Characterizing the Behavior of Water Interacting with a Nano-Pore Material: A Structural Investigation in Native Environment Using Magnetic Resonance Approaches.

The study of fluid absorption, particularly that of water, into nanoporous materials has garnered increasing attention in the last decades across a broad range of disciplines. However, most investigation approaches to probe such behaviors are limited by characterization conditions and may lead to misinterpretations. In this study, a combined MRI and MAS NMR method was used to study a nanoporous silica glass to acquire information about its structural framework and interactions with confined water in a native humid environment. Specifically, MRI was used for a quantitative analysis of water extent. While MAS NMR techniques provided structural information of silicate materials, including interactive surface area and framework packing. Analysis of water spin-spin relaxation times (T2) suggested differences in water confinement within the characterized framework. Subsequent unsuccessful delivery of paramagnetic molecule into the pores enabled a quantitative assessment of the dimensions that "bottleneck" the pores. Finally, pore sizes were derived from the paramagnetic molecular size, density function theory (DFT) simulation and characterizations on standard samples. Our result matches with Brunauer-Emmett-Teller (BET) analysis that the pore size is less than 1.3 nm. The use of a paramagnetic probe for pore size determination introduces a new approach of characterization in the liquid phase, offering an alternative to the conventional BET analysis that uses gas molecule as probes.

An efficient and universal parallel algorithm for high-dimensional quantum dynamics in poly-atomic reactions.

This study presents a parallel algorithm for high-dimensional quantum dynamics simulations in poly atomic reactions, integrating distributed- and shared-memory models. The distributions of the wave function and potential energy matrix across message passing interface processes are based on bundled radial and angular dimensions, with implementations featuring either two- or one-sided communication schemes. Using realistic parameters for the H + NH3 reaction, performance assessment reveals linear scalability, exceeding 90% efficiency with up to 600 processors. In addition, owing to the universal and concise structure, the algorithm demonstrates remarkable extensibility to diverse reaction systems, as demonstrated by successes with six-atom and four-atom reactions. This work establishes a robust foundation for high-dimensional dynamics studies, showcasing the algorithm's efficiency, scalability, and adaptability. The algorithm's potential as a valuable tool for unraveling quantum dynamics complexities is underscored, paving the way for future advancements in the field.

Identification of biomimetic nanoplatform-mediated delivery of si-ISG15 for treatment of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is recognized as the most malicious form of breast cancer and exhibits an alarming tendency for recurrence, a heightened propensity for metastasis, and an overwhelmingly grim prognosis. Therefore, effective therapy approaches for TNBC are urgently required. In this study, the interferon-stimulated gene 15 (ISG15) expression level was analyzed by bioinformatics and verified by Western blot analysis. The effects of ISG15 on the proliferation and metastasis of TNBC cells were assessed using MTT, Colony formation, EdU, Transwell, and Flow cytometry assays. We also developed a cancer cell-biomimetic nanoparticle delivery system and evaluated its therapeutic efficacy in vivo. In this study, we reported that ISG15 was upregulated in TNBC, and its high expression level correlated with an increased risk of tumorigenesis. Through in vitro and in vivo studies, we discovered that ISG15 knockdown drastically suppressed cell proliferation, invasion, and migration and induced apoptosis in TNBC cells. Our findings revealed that ISG15 was a candidate therapeutic target in TNBC because of its key role in malignant growth and invasion. Moreover, co-immunoprecipitation showed that ISG15 exerted oncogenic functions through its interaction with ATP binding cassette subfamily E member 1 and activated the Janus kinase/signal transducers and activators of the transcription signaling pathway. Furthermore, we created a nanoparticle-based siRNA camouflaged using a cancer cell membrane vesicle delivery system (the CM@NP complex) and confirmed its therapeutic effects in vivo. Our findings confirmed that ISG15 may play a pivotal oncogenic role in the development of TNBC and that CM@siRNA-NP complexes are an effective delivery system and a novel biological strategy for treating TNBC.

Revisiting ultrasmall phosphine-stabilized rhodium-doped gold clusters AunRh (n = 5, 6, 7, 8): geometric, electronic, and vibrational properties.

Incorporation of other transition metals in Au nanoclusters has been thriving recently due to its effect on their electronic and photophysical properties. Here, the ultrasmall phosphine-stabilized Rh-doped gold clusters AunRh (n = 5, 6, 7, 8), with metal core structures represented as fragments of a rhodium-centered icosahedron, are considered. The geometric and electronic properties of these nanoclusters are revisited and analyzed using density functional theory (DFT). Moreover, infrared spectra are simulated to identify the effects of Rh doping on the clusters through vibrational properties. Peaks are assigned to breathing-like normal modes for all AuRh clusters except for Au8Rh, likely due to the presence of bound Cl ligands. Unlike their pure gold core counterparts, the % motions of both Au and Rh atoms are lower in the mixed metal clusters, suggesting more restrained metal cores by rhodium, which could result in other novel physical and chemical properties not hitherto discovered.

Facilitating mitigation of agricultural non-point source pollution and improving soil nutrient conditions: The role of low temperature co-pyrolysis biochar in nitrogen and phosphorus distribution.

The current study generated co-pyrolysis biochar by pyrolyzing rice straw and pig manure at 300 °C and subsequently applying it in a field. Co-pyrolysis biochar demonstrated superior efficiency in mitigating agricultural non-point source pollution compared to biochar derived from individual sources. Furthermore, it displayed notable capabilities in retaining and releasing nutrients, resulting in increased soil levels of total nitrogen, total phosphorus, and organic matter during the maturation stage of rice. Moreover, co-pyrolysis biochar influences soil microbial communities, potentially impacting nutrient cycling. During the rice maturation stage, the soil treated with co-pyrolysis biochar exhibited significant increases in available nutrients and rice yield compared to the control (p < 0.05). These findings emphasize the potential of co-pyrolysis biochar for in-situ nutrient retention and enhanced soil nutrient utilization. To summarize, the co-pyrolysis of agricultural waste materials presents a promising approach to waste management, contributing to controlling non-point source pollution, improving soil fertility, and promoting crop production.

Regulating polystyrene glass transition temperature by varying the hydration levels of aromatic ring/Li+ interaction.

Polymer properties can be altered via lithium ion doping, whereby adsorbed Li+ binds with H2O within the polymer chain. However, direct spectroscopic evidence of the tightness of Li+/H2O binding in the solid state is limited, and the impact of Li+ on polymer sidechain packing is rarely reported. Here, we investigate a polystyrene/H2O/LiCl system using solid-state NMR, from which we determined a dipolar coupling of 11.4 kHz between adsorbed Li+ and H2O protons. This coupling corroborates a model whereby Li+ interacts with the oxygen atom in H2O via charge affinity, which we believe is the main driving force of Li+ binding. We demonstrated the impact of hydrated Li+ on sidechain packing and dynamics in polystyrene using proton-detected solid-state NMR. Experimental data and density functional theory (DFT) simulations revealed that the addition of Li+ and the increase in the hydration levels of Li+, coupled with aromatic ring binding, change the energy barrier of sidechain packing and dynamics and, consequently, changes the glass transition temperature of polystyrene.

In-situ retention of nitrogen, phosphorus in agricultural drainage and soil nutrients by biochar at different temperatures and the effects on soil microbial response.

This study conducted a two-year experiment to investigate the impacts of biochar with various temperatures (350 °C, 500 °C, and 650 °C), on the reduction of pollutants in agricultural runoff and the enhancement of soil fertility. The results showed that the biochar significantly reduced the concentrations of total nitrogen and total phosphorus in farmland runoff. Moreover, higher-temperature biochar demonstrated greater efficacy in decreasing pollutants in farmland drainage. Treatment with RB650 resulted in a reduction of the total nitrogen and total phosphorus output load by 29.31-30.67 % and 21.92-25.21 %, respectively, compared to RB350. Furthermore, biochar exhibited substantial enhancements in soil fertility. This was supported by heightened soil organic matter content, increased availability of nutrients, and a noteworthy (P < 0.05) upsurge in pH, organic matter, total nitrogen, and total phosphorus content observed in the second year following the application of biochar. Biochar has the potential to enhance soil enzyme activity and affect microbial community composition, thereby facilitating nutrient cycling. The findings illustrated the regenerative and recyclable characteristics of biochar's adsorption activity throughout crop growth. This process enables sustained improvement in soil nutrient retention capacity and fertility. Thus, it emphasizes the potential of biochar as an in-situ model for nutrient retention and recycling, offering an effective approach to mitigate agricultural non-point source (NPS) pollution and enhance soil fertility.

Evaluating the Use of Graph Neural Networks and Transfer Learning for Oral Bioavailability Prediction.

Oral bioavailability is a pharmacokinetic property that plays an important role in drug discovery. Recently developed computational models involve the use of molecular descriptors, fingerprints, and conventional machine-learning models. However, determining the type of molecular descriptors requires domain expert knowledge and time for feature selection. With the emergence of the graph neural network (GNN), models can be trained to automatically extract features that they deem important. In this article, we exploited the automatic feature selection of GNN to predict oral bioavailability. To enhance the prediction performance of GNN, we utilized transfer learning by pre-training a model to predict solubility and obtained a final average accuracy of 0.797, an F1 score of 0.840, and an AUC-ROC of 0.867, which outperformed previous studies on predicting oral bioavailability with the same test data set.

Quantitative single-molecule study reveals site-specific photo-oxidation activities and kinetics on 2D g-C3N4.

We report the utilization of single-molecule fluorescence microscopy to in situ quantify the photo-oxidation reaction kinetics on g-C3N4. The wrinkle structure shows the highest reactivity and direct dissociation rate. The basal plane exhibits the highest affinity to reactants and products and indirect dissociation rate constant, followed by edges and wrinkles.

Peptide ARHGEF9 Inhibits Glioma Progression via PI3K/AKT/mTOR Pathway.

Background: The most prevalent malignant tumor in a human brain nervous system is called glioma. Peptide is a compound formed by the peptide bond of α-amino acids, and the development of polypeptide drugs has been widely used in many fields. We plan to investigate the underlying peptides with clinical value in glioma. Method: Based on public databases, we targeted the common genes between glioma differentially expressed genes (DEGs) and peptide genes related to glioma prognosis. Then, these common genes were analyzed by LASSO-Cox analysis, prognostic risk model, and nomogram to identify key prognostic peptide genes and the target gene in this study. Next, the mechanism of target gene in glioma was explored by bioinformatics analysis and functional experiments. Results: We obtained a total of 26 overlapping genes for the following study. After that, 6 independent prognostic factors (REPIN1, PSD3, RDX, CDK4, FANCI, and ARHGEF9) were obtained and applied to construct the prognostic nomogram, and ARHGEF9 was the target gene in the study. Next, peptide ARHGEF9 was found to inhibit glioma cell development. Through Spearman's correlation analysis, ARHGEF9 had a close relation with PI3K/AKT/mTOR pathway. In functional experiments, peptide ARHGEF9 could suppress the protein expressions of p-PIK3K, p-AKT and p-mTOR, while IGF-1 could reverse this effect. Conclusion: This study identifies 6 new prognostic biomarkers for glioma patients. Among them, peptide ARHGEF9 gene is an inhibitory gene functioning by targeting PI3K/AKT/mTOR pathway.

In situ quantitative single-molecule study of site-specific photocatalytic activity and dynamics on ultrathin g-C3N4 nanosheets.

Graphitic carbon nitride (g-C3N4) has attracted extensive research attention in recent years due to its unique layered structure, facile synthetic route, visible-light-responsive nature, and excellent photocatalytic performance. However, an insightful investigation of site-specific catalytic activities and kinetics on g-C3N4 is still warranted. Here, we fabricated ultrathin g-C3N4 nanosheets through thermal exfoliation. The optimized sample exhibits a high specific surface area of 307.35 m2 g-1 and a remarkable H2 generation activity of 2008 µmol h-1 g-1 with an apparent quantum efficiency of 4.62% at λ = 420 nm. Single-molecule fluorescence microscopy was applied for the first time to spatially resolve the reaction heterogeneities with nanometer precision (∼10 nm). The catalytic kinetics (i.e., reactant adsorption, conversion, and product dissociation) and temporal activity fluctuations were in situ quantified at individual structural features (i.e., wrinkles, edges, and basal planes) of g-C3N4. It was found that the wrinkle and edge exhibited superior photocatalytic activity due to the intrinsic band modulation, which are 20 times and 14.8 times that of the basal plane, respectively. Moreover, due to the steric effect, the basal plane showed the highest adsorption constant and the lowest direct dissociation constant. Density functional theory (DFT) simulations unveiled the adsorption energies of reactant and product molecules on each structure of g-C3N4, which support our experimental results. Such investigation would shed more light on the fundamental understanding of site-specific catalytic dynamics on g-C3N4, which benefits the rational design of 2D layered materials for efficient solar-to-chemical energy conversion.

LGB-Stack: Stacked Generalization with LightGBM for Highly Accurate Predictions of Polymer Bandgap.

Recently, the Ramprasad group reported a quantitative structure-property relationship (QSPR) model for predicting the E gap values of 4209 polymers, which yielded a test set R 2 score of 0.90 and a test set root-mean-square error (RMSE) score of 0.44 at a train/test split ratio of 80/20. In this paper, we present a new QSPR model named LGB-Stack, which performs a two-level stacked generalization using the light gradient boosting machine. At level 1, multiple weak models are trained, and at level 2, they are combined into a strong final model. Four molecular fingerprints were generated from the simplified molecular input line entry system notations of the polymers. They were trimmed using recursive feature elimination and used as the initial input features for training the weak models. The output predictions of the weak models were used as the new input features for training the final model, which completes the LGB-Stack model training process. Our results show that the best test set R 2 and the RMSE scores of LGB-Stack at the train/test split ratio of 80/20 were 0.92 and 0.41, respectively. The accuracy scores further improved to 0.94 and 0.34, respectively, when the train/test split ratio of 95/5 was used.

Prophylactic central lymph node dissection performed selectively with cN0 papillary thyroid carcinoma according to a risk-scoring model.

Background: This study aimed to explore the risk factors of central lymph node metastasis (CLNM) in patients with clinical central lymph node-negative papillary thyroid carcinoma (PTC), and emphasize the guidance of the risk scoring model for prophylactic central lymph node dissection (pCLND) in patients with clinical lymph node-negative (cN0) PTC. Methods: A total of 582 patients with cN0 PTC who underwent unilateral/bilateral thyroidectomy and prophylactic central lymph node dissection (pCLND) in the Affiliated Hospital of Nantong University from January 2020 to February 2021 were retrospectively analyzed. Univariate and multivariate analyses were performed to determine the risk factors of cN0 PTC. According to the independent risk factors of patients with cN0 PTC, a risk-scoring model was established. Then, the rationality of this risk scoring model was verified by additional clinical data of 112 patients with cN0 PTC in the Affiliated Hospital of Nantong University from March 2021 to April 2021. Results: Among 582 cases of cN0 PTC, 53.6% of the patients with cN0 had CLNM. The independent risk factors for CLNM in patients with cN0 PTC included male gender, <45 years of age, tumor with a maximum diameter of ≥1.0 cm, tumor location: middle/lower poles of the thyroid gland, multifocality, and extrathyroidal extension (ETE), and some ultrasound features, such as intra-nodular vascularity, microcalcification, irregular shape, and infiltrative margin. According to independent risk factors, a 24-point risk scoring model was established to predict CLNM in patients with cN0 PTC. Conclusions: Currently, prophylactic central neck lymph node dissection is a controversial operation, which should be selectively performed only for high-risk patients with cN0 PTC. For cN0 PTC patients with scores ≥14 and high-risk patients, even if no CLNM is found before surgery, routine prophylactic CLND is recommended. In addition, for cN0 PTC patients with a score of fewer than 14 points, it is recommended to perform fine-needle aspiration (FNA) before surgery, carefully assess the condition of the central lymph nodes, and then select the best surgical plan based on the results of the assessment.

Observing the Fluctuation Dynamics of Dative Bonds Using Two-Dimensional Electronic Spectroscopy.

We perform two-dimensional electronic spectroscopy on chlorophyll (Chl) a and b molecules in aprotic solvents of different Lewis basicity. By analyzing the ultrafast spectral diffusion dynamics of the Qy transition, we show that a certain timescale of the spectral diffusion dynamics is affected by the solvents' Lewis basicity. Control experiments with Chlorin-e6-a Chl molecule analog-and ab initio time-dependent density functional theory calculations confirm that we are directly probing the fluctuation dynamics of the dative bond between the solvent's lone pair and the Mg2+ center in Chls that is responsible for the Lewis basicity. The observation is indicative of dative bond length and angular fluctuations with timescales ranging between ∼30 and 150 ps and the dative bond-strength-dependent perturbation on the Qy transition frequency of Chls.

Different T-cell subsets in glioblastoma multiforme and targeted immunotherapy.

Glioblastoma multiforme (GBM) is a brain tumor with a high mortality rate. Surgical resection combined with radiotherapy and chemotherapy is the standard treatment for GBM patients, but the 5-year survival rate of patients despite this treatment is low. Immunotherapy has attracted increasing attention in recent years. As the pioneer and the main effector cells of immunotherapy, T cells play a key role in tumor immunotherapy. However, the T cells in GBM microenvironment are inhibited by the highly immunosuppressive environment of GBM, posing huge challenges to T cell-based GBM immunotherapy. This review summarizes the effects of the GBM microenvironment on the infiltration and function of different T-cell subsets and the possible strategies to overcome immunosuppression, and thus enhance the effectiveness of GBM immunotherapy.

Catalytic Approach toward Chiral P,N-Chelate Complexes Utilizing the Asymmetric Hydrophosphination Protocol.

A synthetic procedure for obtaining a chiral P,N ligand was developed by exploiting the versatility of the asymmetric hydrophosphination protocol catalyzed by a phosphapalladacycle complex. The addition of the synthesized ligand to various metal sources led to the generation of chiral and enantioenriched chelate complexes, which can be useful prototypes for catalyst design in the future. The resulting coordination compounds were comprehensively characterized by solid-state (X-ray crystallography) and solution-based (one- and two-dimensional NMR spectroscopy) techniques and natural bond orbital (density functional theory) analysis to determine their structural and key electronic features.

Weighted persistent homology for biomolecular data analysis.

In this paper, we systematically review weighted persistent homology (WPH) models and their applications in biomolecular data analysis. Essentially, the weight value, which reflects physical, chemical and biological properties, can be assigned to vertices (atom centers), edges (bonds), or higher order simplexes (cluster of atoms), depending on the biomolecular structure, function, and dynamics properties. Further, we propose the first localized weighted persistent homology (LWPH). Inspired by the great success of element specific persistent homology (ESPH), we do not treat biomolecules as an inseparable system like all previous weighted models, instead we decompose them into a series of local domains, which may be overlapped with each other. The general persistent homology or weighted persistent homology analysis is then applied on each of these local domains. In this way, functional properties, that are embedded in local structures, can be revealed. Our model has been applied to systematically study DNA structures. It has been found that our LWPH based features can be used to successfully discriminate the A-, B-, and Z-types of DNA. More importantly, our LWPH based principal component analysis (PCA) model can identify two configurational states of DNA structures in ion liquid environment, which can be revealed only by the complicated helical coordinate system. The great consistence with the helical-coordinate model demonstrates that our model captures local structure variations so well that it is comparable with geometric models. Moreover, geometric measurements are usually defined in local regions. For instance, the helical-coordinate system is limited to one or two basepairs. However, our LWPH can quantitatively characterize structure information in regions or domains with arbitrary sizes and shapes, where traditional geometrical measurements fail.

Ultrafast dissociative ionization and large-amplitude vibrational wave packet dynamics of strong-field-ionized di-iodomethane.

We employ few-cycle pulses to strong-field-ionize di-iodomethane (CH2I2) and femtosecond extreme ultraviolet (XUV) transient absorption spectroscopy to investigate the subsequent ultrafast dissociative ionization and vibrational wave packet dynamics. Probing in the spectral region of the I 4d core-level transitions, the time-resolved XUV differential absorption spectra reveal the population of several electronic states of CH2I2 + by strong-field ionization. Global analysis reveals three distinct time scales for the observed dynamics: 20 ± 2 fs, 49 ± 6 fs, and 157 ± 9 fs, ascribed to relaxation of the CH2I2 + parent ion from the Franck-Condon region, dissociation of high-lying excited states of CH2I2 + to I+ (3P2), CH2I, and I2 + (2Π3/2,g), and dissociation of CH2I2 + to I (2P3/2) and CH2I+, respectively. Oscillatory features in the time-resolved XUV differential absorption spectra point to the generation of vibrational wave packets in both the residual CH2I2 and the CH2I2 + parent ion. Analysis of the oscillation frequencies and phases reveals, in the case of neutral CH2I2, C-I symmetric stretching induced by bond softening and I-C-I bending driven by a combination of bond softening and R-selective depletion. In the case of CH2I2 +, both the fundamental and first overtone frequencies of the I-C-I bending mode are observed, indicating large-amplitude I-C-I bending motion, in good agreement with results obtained from ab initio simulations of the XUV transition energy along the I-C-I bend coordinate. These results show that femtosecond XUV absorption spectroscopy is well-suited for studying ultrafast photodissociation and vibrational wave packet dynamics.

Metal-Free Fast Azidation by Using Tetrabutylammonium Azide: Effective Synthesis of Alkyl Azides and Well-Defined Azido-End Polymethacrylates.

An effective method to synthesize azido-end polymethacrylates from tetrabutylammonium azide (BNN3 ) in a nonpolar solvent (toluene) was developed. Several low-mass alkyl halides were reacted with BNN3 in toluene as model reactions and the rate constants of these reactions were determined, to confirm fast BNN3 azidation for tertiary and secondary halides. The end-group transformation of halide-end polymethacrylates was effective and nearly quantitative. Notably, the combination of organocatalyzed living (or reversible deactivation) radical polymerization and BNN3 azidation enabled the metal-free synthesis of azido-end polymethacrylates, including single-azido-end and multi-azido-end functional homopolymers and block copolymers. The rapid and quantitative reaction without the requirement for a large excess of BNN3 , metal-free and polar-solvent-free nature, and broad polymer scope are attractive features of this azidation.

Catalytic and Mechanistic Developments of the Nickel(II) Pincer Complex-Catalyzed Hydroarsination Reaction.

Synthetic challenges have significantly slowed the development of the catalytic asymmetric hydroarsination reaction despite it being a highly attractive C-As bond formation methodology. In addition, there is a poor understanding of the main reaction steps in such reactions which limit further development in the field. Herein, key intermediates of the hydroarsination reaction catalyzed by a PCP NiII -Cl pincer complex are presented upon investigating the reaction with DFT calculations, conductivity measurements, NMR spectroscopy, and catalytic screening. The novel Ni-Cl-As interaction proposed was then contrasted against known NiII -catalyzed hydrophosphination reactions to highlight dissimilarities between them even though P and As share a close group relationship. Lastly, the asymmetric hydroarsination of nitroolefins was further developed to furnish a library of chiral organoarsines in up to 99 % yield and 80 % ee under mild conditions (-20 °C to RT) between 5 to 210 mins.