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Mitigating climate change requires a portfolio of strategies and the use of carbon dioxide removal techniques or negative emissions technologies (NETs) will be necessary to achieve this goal. However, the high implementation costs of advanced NETs lead to expensive carbon credits, hindering their broad acceptance and use. One potential solution involves governmental support through subsidies, aiming to boost the availability of NET-derived carbon credits. This research uses a graphical technique based on an extension of pinch analysis to identify the ideal subsidy level for carbon dioxide removal, taking into account factors such as carbon pricing, supply, and demand. The proposed approach modifies the limiting composite curve (LCC) methodology to accurately determine the optimal subsidy and establish the baseline amount of subsidized carbon dioxide removal needed. The approach enables the convenient and efficient construction of the LCC using a composite table algorithm. To illustrate the proposed methodology, two case studies composed of different NETs and demand sectors are investigated. The results show the most advantageous subsidy levels for these technologies, providing valuable insights to guide policymakers and investors in their decarbonization efforts. This work contributes to the development of effective governance and investment strategies by optimizing NET subsidy allocation. Such optimization is crucial for facilitating the widespread implementation of these technologies, which are in-line with the global efforts to mitigate climate change.

Background: Pectoralis major muscle/myocutaneous flaps (PMMFs) are commonly used in reconstructive surgery, but may result in shoulder disability on the donor side. A systematic review evaluating this morbidity could be beneficial for guiding patients and providers considering this procedure. Methods: In October 2022, a systematic review of studies evaluating quantitative/qualitative measures of functional morbidity after PMMF was conducted. The results were categorized into PMMF's effect on range of motion (ROM), strength, and ability to complete shoulder-related activities/quality of life. Results: Eleven studies were included for analysis, which analyzed standard PMMF and two PMMF variants that spared portions of the muscle. Three of five studies demonstrated reduced shoulder ROM for standard PMMF versus controls lasting at least 4 months after head and neck reconstruction. Two of five studies, including two prospective studies demonstrated reduced shoulder strength for standard PMMF versus controls lasting at least 3 months after surgery. Five of nine studies found significant impairment in the ability to conduct shoulder-related activities, including work, up to one year postoperatively for standard PMMF versus controls. Muscle-sparing PMMF variants exhibited more promising outcomes in some categories. Conclusion: Standard PMMF results in prolonged reductions in shoulder ROM and strength, which may impair patients in shoulder-related activities. Other reconstructive options should be considered in patients who frequently participate in such activities. For patients requiring PMMF, muscle-sparing PMMF variants should be considered as alternatives to the standard PMMF.

Peperomia pellucida, a tropical plant belonging to the Piperaceae family, has long been recognized for its potential medicinal properties, including anti-inflammatory, analgesic, and antimicrobial effects. This study investigates the efficacy of Peperomia pellucida nanoemulsion (PPNE) as a novel therapeutic approach for improving burn wound healing in Wistar rats. The nanoemulsion was formulated using the high-energy ultrasonication method, optimized for droplet size, polydispersity index, and stability. A 30 % burn wound was induced on the dorsum of 60 Wistar rats, which were then divided into three groups: control (untreated), silver sulfadiazine (SSD) treated, and PPNE treated. Inflammatory cytokine levels (TNF-α, IL-6, and IL-1) were measured using enzyme-linked immunosorbent assay (ELISA). Results showed that PPNE treatment significantly accelerated wound closure rates compared to both control and SSD-treated groups, with complete wound closure achieved by day 10 in the PPNE-treated group. Histopathological examination revealed improved re-epithelialization, granulation tissue formation, and collagen deposition in the PPNE group compared to the control and SSD groups. Additionally, PPNE treatment significantly reduced inflammatory cytokine levels and enhanced antioxidant enzyme activities, suggesting a reduction in inflammation and oxidative stress in the treated wounds. In conclusion, this study demonstrates the potential of P. pellucida nanoemulsion as a promising and effective therapeutic approach for improving burn wound healing. The observed enhanced wound healing properties may be attributed to the combined anti-inflammatory, antioxidant, and antimicrobial effects of the PPNE, warranting further investigation and potential clinical application.

COVID-19 is an emerging disease that attacks the respiratory and systemic systems. Various treatments have been used for COVID-19, but no antiviral agents seemed to be efficacious. Many medicinal plants are commonly used for viral infections in Indonesia, including the guajava leaf. The study aimed to determine the effects of Psidium guajava extract supplementation on inflammation markers of asymptomatic and mild COVID-19 patients. The conversion time of PCR results was also evaluated. This study was an experimental, single-blinded, randomized clinical trial (ClinicalTrials.gov: NCT04810728) comparing the efficacy of P. guajava extract at the dose of 1000 mg/8h on top of standard treatment with the standard treatment only for asymptomatic and mild COVID-19 subjects. The primary endpoints were neutrophil and lymphocyte percentages as well as the neutrophil/lymphocyte ratio (NLR) on day 7 of the treatment. The secondary endpoints were high-sensitivity c-reactive protein (hs-CRP) level, PCR-based conversion time, and recovery rate at weeks 2 and 4. A total of 90 subjects were enrolled, and there were 40 subjects in the P. guajava (experimental) group and 41 subjects in the control group who completed the research. On day 7, significantly lower percentage of neutrophil (52.4% vs 58.9%, p = 0.002), higher lymphocyte percentage (35.5%, vs 29.7%, p = 0.002), and lower NLR (1.5 vs 2.1, p = 0.001) were demonstrated in the experimental versus control group. The PCR-based conversion time was shorter (14 days vs 16 days, p

Rationale & Objective: Heart failure (HF) is an important cause of morbidity and mortality among individuals with chronic kidney disease (CKD). A large body of evidence from preclinical and clinical studies implicates excess levels of fibroblast growth factor 23 (FGF23) in HF pathogenesis in CKD. It remains unclear whether the relationship between elevated FGF23 levels and HF risk among individuals with CKD varies by HF subtype. Study Design: Prospective cohort study. Settings & Participants: A total of 3,502 participants were selected in the Chronic Renal Insufficiency Cohort study. Exposure: Baseline plasma FGF23. Outcomes: Incident HF by subtype and total rate of HF hospitalization. HF was categorized as HF with preserved ejection fraction (HFpEF, ejection fraction [EF] ≥ 50%), HF with reduced EF (HFrEF, EF

We analyse the potential of the proposed μ+μ+ and μ+e− collider μTRISTAN to complement the searches for charged-lepton flavour-violation (CLFV) that can be carried out by Belle II. μTRISTAN offers the possibility of directly producing and studying new resonances that could mediate CLFV for a certain range of masses. In addition, we find that it can produce competitive bounds to those from Belle II for cases where the new resonance lies beyond direct reach. We illustrate these points with three Z3 “lepton triality” models, where we also find an example that can only be probed by μTRISTAN. These three models feature doubly-charged scalars, denoted k1,2,3 respectively, that induce both CLFV and flavour-conserving processes. Tree-level k1 exchange induces the CLFV scattering process μ+e−→e+τ−, while k2 interactions induce μ+μ+→τ+e+, μ+e−→τ+μ− and make a non-SM contribution to the flavour-conserving scattering μ+μ+→μ+μ+. The k3 model has a non-SM contribution to the flavour-conserving process μ+e−→μ+e−. Other scattering processes involving k1, k2 or k3 are not relevant for μTRISTAN and outside the scope of our analysis. We quantify the sensitivity of μTRISTAN for each of these processes. For the k1 and k2 cases we compare the μTRISTAN reach to the expected sensitivity of Belle II to the crossing symmetry related CLFV τ decays.

Neighborhoods have been identified as important determinants of health-related outcomes, but limited research has assessed the influence of neighborhood context along the cancer continuum. This study used census tract-level data from the United States Census Bureau and Centers for Disease Control and Prevention to characterize Miami-Dade County census tracts (n = 492) into social vulnerability clusters and assess their associated breast, cervical, and colorectal cancer screening participation rates. We identified disparities by social vulnerability cluster in cancer screening participation rates. Further investigation of geographic disparities in social vulnerability and cancer screening participation could inform equity-focused cancer control efforts.

Plastic pollution is a serious sustainability issue facing the global community. Fragments of macroplastics and microplastics pollute terrestrial and aquatic ecosystems, while nanoplastics can also degrade air quality. The recent COVID-19 pandemic also exacerbated the problem. Large-scale commercial use of plastics recycling technologies is hindered by various socio-economic barriers. In particular, cross-contamination of mixed plastic streams is prevalent due to imperfect waste segregation. The concept of Plastics Recycling Networks is introduced to facilitate planning of reverse supply chains using optimization models. In this work, basic Linear Programming and Mixed-Integer Linear Programming models are developed for matching sources of waste plastic with plastic recycling plants within Plastics Recycling Networks. These models allocate streams while considering the ability of recycling plants to tolerate contaminants. Two illustrative case studies are analyzed to demonstrate the effectiveness of the models, and policy implications for mitigation of plastic pollution are discussed. These models enable planning of networks with some tolerance for contaminants in plastic waste, and can be the basis for developing new variants to handle additional real world aspects.

Optimal deployment of renewable and cleaner energy in power system operations has been the topic of interest to achieve deep cuts in greenhouse gas emissions. However, the intermittency of wind and solar power impedes the large-scale penetration of renewable power generation (RPG) into the power grid. Use of electrical energy storage (EES) facilities has great potential in mitigating the variability of RPG, and will allow reducing the power dependency on fossil fuel based generators (FFBG). Hybrid power systems (HPS) using both RPGs and FFBGs are an alternative means of dealing with variability problem. However, modelling different RPGs integrated with EES and FFBG in consideration of operational constraints, scheduling strategies, and other operational objectives is a challenging task. Previous research and review articles have mostly focused on the modelling, sizing, modes of operation and techno economic aspects of HPS and EES independently. However, no reviews specific to issues of various small scale to large scale EES integrated HPS operation have been published to date. This work presents a comprehensive overview of recent developments in six different EES + HPS and three hybrid EES facilities and underlines the different objectives, detailed real time operational analysis, and solution methodologies. The discussion covers the operation of HPS in both stand-alone and grid connected mode, and looks at the growing application of artificial intelligence (AI) based scheduling strategies for the evaluation of optimal HPS operational paradigms. The proposed review will strengthen the key directions for future research of EES integration and will provide the context for the development of economic, efficient and reliable cleaner power system.

Introduction: While polysubstance use has consistently been associated with higher rates of relapse, few studies have examined subgroups with specific combinations and time course of polysubstance use (i.e., polysubstance use patterns). This study aimed to classify and compare polysubstance use patterns, and their associations with relapse to regular opioid use in 2637 participants in three large opioid use disorder (OUD) treatment trials. Methods: We explored the daily patterns of self-reported substance use in the 28 days prior to treatment entry. Market basket analysis (MBA) and repeated measure latent class analysis (RMLCA) were used to examine the subgroups of polysubstance use patterns, and multiple logistic regression was used to examine associations between identified classes and relapse. Results: MBA and RMLCA identified 34 “associations rules” and 6 classes, respectively. Specific combinations of polysubstance use and time course (high baseline use and rapid decrease of use prior to initiation) predicts a worse relapse outcome. MBA showed individuals who co-used cocaine, heroin, prescription opioids, and cannabis had a higher risk for relapse (OR = 2.82, 95%CI = 1.13, 7.03). In RMLCA, higher risk of relapse was observed in individuals who presented with high baseline prescription opioid (OR = 1.9, 95% CI = 1.3, 2.76) or heroin use (OR = 3.54, 95%CI = 1.86, 6.72), although use decreased in both cases prior to treatment initiation. Conclusions: Our analyses identified subgroups with distinct patterns of polysubstance use. Different patterns of polysubstance use differentially predict relapse outcomes. Interventions tailored to these individuals with specific polysubstance use patterns prior to treatment initiation may increase the effectiveness of relapse prevention.

The variability of renewable energy can be addressed by incorporating energy storage technologies (ESTs). Multiple energy storage technologies are available for renewable energy with wide disparity in attributes. Reports regarding the attributes are conflicting and complex, which makes it a multi-attribute decision analysis problem. To address this issue, new decision support tools are needed to aid in selecting ESTs based on their technical, environmental, and economic characteristics. In this study, a neutrosophic data envelopment analysis (NDEA) technique is developed and applied to selection of ESTs considering neutrosophic uncertainty inherent in new technologies. The decision tool systematically evaluates EST options by considering the expert's degree of satisfaction for higher technical performance, degree of dissatisfaction for lower technical performance and degree of indeterminacy for attaining better technical performance. Two case studies adapted from literature are used to illustrate the decision support tool. The first case study, which is used to demonstrate the tool for EST selection, involves the selection of thermal energy storage options. The second case study involves eight ESTs with different mechanisms: supercapacitor, flywheel, compressed air energy storage, pumped hydro energy storage, Li-ion battery, NiCd battery, NaS battery, and Pb-acid battery. The results reveal certain ESTs that are preferred over wide range of expert's perception to uncertainty in terms of dissatisfaction and indeterminacy. For example, Li-ion battery is DEA efficient if the risk tolerance for indeterminacy is greater than 40% and Pb-acid battery is DEA efficient at falsity tolerance greater than 80% and indeterminacy tolerance of less than 5%. These alternatives can be regarded as robust choices. Insights gained from the application of the decision tool can be used for guiding investment decisions in planning of renewable energy systems with energy storage.

Rationale & Objective: Adherence to recommended medical treatment is critical in chronic kidney disease (CKD) to prevent complications and progression to kidney failure. Overall adherence to treatment is low in CKD, and as few as 40% of patients with kidney failure receive any documented CKD-related care. The purpose of this study was to explore the experiences of patients with CKD and their adherence to CKD treatment plans, and the role their health care providers played in supporting their adherence. Study Design: One-on-one interviews were conducted in 2019-2020 using a semi-structured interview guide. Participants described experiences with adherence to treatment plans and what they did when experiencing difficulty. Setting & Participants: Participants were recruited from the Chronic Renal Insufficiency Cohort (CRIC) study. All CRIC participants were older than 21 years with CKD stages 2-4; this sample consisted of participants from the University of Pennsylvania CRIC site. Analytical Approach: Interviews were recorded, transcribed, and coded using conventional content analysis. Data were organized into themes using NVivo 12. Results: The sample (n = 32) had a mean age of 67 years, 53% were women, 59% were non-White, with a mean estimated glomerular filtration rate of 56.6 mL/min/1.73 m2. From analysis of factors relevant to treatment planning and adherence, following 4 major themes emerged: patient factors (multiple chronic conditions, motivation, outlook), provider factors (attentiveness, availability/accessibility, communication), treatment planning factors (lack of plan, proactive research, provider-focused treatment goals, and shared decision making), and treatment plan responses (disagreeing with treatment, perceived capability deficit, lack of information, and positive feedback). Limitations: The sample was drawn from the CRIC study, which may not be representative of the general population with CKD. Conclusions: These themes align with Behavioral Learning Theory, which includes concepts of internal antecedents (patient factors), external antecedents (provider factors), behavior (treatment planning factors), and consequences (treatment plan responses). In particular, the treatment plan responses point to innovative potential intervention approaches to support treatment adherence in CKD.

Oil palm plantations are the fundamental units in a palm supply chain. The fresh fruit bunch (FFB) yield at a plantation varies based on the maturity (age) of the oil palm trees. Failure to account for the maturity can lead to a demand-supply mismatch. To address this issue, Rajakal et al. (2021) have developed a mathematical optimisation model to determine the optimal maturity of the plantations needed to meet the crude palm oil demand. This article presents the data set on the FFB production and land use change (LUC) emissions at the plantations. The model was coded and solved in LINGO 18.0. The data can be used for further investigation in optimising other related activities in a palm supply chain.

Input-output analysis is used for modelling economic networks with linear equations representing intersectoral links. These models are used extensively to determine the effects of policies and decisions, taking into account sectoral interdependencies. They have also been used to identify optimal responses to various natural or man-made disruptions. An alternative graph theoretic approach to optimizing input-output systems using P-graph has also been developed. However, that approach is limited by the restrictive assumption of the Leontief production function, where each economic sector requires an invariant set of inputs to produce each unit of output; it is assumed in the basic model that these inputs have no substitutability, since their relative proportions are determined by a fixed state of technology. Relaxing this unrealistic assumption is a critical research gap. An improved P-graph model for optimizing input-output systems with partial substitution is developed in this paper. This modelling approach is demonstrated with two case studies involving energy shortages triggered by extreme weather and by military action. Both examples show that the capacity for partial substitution makes economic systems more robust to disruptions.

Fossil fuels will still be used in the coming decades following the agreement to phase down coal and phase out fossil fuels subsidies in COP26. Negative Emissions Technologies (NETs) can offset the emissions caused by the residual use of fossil fuels. NETs such as Afforestation/Reforestation (AR), biochar application (BC), Soil Carbon Sequestration (SCS) Bioenergy with Carbon Capture and Storage (BECCS), Enhanced Weathering (EW), and Direct Air Carbon Capture and Storage (DACCS) remove CO2 from the atmosphere and store it in reservoirs. The large-scale implementation of NETs will incur resource footprints; thus, NETs should operate within the Planetary Boundaries. No single NET can sustainably deliver the required CO2 removal, and optimized regional portfolios of NETs can reduce the biophysical and social impacts of their implementation. In such portfolios, some NETs may have synergistic effects and consume fewer resources when implemented together. In this work, fuzzy mixed-integer programming models are developed to optimize the CO2 removal (CDR) potential of a NETs portfolio while considering possible synergistic interactions, as well as uncertainties in the resource constraints and negative emission targets. The models are illustrated with a regional case study that demonstrates the changes in the optimal NETs portfolio depending on different scenarios.

Introduction: Management of chronic kidney disease (CKD) entails high medical complexity and often results in high hospitalization burden. There are limited data on the associations of longitudinal hospital utilization patterns with adverse clinical outcomes in individuals with CKD. Methods: We derived cumulative all-cause hospitalization trajectory groups using latent class trajectory analysis in 3012 participants of the Chronic Renal Insufficiency Cohort (CRIC) Study who were alive and did not reach end-stage kidney disease (ESKD) within 4 years of study entry. Cox proportional hazards models tested the associations between hospitalization trajectory groups and risks of ESKD and death prior to the onset of ESKD (ESKD-censored death). Results: Within 4 years of study entry, there were 5658 hospitalizations among 3012 participants. We identified 3 distinct subgroups of individuals with CKD based on cumulative all-cause hospitalization trajectories over 4 years: low-utilizer (n = 1066), intermediate-utilizer (n = 1802), and high-utilizer (n = 144). High-utilizers represented a patient population of lower socioeconomic status who had a greater prevalence of comorbid conditions and lower kidney function compared with intermediate- and low-utilizers. After the 4-year ascertainment period to form the trajectory subgroups, there were 544 ESKD events and 437 ESKD-censored deaths during a median follow-up time of 5.1 years. Compared with low-utilizers, intermediate-utilizers and high-utilizers were at 1.49-fold (95% confidence interval [CI] 1.22–1.84) and 1.75-fold (95% CI 1.20–2.56) higher risk of ESKD in adjusted analyses, respectively. Compared with low-utilizers, intermediate-utilizers and high-utilizers were at 1.48-fold (95% CI 1.17–1.87) and 2.58-fold (95% CI 1.74–3.83) higher risk of ESKD-censored death in adjusted analyses, respectively. Conclusions: Trajectories of cumulative all-cause hospitalization identify subgroups of individuals with CKD who are at high risk of ESKD and death.

Consumption of plastic is steadily increasing, making disposal through landfilling, incineration, and open-or closed-loop recycling challenging. The majority of these plastic waste is Polyethylene Terephthalate (PET) bottles, widely used for single-use beverage and liquid containers. This study focuses on using Recycled PET (RPET) bottles as confining material on rectangular concrete columns. This method uses RPET strips that are produced by stripping parts of the RPET bottle which are then wrapped around externally on concrete columns. It can easily be adapted in rural areas with low skilled workers, unlike the conventional methods which makes use of expensive materials and require trained workers. Production of twenty-seven rectangular unreinforced concrete specimens with a size of 100 mm × 100 mm × 300 mm are made. The RPET strips are varied having width of 10 mm and 20 mm, and clear spacing between strips of 10 mm and 25 mm by using two available PET bottles in the industry. A fastening system is proposed, instead of using industrial adhesives, in placing and tying the RPET strips to the rectangular column. Results show a 19% to 70% increase in ultimate compressive strength for rectangular columns which are externally reinforced by RPET. A significant increase in axial strain from the stress-strain diagram is experienced. The proposed method is practical and effective in strengthening concrete structures. The findings suggest that test for long-term durability should be implemented. Life cycle analysis as well as further studies on the scalability of this viable PET waste management solution should be conducted.

Introduction: Although diabetic kidney disease (DKD) is responsible for more than half of all chronic and end-stage kidney disease (ESKD), the association of light (LM) and electron microscopic (EM) structural changes with clinical parameters and prognosis in DKD is incompletely understood. Methods: This is an interim analysis of 62 patients diagnosed with biopsy-confirmed DKD from the multicenter TRIDENT (Transformative Research in Diabetic Nephropathy) study. Twelve LM and 8 EM descriptors, representing changes in glomeruli, tubulointerstitium, and vasculature were analyzed for their relationship with clinical measures of renal function. Patients were followed every 6 months. Results: Multivariable linear regression analysis revealed that estimated glomerular filtration rate (eGFR) upon enrollment correlated the best with interstitial fibrosis. On the other hand, the rate of kidney function decline (eGFR slope) correlated the most with glomerular lesions including global glomerulosclerosis and mesangiolysis. Unbiased clustering analysis based on histopathologic data identified 3 subgroups. The first cluster, encompassing subjects with the mildest histologic lesions, had the most preserved kidney function. The second and third clusters had similar degrees of kidney dysfunction and structural damage, but differed in the degree of glomerular epithelial cell and podocyte injury (podocytopathy DKD subtype). Cox proportional hazard analysis showed that subjects in cluster 2 had the highest risk to reach ESKD (hazard ratio: 17.89; 95% confidence interval: 2.13–149.79). Glomerular epithelial hyperplasia and interstitial fibrosis were significant predictors of ESKD in the multivariate model. Conclusion: The study highlights the association between fibrosis and kidney function and identifies the role of glomerular epithelial changes and kidney function decline.

Carbon footprint analysis of geopolymer concrete can be used to determine its advantages over conventional Portland cement concrete. However, the influence of allocation assumptions has been neglected in previous geopolymer life cycle assessment studies. This research gap is addressed here through an analysis of the effect of allocation scenarios in the assessment of self-healing geopolymer concrete made from coal fly ash and ground granulated blast furnace slag feedstocks. In addition, an empirical, variable-mix “gray box” model was integrated into the life cycle assessment to allow different blends that meet product property specifications to be considered. The cradle-to-gate life cycle assessment was done using OpenLCA and MS Excel, using inventory data from databases and literature. The allocation assumptions are found to significantly affect the results, with carbon footprints ranging from 208.72 kg eq. CO2 to 395.72 kg eq. CO2 per cubic meter of concrete. Using allocation based on economic value, the price of coal fly ash has a greater effect than that of ground granulated blast furnace slag. The implications of this result on the commercial use of geopolymer concrete are discussed, as well as the potential application of the “gray box” approach as a generic methodology in life cycle assessment.

The use of mosquito repellents is an efficient way to prevent mosquito-borne diseases. Despite the accumulation of information about repellents, there remains the challenge of the lack of understanding of their mechanism of action. There is also a need for systematic methods for discovering new alternatives that mitigate the drawbacks of repellents currently in use. To address these research gaps, a computer-aided molecular design (CAMD) framework is developed for the optimal molecular design of mosquito repellents. In this framework, the mosquito repelling attribute of molecules are predicted using a data-driven hyperbox-based machine learning approach in the absence of a mechanistic prediction model. The best set of rules is selected from plausible alternative models developed. For the prediction of important physical properties, a group contribution-based method using reliable models is implemented. Subsequently, the CAMD formulation is developed as a mixed-integer linear programming model to obtain structures with minimum viscosity. Results show that of the structures generated, the hyperbox classifier correctly predicted the repelling ability of all molecules found to be known repellents in literature. The molecules not found in the databases provide key insights on where experimental research to develop new repellents should be targeted. Thus, this newly developed framework can be applied as a systematic technique to screen and narrow down the search space for candidate mosquito repellent molecules before final experimental verification.

Rationale & Objective: Having a usual source of care increases use of preventive services and is associated with improved survival in the general population. We evaluated this association in adults with chronic kidney disease (CKD). Study Design: Prospective, observational cohort study. Setting & Participants: Adults with CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study. Predictor: Usual source of care was self-reported as: 1) clinic, 2) emergency department (ED)/urgent care, 3) other. Outcomes: Primary outcomes included incident end-stage kidney disease (ESKD), atherosclerotic events (myocardial infarction, stroke, or peripheral artery disease), incident heart failure, hospitalization events, and all-cause death. Analytical Approach: Multivariable regression analyses to evaluate the association between usual source of care (ED/urgent care vs clinic) and primary outcomes. Results: Among 3,140 participants, mean age was 65 years, 44% female, 45% non-Hispanic White, 43% non-Hispanic Black, and 9% Hispanic, mean estimated glomerular filtration rate 50 mL/min/1.73 m2. Approximately 90% identified clinic as usual source of care, 9% ED/urgent care, and 1% other. ED/urgent care reflected a more vulnerable population given lower baseline socioeconomic status, higher comorbid condition burden, and poorer blood pressure and glycemic control. Over a median follow-up time of 3.6 years, there were 181 incident end-stage kidney disease events, 264 atherosclerotic events, 263 incident heart failure events, 288 deaths, and 7,957 hospitalizations. Compared to clinic as usual source of care, ED/urgent care was associated with higher risk for all-cause death (HR, 1.53; 95% CI, 1.05-2.23) and hospitalizations (RR, 1.41; 95% CI, 1.32-1.51). Limitations: Cannot be generalized to all patients with CKD. Causal relationships cannot be established. Conclusions: In this large, diverse cohort of adults with moderate-to-severe CKD, those identifying ED/urgent care as usual source of care were at increased risk for death and hospitalizations. These findings highlight the need to develop strategies to improve health care access for this high-risk population.

Introduction: Subclinical changes to cardiac structure and function detected with echocardiography precede the development of clinical heart failure (HF) in persons with chronic kidney disease (CKD). Circulating cardiac biomarkers may reflect these pathophysiological changes. This study investigated associations between established biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP] and high-sensitivity troponin T [hsTnT]) and novel biomarkers (growth differentiation factor 15 [GDF-15], galectin-3 [Gal-3], and soluble ST-2 [sST-2]), using echocardiographic measurements in persons with CKD. Methods: In cross-sectional analyses among 2101 participants with mild to moderate CKD in the Chronic Renal Insufficiency Cohort (CRIC), biomarker levels measured at baseline were evaluated with echocardiographic measurements 1 year later. These included left ventricular mass index (LVMI), left ventricular end-systolic volume (LVESV), left ventricular end-diastolic volume (LVEDV), left ventricular ejection fraction (LVEF), and left atrial diameter (LAD). Multivariable linear regression analyses tested associations of each biomarker with echocardiographic measurements, adjusting for covariates. Results: GDF-15 was significantly associated with higher LVMI (1.0 g/m2.7; 95% CI, 0.4–1.7), LVESV (0.4 ml/m2.7; 95% CI, 0.0–0.7), and LVEDV (0.6 ml/m2.7; 95% CI, 0.1–1.1), but not with LVEF or LAD. These findings were not significant when adjusting for NT-proBNP and hsTnT. Gal-3 and sST-2 had no significant associations. Higher levels of NT-proBNP and hsTnT were associated with all echocardiographic measurements. Conclusion: In patients with CKD, the novel biomarker GDF-15, a marker of inflammation and tissue injury, and clinical biomarkers NT-proBNP and hsTnT, were associated with echocardiographic measurements of subclinical cardiovascular disease. Collectively, these biomarkers may highlight biological pathways that contribute to the development of clinical HF.

Selection of the best green technology for a given application is a multi-criterion decision analysis problem. The tradeoffs that need to be made among conflicting attributes of the alternatives are inherently subjective and require the use of interactive decision analysis tools. In this work, a machine-learning based methodology is developed for ranking green technologies based on multiple criteria. First, an expert generates a training data set by ranking a subset of the alternative technologies using his/her tacit knowledge and preferences. Then, a machine learning procedure known as logical analysis of data (LAD) is used to detect patterns in these rankings. These patterns are approximations of the mental rules used by the expert to compare and rank the competing alternatives; after validation, they can be used to rank other technologies in the same class as those in the training data. This novel methodology is illustrated here for the case of ranking alternative energy storage technologies for stationary applications. This technique provides a rapid means of eliciting expert knowledge for ranking alternatives based on multiple criteria.

Negative emissions technologies (NETs) will be needed to achieve deep cuts in greenhouse gas emissions and mitigate climate change in the coming decades. Enhanced weathering and biochar application are two NETs that are based on the enhancement of naturally occurring processes; compared to other NETs, they have the advantage of relying on mature component technologies. Both technologies offer the prospect of sequestering carbon from the atmosphere at the scale of multiple gigatons per year if deployed commercially via carbon management networks (CMNs). However, planning future CMNs will present similar challenges as optimizing supply chains for current product systems. In this work, a pinch analysis approach for the planning of CMNs based on either enhanced weathering or biochar application is developed. Planning is framed as a source-sink problem typical in process integration (PI) applications, allowing pinch analysis to be applied to determine optimal system targets and synthesize the corresponding CMNs. General principles of pinch analysis are shown to be applicable to the planning problem. Case studies on enhanced weathering and biochar application CMNs are solved to illustrate this approach.

Current construction developments are trending towards more sustainable practices with greener alternative materials such as geopolymers. Geopolymers are a class of cementitious materials based on inorganic polymers, which are promising substitutes for ordinary Portland cement (OPC). However, studies have shown that geopolymers are more prone to crack propagation, which leads to reduced durability and serviceability. This study assesses the environmental impacts of a method for self-healing in geopolymers. The proposed self-healing method makes use of embedded microcapsules containing alkali-activators in geopolymer concrete. This study aims to quantify the expected additional environmental impacts brought about by adding self-healing microcapsules to geopolymers. Life cycle assessment (LCA) of the self-healing geopolymer is important to justify its use from an environmental viewpoint. The system boundaries for this LCA focuses on a cradle-to-gate perspective. The life-cycle inventory analysis (LCI) was done using databases in the OpenLCA software and literature. Life cycle impact assessment (LCIA) was carried out using the CML-IA methodology. Self-healing geopolymer concrete was better in global warming potential but worse in other environmental impact categories than conventional OPC concrete. The main contributors of the impacts are the alkali-activator production and the self-healing microcapsules. For microcapsule production, the solvent and the wall-forming monomer are the primary contributors to the assessed environmental impacts. Based on the LCA, areas for improvement of self-healing for geopolymers are also discussed.

Cancer patients and survivors of cancer have a greater burden of cardiovascular disease compared with the general population. Much of the elevated cardiovascular risk in these individuals is likely attributable to hypertension, because individuals with cancer have a particularly high incidence of hypertension following cancer diagnosis. Treatment with chemotherapy is an independent risk factor for hypertension due to direct effects of many agents on endothelial function, sympathetic activity, and renin-angiotensin system activity, as well as nephrotoxicity. Diagnosis and management of hypertension in cancer patients requires accurate blood pressure measurement and consideration of potential confounding factors, such as adjuvant treatments and acute pain, that can temporarily elevate blood pressure readings. Home blood pressure monitoring can be a useful tool to facilitate longitudinal blood pressure monitoring for titration of antihypertensive medications. Selection of antihypertensive agents in cancer patients should account for treatment-specific morbidities and target organ damage.

Introduction: Assessment of impaired vitamin D metabolism is limited by lack of functional measures. CYP24A1-mediated vitamin D clearance, calculated as the ratio of serum 24,25-dihydroxyvitamin D3 to 25-hydroxyvitamin D3 (the vitamin D metabolic ratio, VDMR), is induced by 1,25-dihydroxyvitamin D and may assess tissue-level activity. We tested associations of the VDMR with risks of death and progression to end-stage renal disease (ESRD) in patients with chronic kidney disease (CKD). Methods: We studied participants from the Chronic Renal Insufficiency Cohort (CRIC), which included a random subset of 1080 CRIC participants plus additional participants who experienced ESRD or died (case cohort study design). Serum 24,25-dihydroxyvitamin D3 and 25-hydroxyvitamin D3 was measured 1 year after enrollment. The primary outcomes included death and progression to ESRD. Using inverse probability weighting, we tested associations of VDMR (24,25[OH]2D3/25[OH]D3) with risks of death and ESRD, adjusting for demographics, comorbidity, and kidney function (estimated glomerular filtration rate [eGFR] and urine protein-to-creatinine ratio [PCR]). Results: There were a total of 708 ESRD events and 650 deaths events over mean (SD) follow-up periods of 4.9 (2.9) years and 6.5 (2.5) years, respectively. Lower VDMR was associated with increased risk of ESRD prior to adjusting for kidney function (hazard ratio [HR], 1.80 per 20 pg/ng lower VDMR; 95% confidence interval [CI], 1.56–2.08), but not with adjustment for kidney function (HR, 0.94 per 20 pg/ng; 95% CI, 0.81–1.10). Lower VDMR was associated with modestly increased mortality risk, including adjustment for kidney function (HR, 1.18 per 20 pg/ng; 95% CI, 1.02–1.36). Conclusion: Lower VDMR, a measure of CYP24A1-mediated vitamin D clearance, was significantly associated with all-cause mortality but not with progression to ESRD in patients with CKD. Keywords: kidney, mortality, vitamin D

Introduction: A cornerstone of kidney disease management is participation in guideline-recommended health behaviors. However, the relationship of these health behaviors with outcomes, and the identification of barriers to health behavior engagement, have not been described among younger and older adults with chronic kidney disease. Methods: Data from a cohort study of 5499 individuals with chronic kidney disease was used to identify health behavior patterns with latent class analysis stratified by age

Rationale & Objective: There are limited data about the prevalence and prognostic significance of orthostatic hypo- and hypertension in patients with chronic kidney disease. The objective of this study is to determine the prevalence of orthostatic hypo- and hypertension in a cohort of patients with chronic kidney disease and examine their association with clinical outcomes. Study Design: Prospective cohort study: Chronic Renal Insufficiency Cohort (CRIC) Study. Setting & Population: 7 clinical centers, participants with chronic kidney disease. Exposures: Orthostatic hypotension (decline in systolic blood pressure [BP] > 20 mm Hg) and orthostatic hypertension (increase in systolic BP > 20 mm Hg) from seated to standing position. Outcomes: Cardiovascular and kidney outcomes and mortality. Analytical Approach: Logistic regression was used to determine factors associated with orthostatic hypo- and hypertension; Cox regression was used to examine associations with clinical outcomes. Results: Mean age of study population (n = 3,873) was 58.1 ± 11.0 years. There was a wide distribution of change in systolic BP from seated to standing (from −73.3 to +60.0 mm Hg); 180 participants (4.6%) had orthostatic hypotension and 81 (2.1%) had orthostatic hypertension. Diabetes, reduced body mass index, and β-blocker use were independently associated with orthostatic hypotension. Black race and higher body mass index were independently associated with orthostatic hypertension. After a median follow-up of 7.9 years, orthostatic hypotension was independently associated with high risk for cardiovascular (HR, 1.12; 95% CI, 1.03-1.21) but not kidney outcomes or mortality. Orthostatic hypertension was independently associated with high risk for kidney (HR, 1.51; 96% CI, 1.14-1.97) but not cardiovascular outcomes or mortality. Limitations: Orthostatic change in BP was ascertained at a single visit. Conclusions: Orthostatic hypotension was independently associated with higher risk for cardiovascular outcomes, whereas orthostatic hypertension was associated with higher risk for kidney outcomes. These findings highlight the importance of orthostatic BP measurement in practice and the need for future investigation to understand the mechanisms and potential interventions to minimize the risk associated with orthostatic changes in BP.

Disruptive events have historically been shown to upset business as usual practices that can leave temporary or lasting changes. The emergence of a pandemic in 2020 triggered a rapid digital transformation. Electronic platforms are able to support essential socio-economic activities through virtual transactions and interactions yet products remain a physical output of raw material consumption. Furthermore, the digital world has also easily provided consumers access to more products than they normally need, allowing for rebound effect through “retail therapy” and “revenge procurement”. As widespread digital consumption becomes the “new normal”, this paper cautions against unsustainable consumption practices in the digital world, cites affluence data, and proposes a systemic design-based poka-yoke strategy as a feasible pathway to sustainable consumption: (i) a resource-based sustainability transition that accounts for the consumption of both intermediate (producer) and end- (finished product) consumers, (ii) a design philosophy in developing products and services that embeds sustainability attributes, and (iii) limiting consumer choices to sustainability-proofed products and systems that can guide and lock-in sustainable consumption.

The COVID-19 pandemic and the ensuing lockdowns has drastically altered modern life. Increased use of telecommuting for work, education, and leisure has led to a surge in demand for electronic products, which has strained both global manufacturing supply chains and upstream mineral stocks and resources. In this paper, we discuss a prospective research and policy agenda that covers the technological, socio-economic, and regulatory aspects needed for an accelerated transition towards enhanced mineral resource efficiency and improved electronic waste management during the pandemic and its aftermath.

Recent developments in (scanning) transmission electron microscopy (S)TEM have enabled in-situ investigations of nanoscale transformations. However, understanding the physical and chemical process defining matter transformations via the analysis of large-scale in-situ (S)TEM imaging data remains challenging. Here, we experimentally investigated a reaction-convection-diffusion model to track spatial-temporal patterns in (S)TEM videos of Pt nanoparticle formation and graphene contamination. Model parameters are pursued by statistical model selection algorithms that balance descriptive capability and model parsimony to aid interpretability and suppress overfitting. Besides conventional bottom-up analysis from individual entities, the integrated mathematical model based on partial differential equations (PDE) utilizing pixel level information provides complementary system status that may serve as a feedback for optimizing experiment setting.

The warming climate presents a challenge to conservation of all threatened and endangered species but particularly to those that exhibit temperature-dependent sex determination such as sea turtles. Changes in temperature may result in changes in the sex ratio of the population which can directly affect reproductive rate, abundance and population dynamics. The NW Atlantic loggerhead turtle population is listed as threatened under the U.S. Endangered Species Act, and one of the smallest subpopulations in this assemblage nests in the northern Gulf of Mexico. Here, we describe the incubation environment of northern Gulf of Mexico loggerheads nesting at several different beaches in Northwest Florida. Temperature dataloggers were placed inside and adjacent to nests on different nesting beaches across Northwest Florida. In addition, incubation durations were recorded from nests deposited on those same beaches. Internal nest temperatures were higher than those in the sand, however sand temperatures were correlated with incubation durations. Sand temperatures differed along the vertical beach profile and according to depth. Temperatures also differed along a geographic gradient across Northwest Florida and in relation to distance from the Apalachicola River. Incubation durations followed a similar pattern. Mean monthly temperatures at all sites were at or lower than 29 °C (range 23.1 °C–29.6 °C at the dunes; 23.8 °C–29.4 °C at mid-beach) which suggests nests in Northwest Florida may be producing a significant number of males, in contrast to the large number of females being produced on Florida’s Atlantic coast. The temperatures and incubation durations on these nesting beaches may be regulated by differing sources of sand and beach orientations across Northwest Florida. Keywords: Gulf of Mexico, Turtle, Sex ratio, Temperature, Climate change, Caretta caretta

Rationale & Objective: Among individuals with chronic kidney disease (CKD), poor self-reported health is associated with adverse outcomes including hospitalization and death. We sought to examine the association between health-related quality-of-life (HRQoL) and depressive symptoms in advanced CKD and subsequent access to the kidney transplant waiting list. Study Design: Prospective cohort study. Setting & Population: 1,676 Chronic Renal Insufficiency Cohort (CRIC) study participants with estimated glomerular filtration rates ≤ 30 mL/min/1.73 m2 at study entry or during follow-up. Exposures: HRQoL ascertained by 5 scales of the Kidney Disease Quality of Life-36 Survey (Physical Component Summary [PCS], Mental Component Summary, Symptoms, Burdens, and Effects), with higher scores indicating better HRQoL, and depressive symptoms ascertained using the Beck Depression Inventory. Outcomes: Time to kidney transplant wait-listing and time to pre-emptive wait-listing. Analytic Approach: Time-to-event analysis using Cox proportional hazards regression. Results: During a median follow-up of 5.1 years, 652 (39%) participants were wait-listed, of whom 304 were preemptively wait-listed. Adjusted for demographics, comorbid conditions, estimated glomerular filtration rate slope, and cognitive function, participants with the highest scores on the Burden and Effects scales, respectively, had lower rates of wait-listing than those with the lowest scores on the Burden (wait-listing adjusted hazard ratio [aHR], 0.70; 95% CI, 0.57-0.85; P

This submission contains the complete balanced process matrix of an off-grid community system primarily powered by a micro-hydroelectric powerplant. The system is meant to provide the needs of the community for electricity, potable water and ice. The system also considers the provision of a diesel engine generator set as a back-up to provide electricity. The data serves as inputs to simulate the performance of the system under different drought scenarios. The data provided here is in support of the co-submitted article of Aviso et al. [1].

This article contains the data set and model code for the negative emission polygeneration system described in Tan et al. (2019). The data was generated utilizing an optimization model implemented in LINGO 18.0 and includes information on the operating state of each process unit in the system. The maximum annual profit of the system was determined at different carbon footprint targets. The data set and model code can be utilized for further analysis on the interdependence between the process units of this polygeneration system, its operational and environmental performance, and the potential impact of integrating new process units into the network. Keywords: Negative emissions technology, Carbon dioxide removal, Polygeneration, Desalination, Carbon tax

Diagnosis of breast ductal carcinoma in situ (DCIS) presents a challenge since we cannot yet distinguish those cases that would remain indolent and not require aggressive treatment from cases that may progress to invasive ductal cancer (IDC). The purpose of this study is to determine the role of Rap1Gap, a GTPase activating protein, in the progression from DCIS to IDC. Immunohistochemistry (IHC) analysis of samples from breast cancer patients shows an increase in Rap1Gap expression in DCIS compared to normal breast tissue and IDCs. In order to study the mechanisms of malignant progression, we employed an in vitro three-dimensional (3D) model that more accurately recapitulates both structural and functional cues of breast tissue. Immunoblotting results show that Rap1Gap levels in MCF10.Ca1D cells (a model of invasive carcinoma) are reduced compared to those in MCF10.DCIS (a model of DCIS). Retroviral silencing of Rap1Gap in MCF10.DCIS cells activated extracellular regulated kinase (ERK) mitogen-activated protein kinase (MAPK), induced extensive cytoskeletal reorganization and acquisition of mesenchymal phenotype, and enhanced invasion. Enforced reexpression of Rap1Gap in MCF10.DCIS-Rap1GapshRNA cells reduced Rap1 activity and reversed the mesenchymal phenotype. Similarly, introduction of dominant negative Rap1A mutant (Rap1A-N17) in DCIS-Rap1Gap shRNA cells caused a reversion to nonmalignant phenotype. Conversely, expression of constitutively active Rap1A mutant (Rap1A-V12) in noninvasive MCF10.DCIS cells led to phenotypic changes that were reminiscent of Rap1Gap knockdown. Thus, reduction of Rap1Gap in DCIS is a potential switch for progression to an invasive phenotype. The Graphical Abstract summarizes these findings.

Introduction: In the general population, medication nonadherence contributes to poorer outcomes. However, little is known about medication adherence among adults with chronic kidney disease (CKD). We evaluated the association of self-reported medication adherence with CKD progression and all-cause death in patients with CKD. Methods: In this prospective observational study of 3305 adults with mild-to-moderate CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study, the baseline self-reported medication adherence was assessed by responses to 3 questions and categorized as high, medium, and low. CKD progression (50% decline in eGFR or incident end-stage renal disease) and all-cause death were measured using multivariable Cox proportional hazards. Results: Of the patients, 68% were categorized as high adherence, 17% medium adherence, and 15% low adherence. Over a median follow-up of 6 years, there were 969 CKD progression events and 675 deaths. Compared with the high-adherence group, the low-adherence group experienced increased risk for CKD progression (hazard ratio = 1.27, 95% confidence interval = 1.05, 1.54) after adjustment for sociodemographic and clinical factors, cardiovascular medications, number of medication types, and depressive symptoms. A similar association existed between low adherence and all-cause death, but did not reach standard statistical significance (hazard ratio = 1.14 95% confidence interval = 0.88, 1.47). Conclusion: Baseline self-reported low medication adherence was associated with an increased risk for CKD progression. Future work is needed to better understand the mechanisms underlying this association and to develop interventions to improve adherence. Keywords: CKD, death, medication adherence, progression

Chronic kidney disease (CKD) is associated with an increased risk of cognitive decline, but the mechanisms remain poorly defined. We sought to determine the relation between serum inflammatory markers and risk of cognitive decline among adults with CKD. Methods: We studied 757 adults aged ≥55 years with CKD participating in the Chronic Renal Insufficiency Cohort Cognitive study. We measured interleukin (IL)−1β, IL-1 receptor antagonist, IL-6, tumor necrosis factor (TNF)−α, high-sensitivity C-reactive protein (hs-CRP), and fibrinogen in baseline plasma samples. We assessed cognitive function at regular intervals in 4 domains and defined incident impairment as a follow-up score more than 1 SD poorer than the group mean. Results: The mean age of the sample was 64.3 ± 5.6 years, and the mean follow-up was 6.2 ± 2.5 years. At baseline, higher levels of each inflammatory marker were associated with poorer age-adjusted performance. In analyses adjusted for baseline cognition, demographics, comorbid conditions, and kidney function, participants in the highest tertile of hs-CRP, the highest tertile of fibrinogen, and the highest tertile of IL-1β had an increased risk of impairment in attention compared to participants in the lowest tertile of each marker. Participants in the highest versus lowest tertile of TNF-α had a lower adjusted risk of impairment in executive function. There was no association between other inflammatory markers and change in cognitive function. Discussion: Among adults with CKD, higher levels of hs-CRP, fibrinogen, and IL-1β were associated with a higher risk of impairment in attention. Higher levels of TNF-α were associated with a lower risk of impaired executive function.

Designers of energy systems often face challenges in balancing the trade-off between cost and reliability. In literature, several papers have presented mathematical models for optimizing the reliability and cost of energy systems. However, the previous models only addressed reliability implicitly, i.e., based on availability and maintenance planning. Others focused on allocation of reliability based on individual equipment requirements via non-linear models that require high computational effort. This work proposes a novel mixed-integer linear programming (MILP) model that combines the use of both input-output (I-O) modelling and linearized parallel system reliability expressions. The proposed MILP model can optimize the design and reliability of energy systems based on equipment function and operating capacity. The model allocates equipment with sufficient reliability to meet system functional requirements and determines the required capacity. A simple pedagogical example is presented in this work to illustrate the features of proposed MILP model. The MILP model is then applied to a polygeneration case study consisting of two scenarios. In the first scenario, the polygeneration system was optimized based on specified reliability requirements. The technologies chosen for Scenario 1 were the CHP module, reverse osmosis unit and vapour compression chiller. The total annualized cost (TAC) for Scenario 1 was 53.3 US$ million/year. In the second scenario, the minimum reliability level for heat production was increased. The corresponding results indicated that an additional auxiliary boiler must be operated to meet the new requirements. The resulting TAC for the Scenario 2 was 5.3% higher than in the first scenario.

We develop a linear programming (LP) model for optimizing enhanced weathering (EW) networks. EW is a negative emissions technology (NET) that involves mining and grinding of naturally occurring CO2-reactive rocks, and subsequently applying the resulting powder to soil to provide ample surface area for contact with the atmosphere and thus accelerate carbon fixation. Use of EW as a carbon management strategy at scale will result in the need to properly match sources (rock crushing plants) with sinks (application sites); the result is a special case of a supply chain optimization problem. The model proposed here can determine optimal matches of sources and sinks in EW-based CMNs, considering material flow and temporal constraints. A case study is solved to illustrate the model. Keywords: Negative emissions technology (NET), Carbon dioxide removal (CDR), Supply chain, Optimization, Carbon management network (CMN)

Human studies report conflicting results on the predictive power of serum lipids on the progression of chronic kidney disease. We aimed to systematically identify the lipids that predict progression to end-stage kidney disease. Methods: From the Chronic Renal Insufficiency Cohort, 79 patients with chronic kidney disease stages 2 to 3 who progressed to end-stage kidney disease over 6 years of follow-up were selected and frequency matched by age, sex, race, and diabetes with 121 nonprogressors with less than 25% decline in estimated glomerular filtration rate during the follow-up. The patients were randomly divided into training and test sets. We applied liquid chromatography-mass spectrometry-based lipidomics on visit year 1 samples. Results: We identified 510 lipids, of which the top 10 coincided with false discovery threshold of 0.058 in the training set. From the top 10 lipids, the abundance of diacylglycerols and cholesteryl esters was lower, but that of phosphatidic acid 44:4 and monoacylglycerol 16:0 was significantly higher in progressors. Using logistic regression models, a multimarker panel consisting of diacylglycerols and monoacylglycerol independently predicted progression. The c-statistic of the multimarker panel added to the base model consisting of estimated glomerular filtration rate and urine protein-to-creatinine ratio as compared with that of the base model was 0.92 (95% confidence interval: 0.88–0.97) and 0.83 (95% confidence interval: 0.76–0.90, P < 0.01), respectively, an observation that was validated in the test subset. Discussion: We conclude that a distinct panel of lipids may improve prediction of progression of chronic kidney disease beyond estimated glomerular filtration rate and urine protein-to-creatinine ratio when added to the base model.

Aim: In hemodialysis patients, the need to have intercurrent sodium and water intake removed by ultrafiltration increases disease burden through the symptoms and signs that occur during hemodialysis (HD). This added burden may be mitigated by reduction of dietary sodium intake. The National Kidney Foundation (NKF) recommends 2400 mg of dietary sodium daily for patients on HD, and the American Heart Association (AHA) suggests 1500 mg, evidence is lacking, however, to support these recommendations in HD. Moreover, little is known about the relationship of specific levels of dietary sodium intake and the severity of symptoms and signs during ultrafiltration. Our goal will be to determine the effects of carefully-monitored levels of sodium-intake as set forth by the NKF and AHA on symptoms and signs in patients undergoing (HD). Methods: We designed a three-group (2400 mg, 1500 mg, unrestricted), double blinded randomized controlled trial with a sample of 42 HD participants to determine whether 1. Symptom profiles and interdialytic weight gains vary among three sodium intake groups; 2. The effect of HD-specific variables on the symptom profiles among the three groups and 3. Whether total body water extracellular volume and intracellular volume measured with bioimpedance varies across the three groups. We will also examine the feasibility of recruitment, enrollment, and retention of participants for the five-day inpatient stay. Conclusion: Curbing dietary sodium intake may lead to improvement in intradialytic symptom amelioration and potential for better long-term outcomes. Generating empirical support will be critical to ascertain, and espouse, the appropriate level of sodium intake for patients receiving HD.

One of the noncellular microenvironmental factors that contribute to malignancy of solid tumors is acidic peritumoral pH. We have previously demonstrated that extracellular acidosis leads to localization of the cysteine pro-tease cathepsin B on the tumor cell membrane and its secretion. The objective of the present study was to determine if an acidic extracellular pH such as that observed in vivo (i.e., pHe 6.8) affects the activity of proteases, e.g., cathepsin B, that contribute to degradation of collagen IV by tumor cells when grown in biologically relevant three-dimensional (3D) cultures. For these studies, we used 1) 3D reconstituted basement membrane overlay cultures of human carcinomas, 2) live cell imaging assays to assess proteolysis, and 3) in vivo imaging of active tumor proteases. At pHe 6.8, there were increases in pericellular active cysteine cathepsins and in degradation of dye-quenched collagen IV, which was partially blocked by a cathepsin B inhibitor. Imaging probes for active cysteine cathepsins localized to tumors in vivo. The amount of bound probe decreased in tumors in bicarbonate-treated mice, a treatment previously shown to increase peritumoral pHe and reduce local invasion of the tumors. Our results are consistent with the acid-mediated invasion hypothesis and with a role for cathepsin B in promoting degradation of a basement membrane protein substrate, i.e., type IV collagen, in an acidic peritumoral environment.

E-cadherin is a main component of the cell-cell adhesion junctions that play a principal role in maintaining normal breast epithelial cell morphology. Breast and other cancers that have up-regulated activity of Ras are often found to have down-regulated or mislocalized E-cadherin expression. Disruption of E-cadherin junctions and consequent gain of cell motility contribute to the process known as epithelial-to-mesenchymal transition (EMT). Enforced expression of E-cadherin or inhibition of Ras-signal transduction pathway has been shown to be effective in causing reversion of EMT in several oncogene-transformed and cancer-derived cell lines. In this study, we investigated MCF10A human breast epithelial cells and derivatives that were transformed with either activated H-Ras or N-Ras to test for the reversion of EMT by inhibition of Ras-driven signaling pathways. Our results demonstrated that inhibition of mitogen-activated protein kinase (MAPK) kinase, but not PI3-kinase, Rac, or myosin light chain kinase, was able to completely restore E-cadherin cell-cell junctions and epithelial morphology in cell lines with moderate H-Ras expression. In MCF10A cells transformed by a high-level expression of activated H-Ras or N-Ras, restoration of E-cadherin junction required both the enforced reexpression of E-cadherin and suppression of MAPK kinase. Enforced expression of E-cadherin alone did not induce reversion from the mesenchymal phenotype. Our results suggest that Ras transformation has at least two independent actions to disrupt E-cadherin junctions, with effects to cause both mislocalization of E-cadherin away from the cell surface and profound decrease in the expression of E-cadherin.

Overexpression of p21-activated kinase 1 (PAK1) occurs during the progression of human breast cancer. We have investigated the role of PAK1 in the premalignant progression of the MCF10 series of human breast epithelial cell lines. Levels of PAK1 expression and activation increased with premalignant progression, and expression of dominant-negative (DN) PAK1 reduced both cell proliferation and migration/invasion. In three-dimensional (3D) overlay cultures in reconstituted basement membrane, the MCF10 series produced an in vitro model for premalignant progression. MCF10AneoT cells formed a hyperplastic morphology in which some spheroids developed abnormal lumens. The MCF10.AT1 line exhibited an atypical hyperplastic morphology of abnormal spheroid clusters that did not form lumens. The MCF10.DCIS cells exhibited dysplastic growth. Expression of DN-PAK1 promoted lumen formation in 3D-cultured MCF10A, NeoT, and AT1 structures, suggesting partial reversion of the premalignant phenotype, but did not affect the atypical budding of AT1 structures or the dysplastic growth of ductal carcinoma in situ structures. Aberrant proteolysis is another important characteristic of breast cancer progression and invasion. DN-PAK1 or knock-down of PAK1 reduced pericellular proteolysis of DQ-collagen IV in the 3D cultures. Treatment of cells with an inhibitor of Rac1 also reduced pericellular proteolysis, and this reduction was reversed by the expression of activated PAK1. Our conclusion is that overexpressed and activated PAK1 may be a key coordinator of aberrant cell survival and proteolysis in breast cancer progression.

The protein kinase, PAKi, is overexpressed in human breast cancer and may contribute to malignancy through induction of proliferation and invasiveness. In this study, we examined the role of PAKi in the survival of detached MCF10A breast epithelial cells to test whether it may also regulate the early stages of neoplasia. MCF10A cells undergo anoikis, as measured by the cleavage of caspase 3 and poly(ADPribose) polymerase (PARP), after more than 8 hours of detachment. Endogenous Akt, PAKi, BAD are phosphorylated in attached MCF10A cells, but these phosphorylation events are all lost during the first 8 hours of detachment. Expression of constitutively active PAKi or Akt suppresses the cleavage of caspase 3 and PARP in detached MCF10A cells. Cooverexpression of active PAKi with dominant-negative Akt, or of active Akt with dominant-negative PAKi, still suppresses anoikis. Thus, Akt and PAKi enhance survival through pathways that are at least partially independent. PAKi-dependent regulation of anoikis is likely to occur early in the apoptotic cascade as expression of dominant-negative PAKi increased the cleavage of the upstream caspase 9, while constitutively active PAKi inhibited caspase 9 activation. These results support a role for activated PAKi in the suppression of anoikis in MCF10A epithelial cells.