Monomeric far-red and near-infrared fluorescent biliproteins of ultrahigh brightness.

Far-red and near-infrared fluorescent proteins have regions of maximum transmission in most tissues and can be widely used as fluorescent biomarkers. We report that fluorescent phycobiliproteins originating from the phycobilisome core subunit ApcF2 can covalently bind biliverdin, named BDFPs. To further improve BDFPs, we conducted a series of studies. Firstly, we mutated K53Q and T144A of BDFPs to increase their effective brightness up to 190% in vivo. Secondly, by homochromatic tandem fusion of high-brightness BDFPs to achieve monomerization, which increases the effective brightness by up to 180% in vivo, and can effectively improve the labeling effect. By combining the above two approaches, the brightness of the tandem BDFPs was much improved compared with that of the previously reported fluorescent proteins in a similar spectral range. The tandem BDFPs were expressed stably while maintaining fluorescence in mammalian cells and Caenorhabditis elegans. They were also photostable and resistant to high temperature, low pH, and chemical denaturation. The tandem BDFPs advantages were proved in applications as biomarkers for imaging in super-resolution microscopy.

Angiogenesis-related immune response may be the prelude to the syndesmophyte formation in Ankylosing spondylitis.

BACKGROUND: Ankylosing spondylitis (AS) is a chronic autoimmune arthritis that mainly affects spine joints. To date, the pathogenesis of AS remains unclear, although immune cells and innate immune response cytokines have been suggested to be crucial players. METHODS: By adopting a single-cell RNA sequencing approach in the AS cynomolgus model, we profiled and characterized PBMC proportions along disease progression. RESULTS: Here, our primary focus was on the activation of an immune cascade-initiating lymphocyte subtype known as CD4+CXCR5+ T follicular helper (Tfh) cells. These Tfhs demonstrated a localized residence in AS bone lesion as an ectopic lymphoid structure. Moreover, Tfhs would serve as an upstream initiator for a pro-angiogenic cascade. Then, an expansion in CD14+ monocytes and DC cells subsets resulted in enhanced expression of angiogenesis genes in these AS cynomolgus monkeys. With a confirmed higher abundance of TNF-α accompanying H-type vascular invasion in the osteophytic region, pronounced expansion of Tfhs at such lesion site signaling for monocytes and DCs intrusion is considered as the prelude to the characteristic angiogenic bony outgrowth in AS known as syndesmophytes. CONCLUSIONS: We explored the intimate relationship between local inflammation and bone formation in AS from the perspective of nascent vascularisation. Hence, our study lays the foundation for elucidating a unified AS pathogenesis through the immune-angiogenesis-osteogenesis axis.

An efficient polynomial-based verifiable computation scheme on multi-source outsourced data.

With the development of cloud computing, users are more inclined to outsource complex computing tasks to cloud servers with strong computing capacity, and the cloud returns the final calculation results. However, the cloud is not completely trustworthy, which may leak the data of user and even return incorrect calculations on purpose. Therefore, it is important to verify the results of computing tasks without revealing the privacy of the users. Among all the computing tasks, the polynomial calculation is widely used in information security, linear algebra, signal processing and other fields. Most existing polynomial-based verifiable computation schemes require that the input of the polynomial function must come from a single data source, which means that the data must be signed by a single user. However, the input of the polynomial may come from multiple users in the practical application. In order to solve this problem, the researchers have proposed some schemes for multi-source outsourced data, but these schemes have the common problem of low efficiency. To improve the efficiency, this paper proposes an efficient polynomial-based verifiable computation scheme on multi-source outsourced data. We optimize the polynomials using Horner's method to increase the speed of verification, in which the addition gate and the multiplication gate can be interleaved to represent the polynomial function. In order to adapt to this structure, we design the corresponding homomorphic verification tag, so that the input of the polynomial can come from multiple data sources. We prove the correctness and rationality of the scheme, and carry out numerical analysis and evaluation research to verify the efficiency of the scheme. The experimental indicate that data contributors can sign 1000 new data in merely 2 s, while the verification of a delegated polynomial function with a power of 100 requires only 18 ms. These results confirm that the proposed scheme is better than the existing scheme.

Prediction of vascular complications in free flap reconstruction with machine learning.

OBJECTIVE: This study aims to explore the risk factors of vascular complications following free flap reconstruction and to develop a clinical auxiliary assessment tool for predicting vascular complications in patients undergoing free flap reconstruction leveraging machine learning methods. METHODS: We reviewed the medical data of patients who underwent free flap reconstruction at the Affiliated Hospital of Zunyi Medical University retrospectively from January 1, 2019, to December 31, 2021. Statistical analysis was used to screen risk factors. A training data set was generated and augmented using the synthetic minority oversampling technique. Logistic regression, random forest and neural network, models were trained, using this dataset. The performance of these three predictive models was then evaluated and compared using a test set, with four metrics, area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS: A total of 570 patients who underwent free flap reconstruction were included in this study, 46 of whom developed postoperative vascular complications. Among the models tested, the neural network model exhibited superior performance on the test set, achieving an AUC of 0.828. Multivariate logistic regression analysis identified that preoperative hemoglobin levels, preoperative fibrinogen levels, operation duration, smoking history, the number of anastomoses, and peripheral vascular injury as statistically significant independent risk factors for vascular complications post-free flap reconstruction. The top five predictive factors in the neural network were fibrinogen content, operation duration, donor site, body mass index (BMI), and platelet count. CONCLUSION: Hemoglobin levels, fibrinogen levels, operation duration, smoking history, and anastomotic veins are independent risk factors for vascular complications following free flap reconstruction. These risk factors enhance the ability of machine learning models to predict the occurrence of vascular complications and identify high-risk patients. The neural network model outperformed the logistic regression and random forest models, suggesting its potential to aid clinicians in early identification of high-risk patients thereby mitigating patient suffering and improving prognosis.

Air-Stable, Large-Area 2D Metals and Semiconductors.

Two-dimensional (2D) materials are popular for fundamental physics study and technological applications in next-generation electronics, spintronics, and optoelectronic devices due to a wide range of intriguing physical and chemical properties. Recently, the family of 2D metals and 2D semiconductors has been expanding rapidly because they offer properties once unknown to us. One of the challenges to fully access their properties is poor stability in ambient conditions. In the first half of this Review, we briefly summarize common methods of preparing 2D metals and highlight some recent approaches for making air-stable 2D metals. Additionally, we introduce the physicochemical properties of some air-stable 2D metals recently explored. The second half discusses the air stability and oxidation mechanisms of 2D transition metal dichalcogenides and some elemental 2D semiconductors. Their air stability can be enhanced by optimizing growth temperature, substrates, and precursors during 2D material growth to improve material quality, which will be discussed. Other methods, including doping, postgrowth annealing, and encapsulation of insulators that can suppress defects and isolate the encapsulated samples from the ambient environment, will be reviewed.

Cell membrane coated nanoparticles: cutting-edge drug delivery systems for osteoporosis therapy.

Osteoporosis, characterized by a reduction in bone mineral density, represents a prevalent skeletal disorder with substantial global health implications. Conventional therapeutic strategies, exemplified by bisphosphonates and hormone replacement regimens, though effective, encounter inherent limitations and challenges. Recent years have witnessed the surge of cell-membrane-coated nanoparticles (CMNPs) as a promising intervention for osteoporosis, leveraging their distinct attributes including refined biocompatibility, heightened pharmaceutical payload capacity, as well as targeted drug release kinetics. However, a comprehensive review consolidating the application of CMNPs-based therapy for osteoporosis remains absent within the existing literature. In this review, we provide a concise overview of the distinctive pathogenesis associated with osteoporosis, alongside an in-depth exploration of the physicochemical attributes intrinsic to CMNPs derived from varied cellular sources. Subsequently, we explore the potential utility of CMNPs, elucidating emerging trends in their deployment for osteoporosis treatment through multifaceted therapeutic approaches. By linking the notable attributes of CMNPs with their roles in mitigating osteoporosis, this review serves as a catalyst for further advances in the design of advanced CMNPs tailored for osteoporosis management. Ultimately, such progress is promising for enhancing outcomes in anti-bone loss interventions, paving the way for clinical translation in the near future.

miR-575/RIPK4 axis modulates cell cycle progression and proliferation by inactivating the Wnt/ß-catenin signaling pathway through inhibiting RUNX1 in colon cancer.

Receptor interacting protein serine/threonine kinase 4 (RIPK4) is widely involved in human cancer development. Nevertheless, its role in colon cancer (COAD) has not been elucidated till now. Our research aimed at exploring the function and underlying molecular mechanism of RIPK4 in COAD progression. Through bioinformatic analyses and RT-qPCR, RIPK4 was discovered to be increased in COAD cells and tissues, and its high level predicted poor prognosis. Loss-of-function assays revealed that RIPK4 silencing suppressed COAD cell growth, induced cell cycle arrest, and enhanced cell apoptosis. In vivo experiments also proved that tumor growth was inhibited by silencing of RIPK4. Luciferase reporter assay validated that RIPK4 was targeted and negatively regulated by miR-575. Western blotting demonstrated that Wnt3a, phosphorylated (p)-GSK-3ß, and cytoplasmic and nuclear ß-catenin protein levels, ß-catenin nuclear translocation, and Cyclin D1, CDK4, Cyclin E, and c-Myc protein levels were reduced by RIPK4 knockdown, which however was reversed by treatment with LiCl, the Wnt/ß-catenin pathway activator. LiCl also offset the influence of RIPK4 knockdown on COAD cell growth, cell cycle process, and apoptosis. Finally, RIPK4 downregulation reduced RUNX1 level, which was upregulated in COAD and its high level predicted poor prognosis. RIPK4 is positively associated with RUNX1 in COAD. Overexpressing RUNX1 antagonized the suppression of RIPK4 knockdown on RUNX1, Wnt3a, p-GSK-3ß, cytoplasmic ß-catenin, nuclear ß-catenin, Cyclin D1, CDK4, Cyclin E, and c-Myc levels. Collectively, miR-575/RIPK4 axis repressed COAD progression via inactivating the Wnt/ß-catenin pathway through downregulating RUNX1.

Magnetic field filtering of the boundary supercurrent in unconventional metal NiTe2-based Josephson junctions.

Topological materials with boundary (surface/edge/hinge) states have attracted tremendous research interest. Additionally, unconventional (obstructed atomic) materials have recently drawn lots of attention owing to their obstructed boundary states. Experimentally, Josephson junctions (JJs) constructed on materials with boundary states produce the peculiar boundary supercurrent, which was utilized as a powerful diagnostic approach. Here, we report the observations of boundary supercurrent in NiTe2-based JJs. Particularly, applying an in-plane magnetic field along the Josephson current can rapidly suppress the bulk supercurrent and retain the nearly pure boundary supercurrent, namely the magnetic field filtering of supercurrent. Further systematic comparative analysis and theoretical calculations demonstrate the existence of unconventional nature and obstructed hinge states in NiTe2, which could produce hinge supercurrent that accounts for the observation. Our results reveal the probable hinge states in unconventional metal NiTe2, and demonstrate in-plane magnetic field as an efficient method to filter out the bulk contributions and thereby to highlight the hinge states hidden in topological/unconventional materials.

Factors and pathways of non-suicidal self-injury in children: insights from computational causal analysis.

Background: Non-suicidal self-injury (NSSI) has become a significant public health issue, especially prevalent among adolescents. The complexity and multifactorial nature of NSSI necessitate a comprehensive understanding of its underlying causal factors. This research leverages the causal discovery methodology to explore these causal associations in children. Methods: An observational dataset was scrutinized using the causal discovery method, particularly employing the constraint-based approach. By integrating machine learning and causal inference techniques, the study aimed to determine direct causal relationships associated with NSSI. The robustness of the causal relationships was evaluated using three methods to construct and validate it: the PC (Peter and Clark) method, Fast Causal Inference (FCI) method, and the GAE (Graphical Autoencoder) method. Results: Analysis identified nine nodes with direct causal relationships to NSSI, including life satisfaction, depression, family dysfunction, sugary beverage consumption, PYD (positive youth development), internet addiction, COVID-19 related PTSD, academic anxiety, and sleep duration. Four principal causal pathways were identified, highlighting the roles of lockdown-induced lifestyle changes, screen time, positive adolescent development, and family dynamics in influencing NSSI risk. Conclusions: An in-depth analysis of the factors leading to Non-Suicidal Self-Injury (NSSI), highlighting the intricate connections among individual, family, and pandemic-related influences. The results, derived from computational causal analysis, underscore the critical need for targeted interventions that tackle these diverse causative factors.

Investigation of Mechanical and Shrinkage Performance for Large-Size Cement-Stabilized Aggregates.

Cement-stabilized macadam materials are widely utilized as semi-rigid base materials in road construction. However, conventional cement-stabilized macadam (CCSM) bases often develop shrinkage cracks during early construction and maintenance due to variations in humidity and temperature. Shrinkage cracks can subsequently result in reflective cracks in the asphalt pavement, significantly reducing the overall service life of the road. This study systematically evaluates the shrinkage and mechanical properties of large-size cement-stabilized macadam (LSCSM). Initially, the mix proportion for LSCSM is determined using the Bailey method. Subsequently, an experimental design based on the response surface method is implemented to comprehensively investigate various properties, including unconfined compressive strength, compressive rebound modulus, flexural strength, and the durability aspects of early drying shrinkage and temperature shrinkage through laboratory experiments. Further, the performance differences between CCSM and LSCSM are analyzed comparatively. The findings reveal that the compressive strength of LSCSM surpasses that of CCSM, albeit with comparatively lower compressive rebound modulus and flexural strength. LSCSM demonstrates a unique blend of characteristics, exhibiting traits of both semi-rigid and flexible materials. Furthermore, LSCSM exhibits favorable crack resistance properties, as evidenced by lower dry shrinkage strain, average dry and temperature shrinkage coefficient compared to CCSM. The proposed LSCSM in this study effectively reduces cement dosage and enhances the crack resistance performance of base materials.

Nonionic surfactant Tween 80-facilitated bacterial transport in porous media: A nonmonotonic concentration-dependent performance, mechanism, and machine learning prediction.

The surfactant-enhanced bioremediation (SEBR) of organic-contaminated soil is a promising soil remediation technology, in which surfactants not only mobilize pollutants, but also alter the mobility of bacteria. However, the bacterial response and underlying mechanisms remain unclear. In this study, the effects and mechanisms of action of a selected nonionic surfactant (Tween 80) on Pseudomonas aeruginosa transport in soil and quartz sand were investigated. The results showed that bacterial migration in both quartz sand and soil was significantly enhanced with increasing Tween 80 concentration, and the greatest migration occurred at a critical micelle concentration (CMC) of 4 for quartz sand and 30 for soil, with increases of 185.2% and 27.3%, respectively. The experimental results and theoretical analysis indicated that Tween 80-facilitated bacterial migration could be mainly attributed to competition for soil/sand surface sorption sites between Tween 80 and bacteria. The prior sorption of Tween 80 onto sand/soil could diminish the available sorption sites for P. aeruginosa, resulting in significant decreases in deposition parameters (70.8% and 33.3% decrease in KD in sand and soil systems, respectively), thereby increasing bacterial transport. In the bacterial post-sorption scenario, the subsequent injection of Tween 80 washed out 69.8% of the bacteria retained in the quartz sand owing to the competition of Tween 80 with pre-sorbed bacteria, as compared with almost no bacteria being eluted by NaCl solution. Several machine learning models have been employed to predict Tween 80-faciliated bacterial transport. The results showed that back-propagation neural network (BPNN)-based machine learning could predict the transport of P. aeruginosa through quartz sand with Tween 80 in-sample (2 CMC) and out-of-sample (10 CMC) with errors of 0.79% and 3.77%, respectively. This study sheds light on the full understanding of SEBR from the viewpoint of degrader facilitation.

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study.

BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performance, and validate its application in real-world clinical implementation. METHODS: We developed a deep-learning model using 16 546 head and neck CTA examination images from 14 517 patients at eight Chinese hospitals. Using an adapted, stepwise implementation and evaluation, 120 certified clinicians from 15 geographically different hospitals were recruited. Initially, the AI model was externally validated with images of 900 digital subtraction angiography-verified CTA cases (examinations) and compared with the performance of 24 clinicians who each viewed 300 of these cases (stage 1). Next, as a further external validation a multi-reader multi-case study enrolled 48 clinicians to individually review 298 digital subtraction angiography-verified CTA cases (stage 2). The clinicians reviewed each CTA examination twice (ie, with and without the AI model), separated by a 4-week washout period. Then, a randomised open-label comparison study enrolled 48 clinicians to assess the acceptance and performance of this AI model (stage 3). Finally, the model was prospectively deployed and validated in 1562 real-world clinical CTA cases. FINDINGS: The AI model in the internal dataset achieved a patient-level diagnostic sensitivity of 0·957 (95% CI 0·939-0·971) and a higher patient-level diagnostic sensitivity than clinicians (0·943 [0·921-0·961] vs 0·658 [0·644-0·672]; p<0·0001) in the external dataset. In the multi-reader multi-case study, the AI-assisted strategy improved clinicians' diagnostic performance both on a per-patient basis (the area under the receiver operating characteristic curves [AUCs]; 0·795 [0·761-0·830] without AI vs 0·878 [0·850-0·906] with AI; p<0·0001) and a per-aneurysm basis (the area under the weighted alternative free-response receiver operating characteristic curves; 0·765 [0·732-0·799] vs 0·865 [0·839-0·891]; p<0·0001). Reading time decreased with the aid of the AI model (87·5 s vs 82·7 s, p<0·0001). In the randomised open-label comparison study, clinicians in the AI-assisted group had a high acceptance of the AI model (92·6% adoption rate), and a higher AUC when compared with the control group (0·858 [95% CI 0·850-0·866] vs 0·789 [0·780-0·799]; p<0·0001). In the prospective study, the AI model had a 0·51% (8/1570) error rate due to poor-quality CTA images and recognition failure. The model had a high negative predictive value of 0·998 (0·994-1·000) and significantly improved the diagnostic performance of clinicians; AUC improved from 0·787 (95% CI 0·766-0·808) to 0·909 (0·894-0·923; p<0·0001) and patient-level sensitivity improved from 0·590 (0·511-0·666) to 0·825 (0·759-0·880; p<0·0001). INTERPRETATION: This AI model demonstrated strong clinical potential for intracranial aneurysm detection with improved clinician diagnostic performance, high acceptance, and practical implementation in real-world clinical cases. FUNDING: National Natural Science Foundation of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Langerhans cell histiocytosis in children with refractory diarrhoea and hypoalbuminaemia as the initial presentation: two case reports and a literature review.

Langerhans cell histiocytosis (LCH) involving the gastrointestinal tract is a rare condition for which clinical experience is limited. We describe the cases of two patients who initially presented with chronic diarrhoea, hypoproteinaemia, and intermittent fever. These findings suggest that in cases of refractory diarrhoea accompanied by recurrent hypoalbuminaemia, especially with abdominal rash, LCH should be considered. Gastrointestinal endoscopy, biopsy, and imaging studies are essential for obtaining a definitive diagnosis. This approach might be helpful for the early recognition of gastrointestinal tract involvement in LCH.

Spatial heterogeneity of neo- and paleo-endemism for plants in Madagascar.

Madagascar is a biogeographically unique island with a remarkably high level of endemism. However, endemic taxa in Madagascar are massively threatened due to unprecedented pressures from anthropogenic habitat modification and climate change. A comprehensive phylogeny-based biodiversity evaluation of the island remains lacking. Here, we identify hotspots of taxonomic and phylogenetic plant diversity and neo- and paleo-endemism by generating a novel dated tree of life for the island. The tree is based on unprecedented sampling of 3,950 species (33% of the total known species) and 1,621 genera (93% of the total known genera and 69% of endemic genera) of Malagasy vascular plants. We find that island-endemic genera are concentrated in multiple lineages combining high taxonomic and phylogenetic diversity. Integrating phylogenetic and geographic distribution data, our results reveal that taxon richness and endemism are concentrated in the northern, eastern, and southeastern humid forests. Paleo-endemism centers are concentrated in humid eastern and central regions, whereas neo-endemism centers are concentrated in the dry and spiny forests in western and southern Madagascar. Our statistical analysis of endemic genera in each vegetation region supports a higher proportion of ancient endemic genera in the east but a higher proportion of recent endemic genera in the south and west. Overlaying centers of phylogenetic endemism with protected areas, we identify conservation gaps concentrated in western and southern Madagascar. These gaps should be incorporated into conservation strategies to aid the protection of multiple facets of biodiversity and their benefits to the Malagasy people.

Absolute Configuration of Oxabornyl Polyenes Prugosenes A1-A3 and Structural Revision of Prugosene A2.

Oxabornyl polyenes represent a unique group of polyketides characterized by a central polyene core flanked by a conserved oxabornyl moiety and a structurally diverse oxygen heterocyclic ring. They are widely distributed in fungi and possess a variety of biological activities. Due to the significant spatial separation between the two stereogenic ring systems, it is difficult to establish their overall relative configurations. Here, we isolated three oxabornyl polyenes, prugosenes A1-A3 (1-3), from Talaromyces sp. JNU18266-01. Although these compounds were first reported from Penicillium rugulosum, their overall relative and absolute configurations remained unassigned. By employing ozonolysis in combination with ECD calculations, we were able to establish their absolute configurations, and additionally obtained seven new chemical derivatives (4-10). Notably, through NMR data analysis and quantum chemical calculations, we achieved the structural revision of prugosene A2. Furthermore, prugosenes A1-A3 exhibited potent antiviral activity against the respiratory syncytial virus, with compound 1 displaying an IC50 value of 6.3 µM. Our study thus provides a valuable reference for absolute configuration assignment of oxabornyl polyene compounds.

Serum levels of HMW adiponectin and its receptors are associated with cytokine levels and clinical characteristics in chronic obstructive pulmonary disease.

We aimed to investigate the changes in the levels of high-molecular-weight (HMW) adiponectin, adiponectin receptors, and cytokines in patients with chronic obstructive pulmonary disease (COPD), as well as their potential relationships. Forty-one patients who underwent lobectomy for lung lesions and had a clear postoperative pathological diagnosis were divided into the non-COPD (N = 23) and COPD (N = 18) groups. HMW adiponectin, cytokine, and T-cadherin levels in serum and tissues were detected by enzyme-linked immunosorbent assay. The levels of HMW adiponectin and cytokine (interleukin [IL]-6, IL-10, surfactant protein D, 4-hydroxynonenal, tumor necrosis factor-α, and C reactive protein) in the serum and tissues increased in the COPD group compared to those in the non-COPD group. Patients with COPD exhibited AdipoR1 upregulation and AdipoR2 downregulation. Although T-cadherin did not differ significantly between patients with and those without COPD, its expression was elevated during the progression from COPD with benign lung lesions to combined lung cancer. Furthermore, the HMW adiponectin levels were significantly correlated with the cytokine levels and the clinical characteristics of COPD. HMW adiponectin and its receptors affect the inflammatory process in COPD and may further contribute to the progression of the disease to malignancy.

Deep learning framework for three-dimensional surface reconstruction of object of interest in photoacoustic tomography.

Photoacoustic tomography (PAT) is a non-ionizing hybrid imaging technology of clinical importance that combines the high contrast of optical imaging with the high penetration of ultrasonic imaging. Two-dimensional (2D) tomographic images can only provide the cross-sectional structure of the imaging target rather than its overall spatial morphology. This work proposes a deep learning framework for reconstructing three-dimensional (3D) surface of an object of interest from a series of 2D images. It achieves end-to-end mapping from a series of 2D images to a 3D image, visually displaying the overall morphology of the object. The framework consists of four modules: segmentation module, point cloud generation module, point cloud completion module, and mesh conversion module, which respectively implement the tasks of segmenting a region of interest, generating a sparse point cloud, completing sparse point cloud and reconstructing 3D surface. The network model is trained on simulation data sets and verified on simulation, phantom, and in vivo data sets. The results showed superior 3D reconstruction performance both visually and on the basis of quantitative evaluation metrics compared to the state-of-the-art non-learning and learning approaches. This method potentially enables high-precision 3D surface reconstruction from the tomographic images output by the preclinical PAT system without changing the imaging system. It provides a general deep learning scheme for 3D reconstruction from tomographic scanning data.

A Halloysite Nanotubes-based Probe for Efficient Fluorescence Detection and Adsorption Removal of Pb2+ in Water.

The detection and removal of Pb2+ is of utmost importance for environmental protection and human health due to its toxicity, persistent pollution, and bioaccumulation effects. To address the limitations associated with organic small molecule-based fluorescence probes such as poor water solubility and single functionality in detecting Pb2+, a fluorescence probe based on halloysite nanotubes was developed. This probe not only enables specific, rapid, and reliable detection of Pb2+ but also facilitates efficient removal of it from water. The development of this bifunctional fluorescent probe provides a valuable insight for designing more advanced probes targeting heavy metal ions.

Matched Redox Kinetics on Triazine-Based Carbon Nitride/Ni(OH)2 for Stoichiometric Overall Photocatalytic CO2 Conversion.

Mismatched reaction kinetics of CO2 reduction and H2 O oxidation is the main obstacle limiting the overall photocatalytic CO2 conversion. Here, a molten salt strategy is used to construct tubular triazine-based carbon nitride (TCN) with more adsorption sites and stronger activation capability. Ni(OH)2 nanosheets are then grown over the TCN to trigger a proton-coupled electron transfer for a stoichiometric overall photocatalytic CO2 conversion via "3CO2 + 2H2 O = CH4 + 2CO + 3O2 ." TCN reduces the energy barrier of H2 O dissociation to promote H2 O oxidation to O2 and supply sufficient protons to Ni(OH)2 , whereby the CO2 conversion is accelerated due to the enhanced proton-coupled electron transfer process enabled by the sufficient proton supply from TCN. This work highlights the importance of matching the reaction kinetics of CO2 reduction and H2 O oxidation by proton-coupled electron transfer on stoichiometric overall photocatalytic CO2 conversion.

The Role and Therapeutic Potential of Non-coding RNAs in Resistance to EGFR-TKIs targeted therapy for Non-small Cell Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide, of which non-small cell lung cancer (NSCLC) is the most common type, and epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are widely used for the treatment of NSCLC. EGFR-TKIs are known to develop a drug-resistant response after a certain number of cycles of dosing, and how to alleviate or even reverse EGFR-TKI resistance is an urgent problem at present. This review focuses on the role of ncRNAs in the resistance of NSCLC to EGFR-TKIs and the potential mechanisms underlying the development of NSCLC resistance to EGFR-TKIs. NcRNAs are involved in NSCLC resistance to EGFR-TKIs by mediating cellular drug efflux, epithelial-mesenchymal transition, apoptosis, autophagy, and EGFR mutation. ncRNAs play a crucial role in NSCLC resistance to EGFR-TKIs. Hopefully, the results will provide some guidance and help for the treatment and prognosis of NSCLC.