to be related to the types of explants, regeneration pathways and number of regeneration generations.