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Abstract Brain damage caused by acute hypoxia is associated with the physiological activities of mitochondria. Although mitochondria being dynamically regulated, our comprehensive understanding of the response of specific brain cell types to acute hypoxia remains ambiguous. Tumor necrosis factor receptor-associated protein 1 (TRAP1), a mitochondrial-based molecular chaperone, plays a role in controlling mitochondrial movements. Herein, we demonstrated that acute hypoxia significantly alters mitochondria morphology and functionality in both in vivo and in vitro brain injury experiments. Summary-data-based Mendelian Randomization (SMR) analyses revealed possible causative links between mitochondria-related genes and hypoxia injury. Advancing the protein-protein interaction network and molecular docking further elucidated the associations between TRAP1 and mitochondrial dynamics. Furthermore, it was shown that TRAP1 knockdown levels variably affected the expression of key mitochondrial dynamics proteins (DRP1, FIS1, and MFN1/2) in primary hippocampal neurons, astrocytes, and BV-2 cell, leading to changes in mitochondrial structure and function. Understanding the function of TRAP1 in altering mitochondrial physiological activity during hypoxia-induced acute brain injury could help serve as a potential therapeutic target to mitigate neurological damage.

Abstract Objective To explore the cardiac structural and functional changes in obstructive sleep apnea-hypopnea syndrome (OSAHS) patients with heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF). Methods This retrospective study included 336 OSAHS patients with HFpEF. They were divided into Groups A (without an AF history and no AF episodes during cardiac color ultrasound examination), B (an AF history but no AF episodes), and C (an AF history and AF episodes). They all received cardiac color ultrasound examinations. Cardiac structural and functional changes in ultrasonic cardiograms were compared between the three groups. Results Compared with Groups A and B, Group C showed increased left atrial diameter (LAD), left atrial volume (LAV), right ventricular diameter at end-diastole (RV-D1), right ventricular diameter at end-systole (RV-D2), right ventricular outflow tract diameter (RVOT2), right atrial diameter at end-diastole (RA-D1), right atrial diameter at end-systole (RA-D2), and right atrial area (RAA) (p

Abstract The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has great potential for development due to its advantages of the use of multiple beams, low energy consumption, high repetition frequency, and high measurement sensitivity. However, the weak photon signal emitted by the photon counting lidar is susceptible to the background noise caused by the sun and the atmosphere, which can seriously affect the processing and application of laser data. This paper proposes an improved DBSCAN clustering algorithm for denoising single photon laser point clouds in mountainous areas. Firstly, a grouping method based on elevation and distance statistics is proposed to reduce the influence of terrain undulations on denoising accuracy. Finally, an automatic radius search method is put forward to determine clustering radius of each group, automatically find the optimal radius, and improve the existing DBSCAN clustering method. The method proposed in this paper is compared with the classical DBSCAN algorithm. The results show that the proposed algorithm significantly improves denoising accuracy in mountainous areas and effectively filters out most background noise. Graphical Abstract

Paper Mulberry (Broussonetia papyrifera) possesses medicinal, economic, and ecological significance and is extensively used for feed production, papermaking, and ecological restoration due to its ease of propagation, rapid growth rate, and strong stress resistance. The recent completion of the sequencing of the Paper Mulberry genome has prompted further research into the genetic breeding and molecular biology of this important species. A highly stable reference gene is essential to enhance the quantitative analysis of functional genes in Paper Mulberry; however, none has been identified. Accordingly, in this study, the leaves, stems, roots, petioles, young fruits, and mature fruits of Paper Mulberry plants were selected as experimental materials, and nine candidate reference genes, namely, α-TUB1, α-TUB2, β-TUB, H2A, ACT, DnaJ, UBQ, CDC2, and TIP41, were identified by RT-qPCR. Their stability was assessed using the geNorm, Normfinder, Delta Ct, BestKeeper, and RefFinder algorithms, identifying ACT and UBQ as showing the greatest stability. The expression of BpMYB090, which regulates the production of trichomes, was examined in the leaves of plants of the wild type (which have more trichomes) and mutant (which have fewer trichomes) at various developmental stages to validate the results of this study. As a result, their identification addresses a critical gap in the field of Paper Mulberry research, providing a solid foundation for future research that will concentrate on the characterization of pertinent functional genes in this economically valuable species.

Sunflower seed meal, a by-product of sunflower seed oil production, is a high-quality protein source that is nutritious in terms of abundant protein, has reasonable amino acid composition and is hypoallergenic. At present, most reviews on sunflower seed meal focus on the fields of its processing and application status, comprehensive utilization, active ingredients, modification technologies and application in feed. However, due to the presence of polyphenols (mainly chlorogenic acid), sunflower seed meal is susceptible to browning during preparation and processing, which seriously restricts its deep development and utilization. The major techniques for the removal of chlorogenic acid from sunflower seed meal include water extraction, organic solvent extraction, physical field assisted method, enzymatic method, salt inhibition method and resin adsorption, but they have been scarcely reviewed systematically. In this paper, we review the latest research progress on the composition of sunflower seed protein, its interaction with chlorogenic acid, the removal methods of chlorogenic acid from sunflower seed meal, and the application of sunflower seed protein in the food field in order to provide a reference for further processing and utilization of sunflower seed meal.

During the development of service-based software systems, Geospatial Service (GS) replacement is often performed, which requires the discovery of functionally similar services in service registries to replace failed services. Compared to real-time similarity computations, direct extraction of similar services from constructed similarity relationships can yield higher replacement efficiency. However, missing and inconsistent service-registry information impedes accurate similarity relationship construction. Here, we propose a Graph Neural Network (GNN)-based model for GS Similarity Relationship construction considering service descriptions and tags, which is named GSSR-GNN. As the sparsity of the service similarity relationship graph constructed based on labeled samples limits the information propagation ability, a graph augmentation method for similarity relationship construction among second-order neighbors is proposed. Considering the differences in the semantic-information feature distributions, such as the service descriptions and tags, a feed-forward neural network-based fusion method is designed to embed them into the same vector space. Pre-trained Bidirectional Encoder Representations from Transformers (BERT) and WordNet models are introduced to enhance the service-representation expressiveness. When an enhanced service representation is input to the GNN, the similarity is calculated and the service similarity relationship is obtained. Experimental results show that the proposed model constructs service similarity relationships with high precision, thus improving the service replacement efficiency and reducing the computational cost of service registry during service replacement.

Abstract. Background:. Programmed death 1 (PD-1) blockade plus chemotherapy has become the new first-line standard of care for patients with advanced non-small-cell lung cancer (NSCLC). Yet not all NSCLC patients benefit from this regimen. This study aimed to investigate the predictors of PD-1 blockade plus chemotherapy in untreated advanced NSCLC. Methods:. We integrated clinical, genomic, and survival data from 287 patients with untreated advanced NSCLC who were enrolled in one of five registered phase 3 trials and received PD-1 blockade plus chemotherapy or chemotherapy alone. We randomly assigned these patients into a discovery cohort (n = 125), a validation cohort (n = 82), and a control cohort (n = 80). The candidate genes that could predict the response to PD-1 blockade plus chemotherapy were identified using data from the discovery cohort and their predictive values were then evaluated in the three cohorts. Immune deconvolution was conducted using transcriptome data of 1014 NSCLC patients from The Cancer Genome Atlas dataset. Results:. A genomic variation signature, in which one or more of the 15 candidate genes were altered, was correlated with significantly inferior response rates and survival outcomes in patients treated with first-line PD-1 blockade plus chemotherapy in both discovery and validation cohorts. Its predictive value held in multivariate analyses when adjusted for baseline parameters, programmed cell death ligand 1 (PD-L1) expression level, and tumor mutation burden. Moreover, applying both the 15-gene panel and PD-L1 expression level produced better performance than either alone in predicting benefit from this treatment combination. Immune landscape analyses revealed that tumors with one or more variation in the 15-gene panel were associated with few immune infiltrates, indicating an immune-desert tumor microenvironment. Conclusion:. These findings indicate that a 15-gene panel can serve as a negative prediction biomarker for first-line PD-1 blockade plus chemotherapy in patients with advanced NSCLC.

The complex interactions were performed among non-pharmaceutical interventions, vaccinations, and hosts for all epidemics in mainland China during the spread of COVID-19. Specially, the small-scale epidemic in the city described by SVEIR model was less found in the current studies. The SVEIR model with control was established to analyze the dynamical and epidemiological features of two epidemics in Jinzhou City led by Omicron variants before and after Twenty Measures. In this study, the total population (N) of Jinzhou City was divided into five compartments: the susceptible (S), the vaccinated (V), the exposed (E), the infected (I), and the recovered (R). By surveillance data and the SVEIR model, three methods (maximum likelihood method, exponential growth rate method, next generation matrix method) were governed to estimate basic reproduction number, and the results showed that an increasing tendency of basic reproduction number from Omicron BA.5.2 to Omicron BA.2.12.1. Meanwhile, the effective reproduction number for two epidemics were investigated by surveillance data, and the results showed that Jinzhou wave 1 reached the peak on November 1 and was controlled 7 days later, and that Jinzhou wave 2 reached the peak on November 28 and was controlled 5 days later. Moreover, the impacts of non-pharmaceutical interventions (awareness delay, peak delay, control intensity) were discussed extensively, the variations of infection scales for Omicron variant and EG.5 variant were also discussed. Furthermore, the investigations on peaks and infection scales for two epidemics in dynamic zero-COVID policy were operated by the SVEIR model with control. The investigations on public medical requirements of Jinzhou City and Liaoning Province were analyzed by using SVEIR model without control, which provided a possible perspective on variant evolution in the future.

Background: The structure of age groups and social contacts of the total population influenced infection scales and hospital-bed requirements, especially influenced severe infections and deaths during the global prevalence of COVID-19. Before the end of the year 2022, Chinese government implemented the national vaccination and had built the herd immunity cross the country, and announced Twenty Measures (November 11) and Ten New Measures (December 7) for further modifications of dynamic zero-COVID polity on the Chinese mainland. With the nation-wide vaccination and modified measures background, Fuzhou COVID-19 large wave (November 19, 2022–February 9, 2023) led by Omicron BA.5.2 variant was recorded and prevailed for three months in Fujian Province. Methods: A multi-age groups susceptible-exposed-infected-hospitalized-recovered (SEIHR) COVID-19 model with social contacts was proposed in this study. The main object was to evaluate the impacts of age groups and social contacts of the total population. The idea of Least Squares method was governed to perform the data fittings of four age groups against the surveillance data from Fujian Provincial Center for Disease Control and Prevention (Fujian CDC). The next generation matrix method was used to compute basic reproduction number for the total population and for the specific age group. The tendencies of effective reproduction number of four age groups were plotted by using the Epiestim R package and the SEIHR model for in-depth discussions. The sensitivity analysis by using sensitivity index and partial rank correlation coefficients values (PRCC values) were operated to reveal the differences of age groups against the main parameters. Results: The main epidemiological features such as basic reproduction number, effective reproduction number and sensitivity analysis were extensively discussed for multi-age groups SEIHR model in this study. Firstly, by using of the next generation matrix method, basic reproduction number R0 of the total population was estimated as 1.57 using parameter values of four age groups of Fuzhou COVID-19 large wave. Given age group k, the values of R0k (age group k to age group k), the values of R0k (an infected of age group k to the total population) and the values of R^0k (an infected of the total population to age group k) were also estimated, in which the explorations of the impacts of age groups revealed that the relationship R0k>R0k>R^0k was valid. Then, the fluctuating tendencies of effective reproduction number Rt were demonstrated by using two approaches (the surveillance data and the SEIHR model) for Fuzhou COVID-19 large wave, during which high-risk group (G4 group) mainly contributed the infection scale due to high susceptibility to infection and high risks to basic diseases. Further, the sensitivity analysis using two approaches (the sensitivity index and the PRCC values) revealed that susceptibility to infection of age groups played the vital roles, while the numerical simulation showed that infection scale varied with the changes of social contacts of age groups. The results of this study claimed that the high-risk group out of the total population was concerned by the local government with the highest susceptibility to infection against COVID-19. Conclusions: This study verified that the partition structure of age groups of the total population, the susceptibility to infection of age groups, the social contacts among age groups were the important contributors of infection scale. The less social contacts and adequate hospital beds for high-risk group were profitable to control the spread of COVID-19. To avoid the emergence of medical runs against new variant in the future, the policymakers from local government were suggested to decline social contacts when hospital beds were limited.