Tetrapodal textured Janus textiles for accessible menstrual health.

Menstruating individuals without access to adequate hygiene products often improvise with alternatives that pose health risks and limit their participation in society. We describe here a menstrual hygiene product based on low-cost materials, which are integrated onto fabrics to imbue unidirectional permeability. A body-facing "Janus" fabric top layer comprising ZnO tetrapods spray-coated onto polyester mosquito netting imparts hierarchical texturation, augmenting the micron-scale texturation derived from the weave of the underlying fabric. The asymmetric coating establishes a gradient in wettability, which underpins flash spreading and unidirectional permeability. The hygiene product accommodates a variety of absorptive media, which are sandwiched between the Janus layer and a second outward-facing coated densely woven fabric. An assembled prototype demonstrates outstanding ability to wick saline solutions and a menstrual fluid simulant while outperforming a variety of commercially alternatives. The results demonstrate a versatile menstrual health product that provides a combination of dryness, discretion, washability, and safety.

Mitigation insights from emergency managers on working with stakeholders.

Emergency managers have the important responsibility of planning and implementing mitigation policies and programs to reduce losses to life and property. To accomplish these goals, they must use limited time and resources to ensure the communities they serve have adequately mitigated against potential disasters. As a result, it is common to collaborate and coordinate with a wide variety of partner agencies and community organizations. While it is well established that strengthening relationships and increasing familiarity improve coordination, this article advances that narrative by providing direct insights on the ways a select group of local, state, and federal emergency managers view relationships with other mitigation stakeholders. Using insights from a 1-day workshop hosted at the University of Delaware to gather information from mitigation stakeholders, this article provides a discussion of commonalities and challenges workshop participants identified with other stakeholder groups. These insights can inform other emergency managers about potential collaborators and coordination opportunities with similar stakeholders in their own communities.

Inhibition of LILRB2 by a Novel Blocking Antibody Designed to Reprogram Immunosuppressive Macrophages to Drive T-Cell Activation in Tumors.

Tumor-associated macrophages (TAM) play an important role in maintaining the immunosuppressive state of the tumor microenvironment (TME). High levels of CD163+ TAMs specifically are associated with poor prognosis in many solid tumor types. Targeting TAMs may represent a key approach in development of the next generation of cancer immune therapeutics. Members of the leukocyte immunoglobulin-like receptor B (LILRB) family, including LILRB2 (ILT4), are known to transmit inhibitory signals in macrophages and other myeloid cells. Leveraging bulk and single cell RNA-sequencing datasets, as well as extensive immunophenotyping of human tumors, we found that LILRB2 is highly expressed on CD163+ CD11b+ cells in the TME and that LILRB2 expression correlates with CD163 expression across many tumor types. To target LILRB2, we have developed JTX-8064, a highly potent and selective antagonistic mAb. JTX-8064 blocks LILRB2 binding to its cognate ligands, including classical and nonclassical MHC molecules. In vitro, JTX-8064 drives the polarization of human macrophages and dendritic cells toward an immunostimulatory phenotype. As a result, human macrophages treated with a LILRB2 blocker are reprogrammed to increase the activation of autologous T cells in co-culture systems. Furthermore, JTX-8064 significantly potentiates the activity of anti-PD-1 in allogeneic mixed lymphocyte reaction. In a human tumor explant culture, pharmacodynamic activity of JTX-8064 was observed in monotherapy and in combination with anti-PD-1. Collectively, our work provides strong translational and preclinical rationale to target LILRB2 in cancer.

Structure-Dependent Accessibility of Phonon-Coupled Radiative Relaxation Pathways Probed by X-ray-Excited Optical Luminescence.

Rare-earth scheelites represent a diverse family of compounds with multiple degrees of freedom, which enables the incorporation of a wide range of lanthanide color centers. Precise positioning of quantum objects is attainable by the choice of alkali cations and lattice connectivity of polyanion units. Herein, we report the structure-dependent energy transfer and lattice coupling of optical transitions in La3+- and Dy3+-containing scheelite-type double and quadruple molybdates NaLa1-xDyx(MoO4)2 and Na5La1-xDyx(MoO4)4. X-ray excitation of La3+ core states generates excited-state electron-hole pairs, which, upon thermalizing across interconnected REO8 polyhedra in double molybdates, activate a phonon-coupled excited state of Dy3+. A pronounced luminescence band is observed corresponding to optical cooling of the lattice upon preferential radiative relaxation from a "hot" state. In contrast, combined X-ray absorption near-edge structure and X-ray-excited optical luminescence studies reveal that such a lattice coupling mechanism is inaccessible in quadruple molybdates with a greater separation of La3+-Dy3+ centers.

Halide Replacement with Complete Preservation of Crystal Lattice in Mixed-Anion Lanthanide Oxyhalides.

A challenge in anion control in periodic solids is to preserve the crystal lattice while substituting for different anions of widely varying size and hardness. Post-synthetic modification routes that place cations or anions in non-equilibrium configurations are promising; however, such methods remain relatively unexplored for anion placement. Here, we report the synthesis of LaOI nanocrystals by a non-hydrolytic sol-gel condensation reaction and their transformation into LaOBr, LaOCl, and LaOF nanocrystals along hard-soft acid-base principles using post-synthetic metathesis reactions with ammonium halides. Anion displacement proceeds along halide planes, preserving the tetragonal matlockite structure. Energy-variant X-ray excited optical luminesce signatures of alloyed Tb3+ -ions is a sensitive quantum reporter of the preservation of the cation sublattice and hardening of the crystal structure upon anion replacement.

Navigating the design space of inorganic materials synthesis using statistical methods and machine learning.

Data-driven approaches have brought about a revolution in manufacturing; however, challenges persist in their applications to synthetic strategies. Their application to the deterministic navigation of reaction trajectories to stabilize crystalline solids with precise composition, atomic connectivity, microstructural dimensionality, and surface structure remains a frontier in inorganic materials research. The design of synthetic methodologies for the preparation of inorganic materials is often inefficient in terms of exploration of potentially vast design spaces spanning multiple process variables, reaction sequences, as well as structural parameters and reactivities of precursors and structure-directing agents. Reported synthetic methods are further limited in terms of the insight they provide into underlying chemical and physical principles. The recent surge in interest in accelerating the discovery of new materials can be considered as an opportunity to re-evaluate our approach to materials synthesis, and for considering new frameworks for exploration that are systematic and strategic in approach. Herein, we outline with the help of several illustrative examples, the challenges, opportunities, and limitations of data-driven synthesis design. The account collates discussion of design-of-experiments sampling methods, machine learning modeling, and active learning to develop experimental workflows that accelerate the experimental navigation of synthetic landscapes.

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1-Decision Support System.

This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human-natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program.

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2-Hazard Modeling.

Hurricane track and intensity can change rapidly in unexpected ways, thus making predictions of hurricanes and related hazards uncertain. This inherent uncertainty often translates into suboptimal decision-making outcomes, such as unnecessary evacuation. Representing this uncertainty is thus critical in evacuation planning and related activities. We describe a physics-based hazard modeling approach that (1) dynamically accounts for the physical interactions among hazard components and (2) captures hurricane evolution uncertainty using an ensemble method. This loosely coupled model system provides a framework for probabilistic water inundation and wind speed levels for a new, risk-based approach to evacuation modeling, described in a companion article in this issue. It combines the Weather Research and Forecasting (WRF) meteorological model, the Coupled Routing and Excess STorage (CREST) hydrologic model, and the ADvanced CIRCulation (ADCIRC) storm surge, tide, and wind-wave model to compute inundation levels and wind speeds for an ensemble of hurricane predictions. Perturbations to WRF's initial and boundary conditions and different model physics/parameterizations generate an ensemble of storm solutions, which are then used to drive the coupled hydrologic + hydrodynamic models. Hurricane Isabel (2003) is used as a case study to illustrate the ensemble-based approach. The inundation, river runoff, and wind hazard results are strongly dependent on the accuracy of the mesoscale meteorological simulations, which improves with decreasing lead time to hurricane landfall. The ensemble envelope brackets the observed behavior while providing "best-case" and "worst-case" scenarios for the subsequent risk-based evacuation model.

A prospective study of consecutive emergency medical admissions to compare a novel automated computer-aided mortality risk score and clinical judgement of patient mortality risk.

OBJECTIVES: To compare the performance of a validated automatic computer-aided risk of mortality (CARM) score versus medical judgement in predicting the risk of in-hospital mortality for patients following emergency medical admission. DESIGN: A prospective study. SETTING: Consecutive emergency medical admissions in York hospital. PARTICIPANTS: Elderly medical admissions in one ward were assigned a risk of death at the first post-take ward round by consultant staff over a 2-week period. The consultant medical staff used the same variables to assign a risk of death to the patient as the CARM (age, sex, National Early Warning Score and blood test results) but also had access to the clinical history, examination findings and any immediately available investigations such as ECGs. The performance of the CARM versus consultant medical judgement was compared using the c-statistic and the positive predictive value (PPV). RESULTS: The in-hospital mortality was 31.8% (130/409). For patients with complete blood test results, the c-statistic for CARM was 0.75 (95% CI: 0.69 to 0.81) versus 0.72 (95% CI: 0.66 to 0.78) for medical judgements (p=0.28). For patients with at least one missing blood test result, the c-statistics were similar (medical judgements 0.70 (95% CI: 0.60 to 0.81) vs CARM 0.70 (95% CI: 0.59 to 0.80)). At a 10% mortality risk, the PPV for CARM was higher than medical judgements in patients with complete blood test results, 62.0% (95% CI: 51.2 to 71.9) versus 49.2% (95% CI: 39.8 to 58.5) but not when blood test results were missing, 50.0% (95% CI: 24.7 to 75.3) versus 53.3% (95% CI: 34.3 to 71.7). CONCLUSIONS: CARM is comparable with medical judgements in discriminating in-hospital mortality following emergency admission to an elderly care ward. CARM may have a promising role in supporting medical judgements in determining the patient's risk of death in hospital. Further evaluation of CARM in routine practice is required.

BDNF infusion into the MPN mag is sufficient to restore copulatory behavior in the castrated Syrian hamster.

Testosterone plays a key role in the expression of male sex behavior by influencing cellular activity and synapses within the magnocellular medial preoptic nucleus (MPN mag), a sub-nucleus of the medial preoptic area (MPOA) in the Syrian hamster. Although the mechanisms underlying hormonally-induced synaptic plasticity in this region remain elusive, the data suggests that an increase in synaptic density may mediate testosterone's effects on copulation. As brain derived neurotrophic factor (BDNF) plays an integral role in regulating synaptic plasticity and gonadal steroids regulate the levels of BDNF, we hypothesize that BDNF may mediate the effects of gonadal hormones on copulatory behavior. To test this hypothesis, we infused BDNF or controls into the MPN mag of long-term castrates. Our results indicate that BDNF, but not the controls, restored copulatory behavior in castrated male Syrian hamsters. Furthermore, the rise of BDNF expression in the MPOA preceded the rise of synaptophysin following testosterone replacement in castrated males. These data are consistent with our hypothesis, implicating a role for BDNF in mediating testosterone's action on copulation and suggest that the delay in testosterone's restoration of copulation is, in part, due to the delay in the increase of BDNF and synaptophysin.

Implementation and evolution of a regional chronic disease self-management program.

OBJECTIVE: To establish a comprehensive, community-based program to improve and sustain self-management support for individuals with chronic diseases and complement office-based strategies to support behaviour change. PARTICIPANTS: Health service delivery organizations. SETTING: The Champlain Local Health Integration Network (LHIN), a health district in Eastern Ontario. INTERVENTION: We created Living Healthy Champlain (LHC), a regional organization providing peer leader training and coordination for the group Stanford Chronic Disease Self-Management Program (CDSMP); skills training and mentorship in behaviour change approaches for health care providers; and support to organizations to integrate self-management support into routine practice. We used the RE-AIM framework to evaluate the overall program's impact by exploring its reach, effectiveness, adoption, implementation and maintenance. OUTCOME: A total of 232 Stanford CDSMP sessions (63 during the pilot project and 169 post-pilot) have been held at 127 locations in 24 cities across the Champlain LHIN, reaching approximately 4,000 patients. The effectiveness of the service was established through ongoing evidence reviews, a focus group and a pre-post utilization study of the pilot. LHC trained over 300 peer volunteers to provide the Stanford CDSMP sessions, 98 of whom continue to activelyhost workshops. An additional 1,327 providers have been trained in other models of self-management support, such as Health Coaching and Motivational Interviewing. Over the study period, LHC grew from a small pilot project to a regional initiative with sustainable provincial funding and was adopted by the province as a model for similar service delivery across Ontario. CONCLUSION: A community-based self-management program working in partnership with primary care can be effectively and broadly implemented in support of patients living with chronic conditions.

Statistical Modeling of Fire Occurrence Using Data from the Tohoku, Japan Earthquake and Tsunami.

In this article, we develop statistical models to predict the number and geographic distribution of fires caused by earthquake ground motion and tsunami inundation in Japan. Using new, uniquely large, and consistent data sets from the 2011 Tohoku earthquake and tsunami, we fitted three types of models-generalized linear models (GLMs), generalized additive models (GAMs), and boosted regression trees (BRTs). This is the first time the latter two have been used in this application. A simple conceptual framework guided identification of candidate covariates. Models were then compared based on their out-of-sample predictive power, goodness of fit to the data, ease of implementation, and relative importance of the framework concepts. For the ground motion data set, we recommend a Poisson GAM; for the tsunami data set, a negative binomial (NB) GLM or NB GAM. The best models generate out-of-sample predictions of the total number of ignitions in the region within one or two. Prefecture-level prediction errors average approximately three. All models demonstrate predictive power far superior to four from the literature that were also tested. A nonlinear relationship is apparent between ignitions and ground motion, so for GLMs, which assume a linear response-covariate relationship, instrumental intensity was the preferred ground motion covariate because it captures part of that nonlinearity. Measures of commercial exposure were preferred over measures of residential exposure for both ground motion and tsunami ignition models. This may vary in other regions, but nevertheless highlights the value of testing alternative measures for each concept. Models with the best predictive power included two or three covariates.

Modeling insurer-homeowner interactions in managing natural disaster risk.

The current system for managing natural disaster risk in the United States is problematic for both homeowners and insurers. Homeowners are often uninsured or underinsured against natural disaster losses, and typically do not invest in retrofits that can reduce losses. Insurers often do not want to insure against these losses, which are some of their biggest exposures and can cause an undesirably high chance of insolvency. There is a need to design an improved system that acknowledges the different perspectives of the stakeholders. In this article, we introduce a new modeling framework to help understand and manage the insurer's role in catastrophe risk management. The framework includes a new game-theoretic optimization model of insurer decisions that interacts with a utility-based homeowner decision model and is integrated with a regional catastrophe loss estimation model. Reinsurer and government roles are represented as bounds on the insurer-insured interactions. We demonstrate the model for a full-scale case study for hurricane risk to residential buildings in eastern North Carolina; present the results from the perspectives of all stakeholders-primary insurers, homeowners (insured and uninsured), and reinsurers; and examine the effect of key parameters on the results.

Quantitative assessment of post-disaster housing recovery: a case study of Punta Gorda, Florida, after Hurricane Charley.

Quantitative assessment of post-disaster housing recovery is critical to enhancing understanding of the process and improving the decisions that shape it. Nevertheless, few comprehensive empirical evaluations of post-disaster housing recovery have been conducted, and no standard measurement methods exist. This paper presents a quantitative assessment of housing recovery in Punta Gorda, Florida, United States, following Hurricane Charley of August 2004, including an overview of the phases of housing recovery, progression of recovery over time, alternative trajectories of recovery, differential recovery, incorporation of mitigation, and effect on property sales. The assessment is grounded in a conceptual framework that considers the recovery of both people and place, and that emphasises recovery as a process, not as an endpoint. Several data sources are integrated into the assessment--including building permits, remotely sensed imagery, and property appraiser data--and their strengths and limitations are discussed with a view to developing a standardised method for measuring and monitoring housing recovery.

Using focus groups for program planning and evaluation.

School nurses often find themselves developing health-related programs for children and adolescents. One way to create compelling and interesting programs that meet the needs of students is to include them in the planning, development, and evaluation of such programs through focus groups. Children provide a perspective about their particular needs, interests, and understandings that cannot be obtained from adults or health care professionals. When children take part in program planning, the programs become more appealing to children because of the feedback from their perspective. This article describes ways focus groups can be used to examine the effectiveness and usability of health-related programs. Included is a discussion of the pros and cons of using focus groups with school-age children for planning and evaluating programs and guidelines for conducting focus groups.

Application of a regional hurricane wind risk forecasting model for wood-frame houses.

Hurricane wind risk in a region changes over time due to changes in the number, type, locations, vulnerability, and value of buildings. A model was developed to quantitatively estimate changes over time in hurricane wind risk to wood-frame houses (defined in terms of potential for direct economic loss), and to estimate how different factors, such as building code changes and population growth, contribute to that change. The model, which is implemented in a simulation, produces a probability distribution of direct economic losses for each census tract in the study region at each time step in the specified time horizon. By changing parameter values and rerunning the analysis, the effects of different changes in the built environment on the hurricane risk trends can be estimated and the relative effectiveness of hypothetical mitigation strategies can be evaluated. Using a case study application for wood-frame houses in selected counties in North Carolina from 2000 to 2020, this article demonstrates how the hurricane wind risk forecasting model can be used: (1) to provide insight into the dynamics of regional hurricane wind risk-the total change in risk over time and the relative contribution of different factors to that change, and (2) to support mitigation planning. Insights from the case study include, for example, that the many factors contributing to hurricane wind risk for wood-frame houses interact in a way that is difficult to predict a priori, and that in the case study, the reduction in hurricane losses due to vulnerability changes (e.g., building code changes) is approximately equal to the increase in losses due to building inventory growth. The potential for the model to support risk communication is also discussed.