Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery

As the COVID-19 epidemic began to worsen in the first months of 2020, stringent lockdown policies were implemented in numerous cities throughout the world to control human transmission and mitigate its spread. Although transportation density reduction inside the city was felt subjectively, there has thus far been no objective and quantitative study of its variation to reflect the intracity population flows and their corresponding relationship with lockdown policy stringency from the view of remote sensing images with the high resolution under 1m. Accordingly, we here provide a quantitative investigation of the transportation density reduction before and after lockdown was implemented in six epicenter cities (Wuhan, Milan, Madrid, Paris, New York, and London) around the world during the COVID-19 epidemic, which is accomplished by extracting vehicles from the multi-temporal high-resolution remote sensing images. A novel vehicle detection model combining unsupervised vehicle candidate extraction and deep learning identification was specifically proposed for the images with the resolution of 0.5m. Our results indicate that transportation densities were reduced by an average of approximately 50% (and as much as 75.96%) in these six cities following lockdown. The influences on transportation density reduction rates are also highly correlated with policy stringency, with an R^2 value exceeding 0.83. Even within a specific city, the transportation density changes differed and tended to be distributed in accordance with the city's land-use patterns. Considering that public transportation was mostly reduced or even forbidden, our results indicate that city lockdown policies are effective at limiting human transmission within cities.Comment: 14 pages, 7 figures, submitted to IEEE JSTAR

Shared decision-making in healthcare in mainland China: a scoping review

BackgroundShared decision-making (SDM) facilitates the participation of healthcare professionals and patients in treatment decisions. We conducted a scoping review to assess SDM’s current status in mainland China, referencing the Ottawa Decision Support Framework (ODSF).MethodsOur review encompassed extensive searches across six English and four Chinese databases, and various gray literature until April 30, 2021. Results were synthesized using thematic analysis.ResultsOut of the 60 included studies, we identified three key themes based on the ODSF framework: decisional needs, decision support, and decisional outcomes. However, there appears to be a lack of comprehensive understanding of concepts related to decisional needs in China. Only a few studies have delved into feasibility, preference, choice, and outcome factors in the SDM process. Another challenge emerges from an absence of uniform standards for developing patient decision aids (PDAs). Furthermore, regarding health outcome indicators, their predominant focus remains on physiological needs.ConclusionSDM is in its infancy in mainland China. It is important to explore the concept and expression of decisional needs in the context of Chinese culture. Subsequent studies should focus on constructing a scientifically rigorous and systematic approach for the development of PDAs, and considering the adaptation of SDM steps to the clinical context in China during SDM implementation. Concurrently, The focus on health outcomes in Chinese SDM studies, driven by the unique healthcare resource landscape, underscores the necessity of prioritizing basic needs within limited resources.Systematic review registrationhttps://inplasy.com/?s=202130021

Identification of Genetically Predicted DNA Methylation Markers Associated with Non-small Cell Lung Cancer Risk among 34,964 Cases and 448,579 Controls

BACKGROUND: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10 CONCLUSIONS: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls.

BackgroundAlthough the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated.MethodsThe genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways.ResultsOf the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified.ConclusionsSixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby.Plain language summaryThe epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer

Analysis of the current situation of realistic reviews in nursing: protocol for a scoping review

The theory of clinical nursing is a systematic, theoretical and logical description of the nursing phenomenon and its essence, which can be used to explain the clinical nursing phenomenon and its relationship, and predict and control the nursing outcome. Nursing theory is very important to guide clinical practice and avoid practice blindness. With nursing as a first-level discipline, the research on nursing theory in China has gradually increased, but it is still in the primary stage of introducing, learning, validating application and understanding of nursing theory abroad. Compared with theoretical research in other mature fields or foreign nursing theory, the number of research is insufficient. Therefore, the nursing discipline needs to strengthen the research on the basic evolution mechanism and develop the nursing theory, to improve the scientific nature and popularization of nursing practice. Realist review, also known as Realist synthesis, is a theory-driven systematic review of complex interventions from the perspective of Realist philosophy. It does not answer the question of whether interventions are effective or not, but rather explains the theoretical mechanism by which interventions work, that is, explaining "what interventions can be applied to what populations in what contexts". This method was developed by Sociology professor Ray Pawson and gradually expanded from social policy formulation to health care, public health, health-related policy formulation, and other fields. The number of articles applying this method in nursing is increasing. However, no scholars in China have published such studies at present. Only scholars have expounded the philosophical view of realism integration and its difference from systematic reviews from a philosophical perspective, as well as introduced and interpreted the reporting standard of realism review. At present, there is still a lack of systematic review and evaluation of these studies. Scoping review is a method to quickly describe the research progress of a certain knowledge field, summarize the knowledge of existing studies and understand their shortcomings. Therefore, this study adopted the scoping review framework of Arksey and O 'Malley to sort out and analyze the published realist reviews in the field of nursing at home and abroad, aiming to understand the research status of this field and introduce the theories and methods of realistic reviews, which provides new ideas for theoretical research in the nursing field in China

GETV nsP2 plays a critical role in the interferon antagonism and viral pathogenesis

Abstract Getah virus (GETV) was becoming more serious and posing a potential threat to animal safety and public health. Currently, there is limited comprehension regarding the pathogenesis and immune evasion mechanisms employed by GETV. Our study reveals that GETV infection exhibits the capacity for interferon antagonism. Specifically, the nonstructural protein nsP2 of GETV plays a crucial role in evading the host immune response. GETV nsP2 effectively inhibits the induction of IFN-β by blocking the phosphorylation and nuclear translocation of IRF3. Additionally, GETV nsP2 hinders the phosphorylation of STAT1 and its nuclear accumulation, leading to significantly impaired JAK-STAT signaling. Furthermore, the amino acids K648 and R649, situated in the C-terminal region of GETV nsP2, play a crucial role in facilitating nuclear localization. Not only do they affect the interference of nsP2 with the innate immune response, but they also exert an influence on the pathogenicity of GETV in mice. In summary, our study reveals novel mechanisms by which GETV evades the immune system, thereby offering a foundation for comprehending the pathogenic nature of GETV. Video Abstrac

Hybrid Exercise Program for Sarcopenia in Older Adults: The Effectiveness of Explainable Artificial Intelligence-Based Clinical Assistance in Assessing Skeletal Muscle Area

Background: Sarcopenia is a geriatric syndrome characterized by decreased skeletal muscle mass and function with age. It is well-established that resistance exercise and Yi Jin Jing improve the skeletal muscle mass of older adults with sarcopenia. Accordingly, we designed an exercise program incorporating resistance exercise and Yi Jin Jing to increase skeletal muscle mass and reverse sarcopenia in older adults. Additionally, machine learning simulations were used to predict the sarcopenia status after the intervention. Method: This randomized controlled trial assessed the effects of sarcopenia in older adults. For 24 weeks, 90 older adults with sarcopenia were divided into intervention groups, including the Yi Jin Jing and resistance training group (YR, n = 30), the resistance training group (RT, n = 30), and the control group (CG, n = 30). Computed tomography (CT) scans of the abdomen were used to quantify the skeletal muscle cross-sectional area at the third lumbar vertebra (L3 SMA). Participants’ age, body mass, stature, and BMI characteristics were analyzed by one-way ANOVA and the chi-squared test for categorical data. This study explored the improvement effect of three interventions on participants’ L3 SMA, skeletal muscle density at the third lumbar vertebra (L3 SMD), skeletal muscle interstitial fat area at the third lumbar vertebra region of interest (L3 SMFA), skeletal muscle interstitial fat density at the third lumbar vertebra (L3 SMFD), relative skeletal muscle mass index (RSMI), muscle fat infiltration (MFI), and handgrip strength. Experimental data were analyzed using two-way repeated-measures ANOVA. Eleven machine learning models were trained and tested 100 times to assess the model’s performance in predicting whether sarcopenia could be reversed following the intervention. Results: There was a significant interaction in L3 SMA (p < 0.05), RSMI (p < 0.05), MFI (p < 0.05), and handgrip strength (p < 0.05). After the intervention, participants in the YR and RT groups showed significant improvements in L3 SMA, RSMI, and handgrip strength. Post hoc tests showed that the YR group (p < 0.05) yielded significantly better L3 SMA and RSMI than the RT group (p < 0.05) and CG group (p < 0.05) after the intervention. Compared with other models, the stacking model exhibits the best performance in terms of accuracy (85.7%) and F1 (75.3%). Conclusion: One hybrid exercise program with Yi Jin Jing and resistance exercise training can improve skeletal muscle area among older adults with sarcopenia. Accordingly, it is possible to predict whether sarcopenia can be reversed in older adults based on our stacking model

Two Sweet Sorghum (<i>Sorghum bicolor</i> L.) WRKY Transcription Factors Promote Aluminum Tolerance via the Reduction in Callose Deposition

Aluminum (Al) toxicity is a primary limiting factor for crop production in acidic soils. The WRKY transcription factors play important roles in regulating plant growth and stress resistance. In this study, we identified and characterized two WRKY transcription factors, SbWRKY22 and SbWRKY65, in sweet sorghum (Sorghum bicolor L.). Al induced the transcription of SbWRKY22 and SbWRKY65 in the root apices of sweet sorghum. These two WRKY proteins were localized in the nucleus and exhibited transcriptional activity. SbWRKY22 showed the significant transcriptional regulation of SbMATE, SbGlu1, SbSTAR1, SbSTAR2a, and SbSTAR2b, which are major known Al tolerance genes in sorghum. Interestingly, SbWRKY65 had almost no effect on the aforementioned genes, but it significantly regulated the transcription of SbWRKY22. Therefore, it is speculated that SbWRKY65 might indirectly regulate Al-tolerance genes mediated by SbWRKY22. The heterologous expression of SbWRKY22 and SbWRKY65 greatly improved the Al tolerance of transgenic plants. The enhanced Al tolerance phenotype of transgenic plants is associated with reduced callose deposition in their roots. These findings suggest the existence of SbWRKY22- and SbWRKY65-mediated Al tolerance regulation pathways in sweet sorghum. This study extends our understanding of the complex regulatory mechanisms of WRKY transcription factors in response to Al toxicity

Cultural adaptation of the Pan-Canadian Oncology Symptom triage and remote support practice guide for cancer-related fatigue in China: Integration of traditional Chinese medicine nursing evidence

Objective: This study aimed at culturally adapting pan-Canadian Oncology Symptom Triage and Remote Support (COSTaRS) Cancer-related fatigue (CRF) Practice Guide to enable its use in China. This article focuses on presenting the key cultural adaptation step: supplementing traditional Chinese medicine (TCM) nursing recommendations for CRF symptom management according to evidence. Methods: Guided by A Guideline Adaptation and Implementation Planning Resource (CAN-IMPLEMENT), the process for cultural adaptation of the CRF guide in the COSTaRS project included translation, expert committee review, acceptability and feasibility assessment, and targeted adaptation to include TCM nursing techniques for CRF management via the Delphi method. Results: First, an expert committee of nurses, nurse leaders, and researchers was established. The practice guide was translated and verified by the members of the expert committee. Nurses then rated the practice guide for acceptability and feasibility. Concurrently, 83 stakeholders (nurses and patients) identified five relevant TCM nursing techniques: acupuncture, moxibustion, acupressure therapy, Taijiquan, and auricular acupoint embedding. A systematic review of literature identified three clinical practice guidelines and four systematic reviews. Through two rounds of Delphi expert consultation, five TCM care strategies were added into the culturally adapted COSTaRS practice guide. Conclusions: Cultural adaptation of the Canadian CRF practice guide involved not only language translation but also the addition of relevant TCM evidence. Combining TCM evidence and the Delphi method was a novel aspect of the cultural adaptation process. Further research is needed to investigate the implementation of the guide in appropriate settings in China

The Effectiveness of a Hybrid Exercise Program on the Physical Fitness of Frail Elderly

Background: Frailty is a serious physical disorder affecting the elderly all over the world. However, the frail elderly have low physical fitness, which limits the effectiveness of current exercise programs. Inspired by this, we attempted to integrate Baduanjin and strength and endurance exercises into an exercise program to improve the physical fitness and alleviate frailty among the elderly. Additionally, to achieve the goals of personalized medicine, machine learning simulations were performed to predict post-intervention frailty. Methods: A total of 171 frail elderly individuals completed the experiment, including a Baduanjin group (BDJ), a strength and endurance training group (SE), and a combination of Baduanjin and strength and endurance training group (BDJSE), which lasted for 24 weeks. Physical fitness was evaluated by 10-meter maximum walk speed (10 m MWS), grip strength, the timed up-and-go test (TUGT), and the 6 min walk test (6 min WT). A one-way analysis of variance (ANOVA), chi-square test, and two-way repeated-measures ANOVA were carried out to analyze the experimental data. In addition, nine machine learning models were utilized to predict the frailty status after the intervention. Results: In 10 m MWS and TUGT, there was a significant interactive influence between group and time. When comparing the BDJ group and the SE group, participants in the BDJSE group demonstrated the maximum gains in 10 m MWS and TUGT after 24 weeks of intervention. The stacking model surpassed other algorithms in performance. The accuracy and precision rates were 75.5% and 77.1%, respectively. Conclusion: The hybrid exercise program that combined Baduanjin with strength and endurance training proved more effective at improving fitness and reversing frailty in elderly individuals. Based on the stacking model, it is possible to predict whether an elderly person will exhibit reversed frailty following an exercise program