Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profiling.

The COVID-19 pandemic has raised several global public health challenges to which the international medical community have responded. Diagnostic testing and the development of vaccines against the SARS-CoV-2 virus have made remarkable progress to date. As the population is now faced with the complex lifestyle and medical decisions that come with living in a pandemic, a forward-looking understanding of how a COVID-19 diagnosis may affect the health of an individual represents a pressing need. Previously we used whole genome microarray to identify 200 3D genomic marker leads that could predict mild or severe COVID-19 disease outcomes from blood samples in a multinational cohort of COVID-19 patients. Here, we focus on the development and validation of a qPCR assay to accurately predict severe COVID-19 disease requiring intensive care unit (ICU) support and/or mechanical ventilation. From 200 original biomarker leads we established a classification model containing six markers. The markers were qualified and validated on 38 COVID-19 patients from an independent cohort. Overall, the six-marker model obtained a positive predictive value of 93% and balanced accuracy of 88% across 116 patients for the prognosis of COVID-19 severity requiring ICU care/ventilation support. The six-marker signature identifies individuals at the highest risk of developing severe complications in COVID-19 with high predictive accuracy and can assist in patient prognosis and clinical management decisions.

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Comprehensive single-cell sequencing reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of nasopharyngeal carcinoma

Nature Communications ◽

10.1038/s41467-021-21795-z ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Lanqi Gong ◽

Dora Lai-Wan Kwong ◽

Wei Dai ◽

Pingan Wu ◽

Shanshan Li ◽

...

Keyword(s):

Nasopharyngeal Carcinoma ◽

Single Cell ◽

Rna Sequencing ◽

Progression Free Survival ◽

Developmental Trajectory ◽

Free Survival ◽

Genetic Profiling ◽

Single Cell Rna Sequencing ◽

Infiltrating Cells ◽

Patient Prognosis

AbstractThe tumor microenvironment (TME) of nasopharyngeal carcinoma (NPC) harbors a heterogeneous and dynamic stromal population. A comprehensive understanding of this tumor-specific ecosystem is necessary to enhance cancer diagnosis, therapeutics, and prognosis. However, recent advances based on bulk RNA sequencing remain insufficient to construct an in-depth landscape of infiltrating stromal cells in NPC. Here we apply single-cell RNA sequencing to 66,627 cells from 14 patients, integrated with clonotype identification on T and B cells. We identify and characterize five major stromal clusters and 36 distinct subpopulations based on genetic profiling. By comparing with the infiltrating cells in the non-malignant microenvironment, we report highly representative features in the TME, including phenotypic abundance, genetic alternations, immune dynamics, clonal expansion, developmental trajectory, and molecular interactions that profoundly influence patient prognosis and therapeutic outcome. The key findings are further independently validated in two single-cell RNA sequencing cohorts and two bulk RNA-sequencing cohorts. In the present study, we reveal the correlation between NPC-specific characteristics and progression-free survival. Together, these data facilitate the understanding of the stromal landscape and immune dynamics in NPC patients and provides deeper insights into the development of prognostic biomarkers and therapeutic targets in the TME.

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World Health Report on Vision: Aging Implications for Global Vision and Eye Health

Innovation in Aging ◽

10.1093/geroni/igaa057.2933 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 807-808

Author(s):

Bonnielin Swenor ◽

Varshini Varadaraj ◽

Moon Jeong Lee ◽

Heather Whitson ◽

Pradeep Ramulu

Keyword(s):

Older Adults ◽

Visual Impairment ◽

Vision Loss ◽

World Health ◽

World Health Report ◽

Global Public Health ◽

Eye Care ◽

Health Report ◽

Public Health Challenges ◽

Health Organization

Abstract In 2019, the World Health Organization World Report on Vision estimated that that 2.2 billion people have a vision impairment, of which almost half could have been prevented or is yet to be addressed. As the global population ages and the prevalence of visual impairment increases, inequities in eye care and the downstream health and aging consequences of vision loss will become magnified. This session will: (1) provide key information regarding the burden of eye disease and visual impairment among older adults worldwide; (2) outline a framework created to conceptualize the aging and long-term health implications of vision loss, and (3) discuss the global public health challenges to eye care and to maximizing health for older adults with visual impairments.

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Contradictions in the promotion of publishing academic and scientific journal articles, and the inability to cope with the new coronavirus (COVID-19)

Antimicrobial Resistance and Infection Control ◽

10.1186/s13756-021-00884-0 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Rostam Jalali ◽

Amin Hosseinian-Far ◽

Masoud Mohammadi

Keyword(s):

Public Health ◽

Health Care ◽

Scientific Journal ◽

Emerging Infectious Diseases ◽

National Institutes Of Health ◽

Global Public Health ◽

Journal Articles ◽

Public Health Challenges ◽

Knowledge And Practice ◽

Nih Roadmap

Abstract Background Translating research into practice is a central priority within the National Institutes of Health (NIH) Roadmap. The underlying aim of the NIH Roadmap is to accelerate the movement of scientific findings into practical health care provisions through translational research. Main text Despite the advances in health sciences, emerging infectious diseases have become more frequent in recent decades. Furthermore, emerging and reemerging pathogens have led to several global public health challenges. A question, and to an extent a concern, arises from this: Why our health care system is experiencing several challenges in encountering the coronavirus outbreak, despite the ever-growing advances in sciences, and the exponential rise in the number of published articles in the first quartile journals and even the ones among the top 1%? Conclusion Two responses could be potentially provided to the above question: First, there seems to be a significant gap between our theoretical knowledge and practice. And second that many scholars and scientists publish papers only to have a longer list of publications, and therefore publishing is viewed as a personal objective, rather than for improving communities’ public health.

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Mixed polysaccharides derived from shiitake mushroom, Poriacocos, Ginger and Tangerine peel prevent the H1N1 virus infections in mice

Bioscience Biotechnology and Biochemistry ◽

10.1093/bbb/zbab174 ◽

2021 ◽

Author(s):

Diqi Yang ◽

Minghua Hu ◽

Hongmei Zhu ◽

Jianguo Chen ◽

Dehai Wang ◽

...

Keyword(s):

Influenza A ◽

Clinical Symptoms ◽

H1n1 Virus ◽

Global Public Health ◽

Virus Infections ◽

Shiitake Mushroom ◽

Virus Challenge ◽

Influenza A H1n1 ◽

Public Health Challenges ◽

Cellular Immune

Abstract The pandemic influenza A (H1N1) virus spread globally and posed one of the most serious global public health challenges. The traditional Chinese medicine is served as a complementary treatment strategy with vaccine immunization. Here, we demonstrated the mixed polysaccharides (MPs) derived from shiitake mushroom, poriacocos, ginger and tyangerine peel prevent the H1N1 virus infections in mice. MPs pretreatment attenuated H1N1 virus-induced weight loss, clinical symptoms and death. The lymphocytes detection results showed the CD3+, CD19+ and CD25+ cell proportions were up-regulated in thymus under MPs pretreatment. Besides, MPs pretreatment reduced the inflammatory cell infiltration and increased the cell proportions of CD19+, CD25+ and CD278+ in lung. However, MPs treatment have no effective therapeutic effect after H1N1 virus challenge. The current study suggested that pretreatment with MPs could attenuate H1N1 virus-induced lung injury and up-regulate humoral and cellular immune responses in non- immunized mice.

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Mechanisms of Antimicrobial Resistance in ESKAPE Pathogens

BioMed Research International ◽

10.1155/2016/2475067 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 324

Author(s):

Sirijan Santajit ◽

Nitaya Indrawattana

Keyword(s):

Public Health ◽

Antimicrobial Resistance ◽

Antimicrobial Agents ◽

Multidrug Resistant ◽

Resistance Mechanisms ◽

Global Public Health ◽

Drug Usage ◽

Inappropriate Use ◽

Public Health Challenges ◽

Eskape Pathogens

The ESKAPE pathogens (Enterococcus faecium,Staphylococcus aureus,Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa, andEnterobacterspecies) are the leading cause of nosocomial infections throughout the world. Most of them are multidrug resistant isolates, which is one of the greatest challenges in clinical practice. Multidrug resistance is amongst the top three threats to global public health and is usually caused by excessive drug usage or prescription, inappropriate use of antimicrobials, and substandard pharmaceuticals. Understanding the resistance mechanisms of these bacteria is crucial for the development of novel antimicrobial agents or other alternative tools to combat these public health challenges. Greater mechanistic understanding would also aid in the prediction of underlying or even unknown mechanisms of resistance, which could be applied to other emerging multidrug resistant pathogens. In this review, we summarize the known antimicrobial resistance mechanisms of ESKAPE pathogens.

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Development and validation of nomogram based on SIRI for predicting the clinical outcome in patients with nasopharyngeal carcinomas

Journal of Investigative Medicine ◽

10.1136/jim-2018-000801 ◽

2018 ◽

Vol 67 (3) ◽

pp. 691-698 ◽

Cited By ~ 17

Author(s):

Yuan Chen ◽

Wenjie Jiang ◽

Dan Xi ◽

Jun Chen ◽

Guoping Xu ◽

...

Keyword(s):

Predictive Accuracy ◽

Peripheral Lymphocyte ◽

Clinicopathological Parameters ◽

Concordance Index ◽

Tumor Node Metastasis ◽

Discriminative Ability ◽

Node Metastasis ◽

Kaplan Meier ◽

Treatment Plans ◽

Development And Validation

The Systemic Inflammation Response Index (SIRI), based on peripheral lymphocyte, neutrophil, and monocyte counts, was recently investigated as a prognostic marker for several tumors. However, use of the SIRI has not been reported for nasopharyngeal carcinoma (NPC). We evaluated the prognostic value of the SIRI in primary and validation cohorts. We also established an effective prognostic nomogram for NPC based on clinicopathological parameters and the SIRI. The predictive accuracy and discriminative ability of the nomogram were determined using the concordance index (C-index) and a calibration curve and were compared with tumor-node-metastasis classifications. Our Kaplan-Meier survival analysis results showed that the SIRI was associated with the overall survival of patients with NPC in the primary and validation cohorts. The SIRI was identified to be an independent prognostic factor for NPC. In addition, we developed and validated a new prognostic nomogram that integrated clinicopathological factors and the SIRI. This nomogram can efficiently predict the prognosis of patients with NPC. The SIRI is a novel, simple and inexpensive prognostic predictor for patients with NPC. The SIRI has important value for predicting the prognosis of patients with NPC and developing individualized treatment plans.

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Characteristics and Causes of Neonatal Mortality in Hospitalized Cases at Benghazi Children's Hospital (2013-2014)

Asian Journal of Pediatric Research ◽

10.9734/ajpr/2020/v3i330131 ◽

2020 ◽

pp. 37-42

Author(s):

Ashraf Rajab ◽

Suad F. Elnasfi ◽

Amal Elfakhri ◽

Raja Elfakhri ◽

Hind K. Elgetaany ◽

...

Keyword(s):

Neonatal Mortality ◽

Lung Diseases ◽

Congenital Heart ◽

Preterm Neonate ◽

Heart Diseases ◽

Neonatal Morbidity ◽

Congenital Heart Diseases ◽

Global Public Health ◽

Common Causes ◽

Public Health Challenges

Background: Neonatal morbidity and mortality are major global public health challenges with approximately 3.1 million babies worldwide dying each year in the first month of life. The vast majority of neonatal death occurs in developing countries. Aims: This study was undertaken to assess the magnitude of neonatal mortality and identify the main causes and associated factors of neonatal mortality. Methodology: A retrospective study of 5791 neonates was conducted in Benghazi children hospital from 1st January 2013 up to December 2014. Results: During the two years of the study there were 5791 neonates admitted to neonatal unit of Benghazi hospital, out of them 389 died (6.7% of total neonatal admissions) accounting for 59.6% of the total Paediatric deaths within the same period, moreover approximately one neonate died every 48 hours throughout the study period. There was a slight predominance of male deaths 225 (57.5%) over females 164 (42.5%). The majority of neonates were Libyan 365 (94%), 212 of them were born in Benghazi, while the remaining 177 from other cities. Preterm neonate accounted for 35% (138) of deceased neonates. The most common causes were lung diseases of prematurity (29%), sepsis (25%), Congenital Heart Diseases (12.5%), post-operative intestinal obstruction (7%), multiple congenital anomalies (7%), intractable convulsions (6.5%). Conclusion: This study indicated that neonatal mortality represented the highest portion of all deaths reported at Benghazi children hospital during the study period. Lung diseases of prematurity was found to be the top leading cause followed by sepsis then congenital heart diseases. Male showed marginal predominance over female in this study. More than one third of deceased neonates were preterm.

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Lifestyle Medicine

Principles of Medical Professionalism ◽

10.1093/med/9780197506226.003.0009 ◽

2021 ◽

pp. 157-178

Author(s):

Gia Merlo

Keyword(s):

Healthy Lifestyle ◽

Lifestyle Changes ◽

Medical Community ◽

Global Public Health ◽

Lifestyle Medicine ◽

Public Health Burden ◽

Obesity And Diabetes ◽

Managing Stress ◽

Treatment Of Obesity ◽

Lifestyle Diseases

This chapter addresses the rise of lifestyle medicine. The impact of chronic diseases on health and quality of life are well-known within the medical community. Preventive medicine has only been partially successful in addressing these problems. For physicians to advocate healthy lifestyle choices for their patients, they must first understand what a healthy lifestyle entails. The Six Pillars of Lifestyle Medicine outline the six main lifestyle changes—healthful eating, increasing physical activity, improving sleep, managing stress, avoiding risky substances, forming and maintaining relationships—that physicians should promote to their patients. The global public health burden of diabetes, obesity, and other lifestyle diseases is increasing at an astounding rate. However, very few training programs have robust educational offerings for physicians on nonpharmacological treatment of obesity and diabetes.

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A role for Biofoundries in rapid development and validation of automated SARS-CoV-2 clinical diagnostics

Nature Communications ◽

10.1038/s41467-020-18130-3 ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 2

Author(s):

Michael A. Crone ◽

Miles Priestman ◽

Marta Ciechonska ◽

Kirsten Jensen ◽

David J. Sharp ◽

...

Keyword(s):

Rapid Development ◽

Community Sample ◽

Diagnostic Testing ◽

Rna Extraction ◽

Clinical Diagnostics ◽

Virus Like Particle ◽

Qpcr Platform ◽

Sample Testing ◽

Alternative Testing ◽

Development And Validation

Abstract The SARS-CoV-2 pandemic has shown how a rapid rise in demand for patient and community sample testing can quickly overwhelm testing capability globally. With most diagnostic infrastructure dependent on specialized instruments, their exclusive reagent supplies quickly become bottlenecks, creating an urgent need for approaches to boost testing capacity. We address this challenge by refocusing the London Biofoundry onto the development of alternative testing pipelines. Here, we present a reagent-agnostic automated SARS-CoV-2 testing platform that can be quickly deployed and scaled. Using an in-house-generated, open-source, MS2-virus-like particle (VLP) SARS-CoV-2 standard, we validate RNA extraction and RT-qPCR workflows as well as two detection assays based on CRISPR-Cas13a and RT-loop-mediated isothermal amplification (RT-LAMP). In collaboration with an NHS diagnostic testing lab, we report the performance of the overall workflow and detection of SARS-CoV-2 in patient samples using RT-qPCR, CRISPR-Cas13a, and RT-LAMP. The validated RNA extraction and RT-qPCR platform has been installed in NHS diagnostic labs, increasing testing capacity by 1000 samples per day.

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Discrimination of Gentiana and Its Related Species Using IR Spectroscopy Combined with Feature Selection and Stacked Generalization

Molecules ◽

10.3390/molecules25061442 ◽

2020 ◽

Vol 25 (6) ◽

pp. 1442 ◽

Cited By ~ 2

Author(s):

Tao Shen ◽

Hong Yu ◽

Yuan-Zhong Wang

Keyword(s):

Genetic Algorithm ◽

Support Vector Machine ◽

Feature Selection ◽

Related Species ◽

Predictive Accuracy ◽

Classification Model ◽

Venn Diagram ◽

Support Vector ◽

Stacked Generalization ◽

Svm Model

Gentiana, which is one of the largest genera of Gentianoideae, most of which had potential pharmaceutical value, and applied to local traditional medical treatment. Because of the phytochemical diversity and difference of bioactive compounds among species, which makes it crucial to accurately identify authentic Gentiana species. In this paper, the feasibility of using the infrared spectroscopy technique combined with chemometrics analysis to identify Gentiana and its related species was studied. A total of 180 batches of raw spectral fingerprints were obtained from 18 species of Gentiana and Tripterospermum by near-infrared (NIR: 10,000–4000 cm−1) and Fourier transform mid-infrared (MIR: 4000–600 cm−1) spectrum. Firstly, principal component analysis (PCA) was utilized to explore the natural grouping of the 180 samples. Secondly, random forests (RF), support vector machine (SVM), and K-nearest neighbors (KNN) models were built while using full spectra (including 1487 NIR variables and 1214 FT-MIR variables, respectively). The MIR-SVM model had a higher classification accuracy rate than the other models that were based on the results of the calibration sets and prediction sets. The five feature selection strategies, VIP (variable importance in the projection), Boruta, GARF (genetic algorithm combined with random forest), GASVM (genetic algorithm combined with support vector machine), and Venn diagram calculation, were used to reduce the dimensions of the data variable in order to further reduce numbers of variables for modeling. Finally, 101 NIR and 73 FT-MIR bands were selected as the feature variables, respectively. Thirdly, stacking models were built based on the optimal spectral dataset. Most of the stacking models performed better than the full spectra-based models. RF and SVM (as base learners), combined with the SVM meta-classifier, was the optimal stacked generalization strategy. For the SG-Ven-MIR-SVM model, the accuracy (ACC) of the calibration set and validation set were both 100%. Sensitivity (SE), specificity (SP), efficiency (EFF), Matthews correlation coefficient (MCC), and Cohen’s kappa coefficient (K) were all 1, which showed that the model had the optimal authenticity identification performance. Those parameters indicated that stacked generalization combined with feature selection is probably an important technique for improving the classification model predictive accuracy and avoid overfitting. The study result can provide a valuable reference for the safety and effectiveness of the clinical application of medicinal Gentiana.

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