Tailored Porous Ferrocene-Based Metal-Organic Frameworks as High-Performance Proton Conductors.

Although crystalline metal-organic frameworks (MOFs) have gained a great deal of interest in the field of proton conduction in recent years, the low stability and poor proton conductivity (σ) of some MOFs have hindered their future applications. As a result, resolving the issues listed above must be prioritized. Due to their exceptional structural stability, MOFs with ferrocene groups that exhibit particular physical and chemical properties have drawn a lot of attention. This study describes the effective preparation of a set of three-dimensional ferrocene-based MOFs, MIL-53-FcDC-Al/Ga and CAU-43, containing both main group metals and 1,1'-ferrocene dicarboxylic acid (H2FcDC). Multiple measurements, including powder X-ray diffraction (PXRD), infrared (IR), and scanning electron microscopy (SEM), confirmed that the addition of ferrocene groups enhanced the thermal, water, and acid-base stabilities of the three MOFs. Consequently, their proton-conductive behaviors were meticulously measured utilizing the AC impedance approach, and their best proton conductivities are 5.20 × 10-3, 2.31 × 10-3, and 1.72 × 10-4 S/cm at 100 °C/98% relative humidity (RH), respectively. Excitingly, MIL-53-FcDC-Al/Ga demonstrated an extraordinarily ultrahigh σ of above 10-4 S·cm-1 under 30 °C/98% RH. Using data from structural analysis, PXRD, SEM, thermogravimetry (TG), and activation energy, their proton transport mechanisms were thoroughly examined. The fact that these MOFs are notably easy to assemble, inexpensive, toxin-free, and stable will increase the range of practical uses for them.

Water-avoidance stress aggravates prostatic inflammation in a murine model of chronic prostatitis.

OBJECTIVES: To date, few studies have considered the influence of psychological factors on chronic prostatitis (PRO) models. Here, we aimed to refine a murine PRO model combining chemically induced prostatitis with psychological stress. METHODS: A total of 40 mice were randomly divided into four groups: normal control (NC) group, PRO group, water avoidance stress (WAS) group, and PRO + WAS group. Ten mice were assigned to each group: five for cystometrograms (CMGs) and five for von Frey testing and histological analysis. PRO was induced through a prostatic injection of 10% paraformaldehyde. The WAS mice were placed on the middle platform for 1 h per day for 10 consecutive days. RESULTS: The results of the von Frey test demonstrated that both WAS and PRO induced bladder hyperalgesia in mice, and the WAS + PRO group showed significant pelvic pain symptoms either. The CMG results suggested that the PRO group, the WAS group, and the PRO + WAS group all exhibited bladder overactivity, presented as a shortened micturition interval and decreased threshold pressure evoking bladder contraction. The symptoms of the PRO group and the PRO + WAS group were more severe than those of the WAS group. The tissue staining results indicated that WAS itself caused only mild prostatic inflammation but could significantly aggravate chemical-induced prostatic inflammation, as well as the total number of mast cells and proportion of activated mast cells. CONCLUSIONS: Our refined murine PRO model could manifest persistent bladder overactivity, pelvic hyperalgesia and prostatic inflammation. WAS could induce mild prostatic inflammation and aggravate primary prostatic inflammation.

Medical image analysis using improved SAM-Med2D: segmentation and classification perspectives.

Recently emerged SAM-Med2D represents a state-of-the-art advancement in medical image segmentation. Through fine-tuning the Large Visual Model, Segment Anything Model (SAM), on extensive medical datasets, it has achieved impressive results in cross-modal medical image segmentation. However, its reliance on interactive prompts may restrict its applicability under specific conditions. To address this limitation, we introduce SAM-AutoMed, which achieves automatic segmentation of medical images by replacing the original prompt encoder with an improved MobileNet v3 backbone. The performance on multiple datasets surpasses both SAM and SAM-Med2D. Current enhancements on the Large Visual Model SAM lack applications in the field of medical image classification. Therefore, we introduce SAM-MedCls, which combines the encoder of SAM-Med2D with our designed attention modules to construct an end-to-end medical image classification model. It performs well on datasets of various modalities, even achieving state-of-the-art results, indicating its potential to become a universal model for medical image classification.

Adaptation of Chlorella vulgaris immobilization on rice straw with liquid manure to create a sustainable feedstock for biogas production and potential feed applications.

Rice straw (RS) is a widely available agricultural residue with significant potential for biogas production and feed applications; however, its poor digestibility and nutritional value limit its utilization. This study explores an innovative approach to enhance the digestibility and nutritional value of RS by cultivating Chlorella vulgaris through immobilization technology on RS, using liquid manure (LM) as an alternative to the traditional BG11 medium. The results showed an increase in chlorophyll a (Chl a) after 12 days for both the BG11 medium and LM-based treatments, from 0.13 to 0.34 and 0.24 mg Chl a/g product (DM), respectively. Additionally, the immobilized microalgal biomass increased to 284.18 and 170.14 mg algal biomass/g product (DM), respectively. Soaking under microaerobic conditions during cultivation led to the partial degradation of RS. This, combined with the formed microalgal biofilm, contributed to an improved digestibility of the dry matter, reaching 69.1% and 65.9% for the final products based on the BG11 medium and LM mediums, respectively, compared to 52.1% for the raw RS. Furthermore, the crude protein and lipids contents were significantly improved with the potential for applications in feed, reaching 21.4% and 4.1% for the BG11 medium-based product, while they were observed to be 12.8% and 3.0%, respectively, for the LM-based product. Additionally, carbon-to-nitrogen ratio was significantly reduced compared to the raw RS. The higher digestibility and improved nutritional value contributed to increased biogas production, reaching 129.3 and 118.7 mL/g (TS) for the products based on the traditional medium and LM medium, respectively, compared to 86.7 mL/g (TS) for the raw RS. The immobilization mechanism and biofilm development could be attributed to the roughness of the RS and extracellular polymer substances. This study demonstrates that integrating C. vulgaris cultivation on RS with LM as a nutrient source not only enhances the digestibility and nutritional value of RS but also offers a sustainable waste management solution with potential applications in biogas production and animal feed.

Covalent Organic Framework with Multiple Redox Active Sites for High-Performance Aqueous Calcium Ion Batteries.

Organic materials are promising for cation storage in calcium ion batteries (CIBs). However, the high solubility of organic materials in an electrolyte and low electronic conductivity remain the key challenges for high-performance CIBs. Herein, a nitrogen-rich covalent organic framework with multiple carbonyls (TB-COF) is designed as an aqueous anode to address those obstacles. TB-COF demonstrates a high reversible capacity of 253 mAh g-1 at 1.0 A g-1 and long cycle life (0.01% capacity decay per cycle at 5 A g-1 after 3000 cycles). The redox mechanism of Ca2+/H+ co-intercalated in COF and chelating with C═O and C═N active sites is validated. In addition, a novel C═C active site was identified for Ca2+ ion storage. Both computational and empirical results reveal that per TB-COF repetitive unit, up to nine Ca2+ ions are stored after three staggered intercalation steps, involving three distinct Ca2+ ion storage sites. Finally, the evolution process of radical intermediates further elucidates the C═C reaction mechanism.

Functional traits and habitat heterogeneity explain tree growth in a warm temperate forest.

To explore how traits determine demographic performance is an important goal of plant community ecology in explaining the assembly and dynamics of ecological communities. However, whether the prediction of individual-level trait data is more precise compared to species average trait data is questioned. Here, we analyzed the growth and trait data for 11 species collected from October 2018 to October 2020 in a temperate forest, Donglingshan, Beijing. To quantify the relationships between traits and growth rate, we conducted linear regression models at both the species and individual levels, as well as developed structural equation models at both levels. We found there was a clear difference in growth between the warm and cold seasons, with tree growth mainly concentrated in the warm season. Growth rate was positively correlated with the specific leaf area, while negatively correlated with leaf thickness and wood density without considering environmental information. Adding important contextual information in the analysis of species-level structural equation modeling, growth rates were positively correlated with specific leaf area and leaf thickness. However, in the individual-level, there was a negative correlation between growth rate and wood density. Our study showed that individual-level trait data have better predictions for individual growth than species-level data. When we use multiple traits and establish links between traits and tree size, we generated strong predictive relationships between traits and growth rates. Furthermore, our study highlighted that the importance of incorporating topographical factors and considering different seasons to assess the relationship between tree growth and functional traits.

Chemically Stable Low-Dimensional Electrides in Transition Metal-Rich Monochalcogenides: Theoretical and Experimental Explorations.

Electrides, which are ionic crystals composed of excess anionic electrons, are of great interest as an exotic material for fundamental research and practical applications in broad fields of science and technology. However, an inherent chemical instability under ambient conditions at room temperature has been a fatal drawback to be addressed. Here, we report that transition metal-rich monochalcogenides are an emerging class of low-dimensional electrides with excellent chemical and thermal stability in air and water at room temperature through a comprehensive exploration of theoretical prediction and experimental verification. We predict new two-dimensional (2D) electrides crystallized in hexagonal P3̅m1 and P63/mmc structures with strong localization of anionic electrons in a dumbbell shape at the tetrahedral cavity of the interlayer space, which are distinct from the anionic electrons localized at the octahedral cavity in the hexagonal R3̅m structure of the previous 2D [Ca2N]+·e- and [Y2C]2+·2e- electrides. We successfully synthesized the room-temperature stable [Ti2O]2+·2e-, [Ti2S]2+·2e-, [Zr2S]2+·2e-, and primary solid solution [Hf2SxSe1-x]2+·2e- electrides, showing no structural degradation in air and water. Among them, we found that the synthesized [Ti2S]2+·2e- and [Zr2S]2+·2e- electrides are crystallized in orthorhombic symmetry (Pnnm), showing the feature of a one-dimensional (1D) electride with an anionic electron chain, which has never been reported yet. In addition to the successful finding of new 1D and 2D electrides, we discuss the self-passivation effect-driven chemical stability and the role of anionic electrons in determining the physical properties of the newly discovered electrides.

Synthesis and evaluation of Diaza-Crown Ether-Backboned chelator containing hydroxamate groups for Zr-89 chelation chemistry.

Zirconium-89 (89Zr) has been explored for molecularly targeted positron emission tomography (PET) imaging of various diseases. We synthesized and evaluated a novel chelator (DA-18C6-BHA) for 89Zr. The new chelator is structured on a macrocyclic backbone (1,10-diaza-18-crown-6) and contains hydroxamates as acyclic donor groups. The new chelator ((DA-18C6-BHA) was rapidly labeled with 89Zr under mild conditions. The 89Zr-labeled DA-18C6-BHA complex remained stable in human serum and apotransferrin for 7 days. When challenged with excess EDTA solution, 89Zr-labeled DA-18C6-BHA was shown to hold 89Zr without losing considerable radioactivity to EDTA. The 89Zr-labeled DA-18C6-BHA complex displayed high complex stability in normal mice as evidenced by low bone uptake.

A particle-filter framework for robust cryo-EM 3D reconstruction.

Single-particle electron cryomicroscopy (cryo-EM) involves estimating a set of parameters for each particle image and reconstructing a 3D density map; robust algorithms with accurate parameter estimation are essential for high resolution and automation. We introduce a particle-filter algorithm for cryo-EM, which provides high-dimensional parameter estimation through a posterior probability density function (PDF) of the parameters given in the model and the experimental image. The framework uses a set of random support points to represent such a PDF and assigns weighting coefficients not only among the parameters of each particle but also among different particles. We implemented the algorithm in a new program named THUNDER, which features self-adaptive parameter adjustment, tolerance to bad particles, and per-particle defocus refinement. We tested the algorithm by using cryo-EM datasets for the cyclic-nucleotide-gated (CNG) channel, the proteasome, ß-galactosidase, and an influenza hemagglutinin (HA) trimer, and observed substantial improvement in resolution.

Promising bifunctional chelators for copper 64-PET imaging: practical (64)Cu radiolabeling and high in vitro and in vivo complex stability.

Positron emission tomography (PET) using copper-64 is a sensitive and non-invasive imaging technique for diagnosis and staging of cancer. A bifunctional chelator that can present rapid radiolabeling kinetics and high complex stability with (64)Cu is a critical component for targeted PET imaging. Bifunctional chelates 3p-C-NE3TA, 3p-C-NOTA, and 3p-C-DE4TA were evaluated for complexation kinetics and stability with (64)Cu in vitro and in vivo. Hexadentate 3p-C-NOTA and heptadentate 3p-C-NE3TA possess a smaller TACN-based macrocyclic backbone, while nonadentate 3p-C-DE4TA is constructed on a larger CYCLEN-based ring. The frequently explored chelates of (64)Cu, octadentate C-DOTA and hexadentate C-NOTA were also comparatively evaluated. Radiolabeling kinetics of bifunctional chelators with (64)Cu was assessed under mild conditions. All bifunctional chelates instantly bound to (64)Cu in excellent radiolabeling efficiency at room temperature. C-DOTA was less efficient in binding (64)Cu than all other chelates. All (64)Cu-radiolabeled bifunctional chelates remained stable in human serum without any loss of (64)Cu for 2 days. When challenged by an excess amount of EDTA, (64)Cu complexes of C-NOTA, 3p-C-NE3TA and 3p-C-NOTA were shown to be more stable than (64)Cu-C-DOTA and (64)Cu-3p-C-DE4TA. (64)Cu complexes of the new chelates 3p-C-NE3TA and 3p-C-NOTA displayed comparable in vitro and in vivo complex stability to (64)Cu-C-NOTA. In vivo biodistribution result indicates that the (64)Cu-radiolabeled complexes of 3p-C-NOTA and 3p-C-NE3TA possess excellent in vivo complex stability, while (64)Cu-3p-C-DE4TA was dissociated as evidenced by high renal and liver retention in mice. The results of in vitro and in vivo studies suggest that the bifunctional chelates 3p-C-NE3TA and 3p-C-NOTA offer excellent chelation chemistry with (64)Cu for potential PET imaging applications.

A novel prognostic signature related to programmed cell death in osteosarcoma.

Background: Osteosarcoma primarily affects children and adolescents, with current clinical treatments often resulting in poor prognosis. There has been growing evidence linking programmed cell death (PCD) to the occurrence and progression of tumors. This study aims to enhance the accuracy of OS prognosis assessment by identifying PCD-related prognostic risk genes, constructing a PCD-based OS prognostic risk model, and characterizing the function of genes within this model. Method: We retrieved osteosarcoma patient samples from TARGET and GEO databases, and manually curated literature to summarize 15 forms of programmed cell death. We collated 1621 PCD genes from literature sources as well as databases such as KEGG and GSEA. To construct our model, we integrated ten machine learning methods including Enet, Ridge, RSF, CoxBoost, plsRcox, survivalSVM, Lasso, SuperPC, StepCox, and GBM. The optimal model was chosen based on the average C-index, and named Osteosarcoma Programmed Cell Death Score (OS-PCDS). To validate the predictive performance of our model across different datasets, we employed three independent GEO validation sets. Moreover, we assessed mRNA and protein expression levels of the genes included in our model, and investigated their impact on proliferation, migration, and apoptosis of osteosarcoma cells by gene knockdown experiments. Result: In our extensive analysis, we identified 30 prognostic risk genes associated with programmed cell death (PCD) in osteosarcoma (OS). To assess the predictive power of these genes, we computed the C-index for various combinations. The model that employed the random survival forest (RSF) algorithm demonstrated superior predictive performance, significantly outperforming traditional approaches. This optimal model included five key genes: MTM1, MLH1, CLTCL1, EDIL3, and SQLE. To validate the relevance of these genes, we analyzed their mRNA and protein expression levels, revealing significant disparities between osteosarcoma cells and normal tissue cells. Specifically, the expression levels of these genes were markedly altered in OS cells, suggesting their critical role in tumor progression. Further functional validation was performed through gene knockdown experiments in U2OS cells. Knockdown of three of these genes-CLTCL1, EDIL3, and SQLE-resulted in substantial changes in proliferation rate, migration capacity, and apoptosis rate of osteosarcoma cells. These findings underscore the pivotal roles of these genes in the pathophysiology of osteosarcoma and highlight their potential as therapeutic targets. Conclusion: The five genes constituting the OS-PCDS model-CLTCL1, MTM1, MLH1, EDIL3, and SQLE-were found to significantly impact the proliferation, migration, and apoptosis of osteosarcoma cells, highlighting their potential as key prognostic markers and therapeutic targets. OS-PCDS enables accurate evaluation of the prognosis in patients with osteosarcoma.

Predictive Nature of High-Throughput Assays in ADC Formulation Screening.

Utilization of high-throughput biophysical screening techniques during early screening studies is warranted due to the limited amount of material and large number of samples. But the predictability of the data to longer-term storage stability is critical as the high-throughput methods assist in defining the design space for the longer-term studies. In this study, the biophysical properties of two ADCs in 16 formulation conditions were evaluated using high-throughput techniques. Conformational stability and colloidal stability were evaluated by determining Tm values, kD, B22, and Tagg. In addition, the samples were placed on stability and the extent of aggregate formation over the 8-week interval was determined. The rank order of the 16 different formulations in the high-throughput assays was compared to the rank order observed during the stability studies to assess the predictive capabilities of the screening methods. It was demonstrated that similar rank orders can be expected between high-throughput physical stability indicating assays such as Tagg and B22 and traditional aggregation by SEC data, whereas conformational stability read-outs (Tm) are less predictive. In addition, the high-throughput assays appropriately identified the poor performing formulation conditions, which is ultimately what is desired of screening assays.

BiT-MAC: Mortality prediction by bidirectional time and multi-feature attention coupled network on multivariate irregular time series.

Mortality prediction is crucial to evaluate the severity of illness and assist in improving the prognosis of patients. In clinical settings, one way is to analyze the multivariate time series (MTSs) of patients based on their medical data, such as heart rates and invasive mean arterial blood pressure. However, this suffers from sparse, irregularly sampled, and incomplete data issues. These issues can compromise the performance of follow-up MTS-based analytic applications. Plenty of existing methods try to deal with such irregular MTSs with missing values by capturing the temporal dependencies within a time series, yet in-depth research on modeling inter-MTS couplings remains rare and lacks model interpretability. To this end, we propose a bidirectional time and multi-feature attention coupled network (BiT-MAC) to capture the temporal dependencies (i.e., intra-time series coupling) and the hidden relationships among variables (i.e., inter-time series coupling) with a bidirectional recurrent neural network and multi-head attention, respectively. The resulting intra- and inter-time series coupling representations are then fused to estimate the missing values for a more robust MTS-based prediction. We evaluate BiT-MAC by applying it to the missing-data corrupted mortality prediction on two real-world clinical datasets, i.e., PhysioNet'2012 and COVID-19. Extensive experiments demonstrate the superiority of BiT-MAC over cutting-edge models, verifying the great value of the deep and hidden relations captured by MTSs. The interpretability of features is further demonstrated through a case study.

Bio-organic fertilizers improve Dendrocalamus farinosus growth by remolding the soil microbiome and metabolome.

Organic and microbial fertilizers have potential advantages over inorganic fertilizers in improving soil fertility and crop yield without harmful side-effects. However, the effects of these bio-organic fertilizers on the soil microbiome and metabolome remain largely unknown, especially in the context of bamboo cultivation. In this study, we cultivated Dendrocalamus farinosus (D. farinosus) plants under five different fertilization conditions: organic fertilizer (OF), Bacillus amyloliquefaciens bio-fertilizer (Ba), Bacillus mucilaginosus Krassilnikov bio-fertilizer (BmK), organic fertilizer plus Bacillus amyloliquefaciens bio-fertilizer (OFBa), and organic fertilizer plus Bacillus mucilaginosus Krassilnikov bio-fertilizer (OFBmK). We conducted 16S rRNA sequencing and liquid chromatography/mass spectrometry (LC-MS) to evaluate the soil bacterial composition and soil metabolic activity in the different treatment groups. The results demonstrate that all the fertilization conditions altered the soil bacterial community composition. Moreover, the combination of organic and microbial fertilizers (i.e., in the OFBa and OFBmK groups) significantly affected the relative abundance of soil bacterial species; the largest number of dominant microbial communities were found in the OFBa group, which were strongly correlated with each other. Additionally, non-targeted metabolomics revealed that the levels of soil lipids and lipid-like molecules, and organic acids and their derivatives, were greatly altered under all treatment conditions. The levels of galactitol, guanine, and deoxycytidine were also markedly decreased in the OFBa and OFBmK groups. Moreover, we constructed a regulatory network to delineated the relationships between bamboo phenotype, soil enzymatic activity, soil differential metabolites, and dominant microbial. The network revealed that bio-organic fertilizers promoted bamboo growth by modifying the soil microbiome and metabolome. Accordingly, we concluded that the use of organic fertilizers, microbial fertilizers, or their combination regulated bacterial composition and soil metabolic processes. These findings provide new insights into how D. farinosus-bacterial interactions are affected by different fertilization regiments, which are directly applicable to the agricultural cultivation of bamboo.

Novel Chelating Agents for Zirconium-89-Positron Emission Tomography (PET) Imaging: Synthesis, DFT Calculation, Radiolabeling, and In Vitro and In Vivo Complex Stability.

We report the synthesis and evaluation of novel chelating agents for zirconium-89 (89Zr) with positron emission tomography (PET) imaging applications. New chelating agents NODHA, NOTHA, and NODHA-PY were constructed on 1,4,7-triazacyclononane (TACN) and possess hydroxamic acid or a pyridine ring as an acyclic binding moiety. The new chelating agents were theoretically studied for complexation with Zr(IV). Structures of Zr(IV)-NODHA, Zr(IV)-NOTHA, and Zr(IV)-NODHA-PY were predicted using density functional methods. NODHA was found to form stronger bonds with Zr(IV) when compared to NOTHA and NODHA-PY. The new chelating agents were evaluated for radiolabeling efficiency in binding 89Zr. The corresponding [89Zr]Zr-labeled chelators were evaluated for complex stability in human serum. All new chelating agents rapidly bound to 89Zr in excellent radiolabeling efficiency at room temperature. Among the new [89Zr]Zr-labeled chelators evaluated, [89Zr]Zr-NODHA showed the highest stability in human serum without losing 89Zr, and [89Zr]Zr-NODHA-PY released a considerable amount of 89Zr in human serum. [89Zr]Zr-NODHA, [89Zr]Zr-NODHA-PY, and [89Zr]Zr-DFO were comparatively evaluated for in vivo complex stability by performing biodistribution studies using normal mice. [89Zr]Zr-DFO had the lowest bone uptake at all time points, while [89Zr]Zr-NODHA-PY showed poor stability in mice as evidenced by high bone accumulation at the 24 h time point. [89Zr]Zr-NODHA exhibited better renal clearance but higher bone uptake than [89Zr]Zr-DFO.

Selective Acetylene Adsorption within an Imino-Functionalized Nanocage-Based Metal-Organic Framework.

Removal of CH4 and CO2 from C2H2 streams remains challenging in the chemical industry. Herein, a robust three-dimensional metal-organic framework, Cu-CPAH, was designed and synthesized through a hydrothermal method. Cu-CPAH exhibits highly selective C2H2 adsorption capacity with respect to both CH4 and CO2, which is ascribed to the enrichment of active sites in the framework. Dynamic breakthrough results reveal that Cu-CPAH serves as a solid adsorbent for high-efficiency purification of C2H2 from an equal proportion of C2H2/CO2 or C2H2/CO2/CH4 at room temperature. Discrete Fourier transform simulations confirm that various active sites preferentially interact with C2H2 other than CO2 and CH4, signifying for the first time that the imino functional groups in the cage contribute greatly to the preferential affinity to C2H2 over CO2 and CH4.

New Bifunctional Chelator 3p-C-NEPA for Potential Applications in Lu(III) and Y(III) Radionuclide Therapy and Imaging.

We have developed structurally unique bifunctional chelators in the NETA, NE3TA, and DEPA series for potential radiopharmaceutical applications. As part of our continued research efforts to generate efficient bifunctional chelators for targeted radionuclide therapy and imaging of various diseases, we designed a scorpion-like chelator that is proposed to completely saturate the coordination spheres of Y(III) and Lu(III). We herein report the synthesis and evaluation of a new chelator (3p-C-NEPA) with 10 donor groups for complexation with ß-emitting radionuclides 90Y(III), 86Y(III), and 177Lu(III). The chelator was synthesized and evaluated for radiolabeling kinetics with the readily available radioisotopes 90Y and 177Lu, and the corresponding 90Y or 177Lu-radiolabeled complexes were evaluated for in vitro stability in human serum and in vivo complex stability in mice. The new chelator rapidly bound 90Y or 177Lu and formed a stable complex with the radionuclides. The new chelator 3p-C-NEPA radiolabeled with either 90Y or 177Lu remains stable in human serum without dissociation for 10 days. 177Lu-labeled 3p-C-NEPA produced a favorable in vivo biodistribution profile in normal mice.

A stable nanoscaled Zr-MOF for the detection of toxic mycotoxin through a pH-modulated ratiometric luminescent switch.

A stable nanoscaled single-excitation ratiometric luminescent pH sensor (MPDB-PCN) over a broad pH range from 2.5 to 8.6 is fabricated through post-synthetic modification of PCN-224 with naphthalimide-derived molecules. Due to the rapid, sensitive and linear response to pH, MPDB-PCN is capable of detecting 3-nitropropionic acid (3-NPA), an acid neurotoxin in food safety, with a low detection limit of 15 µM in sugarcane juice.

Proteomic, functional and motif-based analysis of C-terminal Src kinase-interacting proteins.

C-terminal Src kinase (Csk) that functions as an essential negative regulator of Src family tyrosine kinases (SFKs) interacts with tyrosine-phosphorylated molecules through its Src homology 2 (SH2) domain, allowing it targeting to the sites of SFKs and concomitantly enhancing its kinase activity. Identification of additional Csk-interacting proteins is expected to reveal potential signaling targets and previously undescribed functions of Csk. In this study, using a direct proteomic approach, we identified 151 novel potential Csk-binding partners, which are associated with a wide range of biological functions. Bioinformatics analysis showed that the majority of identified proteins contain one or several Csk-SH2 domain-binding motifs, indicating a potentially direct interaction with Csk. The interactions of Csk with four proteins (partitioning defective 3 (Par3), DDR1, SYK and protein kinase C iota) were confirmed using biochemical approaches and phosphotyrosine 1127 of Par3 C-terminus was proved to directly bind to Csk-SH2 domain, which was consistent with predictions from in silico analysis. Finally, immunofluorescence experiments revealed co-localization of Csk with Par3 in tight junction (TJ) in a tyrosine phosphorylation-dependent manner and overexpression of Csk, but not its SH2-domain mutant lacking binding to phosphotyrosine, promoted the TJ assembly in Madin-Darby canine kidney cells, implying the involvement of Csk-SH2 domain in regulating cellular TJs. In conclusion, the newly identified potential interacting partners of Csk provided new insights into its functional diversity in regulation of numerous cellular events, in addition to controlling the SFK activity.

Synthesis of a 2D nitrogen-rich π-conjugated microporous polymer for high performance lithium-ion batteries.

Novel 2D graphene analogues with high conductivity are highly demanded as anode materials for lithium-ion batteries (LIBs). Here we report the preparation and characterization of a π-conjugated microporous polymer NGA-CMP with an experimental bandgap of 2.34 eV. Heated sample NGA-CMP400 is used for the first time as an anode material for LIBs. NGA-CMP400 achieves a high reversible capacity of 701 mA h g-1 at 1 A g-1 with extremely stable cycling performance over 500 cycles. The rational design of this kind of graphene-like 2D material with inherent porosity and enhanced electronic conductivity possesses important significance in carbon-based anode materials for LIBs.