Predicting multiple functions of sustainable flood retention basins under uncertainty via multi-instance multi-label learning

The ambiguity of diverse functions of sustainable flood retention basins (SFRBs) may lead to conflict and risk in water resources planning and management. How can someone provide an intuitive yet efficient strategy to uncover and distinguish the multiple potential functions of SFRBs under uncertainty? In this study, by exploiting both input and output uncertainties of SFRBs, the authors developed a new data-driven framework to automatically predict the multiple functions of SFRBs by using multi-instance multi-label (MIML) learning. A total of 372 sustainable flood retention basins, characterized by 40 variables associated with confidence levels, were surveyed in Scotland, UK. A Gaussian model with Monte Carlo sampling was used to capture the variability of variables (i.e., input uncertainty), and the MIML-support vector machine (SVM) algorithm was subsequently applied to predict the potential functions of SFRBs that have not yet been assessed, allowing for one basin belonging to different types (i.e., output uncertainty). Experiments demonstrated that the proposed approach enables effective automatic prediction of the potential functions of SFRBs (e.g., accuracy >93%). The findings suggest that the functional uncertainty of SFRBs under investigation can be better assessed in a more comprehensive and cost-effective way, and the proposed data-driven approach provides a promising method of doing so for water resources management

Is More, Better? Relationships of Multiple Psychological Well-Being Facets with Cardiometabolic Disease

Objective: Cardiometabolic disease (CMD) is a leading cause of death and disability worldwide. Assessments of psychological well-being taken at one time point are linked to reduced cardiometabolic risk, but psychological well-being may change over time and how longitudinal trajectories of psychological well-being may be related to CMD risk remains unclear. Furthermore, psychological well-being is a multidimensional construct comprised of distinct facets, but no work has examined whether sustaining high levels of multiple facets may confer additive protection. This study tested if trajectories of four psychological well-being facets would be associated with lower risk of self-reported nonfatal CMD. Method: Participants were 4,006 adults aged ≥50 years in the English Longitudinal study of Ageing followed for 18 years at biyearly intervals. Psychological well-being facets were measured in Waves 1–5 using subscales of the Control, Autonomy, Satisfaction, and Pleasure scale. Latent class growth modeling defined trajectories of each facet. Incident CMD cases were self-reported at Waves 6–9. Cox regression models estimated likelihood of incident CMD associated with trajectories of each facet individually and additively (i.e., having persistently high levels on multiple facets over time). Results: After adjusting for relevant covariates, CMD risk was lower for adults with persistently high versus persistently low levels of control and autonomy. When considering potential additive effects, lower CMD risk was also related to experiencing persistently high levels of ≥2 versus 0 psychological well-being facets. Conclusions: Findings suggest having and sustaining multiple facets of psychological well-being is beneficial for cardiometabolic health, and that effects may be additive

Use of routine health information systems to monitor disruptions of coverage of maternal, newborn, and child health services during COVID-19: A scoping review.

BACKGROUND: The COVID-19 pandemic is a unique global health challenge which disrupted essential health services (EHS). Most early data related to EHS during the COVID-19 pandemic came from country and regional "pulse" surveys conducted by the World Health Organization (WHO) and United Nations Children's Fund (UNICEEF), which relied on respondent perceptions and not necessarily routine health information system (RHIS) data. By conducting a scoping review, we aimed to describe the use of RHIS data for monitoring changes in EHS coverage for maternal, newborn, and child health (MNCH) during the COVID-19 pandemic. METHODS: We performed a scoping review using Sample, Phenomenon of Interest, Design, Evaluation, Research type (SPIDER) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Scoping Review (PRISMA-SCR) guidelines. We included descriptive or analytic reports on the availability and use of RHIS data published in peer-reviewed, pre-publication, or gray literature on MNCH essential health services coverage during the COVID-19 pandemic. The following databases were searched for studies published between January 2020 and May 2022: PubMed/MEDLINE, Google Scholar, Google, MedRXiv (pre-publication), Embase, CINAHL, Cochrane, Campbell, and OpenGrey. A single reviewer screened the titles, abstracts, and full texts of the retrieved publications, while a second reviewer screened 20% of the total sample. Publications were tabulated by WHO Region, World Bank income group, country, data sources, study topic, and period. We used content analysis to qualitatively describe the trends and use of data for policy or programming in the studies. RESULTS: We included 264 publications after the full-text review. The publications came from 81 countries, covering all WHO regions and World Bank income groups. The most common data sources were hospital information systems (27%) and primary health care management information systems (26%). Most studies examined data trends before COVID-19 compared to periods during COVID-19. Most publications reported a decrease in MNCH services (45%). Reports with follow-up beyond August 2020 (first six months of pandemic) were significantly more likely to report recovery of service coverage (8% vs 30%, P < 0.001). Low- and middle-income countries reported significantly higher morbidity and/or mortality in COVID-19 periods than high-income countries (54% vs 30%, P < 0.001). Less than 10% of reports described RHIS data quality specifically during the COVID-19 period and only 22% reported program mitigation strategies to address reductions noted from routine data. CONCLUSION: Results suggest awareness and usefulness of RHIS to monitor MNCH service disruptions during the COVID-19 pandemic. However, with only 22% of reports including descriptions of policy or program adaptations, use of RHIS data to monitor MNCH service disruptions was not necessarily followed by data-informed policies or program adaptations. RHIS data on MNCH services should be strengthened to enable its use by program managers and policymakers to respond to direct and indirect effects of future public health emergencies. REGISTRATION: Open Science Framework (available at: https://osf.io/usqp3/?view_only=94731785fcba4377adfa1bdf5754998d)

Cell-specific synaptic plasticity induced by network oscillations

Gamma rhythms are known to contribute to the process of memory encoding. However, little is known about the underlying mechanisms at the molecular, cellular and network levels. Using local field potential recording in awake behaving mice and concomitant field potential and whole-cell recordings in slice preparations we found that gamma rhythms lead to activity-dependent modification of hippocampal networks, including alterations in sharp wave- ripple complexes. Network plasticity, expressed as long-lasting increases in sharp wave-associated synaptic currents, exhibits enhanced excitatory synaptic strength in pyramidal cells that is induced postsynaptically and depends on metabotropic glutamate receptor-5 activation. In sharp contrast, alteration of inhibitory synaptic strength is independent of postsynaptic activation and less pronounced. Further, we found a cell type-specific, directionally biased synaptic plasticity of two major types of GABAergic cells, parvalbumin- and cholecystokinin-expressing interneurons. Thus, we propose that gamma frequency oscillations represent a network state that introduces long-lasting synaptic plasticity in a cell-specific manner

Combining mass spectrometry and genetic labeling in mice to report TRP channel expression

Transient receptor potential (TRP) ion channels play important roles in fundamental biological processes throughout the body of humans and mice. TRP channel dysfunction manifests in different disease states, therefore, these channels may represent promising therapeutic targets in treating these conditions. Many TRP channels are expressed in several organs suggesting multiple functions and making it challenging to untangle the systemic pathophysiology of TRP dysfunction. Detailed characterization of the expression pattern of the individual TRP channels throughout the organism is thus essential to interpret data such as those derived from systemic phenotyping of global TRP knockout mice. Murine TRP channel reporter strains enable reliable labeling of TRP expression with a fluorescent marker. Here we present an optimized method to visualize primary TRP-expressing cells with single cell resolution throughout the entire organism. In parallel, we methodically combine systemic gene expression profiling with an adjusted mass spectrometry protocol to document acute protein levels in selected organs of interest. The TRP protein expression data are then correlated with the GFP reporter expression data. The combined methodological approach presented here can be adopted to generate expression data for other genes of interest and reporter mice. • We present an optimized method to systemically characterize gene expression in fluorescent reporter mouse strains with a single cell resolution. • We methodically combine systemic gene expression profiling with an adjusted mass spectrometry protocol to document acute protein levels in selected organs of interest in mice

Public trust in the Government to control the spread of COVID-19 in England after the first wave-a longitudinal analysis.

BACKGROUND: To control the spread of coronavirus disease 2019 (COVID-19), governments are increasingly relying on the public to voluntarily manage risk. Effectiveness is likely to rely in part on how much the public trusts the Government's response. We examined the English public's trust in the Conservative Government to control the spread of COVID-19 after the initial 'crisis' period. METHODS: We analyzed eight rounds of a longitudinal survey of 1899 smartphone users aged 18-79 in England between October 2020 and December 2021. We fitted a random-effects logit model to identify personal characteristics and opinions associated with trust in the Conservative Government to control the spread of COVID-19. RESULTS: Trust was lowest in January 2021 (28%) and highest in March 2021 (44%). Being older, having lower educational attainment and aligning with the Conservative Party were predictors of higher levels of trust. Conversely, being less deprived, reporting that Government communications were not clear and considering that the measures taken by the Government went too far or not far enough were predictors of being less likely to report a great deal or a fair amount of trust in the Government to control the pandemic. CONCLUSION: Trust in the Government's response was found to be low throughout the study. Our findings suggest that there may be scope to avoid losing trust by aligning Government actions more closely with scientific advice and public opinion, and through clearer public health messaging. However, it remains unclear whether and how higher trust in the Government's response would increase compliance with Government advice

Low-level developmental lead exposure does not predispose to adult alcohol self-administration, but does increase the risk of relapsing to alcohol seeking in mice: Contrasting role of GLT1 and xCT brain expression

Lead (Pb) is a neurotoxic heavy metal pollutant. Despite the efforts to reduce Pb environmental exposure and to prevent Pb poisoning, exposure in human populations persists. Studies of adults with history of childhood lead exposure have consistently demonstrated cognitive impairments that have been associated with sustained glutamate signaling. Additionally, some clinical studies have also found correlations between Pb exposure and increased proclivity to drug addiction. Thus, here we sought to investigate if developmental Pb exposure can increase propensity to alcohol consumption and relapse using an alcohol self-administration paradigm. Because Pb exposure is associated with increased glutamatergic tone, we also studied the effects on the expression of synaptic and non-synaptic glutamate transporters in brain regions associated with drug addiction such as the nucleus accumbens (NAc), dorsomedial striatum (DMS), dorsolateral striatum (DLS), and medial prefrontal cortex (mPFC). We found that while developmental Pb exposure did not increase risk for alcohol self-administration, it did play a role in relapsing to alcohol. The effects were associated with differential expression of the glutamate transporter 1 (GLT1) and the glutamate/cystine antiporter (xCT). In the NAc and DLS the expression of GLT1 was found to be significantly reduced, while no changes were found in DMS or mPFC. Contrastingly, xCT was found to be upregulated in NAc but downregulated in DLS, with no changes in DMS or mPFC. Our data suggest that lead exposure is involved in relapse to alcohol seeking, an effect that could be associated with downregulation of GLT1 and xCT in the DLS