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The effects of nonextensive electrons on nonlinear ion acoustic waves in dusty negative ion plasmas with ion–dust collisions are investigated. Analytical results show that both solitary and shock waves are supported in this system. The wave propagation is governed by a Korteweg–de Vries Burgers-type equation. The coefficients of this equation are modified by the nonextensive parameter q. Numerical calculations indicate that the amplitude of solitary wave and oscillatory shock can be obviously modified by the nonextensive electrons, but the monotonic shock is little affected.

J-aggregation is an efficient strategy for the development of fluorescent imaging agents in the second near-infrared window. However, the design of the second near-infrared fluorescent J-aggregates is challenging due to the lack of suitable J-aggregation dyes. Herein, we report meso -[2.2]paracyclophanyl-3,5-bis- N , N -dimethylaminostyrl BODIPY (PCP-BDP2) as an example of BODIPY dye with J-aggregation induced the second near-infrared fluorescence. PCP-BDP2 shows an emission maximum at 1010 nm in the J-aggregation state. Mechanism studies reveal that the steric and conjugation effect of the PCP group on the BODIPY play key roles in the J-aggregation behavior and photophysical properties tuning. Notably, PCP-BDP2 J-aggregates can be utilized for lymph node imaging and fluorescence-guided surgery in the nude mouse, which demonstrates their potential clinical application. This study demonstrates BODIPY dye as an alternate J-aggregation platform for developing the second near-infrared imaging agents. J-aggregation has been proved to be an efficient strategy for the development of fluorescent imaging agents in the NIR-II spectral region but the design of appropriate J-aggregates is challenging. Here, the authors demonstrate J-aggregation of a BODIPY dye with NIR-II emission and demonstrate lymph node imaging for fluorescence guided surgery.

Background Alfalfa, the “queen of forage”, is the most extensively cultivated forage legume in the world. The development and yield of alfalfa are seriously limited by abiotic stress. MADS-box transcription factors are one of the largest gene families and play a pivotal role in plant development and abiotic stress. However, little is known regarding the MADS-box transcription factors in autotetraploid cultivated alfalfa. Results In the present study, we identified 120 MsMADS-box genes in the alfalfa genome. Phylogenetic analysis indicated that 75 type-I MsMADS-box genes were classified into the Mα, Mβ, and Mγ subgroups, and 45 type-II MsMADS-box genes were classified into 11 subgroups. The promoter region of MsMADS-box genes containing several hormone and stress related elements. Chromosomal location analysis revealed that 117 MsMADS-box genes were unevenly distributed on 32 chromosomes, and the remaining three genes were located on unmapped scaffolds. A total of nine pairs of segmental duplications and four groups of tandem duplications were found. Expression analysis showed that MsMADS-box genes were differentially expressed in various tissues and under abiotic stresses. qRT-PCR analysis revealed that the expression profiles of eight selected MsMADS-box genes were distinct under various stresses. Conclusions In this study, MsMADS-box genes were identified in the cultivated alfalfa genome based on autotetraploid level, and further confirmed by Gene Ontology (GO) analysis, phylogenetic analysis, sequence features and expression analysis. Taken together, these findings will provide clues for further study of MsMADS-box functions and alfalfa molecular breeding. Our study is the first to systematically identify and characterize the MADS-box transcription factors in autotetraploid cultivated alfalfa ( Medicago sativa L.), and eight MsMADS-box genes were significantly involved in response to various stresses.

Urban marathons have become important platforms for fulfilling individuals’ aspirations for a better life and promote residents’ health. This study employs a choice experiment method and utilizes embodied theory to explore attributes and design attributes levels of urban marathon products, based on an analysis of social network text content. Through a questionnaire survey of marathon participants, the results reveal that prioritize embodied experiential attributes in the following order: visual experience, auditory experience, extended recollection, self-transcendence, kinesthetic experience, registration fees, and social bonding. Runners with higher incomes and event expenditure prefer visual experiences, while those who participating more frequently exhibit lower preferences for kinesthetic experience. Runners with higher education levels prioritize off-scene experiences. Based on preference heterogeneity, four distinct runner types are identified: ritual-driven runners, audio-visual experience-oriented, achievement-oriented, and social emotion-oriented. Management implications and recommendations for organizers of urban marathon events are provided.

In this study, the detailed volatile compositions of Chinese herbaceous aroma-type Baijiu (HAB) were characterized by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GC-TOFMS). A total of 606 compounds were tentatively identified by similarity, mass spectral data, and retention indices, among which 247 compounds were positively verified by authentic standards. Esters were present in higher numbers (179), followed by aldehydes and ketones (111), and alcohols (81). In addition, there were also many terpenes (82), sulfides (37), furans (29), nitrogenous compounds (29), lactones (17), and so on. Meanwhile, the extraction effects of volatile components from different sample pretreatment methods (headspace solid-phase microextraction (HS-SPME), solid phase extraction (SPE), and stir bar sorptive extraction (SBSE)) for HAB were also revealed. The results indicated that HS-SPME has a better extraction effect on easily volatile compounds, such as alcohols and sulfides, especially for terpenes. SPE was particularly beneficial for the analysis of nitrogen-containing compounds; SBSE showed medium extraction ability for most types of compounds and was more suitable for the target analysis of trace content substances.

T cell immunotherapy remains an attractive approach for cancer immunotherapy. T cell immunotherapy mainly employs chimeric antigen receptor (CAR)- and T cell receptor (TCR)-engineered T cells. CAR-T cell therapy has been an essential breakthrough in treating hematological malignancies. TCR-T cells can recognize antigens expressed both on cell surfaces and in intracellular compartments. Although TCR-T cells have not been approved for clinical application, a number of clinical trials have been performed, particularly for solid tumors. In this article, we summarized current TCR-T cell advances and their potential advantages for solid tumor immunotherapy.

Composition of gut bacteria and serum metabolites in young, obese individuals is partially restored following weight loss surgery, including Bacteroides thetaiotaomicron , which decreases serum glutamate levels and fat mass gain in mice. Emerging evidence has linked the gut microbiome to human obesity. We performed a metagenome-wide association study and serum metabolomics profiling in a cohort of lean and obese, young, Chinese individuals. We identified obesity-associated gut microbial species linked to changes in circulating metabolites. The abundance of Bacteroides thetaiotaomicron , a glutamate-fermenting commensal, was markedly decreased in obese individuals and was inversely correlated with serum glutamate concentration. Consistently, gavage with B. thetaiotaomicron reduced plasma glutamate concentration and alleviated diet-induced body-weight gain and adiposity in mice. Furthermore, weight-loss intervention by bariatric surgery partially reversed obesity-associated microbial and metabolic alterations in obese individuals, including the decreased abundance of B. thetaiotaomicron and the elevated serum glutamate concentration. Our findings identify previously unknown links between intestinal microbiota alterations, circulating amino acids and obesity, suggesting that it may be possible to intervene in obesity by targeting the gut microbiota.

As Internet of Things (IoT) networks expand globally with an annual increase of active devices, providing better safeguards to threats is becoming more prominent. An intrusion detection system (IDS) is the most viable solution that mitigates the threats of cyberattacks. Given the many constraints of the ever-changing network environment of IoT devices, an effective yet lightweight IDS is required to detect cyber anomalies and categorize various cyberattacks. Additionally, most publicly available datasets used for research do not reflect the recent network behaviors, nor are they made from IoT networks. To address these issues, in this paper, we have the following contributions: (1) we create a dataset from IoT networks, namely, the Center for Cyber Defense (CCD) IoT Network Intrusion Dataset V1 (CCD-INID-V1); (2) we propose a hybrid lightweight form of IDS—an embedded model (EM) for feature selection and a convolutional neural network (CNN) for attack detection and classification. The proposed method has two models: (a) RCNN: Random Forest (RF) is combined with CNN and (b) XCNN: eXtreme Gradient Boosting (XGBoost) is combined with CNN. RF and XGBoost are the embedded models to reduce less impactful features. (3) We attempt anomaly (binary) classifications and attack-based (multiclass) classifications on CCD-INID-V1 and two other IoT datasets, the detection_of_IoT_botnet_attacks_N_BaIoT dataset (Balot) and the CIRA-CIC-DoHBrw-2020 dataset (DoH20), to explore the effectiveness of these learning-based security models. Using RCNN, we achieved an Area under the Receiver Characteristic Operator (ROC) Curve (AUC) score of 0.956 with a runtime of 32.28 s on CCD-INID-V1, 0.999 with a runtime of 71.46 s on Balot, and 0.986 with a runtime of 35.45 s on DoH20. Using XCNN, we achieved an AUC score of 0.998 with a runtime of 51.38 s for CCD-INID-V1, 0.999 with a runtime of 72.12 s for Balot, and 0.999 with a runtime of 72.91 s for DoH20. Compared to KNN, XCNN required 86.98% less computational time, and RCNN required 91.74% less computational time to achieve equal or better accurate anomaly detections. We find XCNN and RCNN are consistently efficient and handle scalability well; in particular, 1000 times faster than KNN when dealing with a relatively larger dataset-Balot. Finally, we highlight RCNN and XCNN’s ability to accurately detect anomalies with a significant reduction in computational time. This advantage grants flexibility for the IDS placement strategy. Our IDS can be placed at a central server as well as resource-constrained edge devices. Our lightweight IDS requires low train time and hence decreases reaction time to zero-day attacks.

Given the unprecedented and profound impact on the traditional sports industry and its economic driving force brought by the “Internet +”, the purpose of this study is to explore the driving relationship between the sports industry and local economic development and deconstruct the dynamic regulation mechanism of “Internet +” on the economic spillover of the sports industry. Empirical data collected from China’s 11 inter-provincial panel data from 2015–2019 were analyzed through the fixed-effects and threshold models. The study finds that the economic spillover of the sports industry has significantly promoted regional economic development, and the regulation effect of the Internet has complex non-linear characteristics. Only when Internet development exceeds a specific threshold can it develop a benign complementary mechanism with the sports industry. The impact of “Internet +” on the threshold regulation of the sports industry economic spillover has spatial and temporal differentiation characteristics in the three dimensions of Internet hardware level, Internet penetration rate, and Internet application value. The results of this study extend the current study, indicating that it is a practical choice for local governments to develop the economy through the sports industry. Provinces and cities should enhance the Internet penetration rate, expand Internet business applications, and upgrade Internet development to a specific point to maximize the drive of positive spillover. Regional heterogeneity requires differential regulation strategies and more concentration on the middle and western regions.

Background Alfalfa is the most extensively cultivated forage legume. Salinity is a major environmental factor that impacts on alfalfa’s productivity. However, little is known about the molecular mechanisms underlying alfalfa responses to salinity, especially the relative contribution of the two important components of osmotic and ionic stress. Results In this study, we constructed the first full-length transcriptome database for alfalfa root tips under continuous NaCl and mannitol treatments for 1, 3, 6, 12, and 24 h (three biological replicates for each time points, including the control group) via PacBio Iso-Seq. This resulted in the identification of 52,787 full-length transcripts, with an average length of 2551 bp. Global transcriptional changes in the same 33 stressed samples were then analyzed via BGISEQ-500 RNA-Seq. Totals of 8861 NaCl-regulated and 8016 mannitol-regulated differentially expressed genes (DEGs) were identified. Metabolic analyses revealed that these DEGs overlapped or diverged in the cascades of molecular networks involved in signal perception, signal transduction, transcriptional regulation, and antioxidative defense. Notably, several well characterized signalling pathways, such as CDPK, MAPK, CIPK, and PYL-PP2C-SnRK2, were shown to be involved in osmotic stress, while the SOS core pathway was activated by ionic stress. Moreover, the physiological shifts of catalase and peroxidase activity, glutathione and proline content were in accordance with dynamic transcript profiles of the relevant genes, indicating that antioxidative defense system plays critical roles in response to salinity stress. Conclusions Overall, our study provides evidence that the response to salinity stress in alfalfa includes both osmotic and ionic components. The key osmotic and ionic stress-related genes are candidates for future studies as potential targets to improve resistance to salinity stress via genetic engineering.