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Public Health Public Health

Proceedings from the CIHLMU occupational safety and health symposium 2019 "Protecting workers' health: global challenges and opportunities in work-related respiratory diseases".

In BMC proceedings

The international CIHLMU Occupational Safety and Health Symposium 2019 was held on 16th March, 2019 at the Ludwig-Maximilians-Universität Munich, Germany. About 60 participants from around the world representing occupational health and safety professionals, students, instructors from several institutions in Germany and abroad, attended the symposium.The main objective of the symposium was to create awareness on global challenges and opportunities in work-related respiratory diseases. One keynote lecture and six presentations were made. While the keynote lecture addressed issues on occupational diseases in the twenty-first century, the six presentations were centered on: Prevention and control of work-related respiratory diseases, considerations; Occupational health and safety in Mining: Respiratory diseases; The prevention of TB among health workers is our collective responsibility; Compensation and prevention of occupational diseases and discussion on how artificial intelligence can support them: Overview of international approaches; Work-related Asthma: Evidence from high-income countries; and The role of imaging in the diagnosis of work- related respiratory diseases. A panel discussion was conducted following the presentations on the importance and challenges of data acquisition which is needed to have a realistic picture of the occupational safety and health status of workers at different levels. The current summary is an attempt to share the proceedings of the symposium.

Gidi Netsanet Workneh, Suraya Anna, Mutayoba Beatrice, Espinoza Bernarda, Meggi Bindiya, Sabi Issa, Noller Jessica Michelle Guggenbuehl, Schmieding Kristina, Tukhanova Nur, Manhart Martina, Heiber Arlett


Occupational diseases, Occupational safety, Protecting workers, Work-related respiratory diseases

Public Health Public Health

A plea to merge clinical and public health practices: reasons and consequences.

In BMC health services research

BACKGROUND : Revisiting professionalism, both as a medical ideal and educational topic, this paper asks whether, in the rise of artificial intelligence, healthcare commoditisation and environmental challenges, a rationale exists for merging clinical and public health practices. To optimize doctors' impact on community health, clinicians should introduce public health thinking and action into clinical practice, above and beyond controlling nosocomial infections and iatrogenesis. However, in the interest of effectiveness they should do everything possible to personalise care delivery. To solve this paradox, we explore why it is necessary for the boundaries between medicine and public health to be blurred.

MAIN BODY : Proceeding sequentially, we derive standards for medical professionalism from care quality criteria, neo-Hippocratic ethics, public health concepts, and policy outcomes. Thereby, we formulate benchmarks for health care management and apply them to policy evaluation. During this process we justify the social, professional - and by implication, non-commercial, non-industrial - mission of healthcare financing and policies. The complexity of ethical, person-centred, biopsychosocial practice requires a human interface between suffering, health risks and their therapeutic solution - and thus legitimises the medical profession's existence. Consequently, the universal human right to healthcare is a right to access professionally delivered care. Its enforcement requires significant updating of the existing medical culture, and not just in respect of the man/machine interface. This will allow physicians to focus on what artificial intelligence cannot do, or not do well. These duties should become the touchstone of their practice, knowledge and ethics. Artificial intelligence must support medical professionalism, not determine it. Because physicians need sufficient autonomy to exercise professional judgement, medical ethics will conflict with attempts to introduce clinical standardisation as a managerial paradigm, which is what happens when industrial-style management is applied to healthcare.

CONCLUSION : Public healthcare financing and policy ought to support medical professionalism, alongside integrated clinical and public health practice, and its management. Publicly-financed health management should actively promote ethics in publicly- oriented services. Commercialised healthcare is antithetical to ethical medical, and to clinical / public health practice integration. To lobby governments effectively, physicians need to appreciate the political economy of care.

Unger Jean-Pierre, Morales Ingrid, De Paepe Pierre, Roland Michel


Health management, Health policy, Medical education, Medical professionalism, Public health

oncology Oncology

Correction to: Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC.

In BMC genomics ; h5-index 78.0

An amendment to this paper has been published and can be accessed via the original article.

Goswami Chitrita, Chawla Smriti, Thakral Deepshi, Pant Himanshu, Verma Pramod, Malik Prabhat Singh, Jayadeva Gupta, Ritu Ahuja, Gaurav Sengupta


General General

Identification of Chronic Hypersensitivity Pneumonitis Biomarkers with Machine Learning and Differential Co-expression Analysis.

In Current gene therapy

AIMS : We would like to identify the biomarkers for chronic hypersensitivity pneumonitis (CHP) and facilitate the precise gene therapy of CHP.

BACKGROUND : Chronic hypersensitivity pneumonitis (CHP) is an interstitial lung disease caused by hypersensitive reactions to inhaled antigens. Clinically, the tasks of differentiating between CHP and other interstitial lungs diseases, especially idiopathic pulmonary fibrosis (IPF), were challenging.

OBJECTIVE : In this study, we analyzed the public available gene expression profile of 82 CHP patients, 103 IPF patients, and 103 control samples to identify the CHP biomarkers.

METHOD : The CHP biomarkers were selected with advanced feature selection methods: Monte Carlo Feature Selection (MCFS) and Incremental Feature Selection (IFS). A Support Vector Machine (SVM) classifier was built. Then, we analyzed these CHP biomarkers through functional enrichment analysis and differential co-expression analysis.

RESULT : There were 674 identified CHP biomarkers. The co-expression network of these biomarkers in CHP included more negative regulations and the network structure of CHP was quite different from the network of IPF and control.

CONCLUSION : The SVM classifier may serve as an important clinical tool to address the challenging task of differentiating between CHP and IPF. Many of the biomarker genes on the differential co-expression network showed great promise in revealing the underlying mechanisms of CHP.

Zhang Hongwei, Wang Steven, Huang Tao


Chronic hypersensitivity pneumonitis, biomarker, classifier, differential coexpression network., feature selection, precise gene therapy

General General

Conditional Adversarial Domain Adaptation Neural Network for Motor Imagery EEG Decoding.

In Entropy (Basel, Switzerland)

Decoding motor imagery (MI) electroencephalogram (EEG) signals for brain-computer interfaces (BCIs) is a challenging task because of the severe non-stationarity of perceptual decision processes. Recently, deep learning techniques have had great success in EEG decoding because of their prominent ability to learn features from raw EEG signals automatically. However, the challenge that the deep learning method faces is that the shortage of labeled EEG signals and EEGs sampled from other subjects cannot be used directly to train a convolutional neural network (ConvNet) for a target subject. To solve this problem, in this paper, we present a novel conditional domain adaptation neural network (CDAN) framework for MI EEG signal decoding. Specifically, in the CDAN, a densely connected ConvNet is firstly applied to obtain high-level discriminative features from raw EEG time series. Then, a novel conditional domain discriminator is introduced to work as an adversarial with the label classifier to learn commonly shared intra-subjects EEG features. As a result, the CDAN model trained with sufficient EEG signals from other subjects can be used to classify the signals from the target subject efficiently. Competitive experimental results on a public EEG dataset (High Gamma Dataset) against the state-of-the-art methods demonstrate the efficacy of the proposed framework in recognizing MI EEG signals, indicating its effectiveness in automatic perceptual decision decoding.

Tang Xingliang, Zhang Xianrui


convolutional neural network, domain adaptation, electroencephalogram (EEG), motor imagery (MI), signal classification

General General

Emergence of Organisms.

In Entropy (Basel, Switzerland)

Since early cybernetics studies by Wiener, Pask, and Ashby, the properties of living systems are subject to deep investigations. The goals of this endeavour are both understanding and building: abstract models and general principles are sought for describing organisms, their dynamics and their ability to produce adaptive behavior. This research has achieved prominent results in fields such as artificial intelligence and artificial life. For example, today we have robots capable of exploring hostile environments with high level of self-sufficiency, planning capabilities and able to learn. Nevertheless, the discrepancy between the emergence and evolution of life and artificial systems is still huge. In this paper, we identify the fundamental elements that characterize the evolution of the biosphere and open-ended evolution, and we illustrate their implications for the evolution of artificial systems. Subsequently, we discuss the most relevant issues and questions that this viewpoint poses both for biological and artificial systems.

Roli Andrea, Kauffman Stuart A


Kantian whole, affordance, biosemiotics, consciousness, constraint closure, critical dynamics, cybernetics, emergence, entailing laws, evolution, information