Forecasting rheumatoid arthritis patient arrivals by including meteorological factors and air pollutants.

The burden of rheumatoid arthritis (RA) has gradually elevated, increasing the need for medical resource redistribution. Forecasting RA patient arrivals can be helpful in managing medical resources. However, no relevant studies have been conducted yet. This study aims to construct a long short-term memory (LSTM) model, a deep learning model recently developed for novel data processing, to forecast RA patient arrivals considering meteorological factors and air pollutants and compares this model with traditional methods. Data on RA patients, meteorological factors and air pollutants from 2015 to 2022 were collected and normalized to construct moving average (MA)- and autoregressive (AR)-based and LSTM models. After data normalization, the root mean square error (RMSE) was adopted to evaluate models' forecast ability. A total of 2422 individuals were enrolled. Not using the environmental data, the RMSEs of the MA- and AR-based models' test sets are 0.131, 0.132, and 0.117 when the training set: test set ratio is 2:1, 3:1, and 7:1, while they are 0.110, 0.130, and 0.112 for the univariate LSTM models. Considering meteorological factors and air pollutants, the RMSEs of the MA- and AR-based model test sets were 0.142, 0.303, and 0.164 when the training set: test set ratio is 2:1, 3:1, and 7:1, while they were 0.108, 0.119, and 0.109 for the multivariable LSTM models. Our study demonstrated that LSTM models can forecast RA patient arrivals more accurately than MA- and AR-based models for datasets of all three sizes. Considering the meteorological factors and air pollutants can further improve the forecasting ability of the LSTM models. This novel method provides valuable information for medical management, the optimization of medical resource redistribution, and the alleviation of resource shortages.

The Multifunction of TRIM26: From Immune Regulation to Oncology.

Ubiquitination, a crucial post-translational modification, plays a role in nearly all physiological processes. Its functional execution depends on a series of catalytic reactions involving numerous proteases. TRIM26, a protein belonging to the TRIM family, exhibits E3 ubiquitin ligase activity because of its RING structural domain, and is present in diverse cell lineages. Over the last few decades, TRIM26 has been documented to engage in numerous physiological and pathological processes as a controller, demonstrating a diverse array of biological roles. Despite the growing research interest in TRIM26, there has been limited attention given to examining the protein's structure and function in existing reviews. This review begins with a concise overview of the composition and positioning of TRIM26 and then proceeds to examine its roles in immune response, viral invasion, and inflammatory processes. Simultaneously, we demonstrate the contribution of TRIM26 to the progression of various diseases, encompassing numerous malignancies and neurologic conditions. Finally, we have investigated the potential areas for future research on TRIM26.

Tough, self-healing, adhesive double network conductive hydrogel based on gelatin-polyacrylamide covalently bridged by oxidized sodium alginate for durable wearable sensors.

Pursuing high-performance conductive hydrogels is still hot topic in development of advanced flexible wearable devices. Herein, a tough, self-healing, adhesive double network (DN) conductive hydrogel (named as OSA-(Gelatin/PAM)-Ca, O-(G/P)-Ca) was prepared by bridging gelatin and polyacrylamide network with functionalized polysaccharide (oxidized sodium alginate, OSA) through Schiff base reaction. Thanks to the presence of multiple interactions (Schiff base bond, hydrogen bond, and metal coordination) within the network, the prepared hydrogel showed outstanding mechanical properties (tensile strain of 2800 % and stress of 630 kPa), high conductivity (0.72 S/m), repeatable adhesion performance and excellent self-healing ability (83.6 %/79.0 % of the original tensile strain/stress after self-healing). Moreover, the hydrogel-based sensor exhibited high strain sensitivity (GF = 3.66) and fast response time (<0.5 s), which can be used to monitor a wide range of human physiological signals. Based on this, excellent compression sensitivity (GF = 0.41 kPa-1 in the range of 90-120 kPa), a three-dimensional (3D) array of flexible sensor was designed to monitor the intensity of pressure and spatial force distribution. In addition, a gel-based wearable sensor was accurately classified and recognized ten types of gestures, achieving an accuracy rate of >96.33 % both before and after self-healing under three machine learning models (the decision tree, SVM, and KNN). This paper provides a simple method to prepare tough and self-healing conductive hydrogel as flexible multifunctional sensor devices for versatile applications in fields such as healthcare monitoring, human-computer interaction, and artificial intelligence.

Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network.

Segmentation of the coronary artery is an important task for the quantitative analysis of coronary computed tomography angiography (CCTA) images and is being stimulated by the field of deep learning. However, the complex structures with tiny and narrow branches of the coronary artery bring it a great challenge. Coupled with the medical image limitations of low resolution and poor contrast, fragmentations of segmented vessels frequently occur in the prediction. Therefore, a geometry-based cascaded segmentation method is proposed for the coronary artery, which has the following innovations: 1) Integrating geometric deformation networks, we design a cascaded network for segmenting the coronary artery and vectorizing results. The generated meshes of the coronary artery are continuous and accurate for twisted and sophisticated coronary artery structures, without fragmentations. 2) Different from mesh annotations generated by the traditional marching cube method from voxel-based labels, a finer vectorized mesh of the coronary artery is reconstructed with the regularized morphology. The novel mesh annotation benefits the geometry-based segmentation network, avoiding bifurcation adhesion and point cloud dispersion in intricate branches. 3) A dataset named CCA-200 is collected, consisting of 200 CCTA images with coronary artery disease. The ground truths of 200 cases are coronary internal diameter annotations by professional radiologists. Extensive experiments verify our method on our collected dataset CCA-200 and public ASOCA dataset, with a Dice of 0.778 on CCA-200 and 0.895 on ASOCA, showing superior results. Especially, our geometry-based model generates an accurate, intact and smooth coronary artery, devoid of any fragmentations of segmented vessels.

Forest carbon stocks increase with higher dominance of ectomycorrhizal trees in high latitude forests.

Understanding the mechanisms controlling forest carbon accumulation is crucial for predicting and mitigating future climate change. Yet, it remains unclear whether the dominance of ectomycorrhizal (EcM) trees influences the carbon accumulation of entire forests. In this study, we analyzed forest inventory data from over 4000 forest plots across Northeast China. We find that EcM tree dominance consistently exerts a positive effect on tree, soil, and forest carbon stocks. Moreover, we observe that these positive effects are more pronounced during unfavorable climate conditions, at lower tree species richness, and during early successional stages. This underscores the potential of increasing the dominance of native EcM tree species not only to enhance carbon stocks but also to bolster resilience against climate change in high-latitude forests. Here we show that forest managers can make informed decisions to optimize carbon accumulation by considering various factors such as mycorrhizal types, climate, successional stages, and species richness.

Survey of Heterodera glycines population abundance and virulence phenotypes during 2021-2022 in Heilongjiang Province.

Soybean cyst nematode (SCN), Heterodera glycines, poses a significant threat to global soybean production. Heilongjiang, the largest soybean-producing province in China, contributes over 40% to the country's total yield. This province has much longer history of SCN infestation. To assess the current situation in Heilongjiang, we conducted a survey to determine the SCN population density and virulence phenotypes during 2021-2022 and compared the data with a previous study in 2015. A total of 377 soil samples from 48 counties representing eleven major soybean-planting regions were collected. The prevalence of SCN increased from 55.4% in 2015 to 59% in the current survey. The population densities ranged from 80 to 26,700 eggs and juveniles per 100 cm3 of soil. Virulence phenotypes were evaluated for 60 representative SCN populations using the HG type test, revealing nine different HG types. The most common virulence phenotypes were HG types 7 and 0, accounting for 56.7% and 20% of all SCN populations, respectively. The prevalence of populations with a reproductive index (FI) greater than 10% on PI548316 increased from 64.5% in 2015 to 71.7%. However, the FI on the commonly used resistance sources PI 548402 (Peking) and PI 437654 remained low at 3.3%. These findings highlight the increasing prevalence and changing virulence phenotypes of SCN in Heilongjiang. They also emphasize the importance of rotating soybean varieties with different resistance sources and urgently identifying new sources of resistance to combat SCN.

Gastric Submucosal Fat Accumulation Is Associated with Insulin Resistance in Patients with Obesity.

PURPOSE: Ectopic fat accumulation plays a significant role in obesity-related metabolic dysfunction, and few studies have reported an association between ectopic gastric fat and metabolic risk factors. We aim to fulfill this need by assessing the degree of gastric submucosal fat accumulation in pathologic sections of 190 sleeve gastrectomy specimens. METHODS: Study patients were divided into two groups (D1 and D2) based on whether fat accumulation exceeded 1/3 of the submucosa of the stomach. Demographic and metabolic risk factors were compared between the two groups. Metabolic risk variables that might be associated with the degree of fat accumulation were screened in the original cohort. After balancing for possible confounders, the robustness of the correlations was assessed using binary and conditional logistic regression analyses. RESULTS: All study patients had fat accumulation in the submucosa of the stomach. C-reactive protein (CRP), body mass index (BMI), visceral fat area (VFA), and insulin resistance (IR) were higher in the D2 group than in the D1 group in the original cohort (P < 0.05). Logistic regression analysis showed that BMI and IR may be associated with increased fat accumulation. After balancing variables other than obesity indicators and IR using propensity score matching, BMI and IR remained significantly different between the two groups (P < 0.05). Further analysis of the matched cohort using two logistic regression analyses showed that IR was an independent risk factor for increased fat accumulation. CONCLUSION: This study indicated that gastric submucosal fat accumulation was prevalent in patients with obesity and was associated with IR.

Deep learning-derived spatial organization features on histology images predicts prognosis in colorectal liver metastasis patients after hepatectomy.

Histopathological images of colorectal liver metastases (CRLM) contain rich morphometric information that may predict patients' outcomes. However, to our knowledge, no study has reported any practical deep learning framework based on the histology images of CRLM, and their direct association with prognosis remains largely unknown. In this study, we developed a deep learning-based framework for fully automated tissue classification and quantification of clinically relevant spatial organization features (SOFs) in H&E-stained images of CRLM. The SOFs based risk-scoring system demonstrated a strong and robust prognostic value that is independent of the current clinical risk score (CRS) system in independent clinical cohorts. Our framework enables fully automated tissue classification of H&E images of CRLM, which could significantly reduce assessment subjectivity and the workload of pathologists. The risk-scoring system provides a time- and cost-efficient tool to assist clinical decision-making for patients with CRLM, which could potentially be implemented in clinical practice.

Dual-Cross-Linked Chitosan-Based Antibacterial Hydrogels with Tough and Adhesive Properties for Wound Dressing.

Biocompatible chitosan-based hydrogels have attracted extensive attention in wound dressing due to their human skin-like tissue characteristics. However, it is a crucial challenge to fabricate chitosan-based hydrogels with versatile properties, including flexibility, stretchability, adhesivity, and antibacterial activity. In this work, a kind of chitosan-based hydrogels with integrated functionalities are facilely prepared by solution polymerization of acrylamide (AAm) and sodium p-styrene sulfonate (SS) in the presence of quaternized carboxymethyl chitosan (QCMCS). Due to the dual cross-linking between QCMCS and P(AAm-co-SS), the optimized QCMCS/P(AAm-co-SS) hydrogel exhibits tough mechanical properties (0.767 MPa tensile stress and 1100% fracture strain) and moderate tissue adhesion (11.4 kPa). Moreover, biological evaluation in vitro illustrated that as-prepared hydrogel possesses satisfactory biocompatibility, hemocompatibility, and excellent antibacterial ability (against S. aureus and E. coli are 98.8% and 97.3%, respectively). Then, the hydrogels are tested in a rat model for bacterial infection incision in vivo, and the results show that they can significantly accelerate epidermal regeneration and wound closure. This is due to their ability to reduce the inflammatory response, promote the formation of collagen deposition and granulation tissue. The proposed chitosan-based antibacterial hydrogels have the potential to be a highly effective wound dressing in clinical wound healing.

Sulfoxide-Containing Bisabolane Sesquiterpenoids with Antimicrobial and Nematicidal Activities from the Marine-Derived Fungus Aspergillus sydowii LW09.

Phytopathogens, such as phytopathogenic bacteria, fungi, and nematodes, have caused great losses of crops every year, seriously threatening human health and agricultural production. Moreover, marine-derived fungi are abundant sources of structurally unique and bioactive secondary metabolites that could be potential candidates for anti-phytopathogenic drugs. One new sulfoxide-containing bisabolane sesquiterpenoid aspersydosulfoxide A (1) and nine known analogues (2-10) were isolated from the marine-derived A. sydowii LW09. The absolute configuration of the sulfur stereogenic center in 1 was determined by electronic circular dichroism (ECD) calculations. Compound 5 showed inhibition activity against Pseudomonas syringae, with a minimum inhibitory concentration (MIC) value of 32 µg/mL, whereas, compounds 2, 7, and 8 showed antibacterial activities toward Ralstonia solanacarum, with the same MIC value at 32 µg/mL. Meanwhile, compounds 3, 7, and 8 inhibited the fungal spore germination of Fusarium oxysporum, with the half maximal effective concentration (EC50) values of 54.55, 77.16, and 1.85 µg/mL, respectively, while compounds 2, 3, 7, and 8 inhibited the fungal spore germination of Alternaria alternata, which could be induced by vacuolization of germ tubes, with EC50 values of 34.04, 44.44, 26.02, and 46.15 µg/mL, respectively. In addition, compounds 3, 7, and 8 exhibited nematicidal activities against Meloidogyne incognita second-stage juveniles (J2s). In addition, compound 8 possessed the strongest nematicidal activity of nearly 80% mortality at 60 h with the half lethal concentration (LC50) values of 192.40 µg/mL. Furthermore, compounds 3, 7, and 8 could paralyze the nematodes and then impair their pathogenicity.

Hydrogel Complex Containing the Antimicrobial Peptide HX-12C Accelerates Healing of Infected Wounds.

Bacterial infections of the wound surface can be painful for patients, and traditional dressings do not effectively address this problem. In this study, an antimicrobial wound dressing is prepared using a novel antimicrobial peptide, HX-12C. This hydrogel system is based on the natural biomaterials sodium alginate and gelatin, utilizing calcium carbonate as a source of Ca2+ , and ionic cross-linking is facilitated by lowering the solution pH. The resulting sodium alginate/gelatin HX-12C-loaded hydrogel (CaAGEAM) has good mechanical and adhesion properties, biocompatibility and in vitro degradability. Its extraordinary antibacterial efficacy (>98%) is verified by an antibacterial experiment. More importantly, in vivo experiments further demonstrate its healing-promotion effect, with a 95% wound healing rate by day 9. Tissue staining demonstrates that the hydrogel containing antimicrobial peptides is effective in suppressing inflammation. The dressing promotes wound healing by stimulating the deposition of skin appendages and collagen. The results of this study suggest that composite hydrogels containing antimicrobial peptides are a promising new type of dressing to promote the healing of infected wounds.

Fully physical crosslinked BSA-based conductive hydrogels with high strength and fast self-recovery for human motion and wireless electrocardiogram sensing.

The emergence of protein hydrogel sensors has attracted intensive attention because of their biocompatibility and biodegradability, and potential application in wearable electronics. However, natural protein hydrogel sensors commonly exhibited low conductivity, weak mechanical strength, and unsatisfactory self-recovery performance. Herein, a fully physical crosslinked conductive BSA-MA-PPy/P(AM-co-AA)/Fe3+ hydrogel based on methacrylic anhydride (MA)-modified and polypyrrole (PPy)-functionalized bovine serum albumin (BSA) introduced into poly(acrylamide-co-acrylic acid) (P(AM-co-AA)) matrix was constructed. Due to the presence of the hydrogen bond complexation and the metal-ligand coordination between ferric ion (Fe3+) and the polymer chain, the as-prepared hydrogel showed outstanding mechanical strength (5.36 MPa tensile stress, 17.66 MJ/m3 toughness, and 1.61 MPa elastic modulus) and fast self-recovery performance (99.89 %/96.18 %/93.57 % stress/elastic modulus/dissipated energy within 10 min at room temperature). Meanwhile, the hydrogel exhibited outstanding conductivity (1.13 S/m) due to the presence of PPy and Fe3+ moieties, high strain sensitivity (GF = 4.98) and good biocompatibility without causing skin allergic reactions. Thus, the hydrogel can be fabricated into strain sensor to monitor the joint motion of the human body. Moreover, it can be used as soft electrode in electrocardiogram device to realize wireless heart-rate monitoring in the real-time conditions (relaxation and post-exercising), which exhibited excellent reusability, stability, and reliability simultaneously.

Advancements, challenges and future perspectives on peptide-based drugs: Focus on antimicrobial peptides.

Among other health related issues, the rising concerns on drug resistance led to look for alternative pharmaceutical drugs that are effective both against infectious and noninfectious diseases. Antimicrobial peptides (AMPs) emerged as potential therapeutic molecule with wide range of applications. With their limitations, AMPs have gained reputable attentions in research as well as in the pharmaceutical industry. This review highlighted the historical background, research trends, technological advancements, challenges, and future perspectives in the development and applications of peptide drugs. Some vital questions related with the need for pharmaceutical production, factors for the slow and steady journey, the importance of oral bioavailability, and the drug resistance possibilities of AMPs were raised and addressed accordingly. Therefore, the current study is believed to provide a profound understanding in the past and current scenarios and future directions on the therapeutic impacts of peptide drugs.

Phaeosphaeridiols A-C: Three New Compounds from Undescribed Phaeosphaeriaceae sp. SGSF723.

Fungi in forest litter are diverse as decomposers but natural products from these fungi are rarely investigated, especially for their antimicrobial activities against crop diseases. In this study, fungal isolate SGSF723 with antimicrobial activities was cultured. A multi-gene phylogenetic analysis showed SGSF723 was an undescribed species in the family Phaeosphaeriaceae. By bio-guided assay, three new compounds (Phaeosphaeridiols A-C) and two known compounds were purified from the ethyl acetate extract. The structures of Phaeosphaeridiols A-C were elucidated as 2-(2'-butenyl)-5 (3″-pentene)-1,3-benzenediol (1), 2-(2'-butenyl)-5-(3″S,4″S-pentane diol)-1,3-benzenediol (2), and 3-(4'-(2″-butenyl)-3',5'-benzenediol phenol)-2-acrylic acid (3) by 2D NMR, HRESIMS, and Mosher's method. Phaeosphaeridiols A-C exhibited moderate or weak antimicrobial activities against plant pathogens by 96-well plate and spore germination assays.

Synthesis of Co3O4 Nanoplates by Thermal Decomposition for the Colorimetric Detection of Dopamine.

Inorganic nanomaterials with enzyme-like activity have been attracting much attention due to their low cost, favorable stability, convenient storage, and simple preparation. Herein, Co3O4 nanoplates with a uniform nanostructure were prepared by the thermolysis of cobalt hydroxide at different temperatures, and the influence of the annealing temperature on the performance of the mimetic enzyme also was reported for the first time. The results demonstrated that Co3O4 nanoplates obtained at an annealing temperature of 200 °C possessed strong oxidase activity and efficiently catalyzed the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) without the addition of hydrogen peroxide to generate the blue color product ox-TMB. Once the annealing temperature was increased to 500 °C and 800 °C, the oxidase activity of Co3O4 decreased rapidly, and was even inactivated. This might be attributed to the relatively large specific surface area of Co3O4 annealed at 200 °C. Besides this, based on the TMB-Co3O4 nanoplate system, a colorimetric analysis method was developed to detect dopamine with a limit of 0.82 µmol/L in a linear range from 1.6 µmol/L to 20 µmol/L.

Parametarhizium hingganense, a Novel Ectomycorrhizal Fungal Species, Promotes the Growth of Mung Beans and Enhances Resistance to Disease Induced by Rhizoctonia solani.

The mutualistic interactions between mycorrhizae and plants first occurred along with the terrestrialization of plants. The majority of vascular plants are in symbiosis with mycorrhizal fungi. Due to their importance to the economy and ecology, arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi emerge as the most popular ones. However, the mechanism underlying the beneficial function of ECM fungi is not as clear as AM fungi. Here, the interaction between Parametarhizium hingganense, a novel fungal species isolated from forest litter, and mung bean (Vigna radiata) was studied. P. hingganense demonstrated P solubilization ability in vitro. Treatment of P. hingganense on the seeds resulted in promoted growth with enhanced P content. The hyphae of green fluorescence protein (GFP)-tagged P. hingganense were found to surround the roots and develop between cells, suggesting the establishment of an ectomycorrhizal symbiosis. Upon symbiosis with P. hingganense, the levels of jasmonic acid (JA) and gibberellin (GA1) and total phenolic and flavonoid content elevated. Meanwhile, damping off caused by Rhizoctonia solani in mycorrhizal plants was alleviated. Taken together, the above findings suggested that symbiosis with P. hingganense conferred growth promotion and priming of defense responses to host plants which should be associated with facilitated P uptake and increased JA and GA1 levels.

Preparation of Copper Nanoplates in Aqueous Phase and Electrochemical Detection of Dopamine.

Compared with gold and silver, cheap copper has attracted more attention and can potentially be applied in non-enzymatic electrochemical sensors due to its excellent conductivity and catalytic activity. In this paper, copper nanoplates were rapidly synthesized using copper bromide as the copper precursor, polyethyleneimine as the stabilizer, and ascorbic acid as a reducing agent in the presence of silver nanoparticles at a reaction temperature of 90 °C. The Cu nanoplates with an average side length of 10.97 ± 3.45 µm were obtained after a short reaction time of 2 h, demonstrating the promoting effect of an appropriate amount of silver nanoparticle on the synthesis of Cu nanoplates. Then, the electrochemical dopamine sensor was constructed by modifying a glass carbon electrode (GCE) with the Cu nanoplates. The results obtained from the test of cyclic voltammetry and chronoamperometry indicated that the Cu-GCE showed a significant electrochemical response for the measurement of dopamine. The oxidation peak current increased linearly with the concentration of dopamine in the range of 200 µmol/L to 2.21 mmol/L, and the corresponding detection limit was calculated to be 62.4 µmol/L (S/N = 3). Furthermore, the anti-interference test showed that the dopamine sensor was not affected by a high concentration of ascorbic acid, glucose, uric acid, etc. Therefore, the constructed Cu-GCE with good selectivity, sensitivity, and stability possesses a high application value in the detection of dopamine.

NOL6 Regulates the Proliferation and Apoptosis of Gastric Cancer Cells via Regulating TP53I3, CDK4 and MCM7 Expression.

Background: Gastric cancer (GC) is a prevalent cancer with high mortality and strong invasiveness, and the entire regulatory networks of GC is still unclear. Objective: The aim of this study was to explore the specific mechanism of the effect of nucleolar protein 6 (NOL6) on the proliferation and apoptosis of GC cells. Methods: The human gastric adenocarcinoma cell line HGC-27 and AGS were cultured. qRT-PCR was used to verify the expression level of NOL6 in GC cells; MTT and EdU were used to test cell proliferation; TUNEL staining and Flow cytometry were used to detect cell apoptosis; The downstream genes and pathways following NOL6 knockdown were explored through the microarray assay and ingenuity pathway analysis, and the downstream genes were finally verified by qRT-PCR and Western blotting. The xenograft mice were used to investigate the effect of NOL6 on GC in vivo. Results: TCGA data analysis showed that NOL6 expression level was higher in GC cells than adjacent normal cells. Over-expression of NOL6 increased proliferation and colony formation, and inhibited the apoptotic rate in AGS and HGC-27 cells, while NOL6 knockdown induced the opposite effects. Through microarray assay and IPA analysis, NOL6-related downstream genes and critical signaling pathways were found. And we verified the relationship between downstream genes and GC. Additionally, NOL6 knockdown could decrease the weight and volume of tumor in the mice. Conclusion: NOL6 knockdown could inhibit cell proliferation and induce cell apoptosis of GC, suggesting that NOL6 may serve as a potential therapeutic target for treating GC.

Ultrasensitive, label-free voltammetric determination of norfloxacin based on molecularly imprinted polymers and Au nanoparticle-functionalized black phosphorus nanosheet nanocomposite.

Norfloxacin (NOR) is an antibiotic commonly used to treat humans and food-producing animals. Owing to NOR abuse, its residues are frequently found in animal-derived food products and the surrounding environment. Therefore, development of an efficient analytical technique for the selective determination of trace NOR is greatly significant for food safety and environmental protection. Here, we fabricated an ultrasensitive, label-free molecularly imprinted polymer (MIP) voltammetric sensor for the selective determination of NOR, based on an Au nanoparticle-functionalized black phosphorus nanosheet nanocomposite (BPNS-AuNP) covered by a polypyrrole-imprinted film. BPNS-AuNP nanocomposites were prepared via an in-situ one-step method without the use of reducing agents. The imprinted polypyrrole film was formed on the surface of the BPNS-AuNPs in the presence of NOR. The physical properties and electrochemical behavior of the MIP/BPNS-AuNPs were investigated using various characterization techniques, and the analytical parameters were optimized. We found that BPNS-AuNPs improve the ambient stability and electrocatalytic activity, providing a large surface area for locating a higher number of specific recognition sites. Consequently, the MIP/BPNS-AuNP/GCE showed excellent sensing performance toward NOR, with a wide linear response range (0.1 nM - 10 µM), an extremely low limit of detection (0.012 nM), and extraordinary selectivity. Moreover, the MIP/BPNS-AuNP/GCE was used to determine NOR in various experimental samples with satisfactory results.

Tough, Self-Recoverable, Spiropyran (SP3) Bearing Polymer Beads Incorporated PAM Hydrogels with Sole Mechanochromic Behavior.

Spiropyran-containing hydrogels that can respond to external stimuli such as temperature, light, and stress have attracted extensive attention in recent years. However, most of them are generally dual or multiple stimuli-responsive to external stimuli, and the interplay of different stimulus responses is harmful to their sensitivity. Herein, spiropyran bearing polymer beads incorporated PAM (poly(AM-co-MA/DMSP3)) hydrogels with sole mechanochromic properties were synthesized by emulsion polymerization of acrylamide (AM) and methyl acrylate (MA) in the presence of spiropyran dimethacrylate mechanophore (DMSP3) crosslinker. Due to the hydrophobic nature of MA and DMSP3, the resultant hydrogel afforded a rosary structure with DMSP3 bearing polymer beads incorporated in the PAM network. It is found that the chemical component (e.g., AM, MA, and DMSP3 concentrations) significantly affect the mechanical and mechanoresponsive properties of the as-obtained poly(AM-co-MA/DMSP3) hydrogel. Under optimal conditions, poly(AM-co-MA/DMSP3) hydrogel displayed high mechanical properties (tensile stress of 1.91 MPa, a tensile strain of 815%, an elastic modulus of 0.67 MPa, and tearing energy of 3920 J/m2), and a good self-recovery feature. Owing to the mechanoresponsive of SP3, the hydrogels exhibited reversible color changes under force-induced deformation and relaxed recovery states. More impressive, the poly(AM-co-MA/DMSP3) hydrogel showed a linear correlation between tensile strain and chromaticity (x, y) as well as a stain and resting time-dependent color recovery rate. This kind of hydrogel is believed to have great potential in the application of outdoor strain sensors.