ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner. The Auto Core Fragment in silico Screening (ACFIS) server is a well-established and effective online tool for FBDD. However, the accurate prediction of protein-fragment binding mode and affinity is still a major challenge for FBDD due to weak binding affinity. Here, we present an updated version (ACFIS 2.0), that incorporates a dynamic fragment growing strategy to consider protein flexibility. The major improvements of ACFIS 2.0 include (i) increased accuracy of hit compound identification (from 75.4% to 88.5% using the same test set), (ii) improved rationality of the protein-fragment binding mode, (iii) increased structural diversity due to expanded fragment libraries and (iv) inclusion of more comprehensive functionality for predicting molecular properties. Three successful cases of drug lead discovery using ACFIS 2.0 are described, including drugs leads to treat Parkinson's disease, cancer, and major depressive disorder. These cases demonstrate the utility of this web-based server. ACFIS 2.0 is freely available at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS2/.

Using Text Mining and Data Visualization Approaches for Investigating Mental Illness from the Perspective of Traditional Chinese Medicine.

Background and Objectives. Anxiety and depressive disorders are the most prevalent mental disorders, and due to the COVID-19 pandemic, more people are suffering from anxiety and depressive disorders, and a considerable fraction of COVID-19 survivors have a variety of persistent neuropsychiatric problems after the initial infection. Traditional Chinese Medicine (TCM) offers a different perspective on mental disorders from Western biomedicine. Effective management of mental disorders has become an increasing concern in recent decades due to the high social and economic costs involved. This study attempts to express and ontologize the relationships between different mental disorders and physical organs from the perspective of TCM, so as to bridge the gap between the unique terminology used in TCM and a medical professional. Materials and Methods. Natural language processing (NLP) is introduced to quantify the importance of different mental disorder descriptions relative to the five depots and two palaces, stomach and gallbladder, through the classical medical text Huangdi Neijing and construct a mental disorder ontology based on the TCM classic text. Results. The results demonstrate that our proposed framework integrates NLP and data visualization, enabling clinicians to gain insights into mental health, in addition to biomedicine. According to the results of the relationship analysis of mental disorders, depots, palaces, and symptoms, the organ/depot most related to mental disorders is the heart, and the two most important emotion factors associated with mental disorders are anger and worry & think. The mental disorders described in TCM are related to more than one organ (depot/palace). Conclusion. This study complements recent research delving into co-relations or interactions between mental status and other organs and systems.

Biometrics Data Visualization of Ginsenosides in Anticancer Investigations.

Ginsenoside extracts have been shown to have anticancer effects by a growing number of studies and have thus become a hot topic in cancer research. Our study used VOSviewer and CiteSpace softwares to conduct a bibliometric approach to co-citation and co-occurrence analysis of countries, institutions, authors, references, and keywords in the field of cancer research to investigate the current status and trends of ginsenosides research in cancer. The web of science core collection (WoSCC) contained a total of 1102 papers. China made the most contributions in this area, with the most publications (742, 67.3%), and collaborated closely with Korea and the USA. The Journal of Ginseng Research, with the most total citations (1607) and an IF of 6.06, is the leading journal in the field of ginsenoside and cancer research, publishing high quality articles. Saponin and its extracts inhibit oxidative stress, promote apoptosis, and inhibits chemotherapy resistance by ginsenosides, all of which are hot research areas in this field. In the coming years, it is expected that the combination of ginsenosides and nanoparticles, in-depth mechanisms of cancer inhibition, and targeted therapy will receive widespread attention.

Integrated care and co-production during a pandemic: responding to the needs of local populations using infographics.

Connecting Care for Children, an integrated care collaborative in northwest London, responded to local child health needs during the start of the COVID-19 pandemic through the co-production of infographics. Here we describe the development and evaluation of co-produced infographics using quality improvement methodology, to highlight their effectiveness in swiftly responding to local community health concerns.

DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal.

Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases.

COVID-19 Prophylaxis Efforts Based on Natural Antiviral Plant Extracts and Their Compounds.

During the time of the novel coronavirus disease 2019 (COVID-19) pandemic, it has been crucial to search for novel antiviral drugs from plants and well as other natural sources as alternatives for prophylaxis. This work reviews the antiviral potential of plant extracts, and the results of previous research for the treatment and prophylaxis of coronavirus disease and previous kinds of representative coronaviruses group. Detailed descriptions of medicinal herbs and crops based on their origin native area, plant parts used, and their antiviral potentials have been conducted. The possible role of plant-derived natural antiviral compounds for the development of plant-based drugs against coronavirus has been described. To identify useful scientific trends, VOSviewer visualization of presented scientific data analysis was used.

Links between perinatal risk factors and maternal psychological distress: A network analysis.

INTRODUCTION: This paper explores a range of perinatal risk factors that may increase maternal vulnerability to postnatal psychological distress in a sample of 17 531 women participating in the Millennium Cohort Study, a diverse British, longitudinal birth cohort study. MATERIAL AND METHODS: Using a graphical network modeling framework, this study models the links between postnatal psychological distress and perinatal risk factors, while controlling for sociodemographic factors and history of depression and anxiety. Postnatal psychological distress was assessed at 9 months postpartum using the Rutter Malaise Inventory. RESULTS: Results of the graphical network models indicate that lower levels of happiness about the pregnancy (Edge weight [w] = 0.084, 95% CI = 0.069-0.100, b = 0.095), smoking during pregnancy (w = 0.026, 95% CI = -0.009-0.060, b = 0.029), infection during pregnancy (w = 0.071, 95% CI = 0.024-0.118, b = 0.090), hyperemesis gravidarum (w = 0.068, 95% CI = 0.013-0.123, b = 0.083), baby in special care (w = 0.048, 95% CI = -0.004-0.099, b = 0.062), not being white (w = 0.101, 95% CI = 0.062-0.140, b = 0.118), being from a more deprived area (w = -0.028, 95% CI = -0.051 to -0.005, b = -0.039), lower income (w = -0.025, 95% CI = -0.055-0.005, b = -0.036), and history of depression or anxiety (w = 0.574, 95% CI = 0.545-0.603, b = 0.764) were associated with increased psychological distress. CONCLUSIONS: Some perinatal risk factors may be directly associated with postnatal psychological distress, but many risk factors appear to be primarily associated with demographic factors. This emphasizes the importance of taking a holistic approach when evaluating an individual's risk of developing postnatal psychological distress.

[Study on drug properties and syndrome-symptom-formula-herb network of traditional Chinese medicine in treatment of effort angina pectoris based on data visualization].

This article aims to explore drug properties and syndrome-symptom-formula-herb network of traditional Chinese medicine(TCM) in the treatment of effort angina pectoris based on data visualization, and provide useful references for clinical diagnosis and treatment. Literatures about TCM formula for effort angina pectoris from databases of CNKI, WanFang, VIP, and CBM were retrieved from the database-building to August 31, 2019. The name of syndromes, symptoms, formulas, and herbs were standardized, and the corresponding databases were established. Frequency, four properties, five flavors, and meridian were analyzed. Visualized syndrome-symptom-formula-herb network relationships were constructed by bioinformatic analysis. A total of 202 formulas were included, and 218 kinds of TCM were involved. There were 56 herbs with the use frequency of more than 10, involving 78 syndromes and 162 symptoms. TCM formulas in the treatment of effort angina pectoris mainly included herbs with effects in invigorating blood circulation and eliminating stasis, tonifying deficiency, Qi-regulating, resolving phlegm and relieving cough and asthma, relieving exterior disorder, and heat-clearing. The main properties were warm, cold and mild(accounting for 95%); the main flavors were sweet, bitter and pungent(accounting for 89%); and meridians were mainly spleen, heart, liver, lung, stomach, and kidney(accounting for 89%). Syndrome-symptom-formula-herb network of TCM in the treatment of effort angina pectoris were successfully constructed. The high-frequency syndromes of this disease were Qi deficiency and blood stasis, Qi stagnation and blood stasis, heart blood stasis, and turbid phlegm and blood stasis, and its high-frequency symptoms were chest tightness, chest pain, palpitation, shortness of breath, fatigue, dark purple tongue, spontaneous sweating, and abundant phlegm. High-frequency core formulas of this disease included Xuefu Zhuyu Decoction, Gualou Xiebai Banxia Decoction, Danshen Decoction, Taohong Siwu Decoction, Shengmai Powder, Buyang Huanwu Decoction and Zhigancao Decoction, and their core herbs included Salviae Miltiorrhizae Radix et Rhizoma, Astragali Radix, Chuanxiong Rhizoma, Ginseng Radix et Rhizoma, Trichosanthis Fructus, Allium Macrostemonis Bulbus, Notoginseng Radix et Rhizoma, Persicae Semen, Carthami Flos, Atractylodis Macrocephalae Rhizoma, Angelicae Sinensis Radix, Paeoniae Radix Rubra, Poria, Pinelliae Rhizoma Praeparatum. Drug properties and syndrome-symptom-formula-herb networks of TCM in the treatment of effort angina pectoris can realize data visualization, objectively reflect the clinical syndrome differentiation and rule of medication, and provide reference for clinical diagnosis and treatment.

Electrochemical impedance spectroscopy characterization of beverages.

This paper compares the results of standard chemical analytical processes and electrochemical impedance spectroscopy (EIS) in the characterization of different beverages, namely ground coffee, soluble coffee, coffee substitutes, barley, cow milk, vegetable drinks, tea, plant infusions and plant mixtures. For the two approaches, the similarities between the experimental data are assessed by means of the Euclidean and Canberra distances. The resulting information is processed by means of the multidimensional scaling (MDS) clustering and visualization algorithm. The results of the chemical analytical processes and EIS reveal identical clusters for the two adopted distances. Furthermore, the robustness of the experimental and computational scheme are assessed by means of the Procrustes technique. The results confirm the effectiveness of combining the EIS and MDS.

Assessment and management of nonpoint source pollution based on multicriteria analysis.

Assessing the potential impacts of nonpoint source (NPS) pollution and proposing sound control strategies are significant global challenges. However, few studies have provided insights into the quantitative risk analysis and efficient management of NPS pollution. This study formulated four evaluation criteria to characterize both the generation and migration of diffuse phosphorus. Multicriteria analysis and the technique for order preference by similarity to ideal solution were combined to develop a NPS pollution risk index model for the evaluation of the potential phosphorus loss at the basin scale. The proposed model is a simple and efficient tool that considers most factors that affect diffuse phosphorus. In the GIS environment, the spatial distribution of the risk index of diffuse phosphorus could be mapped and visualized in the Huai River Basin. With the natural breaks classification method, the study area was divided into the following five regions: a potentially polluted region (3.5%), a lightly polluted region (15.4%), a moderately polluted region (40.7%), a highly polluted region (31.5%), and a seriously polluted region (8.9%). Based on land use composition, geographical location, and sources of diffuse phosphorus of these five regions, corresponding prevention measures were introduced, thus facilitating the management of NPS pollution for policy makers.

Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments.

In the information age, the ability to read and construct data visualizations becomes as important as the ability to read and write text. However, while standard definitions and theoretical frameworks to teach and assess textual, mathematical, and visual literacy exist, current data visualization literacy (DVL) definitions and frameworks are not comprehensive enough to guide the design of DVL teaching and assessment. This paper introduces a data visualization literacy framework (DVL-FW) that was specifically developed to define, teach, and assess DVL. The holistic DVL-FW promotes both the reading and construction of data visualizations, a pairing analogous to that of both reading and writing in textual literacy and understanding and applying in mathematical literacy. Specifically, the DVL-FW defines a hierarchical typology of core concepts and details the process steps that are required to extract insights from data. Advancing the state of the art, the DVL-FW interlinks theoretical and procedural knowledge and showcases how both can be combined to design curricula and assessment measures for DVL. Earlier versions of the DVL-FW have been used to teach DVL to more than 8,500 residential and online students, and results from this effort have helped revise and validate the DVL-FW presented here.

Acoustic and visual pacesetter influence on the energy expenditure in a cycling exercise.

BACKGROUND: The aim of this study was to evaluate the effects of acoustic and visual pacesetters on the energy expenditure in a steady state 30-minute long cycling. METHODS: Eighteen healthy male subjects (age 27.6±4.59 years; height 1.78±0.07 m; body mass 80.1±7.85 kg) performed a 30-minute submaximal exercise at a constant workload on a cycle ergometer. The imposed workload required a metabolic expenditure corresponding to 70% of ventilatory threshold for each subject. Energy expenditure - expressed as a caloric equivalent relative to the total net oxygen consumption during exercise - was evaluated using three conditions: control (CT), no external pacesetter; acoustic (AT), listening to rhythmic acoustic stimuli at 120 beat per minute; and visual (VT), seeing footage consisting of eight different images in a looped sequence at 120 frames per minute. RESULTS: All measured parameters qualified the exercise as requiring mainly an aerobic metabolism, showing no pain and no fatigue. AT and VT energy expenditure (5.0±0.44 and 4.9±0.39 MET respectively) were significantly lower compared to CT (5.5±0.49 MET), while no difference between AT and VT were recognized. CONCLUSIONS: This study confirmed the ergogenic effect of the acoustic pacesetter on a 30-minute steady state rhythmic exercise. Novelty is that the visual pacesetter too was able to increase the mechanical efficiency as the same manner than the acoustic one. The present setting adopting visual pacesetter could be used in special categories, such as the deaf or in innovative technological tools as head-mounted display devices.

A Data Mining and Data Visualization Approach to Examine the Interrelationships Between Life Satisfaction, Secularization and Religiosity.

Previous studies have suggested a positive relationship between secularization and happiness, as well as a geographical, cultural and development pattern, primarily based on data gathered in Europe and the USA. To gain a more holistic view on the interrelationships between secularization, religiosity and subjective perception of well-being, this study utilized the Wave 6 archival data set (2010-2014) of World Values Survey, which contains 74,042 observations from 60 countries. In this study, the rating of satisfaction with life was treated as the dependent variable. Four secular value indices and 12 variables related to religiosity were extracted from the data set for predictive analysis. Data mining tools, such as the partition tree and bootstrap forest approaches, suggested that only secular values were influential. Specifically, secular values had a negative relationship with satisfaction. In addition, hierarchical clustering based on secularization and satisfaction did not suggest a meaningful pattern. For example, the dendrogram showed that South Korea, Lebanon, Estonia and Algeria were grouped together. This implies that secularization and satisfaction could vary from country to country, regardless of their geographical location, culture and development status. Specifically, countries that are similar in terms of satisfaction and secularization are not necessarily culturally similar or geographically clustered. This discourages the idea that these factors (e.g., location, development status, culture) play a role in mediating the relationship between secularization and religiosity. By directly contradicting previous work showing a pattern based on Europe and the USA, this finding challenges the existing understanding of the relationship between these factors. By expanding the scope of study to the whole world, the current analysis suggested that the existing view regarding the positive relationship between secularization and well-being might be oversimplified.

Understanding Older Adult Use of Data Visualizations as a Resource for Maintaining Health and Wellness.

To better understand how older adults use health visualizations and the potential barriers that impact utility, we conducted semistructured interviews with 21 older adults. Within these sessions, we presented participants with two interactive visualizations for exploration. Through an affinity mapping exercise, we extracted five key themes associated with how older adults utilize health visualizations and provide corresponding recommendations as points of consideration for designers developing older adult focused health visualizations. By examining how older adults perceive the utility of health visualizations, we lay the groundwork for design choices that impact eventual use and adoption of systems that generate data for such visualizations.