Miracle-dz/UniFAR-FTUs huggingface dataset:
Nocardia Rubra Cell Wall Skeleton Up-Regulates T Cell Subsets and Inhibits PD-1/PD-L1 Pathway to Promote Local Immune Status of Patients With High-Risk Human Papillomavirus Infection and Cervical Intraepithelial Neoplasia

The Nocardia rubra cell wall skeleton (Nr-CWS) for external use is an immune enhancer, which has been widely used in human cervix diseases such as cervical erosion, but the mechanism of Nr-CWS enhancing immunity is still unclear. The purpose of this study was to explore the effect and mechanism of Nr-CWS on the local immune status of cervical tissue in patients with high-risk human papillomavirus (HR-HPV) infection and cervical precancerous lesion, cervical intraepithelial neoplasia (CIN). The recruited patients with HR-HPV infection and CIN were treated with Nr-CWS. The specimens were taken from these patients before and after local application of Nr-CWS respectively. The normal control specimens were tested simultaneously. Serial section analysis of immunohistochemistry and co-expression analysis were performed to characterize populations of T cells and the expressions of programmed cell death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1). The levels of cytokines in local cervical tissue were also detected. Nr-CWS significantly increased T cells including CD4+, CD8+ T cells, and reduced the expression of PD-L1 in the patients’ local cervical tissues. Co-expression analyses showed that the proportions of PD-1+CD4+ cells in CD4+ T cells and PD-1+CD8+ cells in CD8+ T cells decreased after Nr-CWS application. Furthermore, the increase in the number of immune cells was accompanied by increased pro-inflammatory cytokines interleukin-12 (IL-12), interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and decreased suppressive cytokine IL-10. The results indicate that Nr-CWS, as an immunotherapeutic agent for HR-HPV infection and CIN, plays an immune promoting role related to the upregulation of T cell subsets and the inhibition of PD-1/PD-L1 pathway.
Acute Changes in Carotid-Femoral Pulse-Wave Velocity Are Tracked by Heart-Femoral Pulse-Wave Velocity

Background: Carotid-femoral pulse-wave velocity (cfPWV) is the reference standard measure of central arterial stiffness. However, it requires assessment of the carotid artery, which is technically challenging, and subject-level factors, including carotid artery plaque, may confound measurements. A promising alternative that overcomes these limitations is heart-femoral PWV (hfPWV), but it is not known to what extent changes in cfPWV and hfPWV are associated. Objectives: To determine, (1) the strength of the association between hfPWV and cfPWV; and (2) whether change in hfPWV is associated with change in cfPWV when central arterial stiffness is perturbed. Methods: Twenty young, healthy adults [24.0 (SD: 3.1) years, 45% female] were recruited. hfPWV and cfPWV were determined using Doppler ultrasound at baseline and following a mechanical perturbation in arterial stiffness (120 mmHg thigh occlusion). Agreement between the two measurements was determined using mixed-effects regression models and Bland-Altman analysis. Results: There was, (1) strong (ICC > 0.7) agreement between hfPWV and cfPWV (ICC = 0.82, 95%CI: 0.69, 0.90), and, (2) very strong (ICC > 0.9) agreement between change in hfPWV and cfPWV (ICC = 0.92, 95%CI: 0.86, 0.96). cfPWV was significantly greater than hfPWV at baseline and during thigh occlusion (both P < 0.001). Inspection of the Bland-Altman plot, comparing cfPWV and corrected hfPWV, revealed no measurement magnitude bias. Discussion: The current findings indicate that hfPWV and cfPWV are strongly associated, and that change in cfPWV is very strongly associated with change in hfPWV. hfPWV may be a simple alternative to cfPWV in the identification of cardiovascular risk in clinical and epidemiological settings.
Two-Level Domain Adaptation Neural Network for EEG-Based Emotion Recognition

Emotion recognition plays an important part in human-computer interaction (HCI). Currently, the main challenge in electroencephalogram (EEG)-based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network (TDANN) to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy (MMD) to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network (DANN) to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness (84%), anger (87.04%), and fear (85.32%) on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness (83.79%), anger (84.13%), and fear (81.72%) on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition.
Building Trust Across Borders? Exploring the Trust-Building Process Between the Nonprofit Organizations and the Government in China

According to Sztompka (1996), “trust is a bet on the future contingent action of others” (p. 39). Sometimes trust may be treated as “a psychological trait” at the individual level. However, without doubt, trust can be “shared by a number of individuals” in a certain society (Sztompka, 1998, p. 20). In this perspective, trust is considered at the societal level, which includes, but reaches beyond, the attitudes of individuals. And it is believed that “when there is trust there are increased possibilities for experience and action” (Luhmann, 2017, p. 8); “a nation’s well-being, as well as its ability to compete,” is conditioned on “a single, pervasive cultural characteristic: the level of trust inherent in a society” (Fukuyama, 1995, p. 7). It has been found that the democratic order has a significant trust-generating force because establishing a set of universal criteria that regulates the institutions of both government and civil society contributes to generating social trust among citizens (Sztompka, 1996; Bielefeld, 2006). However, little research has been done to explore the process and mechanism of trust building in countries that have not set up a democratic order. To fill the research gap, this study aims to explore the trust building process among nonprofit organizations (NPOs), the government and service users in a changing China.
Global Trends and Performances of Magnetic Resonance Imaging Studies on Acupuncture: A Bibliometric Analysis

Objectives: To summarize development processes and research hotspots of MRI research on acupuncture and to provide new insights for researchers in future studies. Methods: Publications regarding MRI on acupuncture from inception to 2020 were downloaded from the Web of Science Core Collection. VOSviewer 1.6. 15 and CiteSpace V software were used for bibliometric analyses. The main analyses include collaboration analyses between countries/institutions/authors, co-occurrence analysis between keywords, as well as analyses on keyword bursts, citation references, and clusters of references. Results: A total of 829 papers were obtained with a continually increased trend over time. The most productive country and institution in this field were the People's Republic of China (475) and KyungHee University (70), respectively. Evidence-based Complementary and Alternative Medicine (83) was the most productive journal, and Neuroimage (454) was the most co-cited journal. Dhond's et al. (2008) article (co-citation counts: 58) and Napadow's et al. (2005) article (centrality: 0.21) were the most representative and symbolic references, with the highest co-citation number and centrality, respectively. Jie Tian had the highest number of publications (35) and Kathleen K S Hui was the most influential author (280 co-citations). The four hot topics in MRI on acupuncture were acupuncture, fMRI, pain, and stimulation. The three frontier topics were connectivity, modulation, and fMRI. Based on the clustering of co-cited documents, chronic low back pain, sham electro-acupuncture treatment, and clinical research were the main research directions. Conclusion: This study provides an in-depth perspective for MRI research on acupuncture and provides researchers with valuable information to determine the current status, hot spots, and frontier trends of MRI research on acupuncture.
Assessment of the Segmentation of RGB Remote Sensing Images: A Subjective Approach

The evaluation of remote sensing imagery segmentation results plays an important role in the further image analysis and decision-making. The search for the optimal segmentation method for a particular data set and the suitability of segmentation results for the use in satellite image classification are examples where the proper image segmentation quality assessment can affect the quality of the final result. There is no extensive research related to the assessment of the segmentation effectiveness of the images. The designed objective quality assessment metrics that can be used to assess the quality of the obtained segmentation results usually take into account the subjective features of the human visual system (HVS). A novel approach is used in the article to estimate the effectiveness of satellite image segmentation by relating and determining the correlation between subjective and objective segmentation quality metrics. Pearson’s and Spearman’s correlation was used for satellite images after applying a k-means++ clustering algorithm based on colour information. Simultaneously, the dataset of the satellite images with ground truth (GT) based on the “DeepGlobe Land Cover Classification Challenge” dataset was constructed for testing three classes of quality metrics for satellite image segmentation.
Development of a Comorbidity-Based Nomogram to Predict Survival After Salvage Reirradiation of Locally Recurrent Nasopharyngeal Carcinoma in the Intensity-Modulated Radiotherapy Era

Purpose To assess the impact of comorbidity on treatment outcomes in patients with locally recurrent nasopharyngeal carcinoma (lrNPC) using intensity-modulated radiotherapy (IMRT) and to develop a nomogram that combines prognostic factors to predict clinical outcome and guide individual treatment. Methods This was a retrospective analysis of patients with lrNPC who were reirradiated with IMRT between 2003 and 2014. Comorbidity was evaluated by Adult Comorbidity Evaluation-27 grading (ACE-27). The significant prognostic factors (P < 0.05) by multivariate analysis using the Cox regression model were adopted into the nomogram model. Harrell concordance index (C-index) calibration curves were applied to assess this model. Results Between 2003 and 2014, 469 lrNPC patients treated in our institution were enrolled. Significant comorbidity (moderate or severe grade) was present in 17.1% of patients by ACE-27. Patients with no or mild comorbidity had a 5-year overall survival (OS) rate of 36.2 versus 20.0% among those with comorbidity of moderate or severe grade (P < 0.0001). The chemotherapy used was not significantly different in patients with lrNPC (P > 0.05). For the rT3–4 patients, the 5-year OS rate in the chemotherapy + radiation therapy (RT) group was 30.0 versus 16.7% for RT only (P = 0.005). The rT3–4 patients with no or mild comorbidity were associated with a higher 5-year OS rate in the chemotherapy + RT group than in the RT only group (32.1 and 17.1%, respectively; P=0.003). However, for the rT3–4 patients with a comorbidity (moderate or severe grade), the 5-year OS rate in the chemotherapy + RT group vs. RT alone was not significantly different (15.7 vs. 15.0%, respectively; p > 0.05). Eight independent prognostic factors identified from multivariable analysis were fitted into a nomogram, including comorbidity. The C-index of the nomogram was 0.715. The area under curves (AUCs) for the prediction of 1-, 3-, and 5-year overall survival were 0.770, 0.764, and 0.780, respectively. Conclusion Comorbidity is among eight important prognostic factors for patients undergoing reirradiation. We developed a nomogram for lrNPC patients to predict the probability of death after reirradiation and guide individualized management.
B Cell–Activating Factor Promotes B Cell Survival in Ectopic Lymphoid Tissues in Nasal Polyps

Ectopic lymphoid tissues (eLTs) characterized by B cell aggregation contribute to the local immunoglobulin production in nasal polyps (NPs). B cell-activating factor (BAFF) is vital for B cell survival, proliferation, and maturation. The purpose of this study is to investigate whether BAFF is involved in the B cell survival and eLT formation in NPs. The mRNA and protein levels of BAFF in NP tissues with and without eLTs were detected by PCR and ELISA assay, respectively. The cellular sources of BAFF and active caspase-3-positive B cells in NPs were studied by immunofluorescence staining. B cells purified from NP tissues were stimulated with BAFF and were analyzed by flow cytometry. Stromal cells purified from NP tissues were stimulated with lymphotoxin (LT) α1β2, and BAFF levels in culture supernatants were analyzed by ELISA. Compared with those in control tissues and NPs without eLTs, the BAFF levels were elevated in NPs with eLTs. Abundant BAFF-positive cells and few active caspase-3-positive apoptotic B cells were found in NPs with eLTs, in contrast to those in NPs without eLTs. There was a negative correlation between the numbers of BAFF-positive cells and frequencies of apoptotic B cells in total B cells in NP tissues. BAFF protected nasal polyp B cells from apoptosis in vitro. Stromal cells were an important cellular source of BAFF in NPs with eLTs. LTα1β2 induced BAFF production from nasal stromal cells in vitro. We propose that BAFF contribute to eLT formation in NPs by promoting B cell survival.
CDAE: A Cascade of Denoising Autoencoders for Noise Reduction in the Clustering of Single-Particle Cryo-EM Images

As an emerging technology, cryo-electron microscopy (cryo-EM) has attracted more and more research interests from both structural biology and computer science, because many challenging computational tasks are involved in the processing of cryo-EM images. An important image processing step is to cluster the 2D cryo-EM images according to their projection angles, then the cluster mean images are used for the subsequent 3D reconstruction. However, cryo-EM images are quite noisy and denoising them is not easy, because the noise is a complicated mixture from samples and hardware. In this study, we design an effective cryo-EM image denoising model, CDAE, i.e., a cascade of denoising autoencoders. The new model comprises stacked blocks of deep neural networks to reduce noise in a progressive manner. Each block contains a convolutional autoencoder, pre-trained by simulated data of different SNRs and fine-tuned by target data set. We assess this new model on three simulated test sets and a real data set. CDAE achieves very competitive PSNR (peak signal-to-noise ratio) in the comparison of the state-of-the-art image denoising methods. Moreover, the denoised images have significantly enhanced clustering results compared to original image features or high-level abstraction features obtained by other deep neural networks. Both quantitative and visualized results demonstrate the good performance of CDAE for the noise reduction in clustering single-particle cryo-EM images.
Epidemiology and Burden of Human Papillomavirus and Related Diseases, Molecular Pathogenesis, and Vaccine Evaluation

Diagnosed in more than 90% of cervical cancers, the fourth deadliest cancer in women, human papillomavirus (HPV) is currently the most common pathogen responsible for female cancers. Moreover, HPV infection is associated with many other diseases, including cutaneous and anogenital warts, and genital and upper aerodigestive tract cancers. The incidence and prevalence of these pathologies vary considerably depending on factors including HPV genotype, regional conditions, the study population, and the anatomical site sampled. Recently, features of the cervicovaginal microbiota are found to be associated with the incidence of HPV-related diseases, presenting a novel approach to identify high-risk women through both blood and cervical samples. Overall, the HPV repartition data show that HPV infection and related diseases are more prevalent in developing countries. Moreover, the available (2-, 4-, and 9-valent) vaccines based on virus-like particles, despite their proven effectiveness and safety, present some limitations in terms of system development cost, transport cold chain, and oncogenic HPV variants. In addition, vaccination programs face some challenges, leading to a considerable burden of HPV infection and related diseases. Therefore, even though the new (9-valent) vaccine seems promising, next-generation vaccines as well as awareness programs associated with HPV vaccination and budget reinforcements for immunization are needed.
Thermal Imaging for Plant Stress Detection and Phenotyping

In the last few years, large efforts have been made to develop new methods to optimize stress detection in crop fields. Thus, plant phenotyping based on imaging techniques has become an essential tool in agriculture. In particular, leaf temperature is a valuable indicator of the physiological status of plants, responding to both biotic and abiotic stressors. Often combined with other imaging sensors and data-mining techniques, thermography is crucial in the implementation of a more automatized, precise and sustainable agriculture. However, thermal data need some corrections related to the environmental and measuring conditions in order to achieve a correct interpretation of the data. This review focuses on the state of the art of thermography applied to the detection of biotic stress. The work will also revise the most important abiotic stress factors affecting the measurements as well as practical issues that need to be considered in order to implement this technique, particularly at the field scale.
Repeat Traffic Offenders Improve Their Performance in Risky Driving Situations and Have Fewer Accidents Following a Mindfulness-Based Intervention

Risky decision-making is highly influenced by emotions and can lead to fatal consequences. Attempts to reduce risk-taking include the use of mindfulness-based interventions (MBI), which have shown promising results for both emotion regulation (ER) and risk-taking. However, it is still unclear whether improved emotion regulation is the mechanism responsible for reduced risk-taking. In the present study, we explore the effect of a 5-week MBI on risky driving in a group of repeat traffic offenders by comparing them with non-repeat offenders and repeat offenders without training. We evaluated the driving behavior of the participants through a driving simulation, and self-reported emotion regulation, both before and after the intervention. At baseline, poor emotion regulation was related to a more unstable driving behavior, and speeding. The group that received mindfulness training showed improved performance during risky driving situations and had fewer accidents, although their overall driving behavior remained largely unchanged. The observed trend toward improved emotion regulation was not significant. We discuss whether other effects of MBI – such as self-regulation of attention – could underlie the observed reduction in risky driving in the initial stages. Nonetheless, our findings still confirm the close relationship between emotion regulation skills and risky driving.
Metal-catalyzed amide bond forming reactions in an environmentally friendly aqueous medium: nitrile hydrations and beyond

Amides are versatile building blocks in synthetic organic chemistry, presenting a wide range of pharmacological applications, and are used as raw materials in industry for the large-scale production of engineering plastics, detergents and lubricants. The development of green procedures for the synthesis of this relevant class of compounds from various starting materials, which replace antiquated methods using carboxylic acid derivatives and amines, is therefore of prime interest in modern chemistry. In this review article, a survey of metal-catalyzed synthetic approaches of amides conducted in an environmentally friendly aqueous medium is given.
A Quantile Approach for Retrieving the "Core Urban-Suburban-Rural" (USR) Structure Based on Nighttime Light

Accurate and timely information on the “core urban-suburban-rural” (USR) spatial structure in a metropolitan region is significant for both the scientific and policy-making communities. However, USR is usually considered as a single land use type, such as an impervious area, rather than three combined subcategories in remote-sensing image retrieval, especially for suburban areas, which obscures the details of the urbanization process. In this paper, we propose a quantile approach to retrieve the structure of USR based on stable nighttime light (NTL) data from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) and apply it in the Beijing-Tianjin-Hebei (JJJ) of China from 1995 to 2013. The key parameters of the NTL threshold, which is the maximum change point of the NTL intensity at the USR boundary, used to retrieve the three subcategories of USR are automatically defined based on the quantile approach with three iterations. Then, the overall accuracy and consistency of the retrieval results are evaluated using the corresponding visual interpretation map from Landsat images with a 30 m resolution. Moreover, the influence of parameter uncertainty is compared by introducing the human settlement index (HSI). According to the time-series analysis of USR retrieval in this study, the JJJ experienced rapid urbanization from 1995 to 2013, with the core urban area expanding by 7098 km2 (average increase of 2.7 times), the suburban area expanding by 12,690 km2 (average increase of 2.8 times), and the rural area increasing by 4986 km2 (average increase of 0.38 times). The USR results retrieved based on the approach agree well with the validation of the visual interpretation map, with an overall accuracy (OA) of 0.904 and a kappa coefficient (KC) of 0.650 at the city level. The USR result with the HSI as the input shows that NTL is more suitable for USR structure retrieval as the NTL shows less uncertainty compared with other parameters such as the vegetation index (VI). This study proposes an improved quantile approach for USR mapping from NTL images on a regional scale, which will provide a useful method for urbanization dynamics analysis.