Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing

Clinical notes, which can be embedded into electronic medical records, document patient care delivery and summarize interactions between healthcare providers and patients. These clinical notes directly inform patient care and can also indirectly inform research and quality/safety metrics, among other indirect metrics. Recently, some states within the United States of America require patients to have open access to their clinical notes to improve the exchange of patient information for patient care. Thus, developing methods to assess the cyber risks of clinical notes before sharing and exchanging data is critical. While existing natural language processing techniques are geared to de-identify clinical notes, to the best of our knowledge, few have focused on classifying sensitive-information risk, which is a fundamental step toward developing effective, widespread protection of patient health information. To bridge this gap, this research investigates methods for identifying security/privacy risks within clinical notes. The classification either can be used upstream to identify areas within notes that likely contain sensitive information or downstream to improve the identification of clinical notes that have not been entirely de-identified. We develop several models using unigram and word2vec features with different classifiers to categorize sentence risk. Experiments on i2b2 de-identification dataset show that the SVM classifier using word2vec features obtained a maximum F1-score of 0.792. Future research involves articulation and differentiation of risk in terms of different global regulatory requirements.
Comprehensive Analysis of Immune-Related Prognosis of TK1 in Hepatocellular Carcinoma

Increased expression of TK1 is associated with the progression of a variety of tumors. However, the relationship of TK1 expression with immune cell infiltration and its prognostic value in hepatocellular carcinoma (HCC) are still unknown. In this study the TCGA database was used to evaluate TK1 expression and its impact on survival in patients with HCC. Compared with normal tissue, TK1 in the liver tissue of patients with HCC was significantly up-regulated at both the mRNA and protein levels. Furthermore, TK1 expression was significantly related to pathological stage, tumor stage and lymph node metastasis, with high TK1 expression being an unfavorable prognostic factor for HCC. TK1 expression was also significantly associated with the infiltration of B cells, T cells, and dendritic cells in HCC. Single-cell sequencing analysis revealed that TK1 was associated with relatively large changes in T cells, especially gamma-delta T cells. A prognostic risk score based on TK1-related immune genes (CD40LG and TNFRSF4) was established using COX regression analysis. By integrating the immune-related risk score model with clinical features, a nomogram was constructed to predict the survival rate of HCC patients (1 year, 3-year and 5-year AUC of 0.782, 0.783 and 0.771, respectively). Knockdown of the target gene for TK1 was found to have significant anti-apoptosis and pro-proliferation effects on HepG2 cells. The level of TK1 in the serum and liver tissue of patients with HCC was significantly increased relative to healthy controls. These findings highlight the role of TK1 in the tumor immune response of HCC patients and in the proliferation and apoptosis of HepG2 cells. TK1 could therefore be a potential immunotherapy target for HCC patients, while the two immune genes related to TK1 (CD40LG And TNFRSF4) may be promising prognostic biomarkers in HCC.
Identification of diabetic retinopathy using deep learning algorithm and blood vessel extraction

Retinal blood vessel and retinal vessel tree segmentation are significant components in disease identification systems. Diabetic retinopathy is found using identifying hemorrhages in blood vessels. The debauched vessel segmentation helps in an image segmentation process to improve the accuracy of the system. This paper uses Edge Enhancement and Edge Detection method for blood vessel extraction. It covers drusen, exudates, vessel contrasts and artifacts. After extracting the blood vessel, the dataset is fed into CNN network called EyeNet for identifying DR infected images. It is observed that EyeNet leads to Sensitivity of about 90.02%, Specificity of about 98.77% and Accuracy of about 96.08%.
The Exercising Brain: An Overlooked Factor Limiting the Tolerance to Physical Exertion in Major Cardiorespiratory Diseases?

“Exercise starts and ends in the brain”: this was the title of a review article authored by Dr. Bengt Kayser back in 2003. In this piece of work, the author highlights that pioneer studies have primarily focused on the cardiorespiratory-muscle axis to set the human limits to whole-body exercise tolerance. In some circumstances, however, exercise cessation may not be solely attributable to these players: the central nervous system is thought to hold a relevant role as the ultimate site of exercise termination. In fact, there has been a growing interest relative to the “brain” response to exercise in chronic cardiorespiratory diseases, and its potential implication in limiting the tolerance to physical exertion in patients. To reach these overarching goals, non-invasive techniques, such as near-infrared spectroscopy and transcranial magnetic stimulation, have been successfully applied to get insights into the underlying mechanisms of exercise limitation in clinical populations. This review provides an up-to-date outline of the rationale for the “brain” as the organ limiting the tolerance to physical exertion in patients with cardiorespiratory diseases. We first outline some key methodological aspects of neuromuscular function and cerebral hemodynamics assessment in response to different exercise paradigms. We then review the most prominent studies, which explored the influence of major cardiorespiratory diseases on these outcomes. After a balanced summary of existing evidence, we finalize by detailing the rationale for investigating the “brain” contribution to exercise limitation in hitherto unexplored cardiorespiratory diseases, an endeavor that might lead to innovative lines of applied physiological research.
Non-destructive Measurements of Toona sinensis Chlorophyll and Nitrogen Content Under Drought Stress Using Near Infrared Spectroscopy

Drought is a climatic event that considerably impacts plant growth, reproduction and productivity. Toona sinensis is a tree species with high economic, edible and medicinal value, and has drought resistance. Thus, the objective of this study was to dynamically monitor the physiological indicators of T. sinensis in real time to ensure the selection of drought-resistant varieties of T. sinensis. In this study, we used near-infrared spectroscopy as a high-throughput method along with five preprocessing methods combined with four variable selection approaches to establish a cross-validated partial least squares regression model to establish the relationship between the near infrared reflectance spectroscopy (NIRS) spectrum and physiological characteristics (i.e., chlorophyll content and nitrogen content) of T. sinensis leaves. We also tested optimal model prediction for the dynamic changes in T. sinensis chlorophyll and nitrogen content under five separate watering regimes to mimic non-destructive and dynamic detection of plant leaf physiological changes. Among them, the accuracy of the chlorophyll content prediction model was as high as 72%, with root mean square error (RMSE) of 0.25, and the RPD index above 2.26. Ideal nitrogen content prediction model should have R2 of 0.63, with RMSE of 0.87, and the RPD index of 1.12. The results showed that the PLSR model has a good prediction effect. Overall, under diverse drought stress treatments, the chlorophyll content of T. sinensis leaves showed a decreasing trend over time. Furthermore, the chlorophyll content was the most stable under the 75% field capacity treatment. However, the nitrogen content of the plant leaves was found to have a different and variable trend, with the greatest drop in content under the 10% field capacity treatment. This study showed that NIRS has great potential for analyzing chlorophyll nitrogen and other elements in plant leaf tissues in non-destructive dynamic monitoring.
Physical Activity and Executive Function in Children With ADHD: The Mediating Role of Sleep

This study examined the mediating role of sleep in the relationship between physical activity and executive function in children with attention deficit hyperactivity disorder (ADHD). Fifty-six children with ADHD were recruited from Shenzhen Children's Hospital. Participants wore an accelerometer for seven consecutive days to measure physical activity and sleep quality. Activity counts were analyzed to measure moderate-to-vigorous physical activity (MVPA). Four sleep parameters, including sleep latency (SL), sleep efficiency, total sleep time, and wake after sleep onset were recorded from the actigraph. Three core executive functions, inhibitory control; working memory (WM); and cognitive flexibility (CF), were assessed from computer-based tasks: the flanker task, and the Tower of London and Trail Making Tests, respectively. The regression results showed that MVPA was negatively associated with SL (−0.169; 95%CI [−0.244, −0.112]). WM (total scores) was positively related to MVPA (0.028, 95%CI [0.008, 0.048]), but negatively related to SL (−0.105, 95%CI [−0.167, −0.030]). CF (part B errors) was negatively associated with MVPA (−0.031, 95%CI [−0.055, −0.005]) and positively correlated with SL (0.184, 95%CI [0.092, −0.260]). The indirect effect of SL was found for MVPA and WM (0.018, 95%CI [0.015, 0.034]), supporting the indirect partial mediation. Similarly, the indirect effect of SL was found between MVPA and CF (−0.031, 95%CI [−0.060, −0.012]), supporting the indirect partial mediation. The mediating role of SL in children with ADHD suggests that the intensity of physical activity plays a key role in linking sleep quality and executive function in this group.
Ocimum basilicum Essential Oil Modulates Hematotoxicity, Oxidative Stress, DNA Damage, and Cell Cycle Arrest Induced by β-cyfluthrin in Rat Liver

Pesticides are used in large quantities infrequently, resulting in environmental damage and health issues. The goal of the current study was to explore the ameliorating effect of Ocimum basilicum (Basil) leaves essential oil versus the harmful effects of β-cyfluthrin in rat liver. Male Wistar rats were classified at random into four groups; negative control (corn oil), basil leaves essential oil (BEO, 3 ml/kg), β-cyfluthrin (positive control) (β-Cyf; 15 mg/kg BW, 1/25 LD50), and BEO plus β-Cyf, respectively. The rats were given their doses orally every day for a month. Results revealed that BEO yielded 6.32 mg/g with 33 identified components, representing 97% of the total oil. BEO implicated a considerable level of total phenolic contents, DPPH radical scavenging capacity, ABTS activity, and FRAP. The treatment of β-Cyf dramatically elevated lipid peroxidation (TBARS and H2O2) (LPO), protein oxidation (PC, AOPP, and HYP), and considerably reduced enzymatic (SOD, CAT, GPx, GR, and GST) and non-enzymatic (GSH) antioxidants. After β-Cyf treatment, hematological parameters, body and liver weights, enzyme activity (AST, ALT, ALP, and LDH), as well as protein, albumin, globulin, and total bilirubin levels were all considerably affected. Furthermore, β-Cyf increased the expression of pro-inflammatory genes (TNF-α, IL-6) as well as DNA damage and cell cycle arrest in the G0/G1 phase and decreased the number of cells in S and G2/M phase of liver cells. Moreover, rats given BEO then intoxicated with β-Cyf showed substantial changes in the majority of the parameters tested. Finally, BEO was shown to have high antioxidant efficacy in combating β-Cyf toxicity because of its high phenolic content.
Cycloastragenol Attenuates Osteoclastogenesis and Bone Loss by Targeting RANKL-Induced Nrf2/Keap1/ARE, NF-κB, Calcium, and NFATc1 Pathways

Osteoporosis, which typically affects postmenopausal women, is an osteolytic disease due to over-activation of osteoclasts. However, current drugs targeting osteoclast inhibition face various side effects, making natural compounds with great interest as alternative treatment options. Cycloastragenol (CAG) is a triterpenoid with multiple biological activities. Previously, CAG’s activity against aging-related osteoporosis was reported, but the mechanisms of actions for the activities were not understood. This study demonstrated that CAG dose-dependently inhibited osteoclast formation in receptor activator of nuclear factor-κB ligand (RANKL)-stimulated bone marrow macrophage (BMMs). Mechanism studies showed that CAG inhibited NF-κB, calcium, and nuclear factor of activated T cells 1 (NFATc1) pathways. Additionally, CAG also promoted the nuclear factor-erythroid 2-related factor 2 (Nrf2)/Kelch-like ECH-associated protein 1 (Keap1)/anti-oxidative response element (ARE) pathway that scavenges reactive oxygen species (ROS). Furthermore, CAG was also found to prevent bone loss of postmenopausal osteoporosis (PMO) in a preclinical model of ovariectomized (OVX) mice. Collectively, our research confirms that CAG inhibits the formation and function of osteoclasts by regulating RANKL-induced intracellular signaling pathways, which may represent a promising alternative for the therapy of osteoclast-related disease.
Clinical and Inflammatory Characteristics of the Chinese APAC Cough Variant Asthma Cohort

Background The AtyPical Asthma in China (APAC) cohort is a multi-center prospective, observational cohort set-up to investigate the clinical, pathophysiological features, prognosis, and mechanisms of cough variant asthma (CVA). Objectives To present the characteristics of newly physician-diagnosed adults with CVA (n = 328) compared to mild-moderate classic asthma (CA, n = 206). Methods and Main Results CVA subjects showed a higher proportion of female (67.1 vs. 55.3%, P = 0.0084), abnormal laryngopharyngeal sensations (71 vs. 51%, p < 0.0001) than CA, but presented with near normal spirometry and higher methacholine PD20-FEV1 values [4.2 (1, 8.6) vs. 0.8 (0.4, 4.7), P < 0.0001]. Lower fractional exhaled nitric oxide (FENO) levels [38.5 (19.8, 72.5) vs. 53. (28.5, 92.2), P = 0.0019], blood eosinophil counts [0.2 (0.1, 0.4) vs. 0.3 (0.2, 0.5), P = 0.0014], and sputum eosinophils [2.3 (0.3, 8.0) vs. 12.2 (2, 34.5), p < 0.0001] were found in CVA. Despite lower total serum IgE levels in CVA, there was similar proportion of atopy in both groups. The prevalence of cough in CA was 86.4%, while CVA reported more severe cough on Visual Analog Scale, Cough Evaluation Test, and Leicester Cough Questionnaire, similar anxiety and depression scores but better asthma control scores as reflected by Asthma Control Test compared to CA. No correlation was found between cough assessment outcomes and sputum eosinophil count, blood eosinophil count, FENO, spirometry variables, or PD20-FEV1. Conclusion Cough variant asthma is distinctive from classic asthma in regard to clinical features, lung function, and airway inflammation. Quality of life is badly impaired as well in spite of better asthma control scores.
The Effect of China's Pilot Low-Carbon City Initiative on Enterprise Labor Structure

Based on the background of China's pilot low-carbon city initiative in 2010, 2012, and 2017, this article captures the exogenous change of enterprise labor structure based on A-share listed companies from 2007 to 2019 in Shenzhen and Shanghai Stock exchanges. With the integration of macro data on the city level and micro data on the enterprise level, adopting the time-varying difference-in-differences (DID) model, we found that 1) China's pilot low-carbon city initiative can significantly promote the upgrading of enterprise labor structure; 2) China's pilot low-carbon city initiative can significantly increase R&D investment of listed companies, suggesting that R&D investment is a channel for the impact of China's pilot low-carbon city initiative on enterprise labor structure in the pilot cities; 3) the heterogeneity analysis shows that the labor structure of the state-owned listed companies has been optimized significantly, while the labor structure of the non–state-owned listed companies is not significant. Meanwhile, the labor structure of the listed companies under high-quality government control has been optimized significantly, while the labor structure of the listed companies under low-quality government control is not significant. Overall, our study shows that the pilot low-carbon city initiative has played a governance role in China and optimized enterprise labor structure.
The Role of Circulating Biomarkers in Lung Cancer

Lung cancer is the leading cause of cancer morbidity and mortality worldwide and early diagnosis is crucial for the management and treatment of this disease. Non-invasive means of determining tumour information is an appealing diagnostic approach for lung cancers as often accessing and removing tumour tissue can be a limiting factor. In recent years, liquid biopsies have been developed to explore potential circulating tumour biomarkers which are considered reliable surrogates for understanding tumour biology in a non-invasive manner. Most common components assessed in liquid biopsy include circulating tumour cells (CTCs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), microRNA and exosomes. This review explores the clinical use of circulating tumour biomarkers found in liquid biopsy for screening, early diagnosis and prognostication of lung cancer patients.
Exploring Virome Diversity in Public Data in South America as an Approach for Detecting Viral Sources From Potentially Emerging Viruses

The South American continent presents a great diversity of biomes, whose ecosystems are constantly threatened by the expansion of human activity. The emergence and re-emergence of viral populations with impact on the human population and ecosystem have shown increases in the last decades. In deference to the growing accumulation of genomic data, we explore the potential of South American-related public databases to detect signals that contribute to virosphere research. Therefore, our study aims to investigate public databases with emphasis on the surveillance of viruses with medical and ecological relevance. Herein, we profiled 120 “sequence read archives” metagenomes from 19 independent projects from the last decade. In a coarse view, our analyses identified only 0.38% of the total number of sequences from viruses, showing a higher proportion of RNA viruses. The metagenomes with the most important viral sequences in the analyzed environmental models were 1) aquatic samples from the Amazon River, 2) sewage from Brasilia, and 3) soil from the state of São Paulo, while the models of animal transmission were detected in mosquitoes from Rio Janeiro and Bats from Amazonia. Also, the classification of viral signals into operational taxonomic units (OTUs) (family) allowed us to infer from metadata a probable host range in the virome detected in each sample analyzed. Further, several motifs and viral sequences are related to specific viruses with emergence potential from Togaviridae, Arenaviridae, and Flaviviridae families. In this context, the exploration of public databases allowed us to evaluate the scope and informative capacity of sequences from third-party public databases and to detect signals related to viruses of clinical or environmental importance, which allowed us to infer traits associated with probable transmission routes or signals of ecological disequilibrium. The evaluation of our results showed that in most cases the size and type of the reference database, the percentage of guanine–cytosine (GC), and the length of the query sequences greatly influence the taxonomic classification of the sequences. In sum, our findings describe how the exploration of public genomic data can be exploited as an approach for epidemiological surveillance and the understanding of the virosphere.
Exploring Access to Mental Health and Primary Care Services for People With Severe Mental Illness During the COVID-19 Restrictions

Aims To explore: how satisfied people with severe mental illness (SMI) are with the support received during the pandemic; understand any difficulties encountered when accessing both mental health and primary care services; consider ways to mitigate these difficulties; and assess the perceived need for future support from mental health services. Materials and Methods A representative sample was drawn from a large transdiagnostic clinical cohort of people with SMI, which was recruited between April 2016 and March 2020. The sample was re-surveyed a few months after the beginning of the restrictions. Descriptive frequency statistics were used to analyze the quantitative data. The free text responses were analyzed thematically. Results 367 participants responded to the survey. Two thirds were receiving support from mental health services with the rest supported in primary care or self-managing. A quarter thought they would need more mental health support in the coming year. Half had needed to used community mental health services during the pandemic and the majority had been able to get support. A minority reported that their mental health had deteriorated but they had either not got the supported they wanted or had not sought help. The biggest service change was the reduction in face-to-face appointments and increasing use of phone and video call support. Nearly half of those using mental health services found this change acceptable or even preferred it. However, acceptability was influenced by several factors, and participants were more likely to report that they had received all the support they needed, when seen in person. Discussion Although most participants were satisfied with the mental health support they had received, a minority were not. This, couple with findings on future need for mental health support has implications for post pandemic demand on services. Remote care has brought benefits but also risks that it could increase inequalities in access to services.