Exosome-Mediated Communication in Thyroid Cancer: Implications for Prognosis and Therapeutic Targets.

Thyroid cancer (THCA) is one of the most common malignancies of the endocrine system. Exosomes have significant value in performing molecular treatments, evaluating the diagnosis and determining tumor prognosis. Thus, the identification of exosome-related genes could be valuable for the diagnosis and potential treatment of THCA. In this study, we examined a set of exosome-related differentially expressed genes (DEGs) (BIRC5, POSTN, TGFBR1, DUSP1, BID, and FGFR2) by taking the intersection between the DEGs of the TCGA-THCA and GeneCards datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the exosome-related DEGs indicated that these genes were involved in certain biological functions and pathways. Protein‒protein interaction (PPI), mRNA‒miRNA, and mRNA-TF interaction networks were constructed using the 6 exosome-related DEGs as hub genes. Furthermore, we analyzed the correlation between the 6 exosome-related DEGs and immune infiltration. The Genomics of Drug Sensitivity in Cancer (GDSC), the Cancer Cell Line Encyclopedia (CCLE), and the CellMiner database were used to elucidate the relationship between the exosome-related DEGs and drug sensitivity. In addition, we verified that both POSTN and BID were upregulated in papillary thyroid cancer (PTC) patients and that their expression was correlated with cancer progression. The POSTN and BID protein expression levels were further examined in THCA cell lines. These findings provide insights into exosome-related clinical trials and drug development.

Combined application of mesenchymal stem cells and different glucocorticoid dosing alleviates osteoporosis in SLE murine models.

OBJECTIVE: Bone mesenchymal stem cells (BMSCs) have been tentatively applied in the treatment of glucocorticoid-induced osteoporosis (GIOP) and systemic lupus erythematosus (SLE). However, the effects of BMSCs on osteoporosis within the context of glucocorticoid (GC) application in SLE remain unclear. Our aim was to explore the roles of BMSCs and different doses of GC interventions on osteoporosis in SLE murine models. METHODS: MRL/MpJ-Faslpr mice were divided into eight groups with BMSC treatment and different dose of GC intervention. Three-dimensional imaging analysis and hematoxylin and eosin (H&E) staining were performed to observe morphological changes. The concentrations of osteoprotegerin (OPG) and receptor activator of nuclear factor κB ligand (RANKL) in serum were measured by enzyme-linked immunosorbent assay (ELISA). The subpopulation of B cells and T cells in bone marrows and spleens were analyzed by flow cytometry. Serum cytokines and chemokines were assessed using Luminex magnetic bead technology. RESULTS: BMSCs ameliorated osteoporosis in murine SLE models by enhancing bone mass, improving bone structure, and promoting bone formation through increased bone mineral content and optimization of trabecular morphology. BMSC and GC treatments reduced the number of B cells in bone marrows, but the effect was not significant in spleens. BMSCs significantly promoted the expression of IL-10 while reducing IL-18. Moreover, BMSCs exert immunomodulatory effects by reducing Th17 expression and rectifying the Th17/Treg imbalance. CONCLUSION: BMSCs effectively alleviate osteoporosis induced by SLE itself, as well as osteoporosis resulting from SLE combined with various doses of GC therapy. The therapeutic effects of BMSCs appear to be mediated by their influence on bone marrow B cells, T cell subsets, and associated cytokines. High-dose GC treatment exerts a potent anti-inflammatory effect but may hinder the immunotherapeutic potential of BMSCs. Our research may offer valuable guidance to clinicians regarding the use of BMSC treatment in SLE and provide insights into the judicious use of GCs in clinical practice.

Role of high-frequency ultrasound in differentiating benign and malignant skin lesions: potential and limitations.

PURPOSE: This study examined the diagnostic value of high-frequency ultrasound (HFUS) features in differentiating between benign and malignant skin lesions. METHODS: A total of 1,392 patients with 1,422 skin lesions who underwent HFUS examinations were included in an initial dataset (cohort 1) to identify features indicative of malignancy. Qualitative clinical and HFUS characteristics were recorded for all lesions. To determine which HFUS and clinical features were suggestive of malignancy, univariable and multivariable logistic regression analyses were employed. The diagnostic performance of HFUS features combined with clinical information was evaluated. This assessment was validated using internal data (cohort 2) and multicenter external data (cohort 3). RESULTS: Features significantly associated with malignancy included age above 60 years; lesion location in the head, face, and neck or genital regions; changes in macroscopic appearance; crawling or irregular growth pattern; convex or irregular base; punctate hyperechogenicity; blood flow signals; and feeding arteries. The area under the receiver operating characteristic curve, sensitivity, and specificity of HFUS features combined with clinical information were 0.946, 92.5%, and 86.9% in cohort 1; 0.870, 93.1%, and 80.8% in cohort 2 (610 lesions); and 0.864, 86.2%, and 86.6% in cohort 3 (170 lesions), respectively. However, HFUS is not suitable for evaluating lesions less than 0.1 mm in thickness or lesions exhibiting surface hyperkeratosis. CONCLUSION: In a clinical setting, the integration of HFUS with clinical information exhibited good diagnostic performance in differentiating malignant and benign skin lesions. However, its utility was limited in evaluating extremely thin lesions and those exhibiting hyperkeratosis.

Loss of NAT10 alleviates maternal high-fat diet-induced hepatic steatosis in male offspring of mice.

OBJECTIVE: Metabolic dysfunction-associated steatotic liver disease (MASLD) is becoming an escalating health problem in pediatric populations. This study aimed to investigate the role of N-acetyltransferase 10 (NAT10) in maternal high-fat diet (HFD)-induced MASLD in offspring at early life. METHODS: We generated male hepatocyte-specific NAT10 knockout (Nat10HKO) mice and mated them with female Nat10fl/fl mice under chow or HFD feeding. Body weight, liver histopathology, and expression of lipid metabolism-associated genes (Srebp1c, Fasn, Pparα, Cd36, Fatp2, Mttp, and Apob) were assessed in male offspring at weaning. Lipid uptake assays were performed both in vivo and in vitro. The mRNA stability assessment and RNA immunoprecipitation were performed to determine NAT10-regulated target genes. RESULTS: NAT10 deletion in hepatocytes of male offspring alleviated perinatal lipid accumulation induced by maternal HFD, decreasing expression levels of Srebp1c, Fasn, Cd36, Fatp2, Mttp, and Apob while enhancing Pparα expression. Furthermore, Nat10HKO male mice exhibited reduced lipid uptake. In vitro, NAT10 promoted lipid uptake by enhancing the mRNA stability of CD36 and FATP2. RNA immunoprecipitation assays exhibited direct interactions between NAT10 and CD36/FATP2 mRNA. CONCLUSIONS: NAT10 deletion in offspring hepatocytes ameliorates maternal HFD-induced hepatic steatosis through decreasing mRNA stability of CD36 and FATP2, highlighting NAT10 as a potential therapeutic target for pediatric MASLD.

Engineering a far-red fluorescent probe for rapid detection of Hg(II) ions in both cells and zebrafish.

Abnormal accumulation of mercury ions (Hg2+) in organisms can lead to severe central nervous system and other diseases. Therefore, the monitoring and detection of Hg2+ are of great significance for human health and environmental safety. Herein, we designed and synthesized a novel far-red to NIR emission fluorescent probe (Rho-Hg) based on rhodamine derivative as the fluorophore and thiospirolactone as the recognition site for turn-on detecting of Hg2+ in living cells and zebrafish. The probe Rho-Hg displayed superior sensitivity (detection limit = 17.5 nM), rapid response (<1 min), colorimetric change, high selectivity, and moderate pH stability. Leveraging this probe, we realized the real-time monitoring of Hg2+ in real samples, living cells and zebrafish. By fostering zebrafish embryos and larvae in Hg2+-containing nutrient solution, we noticed that Hg2+ was ingested into the zebrafish liver when zebrafish were grown up to 3 days old, and thus we successfully monitored the accumulation and changes of Hg2+ during zebrafish growth and development. Thus, the probe Rho-Hg could be a powerful tool for sensitive and real-time monitoring of Hg2+ in living systems.

A Large-Scale and Low-Cost Thermoacoustic Loudspeaker Based on Three-Dimensional Graphene Foam.

Graphene is a promising material for thermoacoustic sources due to its extremely low heat capacity per unit area and high thermal conductivity. However, current graphene thermoacoustic devices have limited device area and relatively high cost, which limit their applications of daily use. Here, we adopt a dip-coating method to fabricate a large-scale and cost-effective graphene sound source. This sound source has the three-dimensional (3D) porous structure that can increase the contact area between graphene and air, thus assisting heat to release into the air. In this method, polyurethane (PU) is used as a support, and graphene nanoplates are attached onto the PU skeleton so that a highly flexible graphene foam (GrF) device is obtained. At a measuring distance of 1 mm, it can emit sound at up to 70 dB under the normalized input power of 1 W. Considering its unique porous structure, we establish a thermoacoustic analysis model to simulate the acoustic performance of GrF. Furthermore, the obtained GrF can be made up to 44 in. (100 cm × 50 cm) in size, and it has good flexibility and processability, which broadens the application fields of GrF loudspeakers. It can be attached to the surfaces of objects with different shapes, making it suitable to be used as a large-area speaker in automobiles, houses, and other application scenarios, such as neck mounted speaker. In addition, it can also be widely used as a fully flexible in-ear earphone.

Differentiation and quantification of extracellular polymeric substances from microalgae and bacteria in the mixed culture.

Extracellular polymeric substances (EPS) play significant roles in the formation, function, and interactions of microalgal-bacteria consortia. Understanding the key roles of EPS depends on reliable extraction and quantification methods, but differentiating of EPS from microalgae versus bacteria is challenging. In this work, cation exchange resin (CER) and thermal treatments were applied for total EPS extraction from microalgal-bacteria mixed culture (MBMC), flow cytometry combined with SYTOX Green staining was applied to evaluate cell disruption during EPS extraction, and auto-fluorescence-based cell sorting (AFCS) was used to separate microalgae and bacteria in the MBMC. Thermal extraction achieved much higher EPS yield than CER, but higher temperature and longer time reduced cell activity and disrupted the cells. The highest EPS yield with minimal loss of cell activity and cell disruption was achieved using thermal extraction at 55℃ for 30 min, and this protocol gave good results for MBMC with different microalgae:bacteria (M:B) mass ratios. AFCS combined with thermal treatment achieved the most-efficient biomass differentiation and low EPS loss (<4.5 %) for the entire range of M:B ratios. EPS concentrations in bacteria were larger than in microalgae: 42.8 ± 0.4 mg COD/g TSS versus 9.19 ± 0.38 mg COD/g TSS. These findings document sensitive and accurate methods to extract and quantify EPS from microalgal-bacteria aggregates.

Rational Design of NIR-II G-Quadruplex Fluorescent Probes for Accurate In Vivo Tumor Metastasis Imaging.

Accurate in vivo imaging of G-quadruplexes (G4) is critical for understanding the emergence and progression of G4-associated diseases like cancer. However, existing in vivo G4 fluorescent probes primarily operate within the near-infrared region (NIR-I), which limits their application accuracy due to the short emission wavelength. The transition to second near-infrared (NIR-II) fluorescent imaging has been of significant interest, as it offers reduced autofluorescence and deeper tissue penetration, thereby facilitating more accurate in vivo imaging. Nonetheless, the advancement of NIR-II G4 probes has been impeded by the absence of effective probe design strategies. Herein, through a "step-by-step" rational design approach, we have successfully developed NIRG-2, the first small-molecule fluorescent probe with NIR-II emission tailored for in vivo G4 detection. Molecular docking calculations reveal that NIRG-2 forms stable hydrogen bonds and strong π-π interactions with G4 structures, which effectively inhibit twisted intramolecular charge transfer (TICT) and, thereby, selectively illuminate G4 structures. Due to its NIR-II emission (940 nm), large Stokes shift (90 nm), and high selectivity, NIRG-2 offers up to 47-fold fluorescence enhancement and a tissue imaging depth of 5 mm for in vivo G4 detection, significantly outperforming existing G4 probes. Utilizing NIRG-2, we have, for the first time, achieved high-contrast visualization of tumor metastasis through lymph nodes and precise tumor resection. Furthermore, NIRG-2 proves to be highly effective and reliable in evaluating surgical and drug treatment efficacy in cancer lymphatic metastasis models. We are optimistic that this study not only provides a crucial molecular tool for an in-depth understanding of G4-related diseases in vivo but also marks a promising strategy for the development of clinical NIR-II G4-activated probes.

Dried Blood Spots and Miniaturized Ultrasonic Nebulization Microplasma Optical Emission Spectrometry for Point-of-Care Testing of Blood Lithium.

Despite the significant importance of blood lithium (Li) detection in the treatment of bipolar disorder (BD), its point-of-care testing (POCT) remains a great challenge due to tedious sample preparation and the use of large-footprint atomic spectrometers. Herein, a system coupling dried blood spots (DBS) with a point discharge optical emission spectrometer equipped with a miniaturized ultrasonic nebulizer (MUN-µPD-OES) was developed for POCT of blood Li. Three microliters of whole blood were used to prepare a dried blood spot on a piece of filter paper to which 10 µL of eluent (1% (v/v) formic acid and 0.05% (v/v) Triton-X) was added. Subsequently, the paper was placed onto the vibrating steel membrane of the ultrasonic nebulizer and powered on to generate aerosol. The aerosol was directly introduced to the µPD-OES for quantification of Li by monitoring its atomic emission line at 670.8 nm. The proposed method minimized matrix interference caused by high levels of salts and protein. It is worth noting that the MUN suitably matches the needs of DBS sampling and can provide aerosolized introduction of Li into the assembled µPD-OES, thus eliminating all tedious sample preparation and the need for a commercial atomic spectrometer. Calibration response is linear in the therapeutic range and a limit of detection (LOD) of 1.3 µg L-1 is well below the Li minimum therapeutic concentration (2800 µg L-1). Li in mouse blood was successfully detected in real-time using MUN-µPD-OES after intraperitoneal injection of lithium carbonate, confirming that the system holds great potential for POCT of blood Li for patients with BD.

Machine Learning-Assisted Portable Microplasma Optical Emission Spectrometer for Food Safety Monitoring.

To meet the needs of food safety for simple, rapid, and low-cost analytical methods, a portable device based on a point discharge microplasma optical emission spectrometer (µPD-OES) was combined with machine learning to enable on-site food freshness evaluation and detection of adulteration. The device was integrated with two modular injection units (i.e., headspace solid-phase microextraction and headspace purge) for the examination of various samples. Aromas from meat and coffee were first introduced to the portable device. The aroma molecules were excited to specific atomic and molecular fragments at excited states by room temperature and atmospheric pressure microplasma due to their different atoms and molecular structures. Subsequently, different aromatic molecules obtained their own specific molecular and atomic emission spectra. With the help of machine learning, the portable device was successfully applied to the assessment of meat freshness with accuracies of 96.0, 98.7, and 94.7% for beef, pork, and chicken meat, respectively, through optical emission patterns of the aroma at different storage times. Furthermore, the developed procedures can identify beef samples containing different amounts of duck meat with an accuracy of 99.5% and classify two coffee species without errors, demonstrating the great potential of their application in the discrimination of food adulteration. The combination of machine learning and µPD-OES provides a simple, portable, and cost-effective strategy for food aroma analysis, potentially addressing field monitoring of food safety.

TGF-ß1-triggered BMI1 and SMAD2 cooperatively regulate miR-191 to modulate bone formation.

Transforming growth factor ß 1 (TGF-ß1), as the most abundant signaling molecule in bone matrix, is essential for bone homeostasis. However, the signaling transduction of TGF-ß1 in the bone-forming microenvironment remains unknown. Here, we showed that microRNA-191 (miR-191) was downregulated during osteogenesis and further decreased by osteo-favoring TGF-ß1 in bone marrow mesenchymal stem cells (BMSCs). MiR-191 was lower in bone tissues from children than in those from middle-aged individuals and it was negatively correlated with collagen type I alpha 1 chain (COL1A1). MiR-191 depletion significantly increased osteogenesis and bone formation in vivo. Hydrogels embedded with miR-191-low BMSCs displayed a powerful bone repair effect. Mechanistically, transcription factors BMI1 and SMAD2 coordinately controlled miR-191 level. In detail, BMI1 and pSMAD2 were both upregulated by TGF-ß1 under osteogenic condition. SMAD2 activated miR-191 transcription, while BMI1 competed with SMAD2 for binding to miR-191 promoter region, thus disturbing the activation of SMAD2 on miR-191 and reducing miR-191 level. Altogether, our findings reveal that miR-191 regulated by TGF-ß1-induced BMI1 and SMAD2 negatively modulated bone formation and regeneration, and inhibition of miR-191 might be therapeutically useful to enhance bone repair in clinic.

Nanocellulose-based antimicrobial aerogels with humidity-triggered release of cinnamaldehyde.

Active food packaging with controlled release behavior of volatile antimicrobials is highly desirable for enhancing the quality of fresh produce. In this study, humidity-responsive antimicrobial aerogels were developed using chitosan and dialdehyde nanocellulose, loading with cyclodextrin-cinnamaldehyde inclusion complexes (ICs) for achieving humidity-triggered release of the encapsulated antimicrobial agent. Results showed that the prepared aerogels had capable water absorption ability, which could be served as absorbent pads to take in excessive exudate from packaged fresh produce. More importantly, the accumulative release rate of cinnamaldehyde from the antimicrobial aerogels was significantly improved at RH 98 % compared to that at RH 70 %, which accordingly inactivated all the inoculated Escherichia coli, Staphylococcus aureus and Botrytis cinerea. Additionally, strawberries packaged with the antimicrobial aerogels remained in good conditions after 5 d of storage at 22 ± 1 °C. The prepared composite aerogels had the potential to extend the shelf life of fresh strawberries.

Laser-Induced Skin-like Flexible Pressure Sensor for Artificial Intelligence Speech Recognition.

Skin-like flexible pressure sensors with good sensing performance have great application potential, but their development is limited owing to the need for multistep, high-cost, and low-efficiency preparation processes. Herein, a simple, low-cost, and efficient laser-induced forming process is proposed for the first time to prepare a skin-like flexible piezoresistive sensor. In the laser-induced forming process, based on the photothermal effect of graphene and the foaming effect of glucose, a skin-like polydimethylsiloxanes (PDMS) film with porous structures and surface protrusions is obtained by using infrared laser irradiation of the glucose/graphene/PDMS prepolymer film. Further, based on the skin-like PDMS film with a graphene conductive layer, a new skin-like flexible piezoresistive sensor is obtained. Due to the stress concentration caused by the surface protrusions and the low stiffness caused by the porous structures, the flexible piezoresistive sensor realizes an ultrahigh sensitivity of 1348 kPa-1 at 0-2 kPa, a wide range of 200 kPa, a fast response/recovery time of 52 ms/35 ms, and good stability over 5000 cycles. The application of the sensor to the detection of human pulses and robot clamping force indicates its potential for health monitoring and soft robots. Furthermore, in combination with the neural network (CNN) algorithm in artificial intelligence technology, the sensor achieves 95% accuracy in speech recognition, which demonstrates its great potential for intelligent wearable electronics. Especially, the laser-induced forming process is expected to facilitate the efficient, large-scale preparation of flexible devices with multilevel structures.

The Roadmap of 2D Materials and Devices Toward Chips.

Due to the constraints imposed by physical effects and performance degradation, silicon-based chip technology is facing certain limitations in sustaining the advancement of Moore's law. Two-dimensional (2D) materials have emerged as highly promising candidates for the post-Moore era, offering significant potential in domains such as integrated circuits and next-generation computing. Here, in this review, the progress of 2D semiconductors in process engineering and various electronic applications are summarized. A careful introduction of material synthesis, transistor engineering focused on device configuration, dielectric engineering, contact engineering, and material integration are given first. Then 2D transistors for certain electronic applications including digital and analog circuits, heterogeneous integration chips, and sensing circuits are discussed. Moreover, several promising applications (artificial intelligence chips and quantum chips) based on specific mechanism devices are introduced. Finally, the challenges for 2D materials encountered in achieving circuit-level or system-level applications are analyzed, and potential development pathways or roadmaps are further speculated and outlooked.

"Zero" Intrinsic Fluorescence Sensing-Platforms Enable Ultrasensitive Whole Blood Diagnosis and In Vivo Imaging.

Abnormal physiological processes and diseases can lead to content or activity fluctuations of biocomponents in organelles and whole blood. However, precise monitoring of these abnormalities remains extremely challenging due to the insufficient sensitivity and accuracy of available fluorescence probes, which can be attributed to the background fluorescence arising from two sources, 1) biocomponent autofluorescence (BCAF) and 2) probe intrinsic fluorescence (PIF). To overcome these obstacles, we have re-engineered far-red to NIR II rhodol derivatives that possess weak BCAF interference. And a series of "zero" PIF sensing-platforms were created by systematically regulating the open-loop/spirocyclic forms. Leveraging these advancements, we devised various ultra-sensitive NIR indicators, achieving substantial fluorescence boosts (190 to 1300-fold). Among these indicators, 8-LAP demonstrated accurate tracking and quantifying of leucine aminopeptidase (LAP) in whole blood at various stages of tumor metastasis. Furthermore, coupling 8-LAP with an endoplasmic reticulum-targeting element enabled the detection of ERAP1 activity in HCT116 cells with p53 abnormalities. This delicate design of eliminating PIF provides insights into enhancing the sensitivity and accuracy of existing fluorescence probes toward the detection and imaging of biocomponents in abnormal physiological processes and diseases.

A deep learning fusion network trained with clinical and high-frequency ultrasound images in the multi-classification of skin diseases in comparison with dermatologists: a prospective and multicenter study.

Background: Clinical appearance and high-frequency ultrasound (HFUS) are indispensable for diagnosing skin diseases by providing internal and external information. However, their complex combination brings challenges for primary care physicians and dermatologists. Thus, we developed a deep multimodal fusion network (DMFN) model combining analysis of clinical close-up and HFUS images for binary and multiclass classification in skin diseases. Methods: Between Jan 10, 2017, and Dec 31, 2020, the DMFN model was trained and validated using 1269 close-ups and 11,852 HFUS images from 1351 skin lesions. The monomodal convolutional neural network (CNN) model was trained and validated with the same close-up images for comparison. Subsequently, we did a prospective and multicenter study in China. Both CNN models were tested prospectively on 422 cases from 4 hospitals and compared with the results from human raters (general practitioners, general dermatologists, and dermatologists specialized in HFUS). The performance of binary classification (benign vs. malignant) and multiclass classification (the specific diagnoses of 17 types of skin diseases) measured by the area under the receiver operating characteristic curve (AUC) were evaluated. This study is registered with www.chictr.org.cn (ChiCTR2300074765). Findings: The performance of the DMFN model (AUC, 0.876) was superior to that of the monomodal CNN model (AUC, 0.697) in the binary classification (P = 0.0063), which was also better than that of the general practitioner (AUC, 0.651, P = 0.0025) and general dermatologists (AUC, 0.838; P = 0.0038). By integrating close-up and HFUS images, the DMFN model attained an almost identical performance in comparison to dermatologists (AUC, 0.876 vs. AUC, 0.891; P = 0.0080). For the multiclass classification, the DMFN model (AUC, 0.707) exhibited superior prediction performance compared with general dermatologists (AUC, 0.514; P = 0.0043) and dermatologists specialized in HFUS (AUC, 0.640; P = 0.0083), respectively. Compared to dermatologists specialized in HFUS, the DMFN model showed better or comparable performance in diagnosing 9 of the 17 skin diseases. Interpretation: The DMFN model combining analysis of clinical close-up and HFUS images exhibited satisfactory performance in the binary and multiclass classification compared with the dermatologists. It may be a valuable tool for general dermatologists and primary care providers. Funding: This work was supported in part by the National Natural Science Foundation of China and the Clinical research project of Shanghai Skin Disease Hospital.

Programmable Ferroelectricity in Hf0.5Zr0.5O2 Enabled by Oxygen Defect Engineering.

Ferroelectricity, especially the Si-compatible type recently observed in hafnia-based materials, is technologically useful for modern memory and logic applications, but it is challenging to differentiate intrinsic ferroelectric polarization from the polar phase and oxygen vacancy. Here, we report electrically controllable ferroelectricity in a Hf0.5Zr0.5O2-based heterostructure with Sr-doped LaMnO3, a mixed ionic-electronic conductor, as an electrode. Electrically reversible extraction and insertion of an oxygen vacancy into Hf0.5Zr0.5O2 are macroscopically characterized and atomically imaged in situ. Utilizing this reversible process, we achieved multilevel polarization states modulated by the electric field. Our study demonstrates the usefulness of the mixed conductor to repair, create, manipulate, and utilize advanced ferroelectric functionality. Furthermore, the programmed ferroelectric heterostructures with Si-compatible doped hafnia are desirable for the development of future ferroelectric electronics.

Portable Pyrolysis-Point Discharge Optical Spectrometer for In Situ Plastic Polymer Identification by Coupling with Machine Learning.

Rapid and in situ identification of specific polymers is a challenging and crucial step in plastic recycling. However, conventional techniques continue to exhibit significant limitations in the rapid and field classification of plastic products, especially with the wide range of commercially available color polymers because of their large size, high energy consumption, and slow and complicated analysis procedures. In this work, a simple analytical system integrating a miniature and low power consumption (22.3 W) pyrolyzer (Pyr) and a low temperature, atmospheric pressure point discharge optical emission spectrometer (µPD-OES) was fabricated for rapidly identifying polymer types. Plastic debris is decomposed in the portable pyrolyzer to yield volatile products, which are then swept into the µPD-OES instrument for monitoring the optical emission patterns of the thermal pyrolysis products. With machine learning, five extensively used raw polymers and their consumer plastics were classified with an accuracy of ≥97.8%. Furthermore, the proposed method was applied to the identification of the aged polymers and plastic samples collected from a garbage recycling station, indicating its great potential for identification of environmentally weathered plastics. This portable Pyr-µPD-OES system provides a cost-effective tool for rapid and field identification of polymer types of recycled plastic for proper management and resource recycling.

Increase in the effective viscosity of polyethylene under extreme nanoconfinement.

Understanding polymer transport in nanopores is crucial for optimizing heterogeneously catalyzed processes in polymer upcycling and fabricating high-performance nanocomposite films and membranes. Although confined polymer dynamics have been extensively studied, the behavior of polyethylene (PE)-the most widely used commodity polymer-in pores smaller than 20 nm remains largely unexplored. We investigate the effects of extreme nanoconfinement on PE transport using capillary rise infiltration in silica nanoparticle packings with average pore radii ranging from ∼1 to ∼9 nm. Using in situ ellipsometry and the Lucas-Washburn model, we discover a previously unknown inverse relationship between effective viscosity (ηeff) and average pore radius (Rpore). Additonally, we determine that PE transport under these extreme conditions is primarily governed by physical confinement, rather than pore surface chemistry. We refine an existing theory to provide a generalized formalism to describe the polymer transport dynamics over a wide range of pore radii (from 1 nm and larger). Our results offer valuable insights for optimizing catalyst supports in polymer upcycling and improving infiltration processes for nanocomposite fabrication.

Chemical Approaches to Optimize the Properties of Organic Fluorophores for Imaging and Sensing.

Organic fluorophores are indispensable tools in cells, tissue and in vivo imaging, and have enabled much progress in the wide range of biological and biomedical fields. However, many available dyes suffer from insufficient performances, such as short absorption and emission wavelength, low brightness, poor stability, small Stokes shift, and unsuitable permeability, restricting their application in advanced imaging technology and complex imaging. Over the past two decades, many efforts have been made to improve these performances of fluorophores. Starting with the luminescence principle of fluorophores, this review clarifies the mechanisms of the insufficient performance for traditional fluorophores to a certain extent, systematically summarizes the modified approaches of optimizing properties, highlights the typical applications of the improved fluorophores in imaging and sensing, and indicates existing problems and challenges in this area. This progress not only proves the significance of improving fluorophores properties, but also provide a theoretical guidance for the development of high-performance fluorophores.