Single-Molecule Discrimination of Saccharides Using Carbon Nitride Nanopores.

Structural complexity brings a huge challenge to the analysis of sugar chains. As a single-molecule sensor, nanopores have the potential to provide fingerprint information on saccharides. Traditionally, direct single-molecule saccharide detection with nanopores is hampered by their small size and weak affinity. Here, a carbon nitride nanopore device is developed to discern two types of trisaccharide molecules (LeApN and SLeCpN) with minor structural differences. The resolution of LeApN and SLeCpN in the mixture reaches 0.98, which has never been achieved in solid-state nanopores so far. Monosaccharide (GlcNAcpN) and disaccharide (LacNAcpN) can also be discriminated using this system, indicating that the versatile carbon nitride nanopores possess a monosaccharide-level resolution. This study demonstrates that the carbon nitride nanopores have the potential for conducting structure analysis on single-molecule saccharides.

A potassium-chloride co-transporter with altered genome architecture functions as a suppressor in glioma.

Gliomas, the most lethal tumours in brain, have a poor prognosis despite accepting standard treatment. Limited benefits from current therapies can be attributed to genetic, epigenetic and microenvironmental cues that affect cell programming and drive tumour heterogeneity. Through the analysis of Hi-C data, we identified a potassium-chloride co-transporter SLC12A5 associated with disrupted topologically associating domain which was downregulated in tumour tissues. Multiple independent glioma cohorts were included to analyse the characterization of SLC12A5 and found it was significantly associated with pathological features, prognostic value, genomic alterations, transcriptional landscape and drug response. We constructed two SLC12A5 overexpression cell lines to verify the function of SLC12A5 that suppressed tumour cell proliferation and migration in vitro. In addition, SLC12A5 was also positively associated with GABAA receptor activity and negatively associated with pro-tumour immune signatures and immunotherapy response. Collectively, our study provides a comprehensive characterization of SLC12A5 in glioma and supports SLC12A5 as a potential suppressor of disease progression.

Discovery of novel RNA viruses through analysis of fungi-associated next-generation sequencing data.

BACKGROUND: Like all other species, fungi are susceptible to infection by viruses. The diversity of fungal viruses has been rapidly expanding in recent years due to the availability of advanced sequencing technologies. However, compared to other virome studies, the research on fungi-associated viruses remains limited. RESULTS: In this study, we downloaded and analyzed over 200 public datasets from approximately 40 different Bioprojects to explore potential fungal-associated viral dark matter. A total of 12 novel viral sequences were identified, all of which are RNA viruses, with lengths ranging from 1,769 to 9,516 nucleotides. The amino acid sequence identity of all these viruses with any known virus is below 70%. Through phylogenetic analysis, these RNA viruses were classified into different orders or families, such as Mitoviridae, Benyviridae, Botourmiaviridae, Deltaflexiviridae, Mymonaviridae, Bunyavirales, and Partitiviridae. It is possible that these sequences represent new taxa at the level of family, genus, or species. Furthermore, a co-evolution analysis indicated that the evolutionary history of these viruses within their groups is largely driven by cross-species transmission events. CONCLUSIONS: These findings are of significant importance for understanding the diversity, evolution, and relationships between genome structure and function of fungal viruses. However, further investigation is needed to study their interactions.

Machine learning-based decision support model for selecting intra-arterial therapies for unresectable hepatocellular carcinoma: A national real-world evidence-based study.

IMPORTANCE: Intra-arterial therapies(IATs) are promising options for unresectable hepatocellular carcinoma(HCC). Stratifying the prognostic risk before administering IAT is important for clinical decision-making and for designing future clinical trials. OBJECTIVE: To develop and validate a machine learning(ML)-based decision support model(MLDSM) for recommending IAT modalities for unresectable HCC. DESIGN, SETTING, AND PARTICIPANTS: Between October 2014 and October 2022, a total of 2,959 patients with HCC who underwent initial IATs were enroled retrospectively from 13 tertiary hospitals. These patients were divided into the training cohort (n = 1700), validation cohort (n = 428), and test cohort (n = 200). MAIN OUTCOMES AND MEASURES: Thirty-two clinical variables were input, and five supervised ML algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBM) and Random Forest (RF), were compared using the areas under the receiver operating characteristic curve (AUC) with the DeLong test. RESULTS: A total of 1856 patients were assigned to the IAT alone Group(I-A), and 1103 patients were assigned to the IAT combination Group(I-C). The 12-month death rates were 31.9% (352/1103) in the I-A group and 50.4% (936/1856) in the I-C group. For the test cohort, in the I-C group, the CatBoost model achieved the best discrimination when 30 variables were input, with an AUC of 0.776 (95% confidence intervals [CI], 0.833-0.868). In the I-A group, the LGBM model achieved the best discrimination when 24 variables were input, with an AUC of 0.776 (95% CI, 0.833-0.868). According to the decision trees, BCLC grade, local therapy, and diameter as top three variables were used to guide clinical decisions between IAT modalities. CONCLUSIONS AND RELEVANCE: The MLDSM can accurately stratify prognostic risk for HCC patients who received IATs, thus helping physicians to make decisions about IAT and providing guidance for surveillance strategies in clinical practice.

Tumor microenvironment phenotypes and prognostic evaluation tools for osteosarcoma characterized by different prognostic outcomes and immunotherapy responses.

BACKGROUND: The physiological and immunological characteristics of the tumor microenvironment (TME) have a profound impact on the effectiveness of immunotherapy. The present study aimed to define the TME subtype of osteosarcoma according to the signatures representing the global TME of the tumor, as well as create a new prognostic assessment tool to monitor the prognosis, TME activity and immunotherapy response of patients with osteosarcoma. METHODS: The enrichment scores of 29 functional gene expression signatures in osteosarcoma samples were calculated by single sample gene set enrichment analysis (ssGSEA). TME classification of osteosarcoma was performed and a prognostic assessment tool was created based on 29 ssGSEA scores to comprehensively correlate them with TME components, immunotherapy efficacy and prognosis of osteosarcoma. RESULTS: Three TME subtypes were generated that differed in survival, TME activity and immunotherapeutic response. Four differentially expressed genes between TME subtypes were involved in the development of prognostic assessment tools. The established prognosis assessment tool had strong performance in both training and verification cohorts, could be effectively applied to the survival prediction of samples of different ages, genders and transfer states, and could well distinguish the TME status of different samples. CONCLUSIONS: The present study describes three different TME phenotypes in osteosarcoma, provides a risk stratification tool for osteosarcoma prognosis and TME status assessment, and provides additional information for clinical decision-making of immunotherapy.

Decoding the Pathway-Dependent Self-Assembly of Polymer-Grafted Nanoparticles by Ligand Crystallization.

Functional metamaterials can be constructed by assembling nanoparticles (NPs) into well-ordered structures, which show fascinating properties at different length scales. Using polymer-grafted NPs (PGNPs) as a building block, flexible composite metamaterials can be obtained, of which the structure is significantly affected by the property of polymer ligands. Here, it is demonstrated that the crystallization of polymer ligands determines the assembly behavior of NPs and reveal a pathway-dependent self-assembly of PGNPs into different metastructures in solution. By changing the crystallization degree of polymer ligands, the arrangement structure of NPs can be tailored. When the polymer ligands highly crystallize, the PGNPs assemble into diamond-shaped platelets, in which the NPs arrange disorderedly. When the polymer ligands lowly crystallize, the PGNPs assemble into highly ordered 3D superlattices, in which the NPs pack into a body-centered-cubic structure. The structure transformation of PGNP assemblies can be achieved by thermal annealing to regulate the crystallization of polymer ligands. Interestingly, the diamond-shaped platelets remain "living" for seeded epitaxial growth of newly added crystalline species. This work demonstrates the effects of ligand crystallization on the crystallization of NP, providing new insights into the structure regulation of metamaterials.

MXene-Layered Double Hydroxide Reinforced Epoxy Nanocomposite with Enhanced Electromagnetic Wave Absorption, Thermal Conductivity, and Flame Retardancy in Electronic Packaging.

Due to the increased integration and miniaturization of electronic devices, traditional electronic packaging materials, such as epoxy resin (EP), cannot solve electromagnetic interference (EMI) in electronic devices. Thus, the development of multifunctional electronic packaging materials with superior electromagnetic wave absorption (EMA), high heat dissipation, and flame retardancy is critical for current demand. This study employs an in-situ growth method to load layered double hydroxides (LDH) onto transition metal carbides (MXene), synthesizing a novel composite material (MXene@LDH). MXene@LDH possesses a sandwich structure and exhibits excellent EMA performance, thermal conductivity, and flame retardancy. By adjusting the load of LDH, under the synergistic effect of multiple factors, such as dielectric and polarization losses, this work achieves an EMA material with a remarkable minimum reflection loss (RL) of -52.064 dB and a maximum effective absorption bandwidth (EAB) of 4.5 GHz. Furthermore, MXene@LDH emerges a bridging effect in EP, namely MXene@LDH/EP, leading to a 118.75% increase in thermal conductivity compared to EP. Simultaneously, MXene@LDH/EP contributes to the enhanced flame retardancy compared to EP, resulting in a 46.5% reduction in the total heat release (THR). In summary, this work provides a promising candidate advanced electronic packaging material for high-power density electronic packaging.

Significant Enhancement of Thermoelectric Performance in Bi0.5 Sb1.5 Te3 Thin Film via Ferroelectric Polarization Engineering.

The Bi0.5 Sb1.5 Te3 (BST) thin film shows great promise in harvesting low-grade heat energy due to its excellent thermoelectric performance at room temperature. In order to further enhance its thermoelectric performance, specifically the power factor and output power, new approaches are highly desirable beyond the common "composition-structure-performance" paradigm. This study introduces ferroelectric polarization engineering as a novel strategy to achieve these goals. A Pb(Zr0.52 Ti0.48 )O3 /Bi0.5 Sb1.5 Te3 (PZT/BST) hybrid film is fabricated via magnetron sputtering. Density functional theory calculations demonstrate PZT polarization's influence on charge redistribution and interlayer charge transfer at the PZT/BST interface, facilitating adjustable carrier transport behavior and power factor of the BST film. As a result, a 26.7% enhancement of the power factor, from unpolarized 12.0 to 15.2 µW cm-1 K-2 , is reached by 2 kV out-of-plane downward polarization of PZT. Furthermore, a five-leg generator constructed using this PZT/BST hybrid film exhibits a maximum output power density of 13.06 W m-2 at ΔT = 39 K, which is 20.8% higher than that of the unpolarized one (10.81 W m-2 ). The research presents a new approach to enhance thermoelectric thin films' power factor and output performance by introducing ferroelectric polarization engineering.

Elimination of Intragrain Defect to Enhance the Performance of FAPbI3 Perovskite Solar Cells by Ionic Liquid.

Ionic liquids have been widely used to improve the efficiency and stability of perovskite solar cells (PSCs), and are generally believed to passivate defects on the grain boundaries of perovskites. However, few studies have focused on the relevant effects of ionic liquids on intragrain defects in perovskites which have been shown to be critical for the performance of PSCs. In this work, the effect of ionic liquid 1-hexyl-3-methylimidazolium iodide (HMII) on intragrain defects of formamidinium lead iodide (FAPbI3) perovskite is investigated. Abundant {111}c intragrain planar defects in pure FAPbI3 grains are found to be significantly reduced by the addition of the ionic liquid HMII, shown by using ultra-low-dose selected area electron diffraction. As a result, longer charge carrier lifetimes, higher photoluminescence quantum yield, better charge carrier transport properties, lower Urbach energy, and current-voltage hysteresis are achieved, and the champion power conversion efficiency of 24.09% is demonstrated. These observations suggest that ionic liquids significantly improve device performance resulting from the elimination of {111}c intragrain planar defects.

Does protein pretrained language model facilitate the prediction of protein-ligand interaction?

Protein-ligand interaction (PLI) is a critical step for drug discovery. Recently, protein pretrained language models (PLMs) have showcased exceptional performance across a wide range of protein-related tasks. However, a significant heterogeneity exists between the PLM and PLI tasks, leading to a degree of uncertainty. In this study, we propose a method that quantitatively assesses the significance of protein PLMs in PLI prediction. Specifically, we analyze the performance of three widely-used protein PLMs (TAPE, ESM-1b, and ProtTrans) on three PLI tasks (PDBbind, Kinase, and DUD-E). The model with pre-training consistently achieves improved performance and decreased time cost, demonstrating that enhance both the accuracy and efficiency of PLI prediction. By quantitatively assessing the transferability, the optimal PLM for each PLI task is identified without the need for costly transfer experiments. Additionally, we examine the contributions of PLMs on the distribution of feature space, highlighting the improved discriminability after pre-training. Our findings provide insights into the mechanisms underlying PLMs in PLI prediction and pave the way for the design of more interpretable and accurate PLMs in the future. Code and data are freely available at https://github.com/brian-zZZ/PLM-PLI.

A confinement-regulated (H3C-NH3)+ ion as a smallest dual-wheel rotator showing bisected rotation dynamics.

On the basis of variable-temperature single-crystal X-ray diffraction, rotational energy barrier analysis, variable-temperature/frequency dielectric response, and molecular dynamics simulations, here we report a new crystalline supramolecular rotor (CH3NH3)(18-crown-6)[CuCl3], in which the (H3C-NH3)+ ion functions as a smallest dual-wheel rotator showing bisected rotation dynamics, while the host 18-crown-6 macrocycle behaves as a stator that is not strictly stationary. This study also provides a helpful insight into the dynamics of ubiquitous -CH3/-NH3 groups confined in organic or organic-inorganic hybrid solids.

Spinal microglial M1 polarization contributes paclitaxel-induced neuropathic pain by triggering cells necroptosis.

Paclitaxel (PTX) is a chemotherapeutic agent that is widely used for the treatment of several types of tumors. However, PTX-induced peripheral neuropathy (PIPN) is an adverse effect generally induced by long-term PTX use that significantly impairs the quality of life. Necroptosis has been implicated in various neurodegenerative disorders. Necroptosis of dorsal root ganglion neurons triggers the pathogenesis of PIPN. Therefore, the present study aims to investigate the role of spinal neuronal necroptosis in PIPN. It also explores the potential role of microglial polarization in necroptosis. We established rat models of PIPN via quartic PTX administration on alternate days (accumulated dose: 8 mg/kg). PTX induced obvious neuronal necroptosis and upregulated the expression of receptor-interacting protein kinase (RIP3) and mixed lineage kinase domain-like protein (MLKL) in the spinal dorsal horn. These effects were inhibited with a necroptosis pathway inhibitor, necrostatin-1 (Nec-1). The effect of microglial polarization on the regulation of spinal necroptosis was elucidated by administering minocycline to inhibit PTX-induced M1 polarization of spinal microglia caused by PTX. We observed a significant inhibitory effect of minocycline on PTX-induced necroptosis in spinal cord cells, based on the downregulation of RIP3 and MLKL expression, and suppression of tumor necrosis factor-α and IL-ß synthesis. Additionally, minocycline improved hyperalgesia symptoms in PIPN rats. Overall, this study suggests that PTX-induced polarization of spinal microglia leads to RIP3/MLKL-regulated necroptosis, resulting in PIPN. These findings suggest a potential target for the prevention and treatment of neuropathic pain.

Fulvenallenyl Radical (C7H5·)-Mediated Gas-Phase Synthesis of Bicyclic Aromatic C10H8 Isomers: Can Fulvenallenyl Efficiently React with Closed-Shell Hydrocarbons?

To understand the reactivity of resonantly stabilized radicals, often found in relevant concentrations in gaseous environments, it is important to determine their main reaction pathways. Here, it is investigated whether the fulvenallenyl radical (C7H5·) reacts preferentially with closed-shell molecules or radicals. Electronic structure calculations on the C10H9 potential energy surface accessed by the reactions of C7H5· with methylacetylene (CH3CCH) and allene (H2CCCH2) were combined with RRKM-ME calculations of temperature- and pressure-dependent rate constants using the automated EStokTP software suite and kinetic modeling to assess the reactivity of C7H5· with closed-shell unsaturated hydrocarbons. Experimentally, the reactions were attempted in a chemical microreactor heated to 998 ± 10 K by preparing fulvenallenyl radicals via pyrolysis of trichloromethylbenzene (C7H5Cl3) and seeding the radicals in methylacetylene or allene carrier gas, with product identification by means of photoionization mass spectrometry. The measured photoionization efficiency curve of m/z = 128 was assigned to a linear combination of the reference curves of two C10H8 isomers, azulene (minor) and naphthalene (major), presumably resulting from the C7H5· plus C3H4 reactions. However, the calculations demonstrated that these reactions are too slow, and kinetic modeling of processes in the reactor allowed us to conclude that the observation of naphthalene and azulene is due to the C7H5· plus C3H3· reaction, where propargyl is produced by direct hydrogen atom abstraction by chlorine (Cl) atoms from allene or methylacetylene and Cl stem from the pyrolysis of C7H5Cl3. Modeling results under the copyrolysis conditions of toluene and methylacetylene in high-temperature shock tube experiments confirmed the prevalence of the fulvenallenyl reaction with propargyl over its reactions with C3H4 even when the concentrations of allene and methylacetylene largely exceed that of propargyl. Overall, the reactions of fulvenallenyl with both allene and methylacetylene were found to be noncompetitive in the formation of naphthalene and azulene thus attesting the inefficiency of the fulvenallenyl radical reactions with the prototype closed-shell hydrocarbon species. In the meantime, the new reaction pathways revealed, including H-assisted isomerizations between C10H8 isomers and decomposition reactions of various C10H9 isomers, emerge as relevant and are recommended for inclusion in combustion kinetic models for naphthalene formation.

Screening, characterization, and optimization of the fermentation conditions of a novel cellulase-producing microorganism from soil of Qinghai-Tibet Plateau.

Cellulases play an important role in the bioconversion of lignocellulose. Microorganisms found in extreme environments are a potentially rich source of cellulases with unique properties. Due to the uniqueness of the environment, the abundant microbial resources in the Qinghai-Tibet Plateau (QTP) are worth being explored. The aim of this study was to isolate and characterize an acidic, mesophilic cellulase-producing microorganism from QTP. Moreover, the fermentation conditions for cellulase production were optimized for future application of cellulase in the development of lignocellulose biomass. A novel cellulase-producing strain, Penicillium oxalicum XC10, was isolated from the soil of QTP. The cellulase produced by XC10 was a mesophilic cellulase that exhibited good acid resistance and some cold-adaptation properties, with maximum activity at pH 4.0 and 40°C. Cellulase activity was significantly enhanced by Na+ (p < 0.05) and inhibited by Mg2+, Ca2+, Cu2+, and Fe3+ (p < 0.05). After optimization, maximum cellulase activity (8.56 U/mL) was increased nearly 10-fold. Optimal fermentation conditions included an inoculum size of 3% (v/v) in a mixture of corn straw (40 g/L), peptone (5 g/L), and Mg2+ (4 g/L), at pH 4.0, 33°C, and shaking at 200 rpm. The specific properties of the P. oxalicum XC10 cellulase suggest the enzyme may serve as an excellent candidate for the bioconversion and utilization of lignocellulose biomass generated as agricultural and food-processing wastes.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Efficient removal of Cr (VI) from coal gangue by indigenous bacteria-YZ1 bacteria: Adsorption mechanism and reduction characteristics of extracellular polymer.

The existence of heavy metals (especially Cr (VI)) in coal gangue has brought great safety risks to the environment. The indigenous bacteria (YZ1 bacteria) were separated and applied for removing Cr (VI) from the coal gangue, in which its tolerance to Cr (VI) was explored. The removal mechanism of Cr (VI) was investigated with pyrite in coal gangue, metabolite organic acids and extracellular polymer of YZ1 bacteria. The concentration of Cr (VI) could be stabilized around 0.012 mg/L by the treatment with YZ1 bacteria. The Cr (VI) tolerance of YZ1 bacteria reached 60 mg/L, and the removal efficiency of Cr (VI) was more than 95% by using YZ1 bacteria combined with pyrite. The organic acids had a certain reducing ability to Cr (VI) (removal efficiency of less than 10%). The extracellular polymers (EPS) were protective for the YZ1 bacteria resisting to Cr (VI). The polysaccharides and Humic-like substances in the soluble extracellular polymers (S-EPS) had strong adsorption and reduction effect on Cr (VI), in which the tryptophan and tyrosine proteins in the bound extracellular polymers (LB-EPS and TB-EPS) could effectively promote the reduction of Cr (VI). YZ1 bacteria could obviously reduce the damage of Cr (VI) from coal gangue to the environment.

Isorhamnetin ameliorates cisplatin-induced acute kidney injury in mice by activating SLPI-mediated anti-inflammatory effect in macrophage.

OBJECTIVE: Isorhamnetin (IH) has been reported to have significant anti-inflammatory effects in various diseases, but its role and mechanism in AKI remain unclear. This study aimed to explore the potential role and mechanism of isorhamnetin in inhibiting macrophage related inflammation and improving AKI injury. METHODS: We established an AKI mouse model by intraperitoneal injection of cisplatin in vivo, and constructed an inflammatory cell model by stimulating RAW264.7 cells with LPS. Creatinine and urea nitrogen were measured to evaluate the changes of renal function in AKI mice. The changes of renal pathological structure were observed by H&E staining. The inflammatory factor-related proteins and RNA expression levels were detected by Western blot and real time PCR. RESULTS: Isorhamnetin protected the kidney from cisplatin induced AKI and significantly inhibited the mRNA and protein levels of inflammatory cytokines (IL-1ß, IL-6, and TNF-α) both in AKI kidney and LPS-stimulated RAW264.7 cells. Interestingly, the data also demonstrated that isorhamnetin significantly upregulated the expression of secretory leukocyte peptidase inhibitor (SLPI), an anti-inflammatory factor, in AKI kidney and LPS-stimulated macrophages, as well as inhibited the M1 macrophage and activated M2 macrophage in vitro. Blocking of SLPI by siRNA activated Mincle-associated inflammatory signaling in macrophages, and the inhibitory effect of isorhamnetin on inflammation was significantly attenuated. CONCLUSION: Isorhamnetin inhibits macrophage inflammation and protects kidney in AKI may be related to downregulating Mincle/Syk/NF-κB-maintained macrophage phenotype by activating SLPI.

Single Molecule Protein Segments Sequencing by a Plasmonic Nanopore.

Obtaining sequential and conformational information on proteins is vital to understand their functions. Although the nanopore-based electrical detection can sense single molecule (SM) protein and distinguish among different amino acids, this approach still faces difficulties in slowing down protein translocation and improving ionic current signal-to-noise ratio. Here, we observe the unfolding and multistep sequential translocation of SM cytochrome c (cyt c) through a surface enhanced Raman scattering (SERS) active conical gold nanopore. High bias voltage unfolds SM protein causing more exposure of amino acid residues to the nanopore, which slows down the protein translocation. Specific SERS traces of different SM cyt c segments are then recorded sequentially when they pass through the hotspot inside the gold nanopore. This study shows that the combination of SM SERS with a nanopore can provide a direct insight into protein segments and expedite the development of nanopore toward SM protein sequencing.

Single-Molecule Electrical and Spectroscopic Profiling Protein Allostery Using a Gold Plasmonic Nanopore.

Direct structural and dynamic characterization of protein conformers in solution is highly desirable but currently impractical. Herein, we developed a single molecule gold plasmonic nanopore system for observation of protein allostery, enabling us to monitor translocation dynamics and conformation transition of proteins by ion current detection and SERS spectrum measurement, respectively. Allosteric transition of calmodulin (CaM) was elaborately probed by the nanopore system. Two conformers of CaM were well-resolved at a single-molecule level using both the ion current blockage signal and the SERS spectra. The collected SERS spectra provided structural evidence to confirm the interaction between CaM and the gold plasmonic nanopore, which was responsible for the different translocation behaviors of the two conformers. SERS spectra revealed the amino acid residues involved in the conformational change of CaM upon calcium binding. The results demonstrated that the excellent spectral characterization furnishes a single-molecule nanopore technique with an advanced capability of direct structure analysis.

[Research progress on pathogenic mechanism of sepsis-induced liver injury and treatment with traditional Chinese medicine and its active components].

Sepsis is a systemic inflammatory response syndrome caused by infection, with high morbidity and mortality. Sepsis-induced liver injury(SILI) is one of the manifestations of sepsis-induced multiple organ syndrome. At present, there is no recommended pharmacological intervention for the treatment of SILI. traditional Chinese medicine(TCM), based on the holism and dialectical treatment concept, shows the therapeutic characteristics of multi-target and multi-pathway and can comprehensively prevent and treat SILI by interfering with inflammatory factors, inflammatory signaling pathways, and anti-oxidative stress and inhibiting apoptosis. This article reviewed the experimental studies on the treatment of SILI with TCM to clarify its pathogenic mechanism and therapeutic characteristics, so as to provide more ideas and directions for the development or preparation of new drugs.