Analytic considerations in applying a general economic evaluation reference case to gene therapy

The concept of a reference case, first proposed by the US Panel on Cost-Effectiveness in Health and Medicine, has been used to specify the required methodological features of economic evaluations of health care interventions. In the case of gene therapy, there is a difference of opinion on whether a specific methodologic reference case is required. The aim of this paper is to provide a more detailed analysis of the characteristics of gene therapy and the extent to which these characteristics warrant modifications to the methods suggested in general reference cases for economic evaluation. We argue that a completely new reference case is not required, but propose a tailored checklist that can be used by analysts and decision-makers to determine which aspects of economic evaluation should be considered further, given the unique nature of gene therapy

Modeling and Optimization of Hybrid Fenton and Ultrasound Process for Crystal Violet Degradation Using AI Techniques

\ua9 2023 by the authors. This study conducts a comprehensive investigation to optimize the degradation of crystal violet (CV) dye using the Fenton process. The main objective is to improve the efficiency of the Fenton process by optimizing various physicochemical factors such as the Fe2+ concentration, H2O2 concentration, and pH of the solution. The results obtained show that the optimal dosages of Fe2+ and H2O2 giving a maximum CV degradation (99%) are 0.2 and 3.13 mM, respectively. The optimal solution pH for CV degradation is 3. The investigation of the type of acid for pH adjustment revealed that sulfuric acid is the most effective one, providing 100% yield, followed by phosphoric acid, hydrochloric acid, and nitric acid. Furthermore, the examination of sulfuric acid concentration shows that an optimal concentration of 0.1 M is the most effective for CV degradation. On the other hand, an increase in the initial concentration of the dye leads to a reduction in the hydroxyl radicals formed (HO•), which negatively impacts CV degradation. A concentration of 10 mg/L of CV gives complete degradation of dye within 30 min following the reaction. Increasing the solution temperature and stirring speed have a negative effect on dye degradation. Moreover, the combination of ultrasound with the Fenton process resulted in a slight enhancement in the CV degradation, with an optimal stirring speed of 300 rpm. Notably, the study incorporates the use of Gaussian process regression (GPR) modeling in conjunction with the Improved Grey Wolf Optimization (IGWO) algorithm to accurately predict the optimal degradation conditions. This research, through its rigorous investigation and advanced modeling techniques, offers invaluable insights and guidelines for optimizing the Fenton process in the context of CV degradation, thereby achieving the twin goals of cost reduction and environmental impact minimization

A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes

We developed a diabetes risk score using a novel analytical approach and tested its diagnostic performance to detect individuals at high risk of diabetes, by applying it to the Qatari population. A representative random sample of 5,000 Qataris selected at different time points was simulated using a diabetes mathematical model. Logistic regression was used to derive the score using age, sex, obesity, smoking, and physical inactivity as predictive variables. Performance diagnostics, validity, and potential yields of a diabetes testing program were evaluated. In 2020, the area under the curve (AUC) was 0.79 and sensitivity and specificity were 79.0% and 66.8%, respectively. Positive and negative predictive values (PPV and NPV) were 36.1% and 93.0%, with 42.0% of Qataris being at high diabetes risk. In 2030, projected AUC was 0.78 and sensitivity and specificity were 77.5% and 65.8%. PPV and NPV were 36.8% and 92.0%, with 43.0% of Qataris being at high diabetes risk. In 2050, AUC was 0.76 and sensitivity and specificity were 74.4% and 64.5%. PPV and NPV were 40.4% and 88.7%, with 45.0% of Qataris being at high diabetes risk. This model-based score demonstrated comparable performance to a data-derived score. The derived self-complete risk score provides an effective tool for initial diabetes screening, and for targeted lifestyle counselling and prevention programs.Peer reviewe

Mast cell tryptase stimulates myoblast proliferation; a mechanism relying on protease-activated receptor-2 and cyclooxygenase-2

<p>Abstract</p> <p>Background</p> <p>Mast cells contribute to tissue repair in fibrous tissues by stimulating proliferation of fibroblasts through the release of tryptase which activates protease-activated receptor-2 (PAR-2). The possibility that a tryptase/PAR-2 signaling pathway exists in skeletal muscle cell has never been investigated. The aim of this study was to evaluate whether tryptase can stimulate myoblast proliferation and determine the downstream cascade.</p> <p>Methods</p> <p>Proliferation of L6 rat skeletal myoblasts stimulated with PAR-2 agonists (tryptase, trypsin and SLIGKV) was assessed. The specificity of the tryptase effect was evaluated with a specific inhibitor, APC-366. Western blot analyses were used to evaluate the expression and functionality of PAR-2 receptor and to assess the expression of COX-2. COX-2 activity was evaluated with a commercial activity assay kit and by measurement of PGF₂α production. Proliferation assays were also performed in presence of different prostaglandins (PGs).</p> <p>Results</p> <p>Tryptase increased L6 myoblast proliferation by 35% above control group and this effect was completely inhibited by APC-366. We confirmed the expression of PAR-2 receptor <it>in vivo </it>in skeletal muscle cells and in satellite cells and <it>in vitro </it>in L6 cells, where PAR-2 was found to be functional. Trypsin and SLIGKV increased L6 cells proliferation by 76% and 26% above control, respectively. COX-2 activity was increased following stimulation with PAR-2 agonist but its expression remained unchanged. Inhibition of COX-2 activity by NS-398 abolished the stimulation of cell proliferation induced by tryptase and trypsin. Finally, 15-deoxy-Δ-^12,14-prostaglandin J₂(15Δ-PGJ₂), a product of COX-2-derived prostaglandin D₂, stimulated myoblast proliferation, but not PGE₂and PGF₂α.</p> <p>Conclusions</p> <p>Taken together, our data show that tryptase can stimulate myoblast proliferation and this effect is part of a signaling cascade dependent on PAR-2 activation and on the downstream activation of COX-2.</p

Natural selection on cork oak: allele frequency reveals divergent selection in cork oak populations along a temperature cline

A recent study of population divergence at neutral markers and adaptive traits in cork oak has observed an association between genetic distances at locus QpZAG46 and genetic distances for leaf size and growth. In that study it was proposed that certain loci could be linked to genes encoding for adaptive traits in cork oak and, thus, could be used in adaptation studies. In order to investigate this hypothesis, here we (1) looked for associations between molecular markers and a set of adaptive traits in cork oak, and (2) explored the effects of the climate on among-population patterns in adaptive traits and molecular markers. For this purpose, we chose 9-year-old plants originating from thirteen populations spanning a broad range of climatic conditions. Plants established in a common garden site were genotyped at six nuclear microsatellites and phenotypically characterized for six functional traits potentially related to plant performance. Our results supported the proposed linkage between locus QpZAG46 and genes encoding for leaf size and growth. Temperature caused adaptive population divergence in leaf size and growth, which was expressed as differences in the frequencies of the alleles at locus QpZAG46

Air quality and urban sustainable development: the application of machine learning tools

[EN] Air quality has an efect on a population¿s quality of life. As a dimension of sustainable urban development, governments have been concerned about this indicator. This is refected in the references consulted that have demonstrated progress in forecasting pollution events to issue early warnings using conventional tools which, as a result of the new era of big data, are becoming obsolete. There are a limited number of studies with applications of machine learning tools to characterize and forecast behavior of the environmental, social and economic dimensions of sustainable development as they pertain to air quality. This article presents an analysis of studies that developed machine learning models to forecast sustainable development and air quality. Additionally, this paper sets out to present research that studied the relationship between air quality and urban sustainable development to identify the reliability and possible applications in diferent urban contexts of these machine learning tools. To that end, a systematic review was carried out, revealing that machine learning tools have been primarily used for clustering and classifying variables and indicators according to the problem analyzed, while tools such as artifcial neural networks and support vector machines are the most widely used to predict diferent types of events. The nonlinear nature and synergy of the dimensions of sustainable development are of great interest for the application of machine learning tools.Molina-Gómez, NI.; Díaz-Arévalo, JL.; López Jiménez, PA. (2021). Air quality and urban sustainable development: the application of machine learning tools. 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Adaptive Pulse Width Control for Precise Positioning Under the Influence of Stiction and Coulomb Friction

For the robustness experiment, the friction is increased by increasing the sealing pressure. The PID control exhibits a large overshoot during the transient state, while the other controllers exhibit no overshoot, as shown in Figs. 4 and 5. In the SMC, errors are reduced very slowly and the steady-state error is relatively large as shown in Fig. 5. Settling times of the PID control, the TDC, and the TDSMC are 3.32 s, 2.96 s, and 1.94 s, respectively, as shown in Figs. 4{b) and 5(^). The PID control and the TDC perform very poorly and their settling times are increased by 90.8 and 105.6 percent, respectively, from their nominal values. On the other hand, the TDSMC performs very well and its settling time is increased only by 9 percent from the nominal value. Therefore, the TDSMC has the best performance robustness. Conclusions The TDSMC which is a combination of the TDC and the SMC is proposed for the system with unknown dynamics and disturbances. This method uses the idea of switching of the sliding mode control while reducing the chattering associated with it. Experiments on the position control of a DC motor system with stick-slip friction, were conducted to evaluate performances of the control algorithms. Experiments show that the TDSMC exhibits the best performance robustness and that the TDC and the TDSMC perform better than the PID control with an anti-windup filter and the integral sliding mode control. 227. Youcef-Touini, K., and Bobbet, J., 1991, &quot;Stability of Uncertain Linear Systems With Time Delay,&quot; ASME JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL, Vol. 113, pp. 558-567. Youcef-Toumi, K., and Ito, O., 1990, &quot;A Time Delay Controller for Systems With Unknown Dynamics,&quot; ASME JOURNAL OF DYNAMIC SYSTEMS, MEASURE- MENT, AND CONTROL, Vol. 112, Youcef-Toumi, K., and Reddy, S., 1992, &quot;Analysis of Linear Time Invariant Systems With Time Delay,&quot; ASME JOURNAL OF DYNAMIC SYSTEMS, MEASURE- MENT, AND CONTROL, Vol. 114, Youcef-Toumi, K., and Wu, S.-T., 1992, &quot;Input/Output Linearization Using Time Delay Control,&quot; ASME JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL, Vol. 114, pp. 10-19

Altering Chemosensitivity by Modulating Translation Elongation

BACKGROUND: The process of translation occurs at a nexus point downstream of a number of signal pathways and developmental processes. Modeling activation of the PTEN/AKT/mTOR pathway in the Emu-Myc mouse is a valuable tool to study tumor genotype/chemosensitivity relationships in vivo. In this model, blocking translation initiation with silvestrol, an inhibitor of the ribosome recruitment step has been showed to modulate the sensitivity of the tumors to the effect of standard chemotherapy. However, inhibitors of translation elongation have been tested as potential anti-cancer therapeutic agents in vitro, but have not been extensively tested in genetically well-defined mouse tumor models or for potential synergy with standard of care agents. METHODOLOGY/PRINCIPAL FINDINGS: Here, we chose four structurally different chemical inhibitors of translation elongation: homoharringtonine, bruceantin, didemnin B and cycloheximide, and tested their ability to alter the chemoresistance of Emu-myc lymphomas harbouring lesions in Pten, Tsc2, Bcl-2, or eIF4E. We show that in some genetic settings, translation elongation inhibitors are able to synergize with doxorubicin by reinstating an apoptotic program in tumor cells. We attribute this effect to a reduction in levels of pro-oncogenic or pro-survival proteins having short half-lives, like Mcl-1, cyclin D1 or c-Myc. Using lymphomas cells grown ex vivo we reproduced the synergy observed in mice between chemotherapy and elongation inhibition and show that this is reversed by blocking protein degradation with a proteasome inhibitor. CONCLUSION/SIGNIFICANCE: Our results indicate that depleting short-lived pro-survival factors by inhibiting their synthesis could achieve a therapeutic response in tumors harboring PTEN/AKT/mTOR pathway mutations

A projected decrease in lightning under climate change

Lightning strongly influences atmospheric chemistry, and impacts the frequency of natural wildfires. Most previous studies project an increase in global lightning with climate change over the coming century but these typically use parameterizations of lightning that neglect cloud ice fluxes, a component generally considered to be fundamental to thunderstorm charging. As such, the response of lightning to climate change is uncertain. Here, we compare lightning projections for 2100 using two parameterizations: the widely used cloud-top height (CTH) approach, and a new upward cloud ice flux (IFLUX) approach that overcomes previous limitations. In contrast to the previously reported global increase in lightning based on CTH, we find a 15% decrease in total lightning flash rate with IFLUX in 2100 under a strong global warming scenario. Differences are largest in the tropics, where most lightning occurs, with implications for the estimation of future changes in tropospheric ozone and methane, as well as differences in their radiative forcings. These results suggest that lightning schemes more closely related to cloud ice and microphysical processes are needed to robustly estimate future changes in lightning and atmospheric composition