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Carbon dots (CDs) are known as the rising star of carbon-based nanomaterials and, by virtue of their unique structure and fascinating properties, they have attracted considerable interest in different fields such as biological sensing, drug delivery, photodynamic therapy, photocatalysis, and solar cells in recent years. Particularly, the outstanding electronic and optical properties of the CDs have attracted increasing attention in biomedical and photocatalytic applications owing to their low toxicity, biocompatibility, excellent photostability, tunable fluorescence, outstanding efficient up-converted photoluminescence behavior, and photo-induced electron transfer ability. This article reviews recent progress on the synthesis routes and optical properties of CDs as well as biomedical and photocatalytic applications. Furthermore, we discuss an outlook on future and potential development of the CDs based biosensor, biological dye, biological vehicle, and photocatalysts in this booming research field.

Circular RNAs (circRNAs) have confirmed to participate in diverse biological functions in cancer. However, the expression patterns of circRNAs on hepatocellular carcinoma (HCC) remains unclear. In the present study, we clarified that hsa_circRNA_104348 was dramatically upregulated in HCC tissues and cells. Patients with HCC displaying high hsa_circRNA_104348 level possessed poor prognosis. Has_circ_104348 facilitated proliferation, migration, and invasion, meanwhile suppressed apoptosis of HCC cell. Furthermore, hsa_circRNA_104348 directly targeted miR-187–3p, could regulate miR-187-3p to affect proliferation, migration, invasion, and apoptosis of HCC cells, and may have effect on Wnt/β-catenin signaling pathway. Moreover, RTKN2 could be a direct target of miR-187-3p. In addition, knockdown of hsa_circRNA_104348 attenuated HCC tumorigenesis and lung metastasis in vivo. Taken together, these findings indicated that circular RNA hsa_circRNA_104348 might function as a competing endogenous RNA (ceRNA) to promotes HCC progression by targeting miR-187–3p/RTKN2 axis and activating Wnt/β-catenin pathway.

The spillover of oxygen species is fundamentally important in redox reactions, but the spillover mechanism has been less understood compared to that of hydrogen spillover. Herein Sn is doped into TiO 2 to activate low-temperature (<100 °C) reverse oxygen spillover in Pt/TiO 2 catalyst, leading to CO oxidation activity much higher than that of most oxide-supported Pt catalysts. A combination of near-ambient-pressure X-ray photoelectron spectroscopy, in situ Raman/Infrared spectroscopies, and ab initio molecular dynamics simulations reveal that the reverse oxygen spillover is triggered by CO adsorption at Pt 2+ sites, followed by bond cleavage of Ti-O-Sn moieties nearby and the appearance of Pt 4+ species. The O in the catalytically indispensable Pt-O species is energetically more favourable to be originated from Ti-O-Sn. This work clearly depicts the interfacial chemistry of reverse oxygen spillover that is triggered by CO adsorption, and the understanding is helpful for the design of platinum/titania catalysts suitable for reactions of various reactants. Reverse O spillover has opened new opportunities in improving the catalytic activity and selectivity in various reactions. Herein Sn is doped into TiO2 to activate low-temperature (<100 °C) reverse oxygen spillover in Pt/TiO2 catalyst, leading to enhanced CO oxidation activity.

Accurate classification of follicular-patterned thyroid lesions is not always an easy task on routine surgical hematoxylin-eosin-stained or cytologic fine-needle aspiration specimens. The diagnostic challenges are partially due to differential diagnostic criteria that are often subtle and subjective. In the past decades, tremendous advances have been made in molecular gene profiling of tumors and diagnostic immunohistochemistry, aiding in diagnostic accuracy and proper patient management. To evaluate the diagnostic utility of the most commonly studied immunomarkers in the field of thyroid pathology by review of the literature, using the database of indexed articles in PubMed (US National Library of Medicine) from 1976-2013. Literature review, authors' research data, and personal practice experience. The appropriate use of immunohistochemistry by applying a panel of immunomarkers and using a standardized technical and interpretational method may complement the morphologic assessment and aid in the accurate classification of difficult thyroid lesions.

The disease-information coupling propagation dynamics model is a widely used model for studying the spread of infectious diseases in society, but the parameter settings and sensitivity are often overlooked, which leads to enlarged errors in the results. Exploring the influencing factors of the disease-information coupling propagation dynamics model and identifying the key parameters of the model will help us better understand its coupling mechanism and make accurate recommendations for controlling the spread of disease. In this paper, Sobol global sensitivity analysis algorithm is adopted to conduct global sensitivity analysis on 6 input parameters (different cross regional jump probabilities, information dissemination rate, information recovery rate, epidemic transmission rate, epidemic recovery rate, and the probability of taking preventive actions) of the disease-information coupling model with the same interaction radius and heterogeneous interaction radius. The results show that: (1) In the coupling model with the same interaction radius, the parameters that have the most obvious influence on the peak density of nodes in state A I and the information dissemination scale of the information are the information dissemination rate β I and the information recovery rate μ I . In the coupling model of heterogeneous interaction radius, the parameters that have the most obvious impact on the peak density of nodes in the A I state of the information layer are: information spread rate β I , disease recovery rate μ E , and the parameter that has a significant impact on the scale of information spread is the information spread rate β I and information recovery rate μ I . (2) Under the same interaction radius and heterogeneous interaction radius, the parameters that have the most obvious influence on peak density of nodes in state S E and the disease transmission scale of the disease layer are the disease transmission rate β E , the disease recovery rate μ E , and the probability of an individual moving across regions p jump .

Immunohistochemistry has become an indispensable ancillary study in the identification and classification of undifferentiated neoplasms/tumors of uncertain origin. The diagnostic accuracy has significantly improved because of the continuous discoveries of tissue-specific biomarkers and the development of effective immunohistochemical panels. To identify and classify undifferentiated neoplasms/tumors of uncertain origin by immunohistochemistry. Literature review and authors' research data and personal practice experience were used. To better guide therapeutic decisions and predict prognostic outcomes, it is crucial to differentiate the specific lineage of an undifferentiated neoplasm. Application of appropriate immunohistochemical panels enables the accurate classification of most undifferentiated neoplasms. Knowing the utilities and pitfalls of each tissue-specific biomarker is essential for avoiding potential diagnostic errors because an absolutely tissue-specific biomarker is exceptionally rare. We review frequently used tissue-specific biomarkers, provide effective panels, and recommend diagnostic algorithms as a standard approach to undifferentiated neoplasms.

Although mesenchymal stem cell (MSC) transplantation provides an alternative strategy for end-stage liver disease (ESLD), further widespread application of MSC therapy is limited owing to low cell engraftment efficiency. Improving cell engraftment efficiency plays a critical role in enhancing MSC therapy for liver diseases. In this review, we summarize the current status and challenges of MSC transplantation for ESLD. We also outline the complicated cell-homing process and highlight how low cell engraftment efficiency is closely related to huge differences in extracellular conditions involved in MSC homing journeys ranging from constant, controlled conditions in vitro to variable and challenging conditions in vivo. Improving cell survival and homing capabilities enhances MSC engraftment efficacy. Therefore, we summarize the current strategies, including hypoxic priming, drug pretreatment, gene modification, and cytokine pretreatment, as well as splenectomy and local irradiation, used to improve MSC survival and homing capability, and enhance cell engraftment and therapeutic efficiency of MSC therapy. We hope that this review will provide new insights into enhancing the efficiency of MSC engraftment in liver diseases.

This study utilized electroencephalography (EEG) to compare brain functional and effective connectivity patterns in children with reading difficulties (RD) and math difficulties (MD) during specific tasks. The aim was to identify neurophysiological distinctions between these two learning disorders, which often exhibit high comorbidity. Data from a publicly available dataset of 28 children (11 RD, 17 MD) aged 7-13 years were analyzed. Functional connectivity was quantified using the weighted Phase Lag Index (wPLI), and effective connectivity was assessed with the Directed Transfer Function (DTF). Functional connectivity analysis revealed significant group differences. The RD group showed significantly higher beta band synchronization in the right temporal lobe compared to the MD group. Conversely, the MD group exhibited significantly greater connectivity in the frontal lobe's delta band and the parietal lobe's theta band. However, no statistically significant differences were observed between the groups regarding effective connectivity. These findings highlight specific task-related brain functional connectivity differences between reading and math learning difficulties, suggesting potential compensatory mechanisms in RD and cognitive control challenges in MD. The lack of significant effective connectivity findings may be attributed to the small sample size, which is a key limitation of the study. This research emphasizes the need for larger samples, refined task designs, and multimodal neuroimaging in future studies.

Corona Virus Disease 2019 (COVID-19) has spread rapidly to countries all around the world from the end of 2019, which caused a great impact on global health and has had a huge impact on many countries. Since there is still no effective treatment, it is essential to making effective predictions for relevant departments to make responses and arrangements in advance. Under the limited data, the prediction error of LSTM model will increase over time, and its prone to big bias for medium- and long-term prediction. To overcome this problem, our study proposed a LSTM-Markov model, which uses Markov model to reduce the prediction error of LSTM model. Based on confirmed case data in the US, Britain, Brazil and Russia, we calculated the training errors of LSTM and constructed the probability transfer matrix of the Markov model by the errors. And finally, the prediction results were obtained by combining the output data of LSTM model with the prediction errors of Markov Model. The results show that: compared with the prediction results of the classical LSTM model, the average prediction error of LSTM-Markov is reduced by more than 75%, and the RMSE is reduced by more than 60%, the mean R 2 of LSTM-Markov is over 0.96. All those indicators demonstrate that the prediction accuracy of proposed LSTM-Markov model is higher than that of the LSTM model to reach more accurate prediction of COVID-19.

The deformation and failure mechanisms of layered rocks under the combined effects of bedding-plane orientation and confining pressure are crucial for maintaining the stability of both surface and underground geotechnical structures. In this study, rock specimens with different bedding orientations were fabricated using a custom-designed compaction device, and uniaxial compression tests combined with acoustic emission (AE) monitoring were conducted. Furthermore, the microscopic failure processes of layered rock under varying confining pressures and bedding orientations were simulated using three-dimensional particle flow code (PFC3D). The results reveal that, near the peak stress, the slopes of the cumulative AE ring-down counts and cumulative energy curves rose sharply, indicating that the surface cracks are expanding rapidly. The dominant AE frequencies were concentrated in two low-frequency bands and one high-frequency band, with the low-frequency components prevailing. Under uniaxial compression, the peak strength of the specimens exhibited a ‘U’-shaped dependence on bedding angle, whereas the peak AE ring-down count followed an inverted ‘n’-shaped pattern. The peak AE ring-down count displayed an “m”-shaped pattern under confining pressure. Moreover, increasing confining pressure reduced the peak AE activity and attenuated the effect of bedding orientation.