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Background It has been a consensus that cardiac rehabilitation is an effective comprehensive intervention for patients with coronary heart disease (CHD), but the quality of relevant guidelines is still unclear, and recommendations from the guidelines need to be integrated. Objective To systematically review the guidelines on cardiac rehabilitation in patients with CHD, providing evidence to inform clinical practice. Methods In June 2022, guidelines on cardiac rehabilitation in patients with CHD were searched in electronic databases of the Cochrane Library, Web of Science, PubMed, CNKI, CQVIP and Wanfang Data, relevant guideline repositories and association websites from inception to 30 June 2022. Literature screening and data extraction were performed by two researchers separately according to the inclusion and exclusion criteria. The quality of included guidelines was assessed using the Appraisal of Guidelines for Research & EvaluationⅡ (AGREEⅡ), and recommendations from which were summarized. Results Ten guidelines (eight of them are foreign guidelines) with publication time ranging from 2011 to 2020 were eventually included. The average score of every AGREEⅡ domain was 71% for scope and purpose, 65% for stakeholder involvement, 58% for rigor of development, 80% for clarity of presentation, 64% for applicability, and 45% for editorial independence. Four guidelines were rated as grade A and the remaining six as grade B. Six aspects are involved in recommendations, including basic requirements of cardiac rehabilitation, heath education, risk factors control, psychological support, exercise training, and improvement of cardiac rehabilitation participation. Conclusion The quality of included guidelines is at a moderate to high level. More efforts are needed to improve the domains in stakeholder involvement, rigor of development, applicability, and editorial independence. Recommendations of the 10 guidelines tend to be consistent, but there are still insufficient recommendations on improving cardiac rehabilitation participation. There is a gap in the quality between domestic and foreign guidelines, so it is necessary to develop a high-quality guideline on cardiac rehabilitation for patients with CHD in China.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

As of January of 2021, the highly transmissible B.1.1.7 variant of SARS-CoV-2, which was first identified in the United Kingdom (U.K.), has gained a strong foothold across the world. Because of the sudden and rapid rise of B.1.1.7, we investigated the prevalence and growth dynamics of this variant in the United States (U.S.), tracking it back to its early emergence and onward local transmission. We found that the RT-qPCR testing anomaly of S gene target failure (SGTF), first observed in the U.K., was a reliable proxy for B.1.1.7 detection. We sequenced 212 B.1.1.7 SARS-CoV-2 genomes collected from testing facilities in the U.S. from December 2020 to January 2021. We found that while the fraction of B.1.1.7 among SGTF samples varied by state, detection of the variant increased at a logistic rate similar to those observed elsewhere, with a doubling rate of a little over a week and an increased transmission rate of 35-45%. By performing time-aware Bayesian phylodynamic analyses, we revealed several independent introductions of B.1.1.7 into the U.S. as early as late November 2020, with onward community transmission enabling the variant to spread to at least 30 states as of January 2021. Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Nonlinear deformation is a dynamically changing pattern of multiple surface deformations caused by groundwater overexploitation, underground coal mining, landslides, urban construction, etc., which are often accompanied by severe damage to surface structures or lead to major geological disasters; therefore, the high-precision monitoring and prediction of nonlinear surface deformation is significant. Traditional deep learning methods encounter challenges such as long-term dependencies or difficulty capturing complex spatiotemporal patterns when predicting nonlinear deformations. In this study, we developed a dual-attention-mechanism CNN-LSTM network model (DACLnet) to monitor and accurately predict nonlinear surface deformations precisely. Using advanced time series InSAR results as input, the DACLnet integrates the spatial feature extraction capability of a convolutional neural network (CNN), the advantages of the time series learning of a long short-term memory (LSTM) network, and the enhanced focusing effect of the dual-attention mechanism on crucial information, significantly improving the prediction accuracy of nonlinear surface deformations. The groundwater overexploitation area of the Turpan Basin, China, is selected to test the nonlinear deformation prediction effect of the proposed DACLnet. The results demonstrate that the DACLnet accurately captures developmental trends in historical surface deformations and effectively predicts surface deformations for the next two months in the study area. Compared to traditional LSTM and CNN-LSTM methods, the root mean square error (RMSE) of the DACLnet improved by 85.09% and 68.57%, respectively. These research results can provide crucial technical support for the early warning and prevention of geological disasters and can serve as an effective alternative tool for short-term ground subsidence prediction in areas lacking hydrogeological and other related data. [ABSTRACT FROM AUTHOR]

Background: Sphingolipids not only serve as structural components for maintaining cell membrane fluidity but also function as bioactive molecules involved in cell signaling and the regulation of various biological processes. Their pivotal role in cancer cell development, encompassing cancer cell proliferation, migration, angiogenesis, and metastasis, has been a focal point for decades. However, the contribution of sphingolipids to the complexity of tumor microenvironment promoting cancer progression has been rarely investigated. Methods: Through the integration of publicly available bulk RNA‐seq and single‐cell RNA‐seq data, we conducted a comprehensive analysis to compare the transcriptomic features between tumors and adjacent normal tissues, thus elucidating the intricacies of the tumor microenvironment (TME). Results: Disparities in sphingolipid metabolism (SLM)‐associated genes were observed between normal and cancerous tissues, with the TME characterized by the enrichment of sphingolipid signaling in macrophages. Cellular interaction analysis revealed robust communication between macrophages and cancer cells exhibiting low SLM, identifying the crucial ligand‐receptor pair, macrophage inhibitory factor (MIF)‐CD74. Pseudo‐time analysis unveiled the involvement of SLM in modulating macrophage polarization towards either M1 or M2 phenotypes. Categorizing macrophages into six subclusters based on gene expression patterns and function, the SPP1+ cluster, RGS1+ cluster, and CXCL10+ cluster were likely implicated in sphingolipid‐induced M2 macrophage polarization. Additionally, the CXCL10+, AGER+, and FABP4+ clusters were likely to be involved in angiogenesis through their interaction with endothelial cells. Conclusion: Based on multiple scRNA‐seq datasets, we propose that a MIF‐targeted strategy could potentially impede the polarization from M1 to M2 and impair tumor angiogenesis in low‐SLM non‐small cell lung cancer (NSCLC), demonstrating its potent antitumor efficacy. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly around the world since the first cases were reported in late 2019 (1,2). Prior to [...]

To deeply understand the characteristics of soil freeze–thaw water–heat change in the alpine grassland in the Duogerong Basin of the Yellow River source, the soil water–heat profile change monitoring was carried out based on the field monitoring station in the Duogerong Basin of the Yellow River source. By analyzing the comprehensive monitoring data from September 2022 to September 2023, the characteristics of the soil temperature and water content changes in the freeze–thaw cycle of the alpine grassland in the Duogerong Basin at the source of the Yellow River were explored. The results showed that the temperature and water content of each layer of the soil profile changed periodically, and the range of change was negatively correlated with the depth. The annual freeze–thaw process at the observation site is divided into five stages: 31 October to 3 November is the short initial freezing period, 4 November to 18 April is the stable freezing period, 19 April to 26 April is the early ablation period, 27 April to 30 April is the late ablation period, and 1 May to 30 October is the complete ablation period. The maximum soil freezing depth during the observation period was about 250 cm. Soil temperature and moisture content change affect each other; soil water is essential in heat transfer, and the two correlate well. The research results provide theoretical support for further understanding the characteristics of soil hydrothermal changes during the freeze–thaw process in the alpine grassland permafrost area at the source of the Yellow River. [ABSTRACT FROM AUTHOR]

Transformer can effectively model long rang dependency, but suffer from uncapable to extract local feature patterns. While CNNs exploit local features effectively. In this paper, we seek to combine convolution and Transformers improves over using them individually, and propose improved features using convolution-augmented transformers for keyword spotting. The convolution-augmented transformers are constructed with a ResNet front-end and a convolution-augmented transformers back-end in series. Using this improved feature for keyword spotting task. The results show that the improved features using convolution- augmented transformers can yield at least 3% improvement compared with other features.

In coastal ecosystems, water availability is limited because of the high soil salinity influenced by sea water intrusion, high soil noncapillary porosity, and significant seasonal fluctuation of precipitation. Therefore, water availability is a key determinant of plant growth and distribution in coastal ecosystems. Tamarix chinensis Lour. and Ziziphus jujuba var. spinosa Hu are two coexisting shrub species growing on Chenier Island in the Yellow River Delta (YRD), China. Our aim was to investigate how the water-use strategies of the two species respond to variations in soil moisture to improve understand of their adaptations to drought stress and their coexistence mechanism. During the growing season, the oxygen stable isotope signatures ([delta][sup.18]O) were measured for soil water in different soil depths (0-20, 20-40,40-60, and 60-100 cm), shallow groundwater, and xylem water. The proportional contributions of potential water sources for the two species were calculated by using the IsoSource mixing model. The results showed that the [delta][sup.18]O values of the two species showed a clear seasonal difference. When soil moisture was high and air temperature was low, T. chinensis mainly used water from soil depths of 60-100 cm, while Z. jujuba mainly used water from soil depths of 0-40 cm. When soil moisture was low or air temperature was high, T. chinensis mainly used the saline shallow groundwater, while Z. jujuba mainly used water from soil depths of 20-100 cm. When there was a large amount of precipitation, both T. chinensis and Z. jujuba mainly absorbed water from soil depths of 20-40 cm. Tamarix chinensis and Z. jujuba had different water-use patterns during the growing season, which reflected their adaptations to seasonal fluctuations in soil water content within a water-limited coastal ecosystem, while the niche differentiation in water use of the two species clarifies their coexistence mechanism. Key words: water-use strategies, water resource, coexisting shrubs, coastal zone, Yellow River Delta. Dans les ecosystemes cotiers, la disponibilite de l'eau du sol est reduite a cause de la salinite elevee du sol qui est influencee par l'intrusion de l'eau de mer, de la porosite non capillaire elevee du sol et de la fluctuation saisonniere de la precipitation. Par consequent, la disponibilite de l'eau est un facteur determinant pour la croissance et la repartition des plantes dans les ecosystemes cotiers. Tamarix chinensis Lour. et Ziziphus jujuba var. spinosa Hu sont deux especes d'arbuste qui coexistent et croissent sur l'ile Chenier dans le delta du fleuve Jaune en Chine. Notre objectif consistait a etudier de quelle facon les strategies d'utilisation de l'eau des deux especes reagissent aux variations de l'humidite du sol dans le but d'ameliorer notre comprehension de leur adaptation au stress cause par la secheresse et de leur mecanisme de coexistence. Durant la saison de croissance, la signature de l'isotope stable de l'oxygene ([delta][sup.18]O) a ete mesuree dans l'eau du sol a differentes profondeurs (0-20, 20-40, 40-60, et 60-100 cm), dans les eaux souterraines peu profondes et dans le xyleme. La contribution proportionnelle des sources d'eau potentielles a ete calculee chez les deux especes en utilisant le modele de melange IsoSource. Les resultats indiquent qu'il y a une difference saisonniere claire entre les deux especes d'apres les valeurs de [delta][sup.18]O. Lorsque l'humidite du sol est elevee et la temperature de l'air est basse, T. chinensis utilise surtout l'eau du sol a une profondeur de 60-100 cm tandis que Z. jujuba utilise surtout l'eau du sol a une profondeur de 0-40 cm. Lorsque l'humidite du sol est reduite et que la temperature de l'air est elevee, T. chinensis utilise surtout les eaux souterraines peu profondes et salines tandis que Z. jujuba utilise surtout l'eau du sol a une profondeur de 20-100 cm. Lorsqu'une forte precipitation survient, les deux especes absorbent surtout l'eau du sol situe a 20-40 cm de profondeur. Tamarix chinensis et Z. jujuba ont differents profils d'utilisation de l'eau durant la saison de croissance correspondant a leur adaptation aux fluctuations saisonnieres de la teneur en eau du sol dans un ecosysteme cotier limite en eau, tandis que la differentiation de niche entre les deux especes sur la base de l'utilisation de l'eau clarifie leur mecanisme de coexistence. [Traduit par la Redaction] Mots-cles : strategies d'utilisation de l'eau, ressource hydrique, coexistence de deux arbustes, region cotiere, delta du fleuve Jaune., Introduction Coastal ecosystems are the most dynamic and productive ecosystems in the world (Perez-Ruzafa et al. 2011; Grootjans et al. 1997; Bakun et al. 2015) and are sensitive to climate [...]