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Pathways to strengthening the epidemic intelligence workforce
No full textThe evolving landscape of public health surveillance demands a proficient and diverse workforce adept in data science and analysis. This report summarises discussions from the third session of the WHO Pandemic and Epidemic Intelligence Innovation Forum, focusing on workforce readiness and technological advancements in epidemic intelligence. The forum emphasizes the necessity of multidisciplinary surveillance teams equipped with advanced data skills. Digital tools play a transformative role in data collection and analysis, enabling real-time tracking, integration, and interpretation of diverse data sources. However, effective surveillance relies on inclusive representation and skill development. Collaborative surveillance and interdisciplinary training programs were emphasized as critical pathways to enhance workforce capacity, decision-making, and equity in public health. Case studies from Nigeria, Korea, the UK, and Colombia showcase the role of digital tools and contextual expertise in addressing surveillance gaps. Sustained institutional support, cross-sector partnerships, and investments in data literacy and workforce development are pivotal for creating resilient and inclusive public health systems
Combinatorial prediction of therapeutic perturbations using causally inspired neural networks
No full textPhenotype-driven approaches identify disease-counteracting compounds by analysing the phenotypic signatures that distinguish diseased from healthy states. Here we introduce PDGrapher, a causally inspired graph neural network model that predicts combinatorial perturbagens (sets of therapeutic targets) capable of reversing disease phenotypes. Unlike methods that learn how perturbations alter phenotypes, PDGrapher solves the inverse problem and predicts the perturbagens needed to achieve a desired response by embedding disease cell states into networks, learning a latent representation of these states, and identifying optimal combinatorial perturbations. In experiments in nine cell lines with chemical perturbations, PDGrapher identifies effective perturbagens in more testing samples than competing methods. It also shows competitive performance on ten genetic perturbation datasets. An advantage of PDGrapher is its direct prediction, in contrast to the indirect and computationally intensive approach common in phenotype-driven models. It trains up to 25× faster than existing methods, providing a fast approach for identifying therapeutic perturbations and advancing phenotype-driven drug discovery
On the fracture mechanics validity of small scale tests
No full textThere is growing interest in conducting small-scale tests to gain additional insight into the fracture behaviour of components across a wide range of materials. For example, micro-scale mechanical tests inside of a microscope (in situ) enable direct, high-resolution observation of the interplay between crack growth and microstructural phenomena (e.g., dislocation behaviour or the fracture resistance of a particular interface), and sub-size samples are increasingly used when only a limited amount of material is available. However, to obtain quantitative insight and extract relevant fracture parameters, the sample must be sufficiently large for a
- (HRR) or a
-field to exist. We conduct numerical and semi-analytical studies to map the conditions (sample geometry, material) that result in a valid, quantitative fracture experiment. Specifically, for a wide range of material properties, crack lengths and sample dimensions, we establish the maximum value of the
-integral where an HRR field ceases to exist (i.e., the maximum
value at which fracture must occur for the test to be valid,
). Maps are generated to establish the maximum valid
value (
) as a function of yield strength, strain hardening and minimum sample size. These maps are then used to discuss the existing experimental literature and provide guidance on how to conduct quantitative experiments. Finally, our study is particularised to the analysis of metals that have been embrittled due to hydrogen exposure. The response of relevant materials under hydrogen-containing environments are superimposed on the aforementioned maps, determining the conditions that will enable quantitative insight
Structured decision making: a tool for systems insights into the barriers, synergies and co-benefits for urban air quality action
No full textDespite synergies between action for air pollution and action for health, climate and social wellbeing in cities, siloed thinking and the “wicked” nature of urban air pollution limit optimal decision-making. Systems approaches offer opportunities to identify barriers and opportunities for action towards cleaner air, and to bolster solutions that optimize benefits and limit unintended consequences. Structured decision-making was adapted into participatory workshops as an engagement tool to develop systems insights into the barriers and opportunities for clean air action. 24 participants from 15 countries and a mix of non-governmental organizations, academia, public and private sectors partook in an online workshop. The aim was to understand the synergies and conflicts between stakeholders, and to identify the actions that stakeholders believe are feasible and provide co-benefits for climate, health and social wellbeing. Workshops identified “human health and wellbeing”, “equity” and “planetary health and climate” as shared objectives that drive stakeholders’ work. Participants developed over 100 actions to address these objectives. Highlights included the importance of transport and data related solutions, including air quality monitoring, modelling, and transparency. Stakeholders identified collaboration and integrated approaches as co-beneficial, yet they didn’t consider these particularly feasible. We identified a gap between the call for systems approaches and the evidence on how to implement systems thinking in decision-making practice. Structured decision-making enabled co-production and evaluation of objectives and actions, and promoted cross-sectoral networking between participants. It offers potential as a novel tool for engaging stakeholders and integrating systems insights and multisectoral perspectives into solutions to complex “wicked” problems
High prediction skill of decadal tropical cyclone variability in the North Atlantic and East Pacific in the met office decadal prediction system DePreSys4
No full textThe UK Met Office decadal prediction system DePreSys4 shows skill in predicting the number of tropical cyclones (TCs) and TC track density over the eastern Pacific and tropical Atlantic Ocean on the decadal timescale (up to ACC = 0.93 and ACC = 0.83, respectively, as measured by the anomaly correlation coefficient—ACC). The high skill in predicting the number of TCs is related to the simulation of the externally forced response, with internal climate variability also allowing the improvement in prediction skill. The Skill is due to the model’s ability to predict the temporal evolution of surface temperature and vertical wind shear over the eastern Pacific and tropical Atlantic Ocean. We apply a signal-to-noise calibration framework and show that DePreSys4 predicts an increase in the number of TCs over the eastern Pacific and the tropical Atlantic Ocean in the next decade (2023–2030), potentially leading to high economic losses
The C. elegans gustatory receptor homolog LITE-1 is a chemoreceptor required for diacetyl avoidance
No full textThe nematode C. elegans does not have eyes but can respond to aversive UV and blue light stimulation and even distinguish colours. The gustatory receptor homolog LITE-1 was identified in forward genetic screens for worms that failed to respond to blue light stimulation. When LITE-1 is expressed in body-wall muscles, it causes contraction in response to blue light suggesting that LITE-1 is both necessary and sufficient for blue light response. However, the mechanism of blue light sensation has remained elusive (Edwards et al., 2008; Gong et al., 2016; Hanson et al., 2023). Here we show that in addition to light avoidance, LITE-1 is also required for worms’ avoidance of high concentrations of diacetyl, an odorant that is attractive at low concentrations (Sengupta et al., 1996). Like blue light, diacetyl causes muscle contraction in transgenic worms engineered to express LITE-1 in body-wall muscles. These data are consistent with a direct chemoreceptor function for LITE-1 which would make it a multimodal sensor of aversive stimuli. Having small molecule ligands of LITE-1 may help resolve the light sensing mechanism by guiding the search for a chromophore (direct sensation) or photoproducts that activate the receptor (indirect sensation). A recent screen of a panel of worm strains that collectively contained knockouts of all non-essential GPCRs identified a triple mutant that failed to avoid high concentrations of diacetyl (Pu et al., 2023). One of the mutated genes was lite-1. We tested single mutants of several loss-of-function alleles of lite-1 and found they also failed to avoid high concentrations of diacetyl (Fig. 1A). To identify neurons involved in the response to high concentrations of diacetyl, we used calcium imaging to record from 11 pairs of sensory neurons in worms exposed to pulses of diacetyl. The LITE-1-expressing sensory neurons ADL and ASK showed a clear defect in diacetyl response, whereas another LITE-1-expressing neuron ASH showed a normal response (Fig. 1B). The other tested neurons did not show a response to diacetyl (Fig. S1). The normal response to diacetyl in ASH in the absence of LITE-1 is likely due to its expression of SRI-14 which has previously been shown to respond to high concentration diacetyl (Taniguchi et al., 2014). To confirm that these neurons sense the high diacetyl levels directly and that their responses are not a result of synaptic transmission from other neurons, we recorded from unc-13 mutants which are impaired in synaptic activity and found little effect on the ADL and ASK responses (Fig. 1B and Fig. S1), consistent with direct sensation (although not ruling out a role for neural signalling through gap junctions). To test whether LITE-1 is sufficient for a response to high diacetyl concentrations, we used a strain that expresses LITE-1 in body wall muscles (Edwards et al., 2008). This strain has previously been shown to contract upon blue light stimulation. When animals expressing LITE-1 in muscle are exposed to a 1:50 dilution of diacetyl they show a rapid and near complete paralysis whereas wild-type animals continue to swim (Fig. 1C-D). LITE-1-expressing worms also contract (Fig. 1E). These data strongly suggest that LITE-1 is a chemoreceptor. A parsimonious explanation is that diacetyl binds and activates LITE-1. Consistent with this, molecular docking predicts low micromolar affinity for diacetyl binding to LITE-1 in the same binding pocket that was recently identified as a putative chromophore binding site (Hanson et al., 2023) (Fig. 1F). As with blue light sensation, where a photoproduct may activate LITE-1, we have not ruled out a secondary chemical effect such as a diacetyl metabolite activating LITE-1. We next tested whether lite-1 is required for avoidance of other high concentration odorants. Of the seven odorants tested, lite-1 mutants only showed a defective response to 2,3-pentanedione, a closely-related chemical (Fig. 1G). The effect was weaker than that observed for diacetyl, with the worms still avoiding high concentrations of 2,3-pentanedione but more weakly than wild-type animals. While LITE-1 is best known for its role in light sensation in C. elegans, how it senses light is not yet clear. In particular, an indirect mechanism in which light produces photoproducts that activate the channel has not been ruled out and a priori has always seemed plausible given that LITE-1 is similar to gustatory receptors that are known to sense chemicals (Montell, 2009). A direct diacetyl response would make a photoproduct-based mechanism more plausible and may help in identifying photoproducts with similar moieties. Direct and photoproduct light sensing are not mutually exclusive. Based on LITE-1’s predicted structure and its absorption spectrum, it has recently been proposed that UV may be directly sensed while the blue light response may be mediated through a photoproduct (Hanson et al., 2023). Another approach to mechanistic studies our results suggest is the search—through a chemical screen or molecular docking—for a competitive inhibitor of diacetyl. Whether such a putative inhibitor also disrupted blue light response could help narrow down possible mechanisms. We have shown that LITE-1 is required for the avoidance of high concentrations of diacetyl and provide evidence that it is a chemoreceptor specifically activated by diacetyl and a structurally related compound. Diacetyl is an ecologically relevant molecule present in C. elegans’ natural environment that has been hypothesised to be involved in prey-finding since low concentrations produced by lactic acid bacteria on rotting fruit is attractive (Choi et al., 2016). Avoidance of high concentrations of diacetyl may therefore also be ecologically relevant. In this case, LITE-1 has likely evolved to be a multimodal receptor of aversive stimuli akin to other multimodal receptors such as TRPV1, which responds to heat, capsaicin, and acidic pH (Zhang et al., 2023)
A spectral approach to optimal control of the Fokker–Planck equation
No full textIn this letter, we present a spectral optimal control framework for Fokker-Planck equations based on the standard ground state transformation that maps the Fokker-Planck operator to a Schrödinger operator. Our primary objective is to accelerate convergence toward the (unique) steady state. To fulfill this objective, a gradient-based iterative algorithm with Pontryagin’s maximum principle and the Barzilai-Borwein update is developed to compute time-dependent controls. Numerical experiments on two-dimensional ill-conditioned normal distributions and double-well potentials demonstrate that our approach effectively targets slow-decaying modes, thus increasing the spectral gap
Defining treatment-resistant bipolar depression: recommendations from the ISBD Task Force
No full textObjective
Despite the availability of approved treatments, a substantial proportion of patients with bipolar disorder experience treatment-resistant bipolar depression (TRBD), characterized by persistent depressive symptoms unresponsive to standard therapies. However, a universally accepted definition of TRBD is lacking. This consensus document, developed by the International Society for Bipolar Disorders (ISBD) Task Force on TRBD, aims to provide a standardized definition of TRBD to facilitate clinical trials, research, and treatment strategies.
Methods
The Task Force employed a literature review, clinical trials analysis, and expert consensus meetings to define TRBD.
Results
TRBD was defined as the failure to achieve a significant and sustained clinical response after at least two approved and adequately dosed pharmacological treatments, administered for a sufficient duration with treatment adherence. For bipolar I (BD-I) depression, approved treatments included quetiapine (300–600 mg/day for ≥ 8 weeks), lurasidone (20–120 mg/day for ≥ 6 weeks), the combination of olanzapine (6–12 mg/day) and fluoxetine (25–75 mg/day for ≥ 8 weeks), cariprazine (1.5–3 mg/day for ≥ 6 weeks), and lumateperone (42 mg/day for ≥ 6 weeks). For bipolar II (BD-II) depression, approved treatments included quetiapine (300–600 mg/day for ≥ 8 weeks) and lumateperone (42 mg/day for ≥ 6 weeks).
Conclusion
This consensus definition aims to provide clarity for clinical trials, improve consistency in research, and guide treatment approaches and inform regulatory pathways. It represents a foundational step in addressing the unmet needs in TRBD and promoting the development of innovative therapeutic strategies. Future efforts will focus on adapting the definition to better align with real-world clinical challenges and optimize patient care
Practically optimal UAV mission planning under uncertainty
No full textWhile Unmanned Aerial Vehicle (UAV) technologies have transformed industrial applications, the practical utility of current mission planners is limited by oversimplified assumptions about operational costs and spatial constraints. The central challenge remains in developing planners that can effectively handle energy consumption uncertainty and spatial optimization requirements while maintaining computational efficiency for online deployment on resource-constrained platforms. This thesis addresses this gap, focusing on UAV-enabled wireless power transfer and communication, by showing that combining probabilistic energy estimation with spatial-aware approaches enables robust mission planning under real-world operational constraints.
We develop two complementary frameworks. First, to manage energy uncertainty, we formulate an Uncertain and Dynamic Orienteering Problem (UDOP), introducing the Rapid Online Metaheuristic-based Planner (ROMP) that combines first principle analysis and wind field segmentation, and then advancing it with an ADaptive Approach for Probabilistic paThs (ADAPT). This framework employs a Bayesian method for real-time energy consumption estimation, adapting to dynamic factors like wind. Our experimental results demonstrate that ADAPT achieves a 100% mission success rate across all tested scenarios while maintaining comparable solution quality and computation time.
Second, for spatial optimization, we propose the Close Enough Orienteering Problem with non-uniform neighborhoods (CEOP-N) and solve it with the CRaSZe-AntS algorithm. This hybrid metaheuristic features a Randomized Steiner Zone Discretization (RSZD) scheme that identifies overlapped sub-regions for Particle Swarm Optimization (PSO) to refine continuous waypoint positioning, while an Ant Colony System (ACS) optimizes the discrete visiting sequence. Results show CRaSZe-AntS significantly outperforms single-neighborhood strategies, increasing prize collection by an average of 140.44% and reducing computation time by 55.18%. We extend this approach with CRaSZe-AntS-3D to efficiently handle non-convex geometric constraints in air-to-ground communication scenarios, achieving near-optimal solutions with only a 0.38% deviation from the optimal energy cost.Open Acces
Stimulated emission tomography of spontaneous four-wave mixing in plasmonic nanoantennas
No full textWe used stimulated emission tomography (SET) to assess the efficiency of spontaneous four-wave mixing (SFWM) from a plasmonic nanoantenna under pulsed excitation. We characterize the SFWM photon generation rate by measuring stimulated degenerate four-wave mixing. We produce a map of the SFWM joint spectral density that characterizes the biphoton state, which we find has a broad bandwidth due to the absence of phase matching. The joint spectral density retrieval via SET is fast and straightforward compared to traditional coincidence measurements. By calculating the number of stimulating and generated photons along with the frequency mixing efficiency, we have determined the power-independent intrinsic SFWM generation rate to be on the order of 103 photon pairs per second per mW squared per particle, while the power-independent extrinsic generation rate is approximately 1 photon pair per second per mW squared per particle. There is scope to increase the nonlinear response by scaling up to large area metasurfaces using low-loss dielectric materials that would allow the produced photon pairs to exceed background fluorescence. Such an SFWM metasurface could be a potential alternative to parametric down conversion, which requires rarer second-order nonlinear materials that are also challenging to integrate with photonic structures