Application of artificial intelligence in cancer diagnosis and tumor nanomedicine.

Cancer is a major health concern due to its high incidence and mortality rates. Advances in cancer research, particularly in artificial intelligence (AI) and deep learning, have shown significant progress. The swift evolution of AI in healthcare, especially in tools like computer-aided diagnosis, has the potential to revolutionize early cancer detection. This technology offers improved speed, accuracy, and sensitivity, bringing a transformative impact on cancer diagnosis, treatment, and management. This paper provides a concise overview of the application of artificial intelligence in the realms of medicine and nanomedicine, with a specific emphasis on the significance and challenges associated with cancer diagnosis. It explores the pivotal role of AI in cancer diagnosis, leveraging structured, unstructured, and multimodal fusion data. Additionally, the article delves into the applications of AI in nanomedicine sensors and nano-oncology drugs. The fundamentals of deep learning and convolutional neural networks are clarified, underscoring their relevance to AI-driven cancer diagnosis. A comparative analysis is presented, highlighting the accuracy and efficiency of traditional methods juxtaposed with AI-based approaches. The discussion not only assesses the current state of AI in cancer diagnosis but also delves into the challenges faced by AI in this context. Furthermore, the article envisions the future development direction and potential application of artificial intelligence in cancer diagnosis, offering a hopeful prospect for enhanced cancer detection and improved patient prognosis.

High-Efficiency Photo-Fenton-like Catalyst of FeOOH/g-C3N4 for the Degradation of PNP: Characterization, Catalytic Performance and Mechanism Exploration.

The composite photocatalyst FeOOH/g-C3N4 was prepared through thermal polycondensation and co-precipitation methods, followed by XRD, SEM and UV-vis characterization. The stability of FeOOH/g-C3N4 was explored by the recycling test. The active species in the reaction system were investigated by the capture experiment. The results indicated that the optimal preparation condition for g-C3N4 involved calcination at 600 °C for 4 h. XRD analysis revealed that g-C3N4 exhibits a high-purity phase, and Fe in FeOOH/g-C3N4 exists in a highly dispersed amorphous state. SEM analysis showed that FeOOH/g-C3N4 has a rough surface with an irregular layered structure. Element composition analysis confirmed that the content of elements in the prepared catalyst is consistent with the theoretical calculation. FeOOH/g-C3N4 possesses the largest specific surface area of 143.2 m2/g and a suitable pore distribution. UV-vis DRS analysis showed that the absorption intensity of FeOOH/g-C3N4 is stronger than that of g-C3N4. When the catalyst dosage was 1.0 g/L, the H2O2 dosage was 4 mmol/L, the PNP initial concentration was 10 mg/L and the initial pH value was 5, the PNP removal could reach 92% in 120 min. Even after 5 cycles, the efficiency of PNP removal by FeOOH/g-C3N4 remains nearly 80%. The capture experiment indicated that both •OH and •O2- play roles in the photocatalytic degradation of PNP, with •OH being more significant. These findings affirm that FeOOH has been successfully incorporated into g-C3N4, resulting in a conspicuous catalytic effect on the degradation of PNP in the visible light-assisted Fenton-like reaction.

Differentiation of glioma and solitary brain metastasis: a multi-parameter magnetic resonance imaging study using histogram analysis.

BACKGROUND: Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn't been fully investigated for the differentiation and may have the potential to improve it. METHODS: A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance. RESULTS: Higher ADCkurtosis (P = 0.022), frackurtosis (P<0.001),and fracskewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm)10 (P = 0.045), frac10 (P<0.001),frac90 (P = 0.001), fracmean (P<0.001), and fracentropy (P<0.001) were observed for SBM. frackurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm)10, frac10, and frackurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac10 and frackurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25). CONCLUSIONS: The frac10 and frackurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm)10 helps improving the differentiation specificity.

Image processing based modeling for Rosa roxburghii fruits mass and volume estimation.

The mass and volume of Rosa roxburghii fruits are essential for fruit grading and consumer selection. Physical characteristics such as dimension, projected area, mass, and volume are interrelated. Image-based mass and volume estimation facilitates the automation of fruit grading, which can replace time-consuming and laborious manual grading. In this study, image processing techniques were used to extract fruit dimensions and projected areas, and univariate (linear, quadratic, exponential, and power) and multivariate regression models were used to estimate the mass and volume of Rosa roxburghii fruits. The results showed that the quadratic model based on the criterion projected area (CPA) estimated the best mass (R2 = 0.981) with an accuracy of 99.27%, and the equation is M = 0.280 + 0.940CPA + 0.071CPA2. The multivariate regression model based on three projected areas (PA1, PA2, and PA3) estimated the best volume (R2 = 0.898) with an accuracy of 98.24%, and the equation is V = - 8.467 + 0.657PA1 + 1.294PA2 + 0.628PA3. In practical applications, cost savings can be realized by having only one camera position. Therefore, when the required accuracy is low, estimating mass and volume simultaneously from only the dimensional information of the side view or the projected area information of the top view is recommended.

Maximizing the Radiation Use Efficiency by Matching the Leaf Area and Leaf Nitrogen Vertical Distributions in a Maize Canopy: A Simulation Study.

The radiation use efficiency (RUE) is one of the most important functional traits determining crop productivity. The coordination of the vertical distribution of light and leaf nitrogen has been proven to be effective in boosting the RUE from both experimental and computational evidence. However, previous simulation studies have primarily assumed that the leaf area is uniformly distributed along the canopy depth, rarely considering the optimization of the leaf area distribution, especially for C4 crops. The present study hypothesizes that the RUE may be maximized by matching the leaf area and leaf nitrogen vertical distributions in the canopy. To test this hypothesis, various virtual maize canopies were generated by combining the leaf inclination angle, vertical leaf area distribution, and vertical leaf nitrogen distribution and were further evaluated by an improved multilayer canopy photosynthesis model. We found that a greater fraction of leaf nitrogen is preferentially allocated to canopy layers with greater leaf areas to maximize the RUE. The coordination of light and nitrogen emerged as a property from the simulations to maximize the RUE in most scenarios, particularly in dense canopies. This study not only facilitates explicit and precise profiling of ideotypes for maximizing the RUE but also represents a primary step toward high-throughput phenotyping and screening of the RUE for massive numbers of inbred lines and cultivars.

Unlocking Dynamic Solvation Chemistry and Hydrogen Evolution Mechanism in Aqueous Zinc Batteries.

Understanding the interfacial hydrogen evolution reaction (HER) is crucial to regulate the electrochemical behavior in aqueous zinc batteries. However, the mechanism of HER related to solvation chemistry remains elusive, especially the time-dependent dynamic evolution of the hydrogen bond (H-bond) under an electric field. Herein, we combine in situ spectroscopy with molecular dynamics simulation to unravel the dynamic evolution of the interfacial solvation structure. We find two critical change processes involving Zn-electroplating/stripping, including the initial electric double layer establishment to form an H2O-rich interface (abrupt change) and the subsequent dynamic evolution of an H-bond (gradual change). Moreover, the number of H-bonds increases, and their strength weakens in comparison with the bulk electrolyte under bias potential during Zn2+ desolvation, forming a diluted interface, resulting in massive hydrogen production. On the contrary, a concentrated interface (H-bond number decreases and strength enhances) is formed and produces a small amount of hydrogen during Zn2+ solvation. The insights on the above results contribute to deciphering the H-bond evolution with competition/corrosion HER during Zn-electroplating/stripping and clarifying the essence of electrochemical window widened and HER suppression by high concentration. This work presents a new strategy for aqueous electrolyte regulation by benchmarking the abrupt change of the interfacial state under an electric field as a zinc performance-enhancement criterion.

Remodeling of anti-tumor immunity with antibodies targeting a p53 mutant.

BACKGROUND: p53, the most frequently mutated gene in cancer, lacks effective targeted drugs. METHODS: We developed monoclonal antibodies (mAbs) that target a p53 hotspot mutation E285K without cross-reactivity with wild-type p53. They were delivered using lipid nanoparticles (LNPs) that encapsulate DNA plasmids. Western blot, BLI, flow cytometry, single-cell sequencing (scRNA-seq), and other methods were employed to assess the function of mAbs in vitro and in vivo. RESULTS: These LNP-pE285K-mAbs in the IgG1 format exhibited a robust anti-tumor effect, facilitating the infiltration of immune cells, including CD8+ T, B, and NK cells. scRNA-seq revealed that IgG1 reduces immune inhibitory signaling, increases MHC signaling from B cells to CD8+ T cells, and enriches anti-tumor T cell and B cell receptor profiles. The E285K-mAbs were also produced in the dimeric IgA (dIgA) format, whose anti-tumor activity depended on the polymeric immunoglobulin receptor (PIGR), a membrane Ig receptor, whereas that of IgG1 relied on TRIM21, an intracellular IgG receptor. CONCLUSIONS: Targeting specific mutant epitopes using DNA-encoded and LNP-delivered mAbs represents a potential precision medicine strategy against p53 mutants in TRIM21- or PIGR-positive cancers.

Improving resilience to high temperature in drought: water replenishment enhances sucrose and amino acid metabolisms in maize grain.

Heat stress poses a significant threat to maize, especially when combined with drought. Recent research highlights the potential of water replenishment to ameliorate grain weight loss. However, the mitigating mechanisms of heat in drought stress, especially during the crucial early grain-filling stage, remain poorly understood. We investigated the mechanism for mitigating heat in drought stress by water replenishment from the 12th to the 32nd days after silking in a controlled greenhouse experiment (Exp. I) and field trial (Exp. II). A significant reduction in grain weight was observed in heat stress compared to normal conditions. When water replenishment was applied to increase soil water content (SWC) under heat stress, the grain yield exhibited a notable increase ranging from 28.4 to 76.9%. XY335 variety was used for transcriptome sequencing to analyze starch biosynthesis and amino acid metabolisms in Exp. I. With water replenishment, the transcripts of genes responsible for trehalose 6-phosphate phosphates (TPP), alpha-trehalase (TRE), ADP-glcpyrophosphorylase, and starch synthase activity were stimulated. Additionally, the expression of genes encoding TPP and TRE contributed to an enhanced conversion of trehalose to glucose. This led to the conversion of sucrose from glucose-1-phosphate to ADP-glucose and ADP-glucose to amylopectin, ultimately increasing starch production by 45.1%. Water replenishment to boost SWC during heat stress also elevated the levels of essential amino acids in maize, including arginine, serine, tyrosine, leucine, glutamic acid, and methionine, providing valuable support to maize plants in adversity. Field trials further validated the positive impact of water replenishment on SWC, resulting in a notable increase in grain yield ranging from 7.1 to 9.2%. This study highlights the vital importance of adapting to abiotic stress and underscores the necessity of developing strategies to counteract its adverse effects on crop yield.

An ingestible near-infrared fluorescence capsule endoscopy for specific gastrointestinal diagnoses.

Early diagnosis of gastrointestinal (GI) diseases is important to effectively prevent carcinogenesis. Capsule endoscopy (CE) can address the pain caused by wired endoscopy in GI diagnosis. However, existing CE approaches have difficulty effectively diagnosing lesions that do not exhibit obvious morphological changes. In addition, the current CE cannot achieve wireless energy supply and attitude control at the same time. Here, we successfully developed a novel near-infrared fluorescence capsule endoscopy (NIFCE) that can stimulate and capture near-infrared (NIR) fluorescence images to specifically identify subtle mucosal microlesions and submucosal lesions while capturing conventional white light (WL) images to detect lesions with significant morphological changes. Furthermore, we constructed the first synergetic system that simultaneously enables multi-attitude control in NIFCE and supplies long-term power, thus addressing the issue of excessive power consumption caused by the NIFCE emitting near-infrared light (NIRL). We performed in vivo experiments to verify that the NIFCE can specifically "light up" tumors while sparing normal tissues by synergizing with probes actively aggregated in tumors, thus realizing specific detection and penetration. The prototype NIFCE system represents a significant step forward in the field of CE and shows great potential in efficiently achieving early targeted diagnosis of various GI diseases.

Optical Phenomena in Molecule-Based Magnetic Materials.

Since the last century, we have witnessed the development of molecular magnetism which deals with magnetic materials based on molecular species, i.e., organic radicals and metal complexes. Among them, the broadest attention was devoted to molecule-based ferro-/ferrimagnets, spin transition materials, including those exploring electron transfer, molecular nanomagnets, such as single-molecule magnets (SMMs), molecular qubits, and stimuli-responsive magnetic materials. Their physical properties open the application horizons in sensors, data storage, spintronics, and quantum computation. It was found that various optical phenomena, such as thermochromism, photoswitching of magnetic and optical characteristics, luminescence, nonlinear optical and chiroptical effects, as well as optical responsivity to external stimuli, can be implemented into molecule-based magnetic materials. Moreover, the fruitful interactions of these optical effects with magnetism in molecule-based materials can provide new physical cross-effects and multifunctionality, enriching the applications in optical, electronic, and magnetic devices. This Review aims to show the scope of optical phenomena generated in molecule-based magnetic materials, including the recent advances in such areas as high-temperature photomagnetism, optical thermometry utilizing SMMs, optical addressability of molecular qubits, magneto-chiral dichroism, and opto-magneto-electric multifunctionality. These findings are discussed in the context of the types of optical phenomena accessible for various classes of molecule-based magnetic materials.

Tuning Electron Delocalization of Redox-Active Porous Aromatic Framework for Low-Temperature Aqueous Zn-K Hybrid Batteries with Air Self-Chargeability.

Air self-charging aqueous batteries promise to integrate energy harvesting technology and battery systems, potentially overcoming a heavy reliance on energy and the spatiotemporal environment. However, the exploitation of multifunctional air self-charging battery systems using promising cathode materials and suitable charge carriers remains challenging. Herein, for the first time, we developed low-temperature self-charging aqueous Zn-K hybrid ion batteries (AZKHBs) using a fully conjugated hexaazanonaphthalene (HATN)-based porous aromatic framework as the cathode material, exhibiting redox chemistry using K+ as charge carriers, and regulating Zn-ion solvation chemistry to guide uniform Zn plating/stripping. The unique AZKHBs exhibit the exceptional electrochemical properties in all-climate conditions. Most importantly, the large potential difference causes the AZKHBs discharged cathode to be oxidized using oxygen, thereby initiating a self-charging process in the absence of an external power source. Impressively, the air self-charging AZKHBs can achieve a maximum voltage of 1.15 V, an impressive discharge capacity (466.3 mAh g-1), and exceptional self-charging performance even at -40 °C. Therefore, the development of self-charging AZKHBs offers a solution to the limitations imposed by the absence of a power grid in harsh environments or remote areas.

Chronopotentiometric Nanopore Sensor Based on a Stimulus-Responsive Molecularly Imprinted Polymer for Label-Free Dual-Biomarker Detection.

The development of sensors for detection of biomarkers exhibits an exciting potential in diagnosis of diseases. Herein, we propose a novel electrochemical sensing strategy for label-free dual-biomarker detection, which is based on the combination of stimulus-responsive molecularly imprinted polymer (MIP)-modified nanopores and a polymeric membrane chronopotentiometric sensor. The ion fluxes galvanostatically imposed on the sensing membrane surface can be blocked by the recognition reaction between the target biomarker in the sample solution and the stimulus-responsive MIP receptor in the nanopores, thus causing a potential change. By using two external stimuli (i.e., pH and temperature), the recognition abilities of the stimulus-responsive MIP receptor can be effectively modulated so that dual-biomarker label-free chronopotentiometric detection can be achieved. Using alpha fetoprotein (AFP) and prostate-specific antigen (PSA) as model biomarkers, the proposed sensor offers detection limits of 0.17 and 0.42 ng/mL for AFP and PSA, respectively.

Deep-learning assisted zwitterionic magnetic immunochromatographic assays for multiplex diagnosis of biomarkers.

Magnetic nanoparticle (MNP)-based immunochromatographic tests (ICTs) display long-term stability and an enhanced capability for multiplex biomarker detection, surpassing conventional gold nanoparticles (AuNPs) and fluorescence-based ICTs. In this study, we innovatively developed zwitterionic silica-coated MNPs (MNP@Si-Zwit/COOH) with outstanding antifouling capabilities and effectively utilised them for the simultaneous identification of the nucleocapsid protein (N protein) of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) and influenza A/B. The carboxyl-functionalised MNPs with 10% zwitterionic ligands (MNP@Si-Zwit 10/COOH) exhibited a wide linear dynamic detection range and the most pronounced signal-to-noise ratio when used as probes in the ICT. The relative limit of detection (LOD) values were achieved in 12 min by using a magnetic assay reader (MAR), with values of 0.0062 ng/mL for SARS-CoV-2 and 0.0051 and 0.0147 ng/mL, respectively, for the N protein of influenza A and influenza B. By integrating computer vision and deep learning to enhance the image processing of immunoassay results for multiplex detection, a classification accuracy in the range of 0.9672-0.9936 was achieved for evaluating the three proteins at concentrations of 0, 0.1, 1, and 10 ng/mL. The proposed MNP-based ICT for the multiplex diagnosis of biomarkers holds substantial promise for applications in both medical institutions and self-administered diagnostic settings.

Improvement of the selectivity of a molecularly imprinted polymer-based potentiometric sensor by using a specific functional monomer.

Potentiometric sensors based on the molecularly imprinted polymers (MIPs) as the receptors have been successfully developed for determination of various organic and biological species. However, these MIP receptors may suffer from problems of low selectivity. Especially, it would be difficult to distinguish the target analyte from its structurally similar interferents. In this work, we propose a novel strategy that using specific functional monomer to fabricate MIP with high selectivity towards the target molecule. The density functional theory calculations are used to investigate the interactions between the template and the functional monomer. The binding energy between the template and functional monomer can be used as the criterion for identifying the optimal monomer. As a proof-of-concept experiment, bisphenol A (BPA) is chosen as the template and the MIP is synthesized by the precipitation polymerization method using the specific allyl-ß-cyclodextrin (allyl-ß-CD) with high affinity towards BPA as the functional monomer. The high-affinity MIP is employed as the receptor for the construction of the potentiometric sensor. The proposed potentiometric sensor based on the MIP using allyl-ß-CD as the functional monomer shows an improved response performance in terms of selectivity and sensitivity compared to the conventional potentiometric sensor based on the MIP with the common monomer (i.e., methacrylic acid). This allyl-ß-CD MIP-based potentiometric sensor shows a detection limit of 0.29 µM for BPA, which is about one order of magnitude lower than that obtained by the conventional MIP-based potentiometric sensor. We believe that utilizing a functional monomer with specific recognition ability towards target in the fabrication of MIP could provide an appealing way to construct highly selective MIP-based electrochemical and optical sensors.

Visualizing and Regulating Dynamic Evolution of Interfacial Electrolyte Configuration during De-solvation Process on Lithium-Metal Anode.

Acting as a passive protective layer, solid-electrolyte interphase (SEI) plays a crucial role in maintaining the stability of the Li-metal anode. Derived from the reductive decomposition of electrolytes (e.g., anion and solvent), the SEI construction presents as an interfacial process accompanied by the dynamic de-solvation process during Li-metal plating. However, typical electrolyte engineering and related SEI modification strategies always ignore the dynamic evolution of electrolyte configuration at the Li/electrolyte interface, which essentially determines the SEI architecture. Herein, by employing advanced electrochemical in situ FT-IR and MRI technologies, we directly visualize the dynamic variations of solvation environments involving Li+-solvent/anion. Remarkably, a weakened Li+-solvent interaction and anion-lean interfacial electrolyte configuration have been synchronously revealed, which is difficult for the fabrication of anion-derived SEI layer. Moreover, as a simple electrochemical regulation strategy, pulse protocol was introduced to effectively restore the interfacial anion concentration, resulting in an enhanced LiF-rich SEI layer and improved Li-metal plating/stripping reversibility.

Serine/threonine-protein kinase D2-mediated phosphorylation of DSG2 threonine 730 promotes esophageal squamous cell carcinoma progression.

Desmoglein-2 (DSG2) is a transmembrane glycoprotein belonging to the desmosomal cadherin family, which mediates cell-cell junctions; regulates cell proliferation, migration, and invasion; and promotes tumor development and metastasis. We previously showed serum DSG2 to be a potential biomarker for the diagnosis of esophageal squamous cell carcinoma (ESCC), although the significance and underlying molecular mechanisms were not identified. Here, we found that DSG2 was increased in ESCC tissues compared with adjacent tissues. In addition, we demonstrated that DSG2 promoted ESCC cell migration and invasion. Furthermore, using interactome analysis, we identified serine/threonine-protein kinase D2 (PRKD2) as a novel DSG2 kinase that mediates the phosphorylation of DSG2 at threonine 730 (T730). Functionally, DSG2 promoted ESCC cell migration and invasion dependent on DSG2-T730 phosphorylation. Mechanistically, DSG2 T730 phosphorylation activated EGFR, Src, AKT, and ERK signaling pathways. In addition, DSG2 and PRKD2 were positively correlated with each other, and the overall survival time of ESCC patients with high DSG2 and PRKD2 was shorter than that of patients with low DSG2 and PRKD2 levels. In summary, PRKD2 is a novel DSG2 kinase, and PRKD2-mediated DSG2 T730 phosphorylation promotes ESCC progression. These findings may facilitate the development of future therapeutic agents that target DSG2 and DSG2 phosphorylation. © 2024 The Pathological Society of Great Britain and Ireland.

Huangqi-Guizhi-Wuwu decoction regulates differentiation of CD4+ T cell and prevents against experimental autoimmune encephalomyelitis progression in mice.

BACKGROUND: Multiple sclerosis (MS) is a demyelination disorder caused by an overactive immune response. Its pathological characteristics include CNS inflammation, white matter demyelination, glial cell proliferation, and so on. Huangqi-Guizhi-Wuwu Decoction (HGWD), which is recorded in the Synopsis of the Golden Chamber, is used clinically for the therapy of MS, but its mechanism is still elusive. PURPOSE: This study was aimed to investigate the impact of HGWD on the classical animal model for MS, experimental autoimmune encephalomyelitis (EAE), and explore the underlying action mechanism. RESULTS: HGWD ameliorated the pathogenesis of EAE mice, and improved their neurobehavior and pathological tissue damage. Network pharmacology predictions revealed the action mechanism of HGWD in EAE mice might be related to its effect on the immune system of mice. HGWD effectively suppressed the inflammatory infiltration in CNS, while also preventing the elevation of CD4+T cells of mice with EAE. HGWD could increase the ratio of Treg cells, up-regulate the secretion of IL-10 and Foxp3 mRNA expression, inhibit the ratio of Th1 and Th17 cells, down-regulate the IFN-γ and IL-17 protein expression, as well as the RORγT and T-bet gene expression in EAE mice. In addition, HGWD-containing serum modulated Th1/Th17/Treg cell differentiation in vitro. Moreover, HGWD inhibited the p-JAK1, p-JAK2, p-STAT1, p-STAT3 and p-STAT4 proteins and elevated the p-STAT5 protein in lymphoid tissues of EAE mice. CONCLUSION: HGWD improved the progress of EAE by regulating the proportion of CD4+T cell subtype differentiation, which might be exerted through JAK/STAT signaling pathway, providing a pharmacological basis for the clinical treatment of MS.

SHG-active luminescent thermometers based on chiral cyclometalated dicyanidoiridate(iii) complexes.

Multifunctional optical materials can be realized by combining stimuli-responsive photoluminescence (PL), e.g., optical thermometry, with non-linear optical (NLO) effects, such as second-harmonic generation (SHG). We report a novel approach towards SHG-active luminescent thermometers achieved by constructing unique iridium(iii) complexes, cis-[IrIII(CN)2(R,R-pinppy)2]- (R,R-pinppy = (R,R)-2-phenyl-4,5-pinenopyridine), bearing both a chiral 2-phenylpyridine derivative and cyanido ligands, the latter enabling the formation of a series of molecular materials: (TBA)[IrIII(CN)2(R,R-pinppy)2]·2MeCN (1) (TBA+ = tetrabutylammonium) and (nBu-DABCO)2[IrIII(CN)2(R,R-pinppy)2](i)·MeCN (2) (nBu-DABCO+ = 1-(n-butyl)-1,4-diazabicyclo-[2.2.2]octan-1-ium) hybrid salts, (TBA)2{[LaIII(NO3)3(H2O)0.5]2[IrIII(CN)2(R,R-pinppy)2]2} (3) square molecules, and {[LaIII(NO3)2(dmf)3][IrIII(CN)2(R,R-pinppy)2]}·MeCN (4) coordination chains. Thanks to the chiral pinene group, 1-4 crystallize in non-centrosymmetric space groups leading to SHG activity, while the N,C-coordination of ppy-type ligands to Ir(iii) centers generates visible charge-transfer (CT) photoluminescence. The PL characteristics are distinctly temperature-dependent which was utilized in achieving ratiometric optical thermometry below 220 K. The PL phenomena were rationalized by DFT/TD-DFT calculations indicating an MLCT-type of the emission in obtained Ir(iii) complexes with the rich vibronic structure providing a few emission bands that variously depend on temperature due to the role of thermally activated vibrations. As these crucial vibrational modes depend on the crystal lattice, the thermometry performance differs within 1-4 being the most efficient in 4 while the SHG is by far the best also for 4. This proves that pinene-functionalized cyclometalated dicyanidoiridates(iii) are great prerequisites for tunable PL-NLO conjunction with the most effective multifunctionality ensured by the insertion of these anions into bimetallic frameworks.

Amphiphilic Covalent Organic Framework Nanoparticles for Pickering Emulsion Catalysis with Size Selectivity.

Exploiting advanced amphiphilic solid catalysts is crucial to the development of Pickering emulsion catalysis. Herein, covalent organic framework (COF) nanoparticles constructed with highly hydrophobic monomers as linkers were found to show superior amphiphilicity and they were then developed as a new class of solid emulsifiers for Pickering emulsion catalysis. Employing amphiphilic COFs as solid emulsifiers, Pickering emulsions with controllable emulsion type and droplet sizes were obtained. COF materials have also been demonstrated to serve as porous surface coatings to replace traditional surface modifications for stabilizing Pickering emulsions. After implanting Pd nanoparticles into amphiphilic COFs, the obtained catalyst displayed a 3.9 times higher catalytic efficiency than traditional amphiphilic solid catalysts with surface modifications in the biphasic oxidation reaction of alcohols. Such an enhanced activity was resulted from the high surface area and regular porous structure of COFs. More importantly, because of their tunable pore diameters, Pickering emulsion catalysis with remarkable size selectivity was achieved. This work is the first example that COFs were applied in Pickering emulsion catalysis, providing a platform for exploring new frontiers of Pickering emulsion catalysis.

Can high-yielding maize system decrease greenhouse gas emissions largely while simultaneously enhancing economic and ecosystem benefits through the "Rhizobiont" concept? Evidence from field.

Ensuring high grain yields while minimizing environmental costs is a pressing imperative aligned with the Sustainable Development Goals (SDGs). In this study, we sought to establish a high-yielding maize system (HYMS) by implementing the innovative "Rhizobiont" concept for nutrient management, while substantially reducing greenhouse gas emissions. A 2-yr field study was conducted in a station of China Agriculture University (Wuqiao) with six treatments. The HYMS was established to achieve a harmonious equilibrium among genetic factors, environmental conditions, and management practices. HYMS demonstrated a significant boost in grain yield, averaging 12,706.6 kg ha-1 in 2021 and 13,676.4 kg ha-1 in 2022. These represented substantial increases of 25.6 % and 25.5 %, respectively, when compared to the current farmers practices (CP). More importantly, the N rate in HYMS was optimized to 148.2 kg ha-1 in 2021 and 138.0 kg ha-1 in 2022 with the implementation of the "Rhizobiont" concept. This represented a remarkable reduction of 35.5 % to 39.9 % in N application compared to CP. As a direct consequence, the measured cumulative emissions of greenhouse gases such as CO2, N2O, and CH4 in HYMS were notably decreased, showing reductions of 24.1 %, 36.0 %, and 7.0 %, respectively, compared to CP. Furthermore, the carbon intensity in HYMS was significantly reduced by 43.7 %. These considerable reductions in fertilizer use translated into tangible economic benefits (EB) and ecosystem economic benefit (EEB) in HYMS. EB was found to be 90.9 % higher, while EEB was 117.9 % higher than CP. These findings underscore the vast potential of HYMS and the "Rhizobiont" concept in promoting sustainable agriculture, with far-reaching implications for global food security and the well-being of smallholder farmers.