The use of a multimodal wound matrix to treat a variety of hard-to-heal wounds: a case series surveillance.

OBJECTIVE: This case series examines the use of a multimodal wound matrix (MWM) trialled in a selection of clinical practice settings and on a variety of hard-to-heal wounds. The objective was to evaluate the effects of MWM and its performance in managing such wounds, regardless of clinical setting and ulcer type. METHOD: Treatment of the MWM was conducted by independent wound care practitioners on wounds that were of >4 weeks duration. Treatment was once a week. Assessment was taken after four weeks and at week 12 of the study to assess percentage area reduction (PAR) compared to baseline measurements taken at the first treatment visit. Complete (100%) re-epithelialisation was also recorded. RESULTS: A total of 63 wounds were treated with MWM, and ulcer types were grouped as: diabetic foot ulcers (n=21); venous leg ulcers (n=18); pressure injuries (n=10); and others (n=14). Of the wounds, 78% had 100% re-epithelialisation, with an average PAR of 57% at four weeks and 86% at 12 weeks. The average time to resolution for those wounds that closed was 7.9 weeks. CONCLUSION: Results from this series of independent case studies support the application of MWM to potentially benefit healing in hard-to-heal wounds of different aetiologies of any duration and in a variety of clinical settings.

Climate change exacerbates the environmental impacts of agriculture.

Agriculture's global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture's environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change-reinforcing feedback loop. The challenges raised by climate change underscore the urgent need to transition to sustainable, climate-resilient agricultural systems. This requires investments that both accelerate adoption of proven solutions that provide multiple benefits, and that discover and scale new beneficial processes and food products.

Chitosan-azo dye bioplastics that are reversibly resoluble and recoverable under visible light irradiation.

Biopolymer composite materials were prepared by combining bio-sourced cationic water-soluble chitosan with bi-functional water-soluble anionic azo food dyes amaranth (AMA) or allura red (ALR) as ionic cross-linkers, mixing well in water, and then slow-drying in air. The electrostatically-assembled ionically-paired films showed good long-term stability to dissolution, with no re-solubility in water, and competitive mechanical properties as plastic materials. However, upon exposure of the bioplastics to low power light at sunlight wavelengths and intensities stirring in water, the stable materials photo-disassembled back to their water-soluble and low-toxicity (edible) constituent components, via structural photo-isomerization of the azo ionic crosslinkers. XRD, UV-vis, and IR spectroscopy confirmed that these assemblies are reversibly recoverable and so can in principle represent fully recyclable, environmentally degradable materials triggered by exposure to sunlight and water after use, with full recovery of starting components ready for re-use. A density functional theory treatment of the amaranth azo dye identified a tautomeric equilibrium favouring the hydrazone form and rationalized geometrical isomerization as a mechanism for photo-disassembly. The proof-of-principle suitability of films of these biomaterial composites as food industry packaging was assessed via measurement of mechanical, water and vapour barrier properties, and stability to solvent tests. Tensile strength of the composite materials was found to be 25-30 MPa, with elongation at break 3-5%, in a range acceptable as competitive for some applications to replace oil-based permanently insoluble non-recyclable artificial plastics, as fully recyclable, recoverable, and reusable low-toxicity green biomaterials in natural environmental conditions.

Neutrophil-mediated Inflammatory Plasminogen Degradation, Rather Than High Plasminogen-Activator Inhibitor-1, May Underly Failures and Inefficiencies of Intrapleural Fibrinolysis.

BACKGROUND: Complex pleural space infections often require treatment with multiple doses of intrapleural tissue plasminogen activator (tPA) and deoxyribonuclease, with treatment failure frequently necessitating surgery. Pleural infections are rich in neutrophils, and neutrophil elastase degrades plasminogen, the target substrate of tPA, that is required to generate fibrinolysis. We hypothesized that pleural fluid from patients with pleural space infection would show high elastase activity, evidence of inflammatory plasminogen degradation, and low fibrinolytic potential in response to tPA that could be rescued with plasminogen supplementation. RESEARCH QUESTION: Does neutrophil elastase degradation of plasminogen contribute to intrapleural fibrinolytic failure? STUDY DESIGN AND METHODS: We obtained infected pleural fluid and circulating plasma from hospitalized adults (n = 10) with institutional review board approval from a randomized trial evaluating intrapleural fibrinolytics vs surgery for initial management of pleural space infection. Samples were collected before the intervention and on days 1, 2, and 3 after the intervention. Activity assays, enzyme-linked immunosorbent assays, and Western blot analysis were performed, and turbidimetric measurements of fibrinolysis were obtained from pleural fluid with and without exogenous plasminogen supplementation. Results are reported as median (interquartile range) or number (percentage) as appropriate, with an α value of .05. RESULTS: Pleural fluid elastase activity was more than fourfold higher (P = .02) and plasminogen antigen levels were more than threefold lower (P = .04) than their corresponding plasma values. Pleural fluid Western blot analysis demonstrated abundant plasminogen degradation fragments consistent with elastase degradation patterns. We found that plasminogen activator inhibitor 1 (PAI-1), the native tPA inhibitor, showed high antigen levels before the intervention, but the overwhelming majority of this PAI-1 (82%) was not active (P = .003), and all PAI-1 activity was lost by day 2 after the intervention in patients receiving intrapleural tPA and deoxyribonuclease. Finally, using turbidity clot lysis assays, we found that the pleural fluid of 9 of 10 patients was unable to generate a significant fibrinolytic response when challenged with tPA and that plasminogen supplementation rescued fibrinolysis in all patients. INTERPRETATION: Our findings suggest that inflammatory plasminogen deficiency, not high PAI-1 activity, is a significant contributor to intrapleural fibrinolytic failure. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT03583931; URL: www. CLINICALTRIALS: gov.

Development and validation of the Atri-Risk Conduction Index risk score to predict risk of atrial fibrillation after typical atrial flutter ablation.

BACKGROUND: Identification of patients at risk for atrial fibrillation (AF) after typical atrial flutter (tAFL) ablation is important to guide monitoring and treatment. OBJECTIVE: The purpose of this study was to create and validate a risk score to predict AF after tAFL ablation METHODS: We identified patients who underwent tAFL ablation with no AF history between 2017 and 2022 and randomly allocated to derivation and validation cohorts. We collected clinical variables and measured conduction parameters in sinus rhythm on an electrophysiology recording system (CardioLab, GE Healthcare). Univariate and multivariate logistic regressions (LogR) were used to evaluate association with AF development. RESULTS: A total of 242 consecutive patients (81% male; mean age 66 ± 11 years) were divided into derivation (n =142) and validation (n = 100) cohorts. Forty-two percent developed AF over median follow-up of 330 days. In multivariate LogR (derivation cohort), proximal to distal coronary sinus time (pCS-dCS) ≥70 ms (odds ratio [OR] 16.7; 95% confidence interval [CI] 5.6-49), pCS time ≥36 ms (OR 4.5; 95% CI 1.5-13), and CHADS2-VASc score ≥3 (OR 4.3; 95% CI 1.6-11.8) were independently associated with new AF during follow-up. The Atri-Risk Conduction Index (ARCI) score was created with 0 as minimal and 4 as high-risk using pCS-dCS ≥70 ms = 2 points; pCS ≥36 ms = 1 point; and CHADS2-VASc score ≥3 = 1 point. In the validation cohort, 0% of patients with ARCI score = 0 developed AF, whereas 89% of patients with ARCI score = 4 developed AF. CONCLUSION: We developed and validated a risk score using atrial conduction parameters and clinical risk factors to predict AF after tAFL ablation. It stratifies low-, moderate-, and high-risk patients and may be helpful in individualizing approaches to AF monitoring and anticoagulation.

Novel multi-cluster workflow system to support real-time HPC-enabled epidemic science: Investigating the impact of vaccine acceptance on COVID-19 spread.

We present MacKenzie, a HPC-driven multi-cluster workflow system that was used repeatedly to configure and execute fine-grained US national-scale epidemic simulation models during the COVID-19 pandemic. Mackenzie supported federal and Virginia policymakers, in real-time, for a large number of "what-if" scenarios during the COVID-19 pandemic, and continues to be used to answer related questions as COVID-19 transitions to the endemic stage of the disease. MacKenzie is a novel HPC meta-scheduler that can execute US-scale simulation models and associated workflows that typically present significant big data challenges. The meta-scheduler optimizes the total execution time of simulations in the workflow, and helps improve overall human productivity. As an exemplar of the kind of studies that can be conducted using Mackenzie, we present a modeling study to understand the impact of vaccine-acceptance in controlling the spread of COVID-19 in the US. We use a 288 million node synthetic social contact network (digital twin) spanning all 50 US states plus Washington DC, comprised of 3300 counties, with 12 billion daily interactions. The highly-resolved agent-based model used for the epidemic simulations uses realistic information about disease progression, vaccine uptake, production schedules, acceptance trends, prevalence, and social distancing guidelines. Computational experiments show that, for the simulation workload discussed above, MacKenzie is able to scale up well to 10K CPU cores. Our modeling results show that, when compared to faster and accelerating vaccinations, slower vaccination rates due to vaccine hesitancy cause averted infections to drop from 6.7M to 4.5M, and averted total deaths to drop from 39.4K to 28.2K across the US. This occurs despite the fact that the final vaccine coverage is the same in both scenarios. We also find that if vaccine acceptance could be increased by 10% in all states, averted infections could be increased from 4.5M to 4.7M (a 4.4% improvement) and total averted deaths could be increased from 28.2K to 29.9K (a 6% improvement) nationwide.

The effect of a political crisis on performance of community forests and protected areas in Madagascar.

Understanding the effectiveness of conservation interventions during times of political instability is important given how much of the world's biodiversity is concentrated in politically fragile nations. Here, we investigate the effect of a political crisis on the relative performance of community managed forests versus protected areas in terms of reducing deforestation in Madagascar, a biodiversity hotspot. We use remotely sensed data and statistical matching within an event study design to isolate the effect of the crisis and post-crisis period on performance. Annual rates of deforestation accelerated at the end of the crisis and were higher in community forests than in protected areas. After controlling for differences in location and other confounding variables, we find no difference in performance during the crisis, but community-managed forests performed worse in post-crisis years. These findings suggest that, as a political crisis subsides and deforestation pressures intensify, community-based conservation may be less resilient than state protection.

Tranexamic acid in trauma: After 3 hours from injury, when is it safe and effective to use again?

Tranexamic acid (TXA) has proven mortality benefit if used early after traumatic injury, likely related to a combination of bleeding reduction and other non-bleeding effects. If TXA is given more than 3 h after traumatic injury, there is a significant and paradoxical increased risk of death due to bleeding. TXA has level 1 evidence for use as a bleeding reduction agent in isolated orthopedic operations, but in polytrauma patients undergoing orthopedic operations, it is not clear if and when TXA is safe or effective once outside the 3-h window of proven trauma efficacy.

An agent-based framework to study forced migration: A case study of Ukraine.

The ongoing Russian aggression against Ukraine has forced over eight million people to migrate out of Ukraine. Understanding the dynamics of forced migration is essential for policy-making and for delivering humanitarian assistance. Existing work is hindered by a reliance on observational data which is only available well after the fact. In this work, we study the efficacy of a data-driven agent-based framework motivated by social and behavioral theory in predicting outflow of migrants as a result of conflict events during the initial phase of the Ukraine war. We discuss policy use cases for the proposed framework by demonstrating how it can leverage refugee demographic details to answer pressing policy questions. We also show how to incorporate conflict forecast scenarios to predict future conflict-induced migration flows. Detailed future migration estimates across various conflict scenarios can both help to reduce policymaker uncertainty and improve allocation and staging of limited humanitarian resources in crisis settings.

Differentiating Pathologic from Physiologic Fibrinolysis: Not as Simple as Conventional Thrombelastography.

BACKGROUND: Conventional rapid thrombelastography (rTEG) cannot differentiate fibrinolysis shutdown from hypofibrinolysis, as both of these patient populations have low fibrinolytic activity. Tissue plasminogen activator (tPA) TEG can identify depletion of fibrinolytic inhibitors, and its use in combination with rTEG has the potential to differentiate all 3 pathologic fibrinolytic phenotypes after trauma. We hypothesize tPA-TEG and rTEG in combination can further stratify fibrinolysis phenotypes postinjury to better stratify risk for mortality. STUDY DESIGN: Adult trauma patients (981) with both rTEG and tPA-TEG performed less than 2 hours postinjury were included. rTEG lysis at 30 minutes after maximum amplitude (LY30) was used to initially define fibrinolysis phenotypes (hyperfibrinolysis >3%, physiologic 0.9% to 3%, and shutdown <0.9%), with Youden Index then used to define pathologic extremes of tPA-TEG LY30 (tPA sensitive [depletion of fibrinolytic inhibitors] vs resistant) resulting in 9 groups that were assessed for risk of death. RESULTS: The median New Injury Severity Score was 22, 21% were female, 45% had penetrating injury, and overall mortality was 13%. The tPA-TEG LY30 inflection point for increased mortality was >35.5% (tPA sensitive, odds ratio mortality 9.2, p < 0.001) and <0.3% (tPA resistance, odds ratio mortality 6.3, p = 0.04). Of the 9 potential fibrinolytic phenotypes, 5 were associated with increased mortality. Overall, the 9 phenotypes provided a significantly better prediction of mortality than rTEG or tPA-TEG alone (areas under the operating characteristics curves = 0.80 vs 0.63 and 0.75, respectively, p < 0.0001). These could be condensed to 3 pathologic phenotypes (true hyperfibrinolysis, early fibrinolysis shutdown, and hypofibrinolysis). CONCLUSIONS: The combination of rTEG and tPA-TEG increases the ability to predict mortality and suggests patient-specific strategies for improved outcomes.

Coupled models of genomic surveillance and evolving pandemics with applications for timely public health interventions.

Disease surveillance systems provide early warnings of disease outbreaks before they become public health emergencies. However, pandemics containment would be challenging due to the complex immunity landscape created by multiple variants. Genomic surveillance is critical for detecting novel variants with diverse characteristics and importation/emergence times. Yet, a systematic study incorporating genomic monitoring, situation assessment, and intervention strategies is lacking in the literature. We formulate an integrated computational modeling framework to study a realistic course of action based on sequencing, analysis, and response. We study the effects of the second variant's importation time, its infectiousness advantage and, its cross-infection on the novel variant's detection time, and the resulting intervention scenarios to contain epidemics driven by two-variants dynamics. Our results illustrate the limitation in the intervention's effectiveness due to the variants' competing dynamics and provide the following insights: i) There is a set of importation times that yields the worst detection time for the second variant, which depends on the first variant's basic reproductive number; ii) When the second variant is imported relatively early with respect to the first variant, the cross-infection level does not impact the detection time of the second variant. We found that depending on the target metric, the best outcomes are attained under different interventions' regimes. Our results emphasize the importance of sustained enforcement of Non-Pharmaceutical Interventions on preventing epidemic resurgence due to importation/emergence of novel variants. We also discuss how our methods can be used to study when a novel variant emerges within a population.

Three-in-One: Dye-Volatile Cocrystals Exhibiting Intensity-Dependent Photochromic, Photomechanical, and Photocarving Response.

Cocrystallization of a cis-azobenzene dye with volatile molecules, such as pyrazine and dioxane, leads to materials that exhibit at least three different light-intensity-dependent responses upon irradiation with low-power visible light. The halogen-bond-driven assembly of the dye cis-(p-iodoperfluorophenyl)azobenzene with volatile halogen bond acceptors produces cocrystals whose light-induced behavior varies significantly depending on the intensity of the light applied. Low-intensity (<1 mW·cm-2) light irradiation leads to a color change associated with low levels of cis → trans isomerization. Irradiation at higher intensities (150 mW·mm-2) produces photomechanical bending, caused by more extensive isomerization of the dye. At still higher irradiation intensities (2.25 W·mm-2) the cocrystals undergo cold photocarving; i.e., they can be cut and written on with micrometer precision using laser light without a major thermal effect. Real-time Raman spectroscopy shows that this novel photochemical behavior differs from what would be expected from thermal energy input alone. Overall, this work introduces a rational blueprint, based on supramolecular chemistry in the solid state, for new types of crystalline light-responsive materials, which not only respond to being exposed to light but also change their response based on the light intensity.

Combination of aspirin and rosuvastatin for reduction of venous thromboembolism in severely injured patients: a double-blind, placebo-controlled, pragmatic randomized phase II clinical trial (The STAT Trial).

INTRODUCTION: Venous thromboembolism (VTE) remains a significant source of postinjury morbidity and mortality. Beta-hydroxy beta-methylglutaryl-CoA (HMG-CoA) reductase inhibitors (rosuvastatin) significantly reduced pathologic clotting events in healthy populations in a prior trial. Furthermore, acetylsalicylic acid (ASA) has been shown to be noninferior to prophylactic heparinoids for VTE prevention following orthopedic surgery. We hypothesized that a combination of rosuvastatin/ASA, in addition to standard VTE chemoprophylaxis, would reduce VTE in critically ill trauma patients. METHODS: This was a double-blind, placebo-controlled, randomized trial, evaluating VTE rates in two groups: ASA + statin (Experimental) and identical placebos (Control). Injured adults, 18-65 years old, admitted to the surgical intensive care unit without contraindications for VTE prophylaxis were eligible. Upon initiation of routine VTE chemoprophylaxis (i.e. heparin/heparin-derivatives), they were randomized to the Experimental or Control group. VTE was the primary outcome. RESULTS: Of 112 potentially eligible patients, 33% (n = 37, median new injury severity scale = 27) were successfully randomized, of whom 11% had VTEs. The Experimental group had no VTEs, while the Control group had 6 VTEs (4 PEs and 2 DVTs) in 4 (22%) patients (P = 0.046). The Experimental treatment was not associated with any serious adverse events. Due to the COVID-19 pandemic, the study was interrupted at the second interim analysis at <10% of the planned enrollment, with significance declared at P < 0.012 at that stage. DISCUSSION: The combination of ASA and rosuvastatin with standard VTE prophylaxis showed a favorable trend toward reducing VTEs with no serious adverse events. An appropriately powered phase III multicenter trial is needed to further investigate this therapeutic approach. LEVEL OF EVIDENCE: Level II, Therapeutic.

Halogen bonding with carbon: directional assembly of non-derivatised aromatic carbon systems into robust supramolecular ladder architectures.

Carbon, although the central element in organic chemistry, has been traditionally neglected as a target for directional supramolecular interactions. The design of supramolecular structures involving carbon-rich molecules, such as arene hydrocarbons, has been limited almost exclusively to non-directional π-stacking, or derivatisation with heteroatoms to introduce molecular assembly recognition sites. As a result, the predictable assembly of non-derivatised, carbon-only π-systems using directional non-covalent interactions remains an unsolved fundamental challenge of solid-state supramolecular chemistry. Here, we propose and validate a different paradigm for the reliable assembly of carbon-only aromatic systems into predictable supramolecular architectures: not through non-directional π-stacking, but via specific and directional halogen bonding. We present a systematic experimental, theoretical and database study of halogen bonds to carbon-only π-systems (C-I⋯πC bonds), focusing on the synthesis and structural analysis of cocrystals with diversely-sized and -shaped non-derivatised arenes, from one-ring (benzene) to 15-ring (dicoronylene) polycyclic atomatic hydrocarbons (PAHs), and fullerene C60, along with theoretical calculations and a systematic analysis of the Cambridge Structural Database. This study establishes C-I⋯πC bonds as directional interactions to arrange planar and curved carbon-only aromatic systems into predictable supramolecular motifs. In >90% of herein presented structures, the C-I⋯πC bonds to PAHs lead to a general ladder motif, in which the arenes act as the rungs and halogen bond donors as the rails, establishing a unique example of a supramolecular synthon based on carbon-only molecules. Besides fundamental importance in the solid-state and supramolecular chemistry of arenes, this synthon enables access to materials with exciting properties based on simple, non-derivatised aromatic systems, as seen from large red and blue shifts in solid-state luminescence and room-temperature phosphorescence upon cocrystallisation.

Motifs in SARS-CoV-2 evolution.

We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of coevolving sites in the alignment (motifs), identified via coevolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the coevolutionary coupling of pairs and manifest as coevolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness, and robustness. Lastly, we study how well each lineage is classified by such a system.

PRIME score for prediction of permanent pacemaker implantation after transcatheter aortic valve replacement.

OBJECTIVES: We sought to produce a simple scoring system that can be applied at clinical visits before transcatheter aortic valve replacement (TAVR) to stratify the risk of permanent pacemaker (PPM) after the procedure. BACKGROUND: Atrioventricular block is a known complication of TAVR. Current models for predicting the risk of PPM after TAVR are not designed to be applied clinically to assist with preprocedural planning. METHODS: Patients undergoing TAVR at the University of Colorado were split into a training cohort for the development of a predictive model, and a testing cohort for model validation. Stepwise and binary logistic regressions were performed on the training cohort to produce a predictive model. Beta coefficients from the binary logistic regression were used to create a simple scoring system for predicting the need for PPM implantation. Scores were then applied to the validation cohort to assess predictive accuracy. RESULTS: Patients undergoing TAVR from 2013 to 2019 were analyzed: with 483 included in the training cohort and 123 included in the validation cohort. The need for a pacemaker was associated with five preprocedure variables in the training cohort: PR interval > 200 ms, Right bundle branch block, valve-In-valve procedure, prior Myocardial infarction, and self-Expandable valve. The PRIME score was developed using these clinical features, and was highly accurate for predicting PPM in both the training and model validation cohorts (area under the curve 0.804 and 0.830 in the model training and validation cohorts, respectively). CONCLUSIONS: The PRIME score is a simple and accurate preprocedural tool for predicting the need for PPM implantation after TAVR.