In 2019/2020, the emergence of coronavirus disease 2019 (COVID-19) resulted in rapid increases in infection rates as well as patient mortality. Treatment options addressing COVID-19 included drug repurposing, investigational therapies such as remdesivir, and vaccine development. Combination therapy based on drug repurposing is among the most widely pursued of these efforts. Multi-drug regimens are traditionally designed by selecting drugs based on their mechanism of action. This is followed by dose-finding to achieve drug synergy. This approach is widely-used for drug development and repurposing. Realizing synergistic combinations, however, is a substantially different outcome compared to globally optimizing combination therapy, which realizes the best possible treatment outcome by a set of candidate therapies and doses toward a disease indication. To address this challenge, the results of Project IDentif.AI (Identifying Infectious Disease Combination Therapy with Artificial Intelligence) are reported. An AI-based platform is used to interrogate a massive 12 drug/dose parameter space, rapidly identifying actionable combination therapies that optimally inhibit A549 lung cell infection by vesicular stomatitis virus within three days of project start. Importantly, a sevenfold difference in efficacy is observed between the top-ranked combination being optimally and sub-optimally dosed, demonstrating the critical importance of ideal drug and dose identification. This platform is disease indication and disease mechanism-agnostic, and potentially applicable to the systematic N-of-1 and population-wide design of highly efficacious and tolerable clinical regimens. This work also discusses key factors ranging from healthcare economics to global health policy that may serve to drive the broader deployment of this platform to address COVID-19 and future pandemics.

Background While hand, foot and mouth disease (HFMD) is primarily self-resolving—soaring incidence rate of symptomatic HFMD effectuates economic burden in the Asia-Pacific region. Singapore has seen a conspicuous rise in the number of HFMD cases from 2010s. Here, we aims to identify the serology and genotypes responsible for such outbreaks in hospitals and childcare facilities. Methods We studied symptomatic paediatric HFMD cases from 2013 to 2018 in Singapore. Surveillance for subclinical enterovirus infections was also performed in childcares at the same time period. Results Genotyping 101 symptomatic HFMD samples revealed CV-A6 as the major etiological agent for recent outbreaks. We detected infections with CV-A6 (41.0%), EV-A71 (7%), CV-A16 (3.0%), coxsackievirus A2, CV-A2 (1.0%) and coxsackievirus A10, CV-A10 (1.0%). Phylogenetic analysis of local CV-A6 strains revealed a high level of heterogeneity compared against others worldwide, dissimilar to other HFMD causative enteroviruses for which the dominant strains and genotypes are highly region specific. We detected sub-clinical enterovirus infections in childcare centres; 17.1% (n = 245) tested positive for enterovirus in saliva, without HFMD indicative symptoms at the point of sample collection. Conclusions CV-A6 remained as the dominant HFMD causative strain in Singapore. Silent subclinical enteroviral infections were detected and warrant further investigations.

AimTo gain insight into the presence of islet cell autoimmunity in an ethnic Asian compared with a white European population.MethodsFor this cross‐sectional study we recruited people with adult‐onset diabetes (age of diagnosis 20–60 years), at tertiary referral centres in Germany (n=1020) and Singapore (n=1088). Glutamic acid decarboxylase and islet antigen 2 antibodies were measured according to Islet Autoantibody Standardization Program protocols.ResultsThe prevalence of glutamic acid decarboxylase antibody positivity was 13.9% (95% CI 12.1–16.0; P<0.001) in the white European cohort compared with 6.8% (95% CI 5.5–8.4; P<0.001) in the Asian cohort. Glutamic acid decarboxylase antibody positivity was 11.4% (95% CI 7.7–16.6) in Indian, 6.0% (95% CI 3.6–9.9) in Malay and 5.8% (95% CI 4.3–7.7; P<0.001) in Chinese participants. In the white European participants, the prevalence of islet antigen 2 antibody positivity was 7.8% (95% CI 6.4–9.4) compared with 14.8% (95% CI 12.8–17.0; P<0.001) in the Asian cohort as a whole, and among the three ethnicities in the Asian cohort it was 12.4% (95% CI 8.6–17.7) in Indian, 16.8% (95% CI 12.6–22.2) in Malay and 15.7% (95% CI 13.2–18.6) in Chinese participants. Double antibody positivity was seen in 5.7% (95% CI 4.5–7.1) of white European participants compared with 1.6% (95% CI 1.0–2.5; P<0.01) of Asian participants. In the white European cohort, those who were glutamic acid decarboxylase autoantibody‐positive had a lower BMI than those who were autoantibody‐negative, but this trend was absent in the Asian cohort.ConclusionsA marked prevalence of islet cell autoimmunity was observed in people with adult‐onset diabetes. While glutamic acid decarboxylase antibodies were more frequent in the European cohort, islet antigen 2 antibody positivity was highest in the three ethnic groups in Singapore, suggesting ethnic‐specific differences in antibody profiles.

Ageing-related delays and dysregulated inflammation in wound healing are well-documented in both human and animal models. However, cellular and molecular changes underlying this impairment in healing progression are not fully understood. In this study, we characterised ageing-associated changes to macrophages in wounds of young and aged mice and investigated transcriptomic differences that may impact the progression of wound healing. Full-thickness wounds created on the dorsum of C57BL/6J young and aged mice were excised on Days 3 and 7 post-wounding for analysis by immunohistochemistry, flow cytometry, and RNA sequencing. Our data revealed that macrophages were significantly reduced in aged wounds in comparison to young. Functional transcriptomic analyses showed that macrophages from aged wounds exhibited significantly reduced expression of cell cycle, DNA replication, and repair pathway genes. Furthermore, we uncovered an elevated pro-inflammatory gene expression program in the aged macrophages correlated with poor inflammation resolution and excessive tissue damage observed in aged wounds. Altogether, our work provides insights into how poorly healing aged wounds are phenotypically defined by the presence of macrophages with reduced proliferative capacity and an exacerbated inflammatory response, both of which are pathways that can be targeted to improve healing in the elderly.

The mammalian epidermis undergoes constant renewal replenished by a pool of stem cells and terminal differentiation of their progeny. This is accompanied by changes in gene expression and morphology orchestrated, in part, by epigenetic modifiers. Here, we defined the role of histone acetyltransferase KAT2A in epidermal homeostasis and provided a comparative analysis that revealed key functional divergence with its paralogue, KAT2B. In contrast to KAT2B's reported function in epidermal differentiation, KAT2A supports the undifferentiated state in keratinocytes. RNA-seq analysis of KAT2A- and KAT2B- depleted keratinocytes revealed dysregulated epidermal differentiation. Depletion of KAT2A led to premature expression of epidermal differentiation genes in the absence of inductive signals, whilst loss of KAT2B delayed differentiation. KAT2A acetyltransferase activity was indispensable in regulating epidermal differentiation gene expression. The metazoan-specific N-terminus of KAT2A was also required to support its function in keratinocytes. We further showed that the interplay between KAT2A- and KAT2B- mediated regulation was important for normal cutaneous wound healing in vivo. Overall, these findings reveal a distinct mechanism in which keratinocytes utilize a pair of highly homologous histone acetyltransferases to support divergent functions in self-renewal and differentiation processes.