Search

Implementation of the African Mining Vision in Côte d’Ivoire is weak, and AMV domestication is unlikely to happen soon. Focusing on the artisanal and small-scale mining (ASM) sector, a key section of the AMV, we look at the tumultuous recent history of the diamond mining town Tortiya. The subject of a halting and uneven formalisation process, the case is emblematic for the lack of interest shown in ASM at a policy level. This is due to high costs, and low political and economic returns of formalisation. It underscores a broader lack of strategic vision for the mining sector.

New Findings: What is the main observation in this case? Several studies have reported progressive hypoxaemia once extracorporeal carbon dioxide removal is started in patients with hypercapnic respiratory failure, possibly attributable to an altered respiratory quotient. What insights does it reveal? In this quality control report, we show that the respiratory quotient exhibits only minimal alteration when extracorporeal carbon dioxide removal is started and assume that the progressive hypoxaemia is attributable to an increase in intrapulmonary shunt. Abstract: The use of extracorporeal carbon dioxide removal (ECCO 2R) has been proposed in patients with acute respiratory distress syndrome to achieve lung-protective ventilation and in patients with selective hypercapnic respiratory failure. However, several studies have reported progressive hypoxaemia, as expressed by a need to increase the inspired oxygen fraction (F iO 2) to maintain adequate oxygenation or by a decrease in the ratio of arterial oxygen tension (P aO 2) to F iO 2 once ECCO 2R is started. We present the case of a patient who was admitted to the intensive care unit for a coronavirus disease 2019 pneumonia and who was intubated because of hypercapnic respiratory insufficiency. Extracorporeal carbon dioxide removal was started, and the patient subsequently developed progressive hypoxaemia. To test whether the hypoxaemia was attributable to the ECCO 2R, blood samples were taken in different settings: (1) ‘no ECCO 2R’, blood flow 150 ml/min with a ECCO 2R gas flow of 0 L/min; and (2) ‘with ECCO 2R’, blood flow 400 ml/min with gas flow 12 L/min. We measured P aO 2, alveolar oxygen tension, P aO 2/F iO 2, alveolar–arterial oxygen tension difference, arterial carbon dioxide tension and the respiratory quotient (RQ) by indirect calorimetry in each setting. The RQ was 0.60 without ECCO 2R and 0.57 with ECCO 2R. The alveolar oxygen tension was 220.4 mmHg without ECCO 2R and increased to 240.3 mmHg with ECCO 2R, whereas P aO 2/F iO 2 decreased from 177 to 171. Our study showed only a minimal change in RQ when ECCO 2R was started. We were the first to measure the RQ directly, before and after the initiation of ECCO 2R, in a patient with hypercapnic respiratory failure.

Applied immunology; Predictive markers; Viral infection Immunologia aplicada; Marcadors predictius; Infecció viral Inmunología aplicada; Marcadores predictivos; Infección viral Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient’s immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. This work was supported by Health Holland LSHM20056 grant (PDK), in part from the European Union’s Horizon 2020 research and innovation program under grant agreement No 779295 (PDK), in part supported by the Erasmus foundation (BJAR), grant PI20/00416 from the Instituto de Salud Carlos III (RPB) and the European Regional Development Fund (ERDF) (RPB).

Quantitative or qualitative differences in immunity may drive and predict clinical severity in COVID-19. We therefore measured modules of serum pro-inflammatory, anti-inflammatory and anti-viral cytokines in combination with the anti-SARS-CoV-2 antibody response in COVID-19 patients admitted to tertiary care. Using machine learning and employing unsupervised hierarchical clustering, agnostic to severity, we identified three distinct immunotypes that were shown post-clustering to predict very different clinical courses such as clinical improvement or clinical deterioration. Immunotypes did not associate chronologically with disease duration but rather reflect variations in the nature and kinetics of individual patient’s immune response. Here we demonstrate that immunophenotyping can stratify patients to high and low risk clinical subtypes, with distinct cytokine and antibody profiles, that can predict severity progression and guide personalized therapy.

This article offers preliminary reflections on the potential impact of COVID-19 on artisanal and small-scale mining (ASM) activities – low-tech, labor-intensive mineral extraction and processing – in sub-Saharan Africa. In doing so, it revisits the core ideas put forward in the literature in support of showcasing the sector more prominently in the region’s rural development strategies. For decades, scholars have been gathering evidence that points to ASM being the most important rural nonfarm activity in sub-Saharan Africa, as well as how, in providing a supplementary source of income, the sector helps millions of the region’s impoverished farm-dependent families cope with unexpected economic stresses and shocks. Sub-Saharan Africa has managed to avoid high numbers of COVID-19 infections and deaths thus far but it has already felt the economic impacts of the pandemic, perhaps nowhere more than in its remote rural areas, which are already poverty-stricken and produce food at mostly subsistence levels. Intensifying support for ASM, an economic activity which again, many rural Africans are already involved in and familiar with the benefits it provides, in rural development and adaptation plans linked to COVID-19, should be prioritized by the region’s governments and donors. Findings from ongoing research in Mali, Liberia and Ghana – the locations of three of the largest and most dynamic ASM economies in sub-Saharan Africa – reveal that despite its proven ability to stabilize and catalyze development in the region’s rural economies, that even this sector has been affected by COVID-19. They more importantly shed light on how the pandemic has impacted ASM-dependent communities, and importantly, offer clues on how to make the sector more robust and better position it to steer rural communities through the crisis.

How the human brain retains relevant vocal information while suppressing irrelevant sounds is one of the ongoing challenges in cognitive neuroscience. Knowledge of the underlying mechanisms of this ability can be used to identify whether a person is distracted during listening to a target speech, especially in a learning context. This paper investigates the neural correlates of learning from the speech presented in a noisy environment using an ecologically valid learning context and electroencephalography (EEG). To this end, the following listening tasks were performed while 64-channel EEG signals were recorded: (1) attentive listening to the lectures in background sound, (2) attentive listening to the background sound presented alone, and (3) inattentive listening to the background sound. For the first task, 13 lectures of 5 min in length embedded in different types of realistic background noise were presented to participants who were asked to focus on the lectures. As background noise, multi-talker babble, continuous highway, and fluctuating traffic sounds were used. After the second task, a written exam was taken to quantify the amount of information that participants have acquired and retained from the lectures. In addition to various power spectrum-based EEG features in different frequency bands, the peak frequency and long-range temporal correlations (LRTC) of alpha-band activity were estimated. To reduce these dimensions, a principal component analysis (PCA) was applied to the different listening conditions resulting in the feature combinations that discriminate most between listening conditions and persons. Linear mixed-effect modeling was used to explain the origin of extracted principal components, showing their dependence on listening condition and type of background sound. Following this unsupervised step, a supervised analysis was performed to explain the link between the exam results and the EEG principal component scores using both linear fixed and mixed-effect modeling. Results suggest that the ability to learn from the speech presented in environmental noise can be predicted by the several components over the specific brain regions better than by knowing the background noise type. These components were linked to deterioration in attention, speech envelope following, decreased focusing during listening, cognitive prediction error, and specific inhibition mechanisms.

There is accumulating evidence for auditory dysfunctions in patients with Parkinson's disease (PD). Moreover, a possible relationship has been suggested between altered auditory intensity processing and the hypophonic speech characteristics in PD. Nonetheless, further insight into the neurophysiological correlates of auditory intensity processing in patients with PD is needed primarily. In the present study, high-density EEG recordings were used to investigate intensity dependence of auditory evoked potentials (IDAEPs) in 14 patients with PD and 14 age- and gender-matched healthy control participants (HCs). Patients with PD were evaluated in both the on- and off-medication states. HCs were also evaluated twice. Significantly increased IDAEP of the N1/P2 was demonstrated in patients with PD evaluated in the on-medication state compared to HCs. Distinctive results were found for the N1 and P2 component. Regarding the N1 component, no differences in latency or amplitude were shown between patients with PD and HCs regardless of the medication state. In contrast, increased P2 amplitude was demonstrated in patients with PD evaluated in the on-medication state compared to the off-medication state and HCs. In addition to a dopaminergic deficiency, deficits in serotonergic neurotransmission in PD were shown based on increased IDAEP. Due to specific alterations of the N1-P2 complex, the current results suggest deficiencies in early-attentive inhibitory processing of auditory input in PD. This interpretation is consistent with the involvement of the basal ganglia and the role of dopaminergic and serotonergic neurotransmission in auditory gating.

Purpose of review A growing numerical and complexity of patients requiring nonoperating room anesthesia (NORA) necessitates a multidisciplinary approach of a highly experienced team in a highly technological setting of the cathlab or radiology suite. These requirements are even more magnified in the context of the coronavirus disease 2019 (COVID-19) pandemic. Recent findings This review describes the aspects of risk stratification both in adults and children with respect to patient morphology, airway management, cardiorespiratory function and finally future developments, which could beneficially interfere with imminent management in NORA. Moreover, some particular features related to COVID-19 are also discussed. Summary Apart from a thorough preoperative assessment, preventive strategies and well-chosen monitoring should be implemented to preclude inadvertent events in sometimes high-risk patients. Timely preventive measures and early recognition of complications could only be achieved by a multidisciplinary cooperating team. In addition, the implementation of safety measurements due to the infectious transmission to both the patients and care givers is crucial.

Research on auditory processing in Parkinson's disease (PD) has recently made substantial progress. At present, evidence has been found for altered auditory processing in the clinical stage of PD. The auditory alterations in PD have been demonstrated with low-cost and non-invasive assessments that are already used in routine clinical practice. Since auditory alterations have been reported early in disease progression, it would be highly relevant to investigate whether auditory markers could be provided in the prodromal stage of PD. In addition, auditory alterations in early stage PD might be modulated by dopaminergic medication. Therefore, the aim of this review is (1) to summarize the literature on auditory processing in PD with a specific focus on the early disease stages, (2) to give future perspectives on which audiological and electrophysiological measurements could be useful in the prodromal stage of PD and (3) to assess the effect of dopaminergic medication on potential auditory markers in the prodromal stage of PD.