What We Know So Far: Artificial Intelligence in African Healthcare

Healthcare in Africa is a complex issue influenced by many factors including poverty, lack of infrastructure, and inadequate funding. However, Artificial intelligence (AI) applied to healthcare, has the potential to transform healthcare in Africa by improving the accuracy and efficiency of diagnosis, enabling earlier detection of diseases, and supporting the delivery of personalized medicine. This paper reviews the current state of how AI Algorithms can be used to improve diagnostics, treatment, and disease monitoring, as well as how AI can be used to improve access to healthcare in Africa as a low-resource setting and discusses some of the critical challenges and opportunities for its adoption. As such, there is a need for a well-coordinated effort by the governments, private sector, healthcare providers, and international organizations to create sustainable AI solutions that meet the unique needs of the African healthcare system.Comment: 8 pages, 1 figure, AAAI-23 conference in Washington, DC, International Workshop on the Social Impact of AI for Africa(SIAIA

User or Labor: An Interaction Framework for Human-Machine Relationships in NLP

The bridging research between Human-Computer Interaction and Natural Language Processing is developing quickly these years. However, there is still a lack of formative guidelines to understand the human-machine interaction in the NLP loop. When researchers crossing the two fields talk about humans, they may imply a user or labor. Regarding a human as a user, the human is in control, and the machine is used as a tool to achieve the human's goals. Considering a human as a laborer, the machine is in control, and the human is used as a resource to achieve the machine's goals. Through a systematic literature review and thematic analysis, we present an interaction framework for understanding human-machine relationships in NLP. In the framework, we propose four types of human-machine interactions: Human-Teacher and Machine-Learner, Machine-Leading, Human-Leading, and Human-Machine Collaborators. Our analysis shows that the type of interaction is not fixed but can change across tasks as the relationship between the human and the machine develops. We also discuss the implications of this framework for the future of NLP and human-machine relationships

Effects of a newly developed potent orexin-2 receptor-selective antagonist, compound 1 m, on sleep/wakefulness states in mice

Orexins (also known as hypocretins) play critical roles in the regulation of sleep/wakefulness states by activating two G-protein coupled receptors (GPCRs), orexin 1 (OX1R) and orexin 2 receptors (OX2R). In order to understand the differential contribution of both receptors in regulating sleep/wakefulness states we compared the pharmacological effects of a newly developed OX2R antagonist (2-SORA), Compound 1 m (C1 m), with those of a dual orexin receptor antagonist (DORA), suvorexant, in C57BL/6J mice. After oral administration in the dark period, both C1m and suvorexant decreased wakefulness time with similar efficacy in a dose-dependent manner. While C1m primarily increased total non-rapid eye movement (NREM) sleep time without affecting episode durations and with minimal effects on REM sleep, suvorexant increased both total NREM and REM sleep time and episode durations with predominant effects on REM sleep. Fos-immunostaining showed that both compounds affected the activities of arousal-related neurons with different patterns. The number of Fos-IR noradrenergic neurons in the locus coeruleus was lower in the suvorexant group as compared with the control and C1m-treated groups. In contrast, the numbers of Fos-IR neurons in histaminergic neurons in the tuberomamillary nucleus and serotonergic neurons in the dorsal raphe were reduced to a similar extent in the suvorexant and C1m groups as compared with the vehicle-treated group. Together, these results suggest that an orexin-mediated suppression of REM sleep via potential activation of OX1Rs in the locus coeruleus may possibly contribute to the differential effects on sleep/wakefulness exerted by a DORA as compared to a 2-SORA. © 2014 Etori, Saito, Tsujino and Sakurai

Adapting Pretrained ASR Models to Low-resource Clinical Speech using Epistemic Uncertainty-based Data Selection

While there has been significant progress in ASR, African-accented clinical ASR has been understudied due to a lack of training datasets. Building robust ASR systems in this domain requires large amounts of annotated or labeled data, for a wide variety of linguistically and morphologically rich accents, which are expensive to create. Our study aims to address this problem by reducing annotation expenses through informative uncertainty-based data selection. We show that incorporating epistemic uncertainty into our adaptation rounds outperforms several baseline results, established using state-of-the-art (SOTA) ASR models, while reducing the required amount of labeled data, and hence reducing annotation costs. Our approach also improves out-of-distribution generalization for very low-resource accents, demonstrating the viability of our approach for building generalizable ASR models in the context of accented African clinical ASR, where training datasets are predominantly scarce

Disrupting the HDAC6-ubiquitin interaction impairs infection by influenza and Zika virus and cellular stress pathways

The deacetylase HDAC6 has tandem catalytic domains and a zinc finger domain (ZnF) binding ubiquitin (Ub). While the catalytic domain has an antiviral effect, the ZnF facilitates influenza A virus (IAV) infection and cellular stress responses. By recruiting Ub via the ZnF, HDAC6 promotes the formation of aggresomes and stress granules (SGs), dynamic structures associated with pathologies such as neurodegeneration. IAV subverts the aggresome/HDAC6 pathway to facilitate capsid uncoating during early infection. To target this pathway, we generate designed ankyrin repeat proteins (DARPins) binding the ZnF; one of these prevents interaction with Ub in vitro and in cells. Crystallographic analysis shows that it blocks the ZnF pocket where Ub engages. Conditional expression of this DARPin reversibly impairs infection by IAV and Zika virus; moreover, SGs and aggresomes are downregulated. These results validate the HDAC6 ZnF as an attractive target for drug discovery

Disrupting the HDAC6-ubiquitin interaction impairs infection by influenza and Zika virus and cellular stress pathways.

The deacetylase HDAC6 has tandem catalytic domains and a zinc finger domain (ZnF) binding ubiquitin (Ub). While the catalytic domain has an antiviral effect, the ZnF facilitates influenza A virus (IAV) infection and cellular stress responses. By recruiting Ub via the ZnF, HDAC6 promotes the formation of aggresomes and stress granules (SGs), dynamic structures associated with pathologies such as neurodegeneration. IAV subverts the aggresome/HDAC6 pathway to facilitate capsid uncoating during early infection. To target this pathway, we generate designed ankyrin repeat proteins (DARPins) binding the ZnF; one of these prevents interaction with Ub in vitro and in cells. Crystallographic analysis shows that it blocks the ZnF pocket where Ub engages. Conditional expression of this DARPin reversibly impairs infection by IAV and Zika virus; moreover, SGs and aggresomes are downregulated. These results validate the HDAC6 ZnF as an attractive target for drug discovery

White-light phosphorescence emission from a single molecule: application to OLED

A simple mononuclear cyclometallated iridium(III) complex exhibits white photo- and electro- luminescence in the wavelength range from 440 to 800 nm, which originates from a single emitting excited state of mixed character.Bolink Henk, [email protected] ; Coronado Miralles, Eugenio, [email protected]

The spike gene is a major determinant for the SARS-CoV-2 Omicron-BA. 1 phenotype

Variant of concern (VOC) Omicron-BA.1 has achieved global predominance in early 2022. Therefore, surveillance and comprehensive characterization of Omicron-BA.1 in advanced primary cell culture systems and animal models are urgently needed. Here, we characterize Omicron-BA.1 and recombinant Omicron-BA.1 spike gene mutants in comparison with VOC Delta in well-differentiated primary human nasal and bronchial epithelial cells in vitro, followed by in vivo fitness characterization in hamsters, ferrets and hACE2-expressing mice, and immunized hACE2-mice. We demonstrate a spike-mediated enhancement of early replication of Omicron-BA.1 in nasal epithelial cultures, but limited replication in bronchial epithelial cultures. In hamsters, Delta shows dominance over Omicron-BA.1, and in ferrets Omicron-BA.1 infection is abortive. In hACE2-knock-in mice, Delta and a Delta spike clone also show dominance over Omicron-BA.1 and an Omicron-BA.1 spike clone, respectively. Interestingly, in naïve K18-hACE2 mice, we observe Delta spike-mediated increased replication and pathogenicity and Omicron-BA.1 spike-mediated reduced replication and pathogenicity, suggesting that the spike gene is a major determinant of replication and pathogenicity. Finally, the Omicron-BA.1 spike clone is less well-controlled by mRNA-vaccination in K18-hACE2-mice and becomes more competitive compared to the progenitor and Delta spike clones, suggesting that spike gene-mediated immune evasion is another important factor that led to Omicron-BA.1 dominance

The spike gene is a major determinant for the SARS-CoV-2 Omicron-BA.1 phenotype.

Variant of concern (VOC) Omicron-BA.1 has achieved global predominance in early 2022. Therefore, surveillance and comprehensive characterization of Omicron-BA.1 in advanced primary cell culture systems and animal models are urgently needed. Here, we characterize Omicron-BA.1 and recombinant Omicron-BA.1 spike gene mutants in comparison with VOC Delta in well-differentiated primary human nasal and bronchial epithelial cells in vitro, followed by in vivo fitness characterization in hamsters, ferrets and hACE2-expressing mice, and immunized hACE2-mice. We demonstrate a spike-mediated enhancement of early replication of Omicron-BA.1 in nasal epithelial cultures, but limited replication in bronchial epithelial cultures. In hamsters, Delta shows dominance over Omicron-BA.1, and in ferrets Omicron-BA.1 infection is abortive. In hACE2-knock-in mice, Delta and a Delta spike clone also show dominance over Omicron-BA.1 and an Omicron-BA.1 spike clone, respectively. Interestingly, in naïve K18-hACE2 mice, we observe Delta spike-mediated increased replication and pathogenicity and Omicron-BA.1 spike-mediated reduced replication and pathogenicity, suggesting that the spike gene is a major determinant of replication and pathogenicity. Finally, the Omicron-BA.1 spike clone is less well-controlled by mRNA-vaccination in K18-hACE2-mice and becomes more competitive compared to the progenitor and Delta spike clones, suggesting that spike gene-mediated immune evasion is another important factor that led to Omicron-BA.1 dominance

The African Stopwords project:curating stopwords for African languages

Stopwords are fundamental in Natural Language Processing (NLP) techniques for information retrieval. One of the common tasks in preprocessing of text data is the removal of stopwords. Currently, while high-resource languages like English benefit from the availability of several stopwords, low-resource languages, such as those found in the African continent, have none that are standardized and available for use in NLP packages. Stopwords in the context of African languages are understudied and can reveal information about the crossover between languages. The \textit{African Stopwords} project aims to study and curate stopwords for African languages. In this paper, we present our current progress on ten African languages as well as future plans for the project