Explore the vast range of titles available.

Widely used sea ice concentration and sea ice cover in polar regions are derived mainly from spaceborne microwave radiometer and scatterometer data, and the typical spatial resolution of these products ranges from several to dozens of kilometers. Due to dramatic changes in polar sea ice, high-resolution sea ice cover data are drawing increasing attention for polar navigation, environmental research, and offshore operations. In this paper, we focused on developing an approach for deriving a high-resolution sea ice cover product for the Arctic using Sentinel-1 (S1) dual-polarization (horizontal-horizontal, HH, and horizontal-vertical, HV) data in extra wide swath (EW) mode. The approach for discriminating sea ice from open water by synthetic aperture radar (SAR) data is based on a modified U-Net architecture, a deep learning network. By employing an integrated stacking model to combine multiple U-Net classifiers with diverse specializations, sea ice segmentation is achieved with superior accuracy over any individual classifier. We applied the proposed approach to over 28 000 S1 EW images acquired in 2019 to obtain sea ice cover products in a high spatial resolution of 400 m. The validation by 96 cases of visual interpretation results shows an overall accuracy of 96.10 %. The S1-derived sea ice cover was converted to concentration and then compared with Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration data, showing an average absolute difference of 5.55 % with seasonal fluctuations. A direct comparison with Interactive Multisensor Snow and Ice Mapping System (IMS) daily sea ice cover data achieves an average accuracy of 93.98 %. These results show that the developed S1-derived sea ice cover results are comparable to the AMSR and IMS data in terms of overall accuracy but superior to these data in presenting detailed sea ice cover information, particularly in the marginal ice zone (MIZ). Data are available at https://doi.org/10.11922/sciencedb.00273 (Wang and Li, 2020).

Internet hospitals (IHs) have rapidly developed as a promising strategy to address supply-demand imbalances in China's medical industry, with their capabilities directly dependent on information platform functionality. Furthermore, a novel theory of \"Trinity\" smart hospital has provided advanced guidelines on IH constructions. This study aimed to explore the construction experience, construction models, and development prospects based on operational data from IHs. Based on existing information systems and internet service functionalities, our hospital has built a \"Smart Hospital Internet Information Platform (SHIIP)\" for IH operations, actively to expand online services, digitalize traditional health care, and explore health care services modes throughout the entire process and lifecycle. This article encompasses the platform architecture design, technological applications, patient service content and processes, health care professional support features, administrative management tools, and associated operational data. Our platform has presented a set of data, including 82,279,669 visits, 420,120 online medical consultations, 124,422 electronic prescriptions, 92,285 medication deliveries, 6,965,566 prediagnosis triages, 4,995,824 offline outpatient appointments, 2025 medical education articles with a total of 15,148,310 views, and so on. These data demonstrate the significant role of IH as an indispensable component of our physical hospital services, with deep integration between online and offline health care systems. The upward trends in various data metrics indicate that our IH has gained significant recognition and usage among both the public and healthcare workers, and may have promising development prospects. Additionally, the platform construction approach, which prioritizes comprehensive service digitization and the 'Trinity' of the public, healthcare workers, and managers, serves as an effective means of promoting the development of Internet Hospitals. Such insights may prove invaluable in guiding the development of IH and facilitating the continued evolution of the Internet healthcare sector.

Background Rehabilitation is a critical method for preventing and controlling disabilities. However, the majority of the global demand for rehabilitation services remains unmet, particularly in low- and middle-income countries. This study aims to explore the complex and concealed stratified relationships between socioeconomic status and the utilization of rehabilitation services among older persons with physical disabilities (PD) from gender and age perspectives. Methods A total of 19,782 observations of older persons with PD were included from the 2007–2013 China National Disabled Persons Condition Monitoring data. This study employs a multiplicative interaction effect model based on logistic regression to analyze the differential association between individual socioeconomic status and the utilization of rehabilitation services, considering gender and age. Results From a gender perspective, the positive correlations between high income, high education and the utilization of rehabilitation services are smaller in males (high income: OR = 0.801, 95% CI 0.653–0.983; high education: OR = 0.679, 95% CI 0.433–1.066). From an age perspective, the positive correlation between high income and the utilization of rehabilitation services is greater among middle- to oldest-old individuals with PD (OR = 1.310, 95% CI 1.077–1.593). Conclusion There are structural gender and age differences in the relationship between the socioeconomic status of older persons with PD and their utilization of rehabilitation services. It is recommended to enhance financial subsidies for rehabilitation services and implement tiered payment structures for low-income groups to alleviate their financial burden. To mitigate gender disparities in healthcare, efforts should focus on increasing awareness of rehabilitation services within health education programs, with community health workers playing a more active role in identifying and assisting those in need. Furthermore, strengthening support for family caregiving and integrating medical and nursing services within the framework of long-term care insurance are essential. Additionally, efforts should be made to the development of preventive rehabilitation programs and the establishment of a multi-tiered integrated rehabilitation system that ensures access to basic services for low-income populations and provides premium options to accommodate diverse needs.

Two new quinazolinone diketopiperazine alkaloids, including versicomide E (2) and cottoquinazoline H (4), together with ten known compounds (1, 3, and 5–12) were isolated and identified from Aspergillus versicolor AS-212, an endozoic fungus associated with the deep-sea coral Hemicorallium cf. imperiale, which was collected from the Magellan Seamounts. Their chemical structures were determined by an extensive interpretation of the spectroscopic and X-ray crystallographic data as well as specific rotation calculation, ECD calculation, and comparison of their ECD spectra. The absolute configurations of (−)-isoversicomide A (1) and cottoquinazoline A (3) were not assigned in the literature reports and were solved in the present work by single-crystal X-ray diffraction analysis. In the antibacterial assays, compound 3 exhibited antibacterial activity against aquatic pathogenic bacteria Aeromonas hydrophilia with an MIC value of 18.6 μM, while compounds 4 and 8 exhibited inhibitory effects against Vibrio harveyi and V. parahaemolyticus with MIC values ranging from 9.0 to 18.1 μM.

Acupuncture has been widely used in the treatment of knee osteoarthritis (KOA), but the selection of acupoints is indeterminate and lacks biological basis. The skin temperature of acupoints can reflect the state of local tissue and may be a potential factor for guiding acupoint selection. This study aims to compare the skin temperature of acupoints between KOA patients and the healthy population. This is a protocol for a cross-sectional case-control study with 170 KOA patients and 170 age- and gender-matched healthy individuals. Diagnosed patients aged 45 to 70 will be recruited in the KOA group. Participants in the healthy group will be matched with the KOA group based on mean age and gender distribution. Skin temperature of 11 acupoints (ST35, EX-LE5, GB33, GB34, EX-LE2, ST34, ST36, GB39, BL40, SP9, SP10) will be extracted from infrared thermography (IRT) images of the lower limbs. Other measurements will include demographic data (gender, age, ethnicity, education, height, weight, BMI) and disease-related data (numerical rating scale, pain sites, duration of pain, pain descriptors, pain activities). The results of this study will provide biological evidence for acupoint selection. This study is a precondition for follow-up studies, in which the value of optimized acupoint selection will be verified. ChiCTR2200058867.

Background: The pathophysiological progression during the hyperacute phase of acute ischemic stroke (AIS) critically determines clinical outcomes. Identification of phase-specific biomarkers and elucidation of their temporal regulatory mechanisms are pivotal for optimizing therapeutic interventions.Methods: Disease signature genes and their mechanisms of action were screened based on the Gene Expression Omnibus database. This involved the use of differentially expressed gene screening, weighted gene co-expression network analysis, Mfuzz analysis, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, support vector machines, random forest algorithms, and gene set enrichment analysis. The expression of disease-characteristic genes and their related mechanisms were further validated in both in vivo and in vitro models.Results: Six hyperacute-phase signature genes (Pip5k1c, Nlgn2, Fzd2, Cd86, Agpat1, and Degs2) were identified in the hyperacute phase of AIS. In light of the gene effect mechanism, the regulation of the neuroinflammatory response and apoptosis by the TLR2/TLR4/NF-κB pathway was monitored in the hyperacute phase of AIS at three times: 3, 6, and 12 h. The results indicated a progressively intensified neuroinflammatory response and the fluctuating growth of early apoptosis changes.Conclusion: This study systematically identifies hyperacute-phase-specific biomarkers in AIS and delineates their temporal regulatory logic. The time-course dynamics of neuronal apoptosis and inflammatory regulation in the hyperacute phase of AIS were monitored. The observed biphasic apoptotic pattern provides mechanistic insights for developing chronologically targeted therapies, such as timed inhibition of TLR4/CD86 during 0–3 h to block inflammatory initiation, or administration of Agpat1 agonists at 3–6 h to stabilize mitochondrial function. These findings help alleviate the current ‘molecular blind spot’ in early stroke diagnosis and intervention.

Understanding the extent to which species can adjust their ranges in response to climate change and track areas of suitable climatic conditions is vital for conservation efforts. Nonetheless, the observed changes in species distribution may also result from inadequate field data. This is particularly relevant for epiphyllous liverworts, which exhibit a poikilohydric lifestyle that makes them more vulnerable to climatic fluctuations than many other higher plants. Furthermore, their small plant size increases the chances of under‐detection in epiphyllous liverworts compared to other plant groups. To enhance our understanding of how species distribution is influenced by climate change, establishing long‐term monitoring plots is essential. In this study, we utilize the BEST platform (Biodiversity along Elevational Gradients: Shifts and Transitions) to furnish empirical evidence regarding the habitat shifts of epiphyllous liverworts along the elevational gradient of Mt. Tianmu. To identify the specific microclimatic conditions vital for the growth and development of epiphyllous liverworts, we conducted a transplant experiment. Our systematic observations from the permanent monitoring plots (2018–2022) led to the discovery of a new population of epiphyllous liverworts located at an elevation of 1130 m. By analyzing in situ microclimatic data on air temperature and moisture, collected consistently over 5 years (2017–2022), we characterized the mean, minimum, and variability of the microclimatic conditions essential for epiphyllous liverwort growth. Additionally, results from elevation transplantation experiments underscore the importance of incorporating dispersal constraints when modeling the species distribution of epiphyllous liverworts for precise predictive outcomes. Our results highlight the importance of long‐term monitoring permanent plots in predicting the effects of global changes on species habitat shifts, and underscore the necessity for comprehensive investigations of the distribution of epiphyllous liverworts at the northern boundary of subtropical evergreen broad‐leaved forests in China. Our observations from the permanent monitoring plots indicate a rapid expansion in the distribution range of epiphyllous liverworts under the influence of climate change. We have identified the specific microclimate conditions necessary for the growth of epiphyllous liverworts. The results from elevation transplantation experiments emphasize the significance of considering dispersal limitations when modeling the species distribution of epiphyllous liverworts for accurate predictive outcomes.

Poziotinib and vonoprazan are two drugs mainly metabolized by CYP3A4. However, the drug-drug interaction between them is unknown. To study the interaction mechanism and pharmacokinetics of poziotinib on vonoprazan. In vitro experiments were performed with rat liver microsomes (RLMs) and the contents of vonoprazan and its metabolite were then determined with UPLC-MS/MS after incubation of RLMs with vonoprazan and gradient concentrations of poziotinib. For the in vivo experiment, rats in the poziotinib treated group were given 5 mg/kg poziotinib by gavage once daily for 7 days, and the control group was only given 0.5% CMC-Na. On Day 8, tail venous blood was collected at different time points after the gavage administration of 10 mg/kg vonoprazan, and used for the quantification of vonoprazan and its metabolite. DAS and SPSS software were used for the pharmacokinetic and statistical analyses. In vitro experimental data indicated that poziotinib inhibited the metabolism of vonoprazan (IC 50  = 10.6 μM) in a mixed model of noncompetitive and uncompetitive inhibition. The inhibitory constant K i was 0.574 μM and the binding constant αK i was 2.77 μM. In vivo experiments revealed that the AUC (0- T ) (15.05 vs. 90.95 μg/mL·h) and AUC (0-∞) (15.05 vs. 91.99 μg/mL·h) of vonoprazan increased significantly with poziotinib pretreatment. The MRT (0-∞) of vonoprazan increased from 2.29 to 5.51 h, while the CLz/F value decreased from 162.67 to 25.84 L/kg·h after pretreatment with poziotinib. Poziotinib could significantly inhibit the metabolism of vonoprazan and more care may be taken when co-administered in the clinic.

Purpose Hepatocellular carcinoma (HCC) is a kind of primary liver cancer. It is a common malignant tumor of digestive system that is difficult to predict the prognosis of patients. As an important epigenetic modification, N7 methyl guanosine (m7G) is indispensable in gene regulation. This regulation may affect the development and occurrence of cancer. However, the prognosis of long non coding RNAs (lncRNAs) in HCC is limited, especially how m7G-related lncRNAs regulate the development of HCC has not been reported. Methods The Cancer Genome Atlas (TCGA) provides us with the expression data and corresponding clinical information of HCC patients we need. We used a series of statistical methods to screen four kinds of m7G-related lncRNAs related to HCC prognosis and through a series of verifications, the results were in line with our expectations. Finally, we also explored the IC50 difference and correlation analysis of various common chemotherapy drugs. Result Our study identified four differentially expressed m7g-related lncRNAs associated with HCC prognosis. Survival curve analysis showed that high risk lncRNAs would lead to poor prognosis of HCC patients. M7G signature's AUC was 0.789, which shows that the prognosis model we studied has certain significance in predicting the prognosis of HCC patients. Moreover, our study found that different risk groups have different immune and tumor related pathways through gene set enrichment analysis. In addition, many immune cell functions are significantly different among different risk groups, such as T cell functions, including coordination of type I INF response and coordination of type II INF response. The expression of PDCD1, HHLA2, CTLA-4 and many other immune checkpoints in different risk groups is also different. Additionally, we analyzed the differences of IC50 and risk correlation of 15 chemotherapeutic drugs among different risk groups. Conclusion A novel lncRNAs associated with m7G predicts the prognosis of HCC.

Although blockchain technology has received a significant amount of cutting-edge research on constructing a novel carbon trade market in theory, there is little research on using blockchain in carbon emission trading schemes (ETS). This study intends to address existing gaps in the literature by creating and simulating an ETS system based on blockchain technology. Using the ciphertext-policy attributed-based encryption algorithm and the Fabric network to build a platform may optimize the amount of data available while maintaining privacy security. Considering the augmentation of information interaction during the auction process brought about by blockchain, the learning behavior of bidding firms is introduced to investigate the impact of blockchain on ETS auction. In particular, implementing smart contracts can provide a swift and automatic settlement. The simulation results of the proposed system demonstrate the following: (1) fine-grained access is possible with a second delay; (2) the average annual compliance levels increase by 2% when bidders’ learning behavior is considered; and (3) the blockchain network can process more than 350 reading operations or 7 writing operations in a second. Highlights Novel cooperative management of an ETS platform based on blockchain is proposed. The data access control policy based on CP-ABE is used to solve the contradiction between data privacy on the firm chain and government supervision. A learned auction strategy is proposed to suit the enhancement of information interaction caused by blockchain technology. This study provides a new method for climate change policymakers to consider the blockchain application of the carbon market.