Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis.

BACKGROUND: Although significant advances have been made in intensive care medicine and antibacterial treatment, sepsis is still a common disease with high mortality. The condition of sepsis patients changes rapidly, and each hour of delay in the administration of appropriate antibiotic treatment can lead to a 4-7% increase in fatality. Therefore, early diagnosis and intervention may help improve the prognosis of patients with sepsis. METHODS: We obtained single-cell sequencing data from 12 patients. This included 14,622 cells from four patients with bacterial infectious sepsis and eight patients with sepsis admitted to the ICU for other various reasons. Monocyte differentiation trajectories were analyzed using the "monocle" software, and differentiation-related genes were identified. Based on the expression of differentiation-related genes, 99 machine-learning combinations of prognostic signatures were obtained, and risk scores were calculated for all patients. The "scissor" software was used to associate high-risk and low-risk patients with individual cells. The "cellchat" software was used to demonstrate the regulatory relationships between high-risk and low-risk cells in a cellular communication network. The diagnostic value and prognostic predictive value of Enah/Vasp-like (EVL) were determined. Clinical validation of the results was performed with 40 samples. The "CBNplot" software based on Bayesian network inference was used to construct EVL regulatory networks. RESULTS: We systematically analyzed three cell states during monocyte differentiation. The differential analysis identified 166 monocyte differentiation-related genes. Among the 99 machine-learning combinations of prognostic signatures constructed, the Lasso + CoxBoost signature with 17 genes showed the best prognostic prediction performance. The highest percentage of high-risk cells was found in state one. Cell communication analysis demonstrated regulatory networks between high-risk and low-risk cell subpopulations and other immune cells. We then determined the diagnostic and prognostic value of EVL stabilization in multiple external datasets. Experiments with clinical samples demonstrated the accuracy of this analysis. Finally, Bayesian network inference revealed potential network mechanisms of EVL regulation. CONCLUSIONS: Monocyte differentiation-related prognostic signatures based on the Lasso + CoxBoost combination were able to accurately predict the prognostic status of patients with sepsis. In addition, low EVL expression was associated with poor prognosis in sepsis.

Resolving the Chemical Formula of Nesquehonite via NMR Crystallography, DFT Computation, and Complementary Neutron Diffraction.

Nesquehonite is a magnesium carbonate mineral relevant to carbon sequestration envisioned for carbon capture and storage of CO2 . Its chemical formula remains controversial today, assigned as either a hydrated magnesium carbonate [MgCO3 ⋅ 3H2 O], or a hydroxy- hydrated- magnesium bicarbonate [Mg(HCO3 )OH ⋅ 2H2 O]. The resolution of this controversy is central to understanding this material's thermodynamic, phase, and chemical behavior. In an NMR crystallography study, using rotational-echo double-resonance 13 C{1 H} (REDOR), 13 C-1 H distances are determined with precision, and the combination of 13 C static NMR lineshapes and density functional theory (DFT) calculations are used to model different H atomic coordinates. [MgCO3 ⋅ 3H2 O] is found to be accurate, and evidence from neutron powder diffraction bolsters these assignments. Refined H positions can help understand how H-bonding stabilizes this structure against dehydration to MgCO3 . More broadly, these results illustrate the power of NMR crystallography as a technique for resolving questions where X-ray diffraction is inconclusive.

Supported Lanthanum Borohydride Catalyzes CH Borylation Inside Zeolite Micropores.

The zeolite-supported lanthanide La(BH4 )x -HY30 catalyzes C-H borylation of benzene with pinacolborane (HBpin), providing a complementary approach to precious, late transition metal-catalyzed borylations. The reactive catalytic species are generated from La grafted at the Brønsted acid sites (BAS) in micropores of the zeolite, whereas silanoate- and aluminoate-grafted sites are inactive under the reaction conditions. During typical catalytic borylations, conversion to phenyl pinacolborane (PhBpin) is zero-order in HBpin concentration. A turnover number (TON) of 167 is accessed by capping external silanols, selectively grafting at BAS sites, and adding HBpin slowly to the reaction.

NMR Crystallography: Evaluation of Hydrogen Positions in Hydromagnesite by 13 C{1 H} REDOR Solid-State NMR and Density Functional Theory Calculation of Chemical Shielding Tensors.

Solid-state NMR measurements coupled with density functional theory (DFT) calculations demonstrate how hydrogen positions can be refined in a crystalline system. The precision afforded by rotational-echo double-resonance (REDOR) NMR to interrogate 13 C-1 H distances is exploited along with DFT determinations of the 13 C tensor of carbonates (CO3 2- ). Nearby 1 H nuclei perturb the axial symmetry of the carbonate sites in the hydrated carbonate mineral, hydromagnesite [4 MgCO3 ⋅Mg(OH)2 ⋅4 H2 O]. A match between the calculated structure and solid-state NMR was found by testing multiple semi-local and dispersion-corrected DFT functionals and applying them to optimize atom positions, starting from X-ray diffraction (XRD)-determined atomic coordinates. This was validated by comparing calculated to experimental 13 C{1 H} REDOR and 13 C chemical shift anisotropy (CSA) tensor values. The results show that the combination of solid-state NMR, XRD, and DFT can improve structure refinement for hydrated materials.

Advances and Applications of Cancer Organoids in Drug Screening and Personalized Medicine.

In recent years, the rapid emergence of 3D organoid technology has garnered significant attention from researchers. These miniature models accurately replicate the structure and function of human tissues and organs, offering more physiologically relevant platforms for cancer research. These intricate 3D structures not only serve as promising models for studying human cancer, but also significantly contribute to the advancement of various potential applications in the field of cancer research. To date, organoids have been efficiently constructed from both normal and malignant tissues originating from patients. Using such bioengineering platforms, simulations of infections and cancer processes, mutations and carcinogenesis can be achieved, and organoid technology is also expected to facilitate drug testing and personalized therapies. In conclusion, regenerative medicine has the potential to enhance organoid technology and current transplantation treatments by utilizing genetically identical healthy organoids as substitutes for irreversibly deteriorating diseased organs. This review explored the evolution of cancer organoids and emphasized the significant role these models play in fundamental research and the advancement of personalized medicine in oncology.

The Role of Hydrogel Biomaterials in the Intervention of Wound Healing and Skin Regeneration via Exosomes: A Systematic Review and Meta-Analysis of Preclinical Animal Studies.

Significance: The combination of hydrogel biomaterials with exosomes to facilitate wound healing and skin regeneration is a promising approach. Recent Advances: Recent preclinical animal studies have focused on investigating the efficacy of hydrogel-based delivery systems for exosomes in promoting wound healing and skin regeneration. Critical Issues: Despite encouraging results, critical issues remain unresolved, such as optimizing hydrogel properties to enhance the efficacy of combined therapy with exosomes for wound and bridging the translational gap between preclinical and clinical applications. Future Directions: Future research endeavors should concentrate on refining hydrogel design to enhance exosome delivery efficacy, conducting rigorous clinical trials to assess the safety and efficacy of exosome-loaded hydrogels in human wound healing and skin regeneration, and exploring innovative strategies to maximize therapeutic outcomes.

Organoids: new frontiers in tumor immune microenvironment research.

The tumor microenvironment (TME) contains cells that regulate medication response and cancer growth in a major way. Tumor immunology research has been rejuvenated and cancer treatment has been changed by immunotherapy, a rapidly developing therapeutic approach. The growth patterns of tumor cells in vivo and the heterogeneity, complexity, and individuality of tumors produced from patients are not reflected in traditional two-dimensional tumor cell profiles. On the other hand, an in vitro three-dimensional (3D) model called the organoid model is gaining popularity. It can replicate the physiological and pathological properties of the original tissues in vivo. Tumor cells are the source of immune organoids. The TME characteristics can be preserved while preserving the variety of tumors by cultivating epithelial tumor cells with various stromal and immunological components. In addition to having genetic and physical similarities to human diseases and the ability to partially reconstruct the complex structure of tumors, these models are now widely used in research fields including cancer, developmental biology, regenerative mechanisms, drug development, disease modeling, and organ transplantation. This study reviews the function of organoids in immunotherapy and the tumor immune milieu. We also discuss current developments and suggest translational uses of tumor organoids in immuno-oncology research, immunotherapy modeling, and precision medicine.

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors.

Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors. Here, we report the design of a machine-learning-derived activation strategy that uses sodium amide and cross-linked polymer precursors to synthesize highly porous carbons (i.e., with specific surface areas > 4000 m2/g). Tuning the pore size and oxygen content of the carbonaceous materials, we report a highly porous carbon-base electrode with 0.7 mg/cm2 of electrode mass loading that exhibits a high specific capacitance of 610 F/g in 1 M H2SO4. This result approaches the specific capacitance of a porous carbon electrode predicted by the machine learning approach. We also investigate the charge storage mechanism and electrolyte transport properties via step potential electrochemical spectroscopy and quasielastic neutron scattering measurements.

Ginsenosides extracted from nanoscale Chinese white ginseng enhances anticancer effect.

Ginsenosides, the major chemical composition of Chinese white ginseng (Panax ginseng C. A. Meyer), can inhibit tumor, enhance body immune function, prevent neurodegeneration. In this paper, for the first time we reported that the amount of ginsenosides in the equivalent extraction of the nanoscale Chinese white ginseng particles (NWGP) was 2.5 times more than that of microscale Chinese white ginseng particles (WGP). And the extractions from NWGP (1000 microg/ml) reached a high tumor inhibition of 64% exposed to human lung carcinoma cells (A549) and 74% exposed to human cervical cancer cells (Hela) after 72 h. Our work shows that the nanoscale Chinese WGP greatly improves the bioavailability of ginsenosides.

NMR and Theoretical Study of In-Pore Diffusivity of Ionic Liquid-Solvent Mixtures.

Despite having a lower energy density than common batteries, electric double-layer capacitors (EDLCs) offer several advantages for high-power applications, including high power density, quick charge and discharge time, and long cycle life. Room-temperature ionic liquids (RTILs) have been intensely studied as promising electrolytes for applications in ELDCs because of their wide potential window, low volatility, as well as thermal and chemical stability. The main deficiency of neat RTILs in such applications is the sluggish diffusivity, which restricts the EDLCs' power density. To alleviate the slow diffusivity, RTILs can be used in a mixture with organic solvents. In this study, we applied two-dimensional exchange nuclear magnetic resonance spectroscopy (2D EXSY NMR) and molecular dynamics (MD) simulations to investigate the diffusivity of anions of an RTIL, namely, 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (BMIM+-TFSI-), dissolved in five different organic solvents, in the micropores of activated carbon. We determined that the relative concentrations of ions in solutions in the micropores were higher than those in the bulk solutions and were also solvent-dependent. The ion diffusivities in the pores were found to be almost 2 orders of magnitude slower than in the bulk solutions, with methanol showing the largest relative disparity. These results suggested that the interactions of solvents with the activated carbon are critical not only to the power density of EDLCs but also to the energy density. The comparisons of ion diffusivities between the experiments and the MD simulations suggest the need to consider also the surface functionalities of activated carbon for the simulation of ion diffusion in the micropores of activated carbon.

Multifunctional Separator Allows Stable Cycling of Potassium Metal Anodes and of Potassium Metal Batteries.

This is the first report of a multifunctional separator for potassium-metal batteries (KMBs). Double-coated tape-cast microscale AlF3 on polypropylene (AlF3 @PP) yields state-of-the-art electrochemical performance: symmetric cells are stable after 1000 cycles (2000 h) at 0.5 mA cm-2 and 0.5 mAh cm-2 , with 0.042 V overpotential. Stability is maintained at 5.0 mA cm-2 for 600 cycles (240 h), with 0.138 V overpotential. Postcycled plated surface is dendrite-free, while stripped surface contains smooth solid electrolyte interphase (SEI). Conventional PP cells fail rapidly, with dendrites at plating, and "dead metal" and SEI clumps at stripping. Potassium hexacyanoferrate(III) cathode KMBs with AlF3 @PP display enhanced capacity retention (91% at 100 cycles vs 58%). AlF3 partially reacts with K to form an artificial SEI containing KF, AlF3 , and Al2 O3 phases. The AlF3 @PP promotes complete electrolyte wetting and enhances uptake, improves ion conductivity, and increases ion transference number. The higher of K+ transference number is ascribed to the strong interaction between AlF3 and FSI- anions, as revealed through 19 F NMR. The enhancement in wetting and performance is general, being demonstrated with ester- and ether-based solvents, with K-, Na-, or Li- salts, and with different commercial separators. In full batteries, AlF3 prevents Fe crossover and cycling-induced cathode pulverization.

Diffusivity and Structure of Room Temperature Ionic Liquid in Various Organic Solvents.

Room-temperature ionic liquids (RTILs) hold promise for applications in electric double layer capacitors (EDLCs), owing to a much wider potential window, lower vapor pressure, and better thermal and chemical stabilities compared to conventional aqueous and organic electrolytes. However, because the low diffusivity of ions in neat RTILs negates the EDLCs' advantage of high power density, the ionic liquids are often used in mixture with organic solvents. In this study, we measured the diffusivity of cations and anions in RTIL, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl) ([BMIM+][TFSI-]), mixed with 10 organic solvents, by using the pulsed-field gradient NMR method. The ion diffusivity was found to follow that of neat solvents and in most studied solvents showed an excellent agreement with the predicted values reported in the recent molecular dynamics (MD) study [Thompson, M. W.; J. Phys. Chem. B 2019, 123, 1340-1347]. In two solvents consisting of long-chain molecules, however, the MD simulations predictions slightly underestimated the ionic diffusivities. The degree of ion dissociation was also estimated for each solvent by comparing the ionic conductivity with the molar conductivity derived from the diffusion measurements. The degree of ion dissociation and the hydrodynamic radius of ions suggest that the ions are coordinated by ∼1 solvent molecule. The scarcity of solvent-ion interactions explains the fact that the diffusivity of ions in the mixture significantly depends on the viscosity of the solvent.

A flow-through, elevated-temperature and -pressure NMR apparatus for in-situ CO2 sequestration studies.

We report an apparatus for in-situ nuclear magnetic resonance (NMR) studies of chemical reactions of dissolved 13CO2 with minerals (rock or powder) under continuous flow. The operating range of the apparatus is 18-150°C and 1-140bar. A flow pump is used to circulate a CO2-water solution, with a heated mixing vessel where CO2 gas equilibrates with a water solution. The NMR probe is built around a strong zirconia ceramic vessel, with o-ring sealed connections; the mineral is contained inside. The horizontal orientation of the zirconia vessels allows use of a radio frequency (rf) solenoid for improved spin sensitivity.