Continuous improvements of cell-free synthesis (CFS) systems have generated interest in adopting the technology for the manufacture of biologics. This paper provides an evaluation of the manufacturing cost-effectiveness of CFS for a range of commercial scenarios. The evaluation was performed using an advanced techno-economic engine (TEE) built in Python. The TEE is programmed in an object-oriented environment capable of simulating a plethora of process flowsheets and predicting size and cost metrics for the process and the facility. A case study was formulated to compare the economics of whole bioprocesses based on either a CFS system or a mammalian cell system (CHO) for the manufacture of an antibody drug conjugate (ADC) at different commercial product demand levels (100 – 1000kg/year). The analysis demonstrated the potential of CFS for the commercial manufacture of biologics and identified key cost drivers related with the system. The CFS system showed approximately a two-fold increase in the cost of goods compared to CHO with a significant cost attributed to the in-house manufacture of the bacterial cell extract, necessary for the CFS reaction step in the process. A sensitivity and target analysis highlighted the impetus for further process improvements especially in the titre for the CFS process to become more competitive against well-established systems.

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We read with great interest the article by Khashkhusha TR et al “ACE inhibitors and COVID-19: We don’t know yet”. The authors discuss whether the use of angiotensin-converting enzyme (ACE) inhibitors (ACEIs) in novel coronavirus disease‐19 (COVID‐19) patients is beneficial or harmful. ACEIs and angiotensin receptor antagonists (ARBs) both upregulate ACE2 levels. We believe that ARBs should be preferred since, unlike ARBs, ACEIs may increase angiotensin II through the chymase pathway. We would like to discuss potential harms ACEI may cause through secondary bradykinin-chymase pathways.

Purpose: To evaluate the prognostic factors affecting surgical margin and recurrence in patients who underwent partial nephrectomy for renal masses. Materials and Methods: Data of 125 patients who underwent open or laparoscopic partial nephrectomy due to renal mass between January 2006 and January 2019 were analyzed retrospectively. Demographic data, habits, additional diseases, clinical and laboratory findings, operational data, the morphology of the tumor in computerized tomography or magnetic-resonance imaging and follow-up data were scanned and acquired via our hospital’s system and archive. Results: Average age was 54.4, male-female ratio was 1.55 and average tumor size was 3.31 cm. 104 patients had malignant pathology and 21 was benign. Positive surgical margin rate was 5.6% and recurrence rate was 3.2%. Average follow-up was 47.4 months. Pathological size of the tumor was larger (p=0.006), warm-ischemia period was lower (p=0.003), and PADUA score was higher (p=0.015) in open technique. Tumor size and tumor stage were statistically higher in patients with recurrence (p=0.009, p<0.001 respectively). No statistically significant difference was observed between surgical margin positivity and tumor size, Fuhrman grades, PADUA scores, R.E.N.A.L. scores, and C-index. (p>0.05) Conclusion: Surgical margin positivity after partial nephrectomy is not significantly associated with tumor characteristics and anatomical scoring systems. Tumor size and stage after partial nephrectomy are valuable parameters in evaluating the recurrence risk. Keywords: nephrectomy, recurrence, margins of excision, prognosis

Background and Aim: Despite transrectal ultrasound (TRUS) being regarded as gold-standard for prostate volume estimation, concerns have been raised in literature concerning its accuracy especially in men with above-average prostate volumes. We aimed to evaluate the performance of TRUS for prostate volume estimation in a cohort of sub-Saharan African men since they are known to have relatively large mean prostate volumes. Methods: This was a prospective study of 77 sub-Saharan African men who had open simple prostatectomy for Benign Prostate Hyperplasia (BPH). Pre-operative TRUS determined total prostate volume (TPV) and transition zone volume (TZV). Following surgical enucleation, the adenoma was weighed (EPW) and its volume (EPV) also determined by fluid displacement. TRUS was repeated six weeks post-operatively to calculate the TRUS-estimated specimen volume (TESV). Results: The mean EPV, EPW, TRUS-estimated TZV, TRUS-estimated TPV and TESV were 79.1 ± 62.9mls, 79.1 ± 62.9g, 53.3 ± 28.5mls, 93.1 ± 48.9mls and 69.9 ± 44.6mls respectively. Pearson’s correlation showed perfect relationship between EPW and EPV with no difference in their mean values (r=1.000; P<0.001). Pearson’s correlation between TRUS-estimated TPV vs EPV, TRUS-estimated TZV vs EPV, and between TESV vs EPV were 0.932, 0.865 and 0.930 respectively (p = 0.0000). TRUS significantly under-estimated the TZV and TESV by 25.8ml and 9.2ml respectively; unrelated to severity of prostate enlargement. Conclusion: TRUS underestimates prostate volume, independent of prostate size. We propose simple formulae that could be used to improve the prostate volume determination from TRUS, especially if magnetic resonance imaging is not readily available or contraindicated.

The coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 infections has led to substantial unmet need for treatments, many of which will require testing in appropriate animal models of this disease. Vaccine trials are already underway, but there remains an urgent need to find other therapeutic approaches to either target SARS-CoV-2 or the complications arising from viral infection, particularly the dysregulated immune response and systemic complications which have been associated with progression to severe COVID-19. At the time of writing, in vivo studies of SARS-CoV-2 infection have been described using macaques, cats, ferrets, hamsters, and transgenic mice expressing human angiotensin I converting enzyme 2 (ACE2). These infection models have already been useful for studies of transmission and immunity, but to date only partially model the mechanisms implicated in human severe COVID-19. There is therefore an urgent need for development of animal models for improved evaluation of efficacy of drugs identified as having potential in the treatment of severe COVID-19. These models need to recapitulate key mechanisms of COVID-19 severe acute respiratory distress syndrome and reproduce the immunopathology and systemic sequelae associated with this disease. Here, we review the current models of SARS-CoV-2 infection and COVID-19-related disease mechanisms and suggest ways in which animal models can be adapted to increase their usefulness in research into COVID-19 pathogenesis and for assessing potential treatments.

IntroductionDespite advances in clinical intervention and drug treatment, cardiovascular disease (CVD) remains a leading cause of mortality worldwide except Africa [1]. According to the Global Burden of Disease Study 2016, the CVD resulted in 17.6 million deaths in 2016, which increased by 14.5% between 2006 and 2016 [2]. As the prevalence of chronic diseases increases steeply with age, it is crunch time for us to understand the biology of CVD and make effort to find new strategies for clinical intervention.However, the pathological process of cardiovascular disease is very complicated, including the control of oxidative stress, inflammation, angiogenesis, cell proliferation, atherosclerosis, tissue repairing and cardiac electrophysiology. In addition to the differential expression of genes, the regulation network of these pathological changes also involves the multiple molecules such as miRNA, lncRNA, and exosomes. Different molecules form a thorough interaction network to jointly regulate the development of CVD.Importantly, mounting evidence suggested significant roles of bioactive small molecules (BSMs) in cardiovascular system. BSMs, which include gaseous signal molecules, small molecules proteins, active peptides, active amino acids and derivatives, amines, lipids, metal ions, etc., play pivotal roles as signaling messengers maintaining cardiovascular homeostasis and in the pathogenesis of many cardiovascular disorders [3, 4]. Therefore, elucidating the dynamic changes and mutual regulatory networks of BSMs and studying their physiological functions of the heart will help reveal important molecular events and explore potential drug targets in the development of cardiovascular disease. It is no exaggeration to say that BSMs provide new insights for the prevention and treatment of cardiovascular diseases.This review summarizes five main features of BSMs in cardiovascular research after a short introduction about the current understanding of BSMs and then analyses current advances and challenges of BSMs in drug discovery and other application in cardiovascular diseases.

Quantitative systems pharmacology (QSP) is a relatively new discipline within modelling and simulation that has gained wide attention over the past few years. The application of QSP models spans drug-target identification and validation, through all drug development phases as well as clinical applications. Due to their detailed mechanistic nature, QSP models are capable of extrapolating knowledge to predict outcomes in scenarios that have not been tested experimentally making them an important resource in experimental and clinical pharmacology. However, these models are complicated to work with due to their size and inherent complexity. This makes many applications of QSP models for simulation, parameter estimation and trial design computationally intractable. A number of techniques have been developed to simplify QSP models into smaller models that are more amenable to further analyses while retaining their accurate predictive capabilities. Different simplification techniques have different strengths and weaknesses and hence different utilities. Understanding the utilities of different methods is essential for selection of the best method for a particular situation. In this paper, we have created an overall framework for model simplification techniques that allows a natural categorisation of methods based on their utility. We provide a brief description of the concept underpinning the different methods and example applications. A summary of the utilities of methods is intended provide a guide to modellers in their model endeavours to simplify these complicated models.

Due to COVID-19 global pandemic, treatment with HCQ, although controversial, has been widely prescribed. The aim of our study was to identify drug-drug interactions (DDI) between HCQ and long-term treatments of COVID-19 patients, focusing on drugs which can cause or promote QT prolongation. From March 13 to April 14 2020, 61 patients were treated with HCQ in our hospital. More than a half of patients (62%) had at least one DDI between HCQ and their long-term treatments. A large number of drug classes were involved, included contraindicated drugs The mean of co-medication contraindicated or not recommended with HCQ per patient was 1.9 CI95% [1.48 to 2.27]. All contraindicated drugs were discontinued at the beginning of HCQ treatment due to multidisciplinary meetings involving physicians and clinical pharmacists. To our knowledge this is the first study about DDI between HCQ and long-term treatments of COVID-19 patients.

Stroke is a devastating complication following coronary artery bypass grafting, which thankfully occurs with low incidence. The role of preoperative carotid ultrasound remains unclear. Whilst it is a cheap and reliable way of diagnosing carotid stenosis, it is unclear if and how this knowledge should impact on subsequent patient management. The evidence overall suggests that patients with severe carotid stenosis are likely to have an increased incidence of postoperative stroke -- however, the prevalence of severe carotid stenosis is low, and even in this cohort of patients, the incidence is not particularly high. In screened patients identified to have severe carotid stenosis, there appears to be a generally low appetite for undertaking carotid intervention internationally either prior to or concurrently with the coronary artery bypass grafting. Putting this all together, the widespread screening of asymptomatic patients would appear to not be justified.

Dear Editors,Sriram et al., recently argued that an imbalance between angiotensin converting enzyme-1 (ACE1) and ACE2 explained why only a small proportion of those infected with SARS-CoV-2 develop severe COVID-19 disease (Sriram & Insel, 2020). Their theory provides a parsimonious explanation for why all around the world severe COVID-19 is closely linked to older ages as well as certain comorbidities such as hypertension, diabetes, obesity and heart failure but not others such as asthma, COPD and HIV (Sriram & Insel, 2020). Older age as well as hypertension, diabetes, obesity and heart failure are all associated with a relative upregulation of the pro-inflammatory ACE1/angiotensin II/angiotensin 2 receptor 1-axis and downregulation of the anti-inflammatory ACE2/angiotensin (1-7)/Mas axis. This imbalance is aggravated by SARS-CoV-2 which uses ACE2 for cell entry and results in downregulation of ACE2 expression in alveolar cells and elsewhere. Individuals with this ACE1 proinflammatory, pro-apoptotic, pro-fibrotic bias are more likely to respond to COVID-19 with an untargeted, hyperinflammatory response that can progress to an acute respiratory distress syndrome-type illness before their adaptive immune system can adequately respond to the viral infection (Sriram & Insel, 2020). Individuals with a balanced ACE1/ACE2 system by contrast do not develop this hyperinflammatory response and are able to mount an effective immune response and eradicate the virus with few or no symptoms.Whilst this is likely a simplification of the pathophysiology of severe COVID-19, it does potentially offer a cheap, low risk strategy for whole populations to reduce their risk of severe COVID-19 – exercise. A number of studies in a range of animals, including humans, have found that exercise results in a number of health and metabolic benefits including upregulating ACE2 and downregulating ACE1 (Echeverria-Rodriguez, Gallardo-Ortiz, Del Valle-Mondragon, & Villalobos-Molina, 2020; Magalhaes et al., 2020). One study for example estimated that every hour run prolongs one’s life by 7 hours (Lee et al., 2017). These considerations led us to add to the hypothesis of Sriram et al., that the promotion of exercise, particularly in those at risk for severe COVID-19 will reduce the probability of them developing severe COVID-19. The available evidence is that both moderate- and high intensity aerobic exercise result in the rapid upregulation of the ACE2 versus ACE1 axis (Magalhaes et al., 2020). Randomized controlled trials in animal models of COVID-19 (Chan et al., 2020) or high-risk groups of humans would be required to test if this is protective against severe COVID-19 as well as to ascertain what the optimal training regimens for specific risk profiles would be. Pending these studies, a reasonable argument could made that the health benefits of exercise in these risk groups are so well established that this novel hypothesis could still be shared with target groups (Lee et al., 2017).

Background: Minimally invasive mitral valve replacement has become popular across the world. However, annular rupture and patient – prosthetic mismatch (PPM) are still problematic, particularly in the Asian population. To avoid this, a predictor model could be beneficial. Our study aimed to assess the value of mitral valve diameters measured on TTE and CT scan on predicting the actual mitral prostheses. Methods: From January 2018 to December 2019, a total number of 96 patients underwent minimally invasive mitral valve replacement. The association between imaging measurements with the outcome was checked by scatter plot and Pearson’s correlation coefficient. Univariable linear regression was used to build the prediction model. Results: The three strongest correlation for the whole population are the following features: Mean TTE diameter (0.702), mean diameter on CT lowest plane through the mitral annulus (0.679), area-derived diameter on CT highest plane through the mitral annulus (0.665). The prosthetic size of the tissue valve group seemed to be more correlated to the calculated annulus diameters than that of the mechanical valve group. Tissue valve size predictor models based on these calculated diameters were 16.19 + 0.27  d (r = 0.744), 12.74 + 0.44  d (r = 0.756) and 12.79 + 0.38  d (r = 0.730), respectively. Conclusion: Mitral prosthetic size could be predicted with the mitral diameters measured on TTE and CT scan. The overall correlation coefficient varied from 0.665 (CT Scan) to 0.702 (TTE). These models performed better when applied to bioprosthesis.

The sedimentation of dilute particle suspensions in a channel flow into a cavity at finite Reynolds number is analysed numerically using a coupled lattice Boltzmann method with the discrete element method. The effects of fluid inertia, particle density and cavity size on the trap efficiency in the cavity are systematically investigated. The results show that decreasing the Reynolds number, and increasing the length and depth of the cavity all lead to an increase in the trap efficiency. A close examination of the trajectory of particles reveals three distinct dynamic behaviours in the cavity flow: i) resuspension, ii) circulation in the central vortex and iii) deposition near the tailing edge of the cavity. Three distinctive regimes were then identified using a dimensionless trap number Tp: a resuspension regime with Tp<1, a fully trapped regime with Tp>2.5, and a continuous circulating regime in between.

Techniques such as micro-tomography (µCT) and nuclear magnetic resonance (NMR) methods have been used to characterize porous media for decades. Magnetic Resonance Imaging (MRI) offers direct visualization of pore architecture through a vast number of pulse sequences. In this work, we tested the MRI pulse sequence Zero Echo Time (ZTE) in the study of sandstone and carbonate. ZTE has been used previously to image highly porous geological material with relative success. In this research, ZTE was used to study porous systems tighter than those previously reported. We show that ZTE can resolve not only pore systems, but also a combination of fractures and pores simultaneously. Additionally, Pore Cluster Analysis (PCA), combined with ZTE, can be used to analyze connectivity of relatively large volume core plugs. By combining Time-Domain NMR pore-size analysis and PCA, we show that careful selection of resolution is necessary to understand transport in porous media.

This work proposes a systematic approach for the design of formulated products incorporating consumer assessment and heuristic knowledge. The methodology is divided into two main phases: Consumer assessment and product realization. In the first part, product attributes valued by consumers and their interactions are identified through usability tests performed on a reference product, and fuzzy integral analysis. In the second phase, alternative product formulations are generated using a mixed-integer optimization approach, which incorporates heuristic rules regarding the choice of ingredients and their amounts. The results from the consumer assessment phase are transformed into additional heuristics and incorporated into the design. Using two commercial skin moisturizers as references, different alternative formulations are generated at a lab scale. Those formulations that included additional heuristics are shown to be more similar to the references. As a result, the incorporation of consumer preferences significantly reduced the time and resources spent on the design process.

Diverse engineering fields request flash calculations like isothermal flash, isenthalpic flash, and isentropic flash. They can be cast as minimization of a thermodynamic state-function and solved by Michelsen’s Q-function approach. Flash calculations for open systems, i.e. systems where chemical potentials are specified instead of the mole numbers for some components, also belong to this scope. By analyzing the construction of Q-functions through Legendre transforms, we extend this approach to the flash for open systems in the absence or presence of chemical reactions, resulting in general formulations for various specifications. For systems without reactions, the classical framework using mole numbers as independent variables is employed; for those with reactions, the modified-RAND framework is employed. We present examples for open systems at constant temperature and pressure. Using the Q-function minimization, we can solve multicomponent non-reactive or reactive systems at a specified chemical potential with quadratic convergence over a wide range of conditions.

Determining the conversion efficiency of thermal exergy into the work of separation is of great importance for distillation process. In this study, an ideal thermodynamic efficiency equation not containing physical property data was proposed for calculating the thermodynamic efficiency of the continuous distillation process of ideal binary mixture. Benzene-toluene mixture was taken as an ideal binary mixture, and the accurate and approximate thermodynamic efficiencies of the continuous distillation of benzene-toluene ideal mixture were calculated by the thermodynamic efficiency equation based on the relevant physical property data and the proposed ideal thermodynamic efficiency equation, respectively. The results showed that the difference between the calculated thermodynamic efficiencies was less than 5%, demonstrating the feasibility of calculating the thermodynamic efficiency of the continuous distillation process of ideal binary mixture using the ideal thermodynamic efficiency equation.

This article concerns with the thermoelastic corner-edge type system with singular potential function on a wedge manifold with corner singularities. First, we introduce weighted $p-$Sobolev spaces on manifolds with corner-edge singularities. Then, we prove the corner-edge type Sobolev inequality , Poincar$\acute{e}$ inequality and Hardy inequality and obtain some results about the compactness of embedding maps on the weighted corner-edge Sobolev spaces. Finally, as an application of these results, we apply the potential well theory and the Faedo-Galerkin approximations to obtain the global weak solutions for the thermoelastic corner-edge type system.

In the last three decades, we can see that an enthralling research topic that attracted the consideration of many researchers is mathematical modelling of biological systems. This paper is organised with the aim of getting some new simulations of lassa hemmorhagic fever; a deathly diseases in pregnant women via Caputo-Fabrizio fractional order derivative with the help of the Euler method. Lassa hemorrhagic fever is biocidal and epidemical disease, whose outbreaks were first conrmed in African countries. As compare to the Ebola virus this virus kills pregnant women’s more. On 8 January, Lassa virus was detached in Vero cell cultures from a blood sample, which was ejective to be 12 days after the invasion of the illness. In this manuscript, important lemma and theorems are considered to exhibit the existence and uniqueness analysis, stability of proposed fractional approximation method. Results are provided to conrm the effectiveness of used approximation method by graphical simulations for different values of β.

In this work a numerical technique, combination of Lucas and Fibonacci polynomials, is proposed for the solution of one- and two-dimensional nonlinear heat type equations. In first round, for discretization, finite difference has been used for time and Crank Nicolson scheme for spatial part. In second round, the unknown functions have been approximated by Lucas polynomial while their derivatives by Fibonacci polynomials. With the help of these approximations, the nonlinear partial differential equation transforms to a system of algebraic equations which can be solved easily. Convergence of the method has been investigated numerically. Performance of the method has been studied by taking one- and two-dimensional heat and burger equations. Efficiency of the technique has been investigated in terms of root mean square (RMS), L2 and L_infnty norms. The obtained results are then compared with those available in the literature.

In this article we analyze the evolutionary dynamics of the novel coronavirus epidemic (covid-19) using observed data from several cities and places in the world. We have used a SIR-type (Susceptible, Infectious and Recovered) model improved with some adaptions in order to increase its predictive skills, i.e., we have included the circulation restriction effect and considered a phenomenon we have called adherence zone, generating the Modified SIR model (ModSIR). Comparing the results produced with ModSIR with real observations obtained for several places in the world we have found that ModSIR presented good predictive skill, as long as combined with good enough parametric identification. At the end of this article we present a study in which we simulated an epidemic in a hypothetical city of 211000 inhabitants. We have extracted several useful conclusions by analyzing some epidemic scenarios in which we evaluate epidemic control by adopting the circulation restriction as a control variable.

Throughout the globe, mankind is in vastly infected situations due to a cruel and destructive virus called coronavirus (COVID-19). The pivotal aim of the present investigation is to analyze and examine the evolution of COVID-19 in India with the available data in two cases first from the beginning to 31st March and beginning to 23rd April in order to show its exponential growth in the crucial period. The present situation in India with respect to confirmed, active, recovered and deaths cases have been illustrated with the aid of available data. The species of novel virus and its stages of growth with respect some essential points are presented. The exponential growth of projected virus by the day-to-day base is captured in 2D plots to predict its developments and identify the needs to control its spread on mankind. Moreover, the SEIR model is considered to present some interesting consequences about COVID-19 within the frame of fractional calculus. A newly proposed technique called q-Homotopy analysis transform method (q-HATM) is hired to find the solution for the nonlinear system portraying projected model and also presented the existence and uniqueness of the obtained results with help of fixed point theory. The behaviour has been captured with respect to fractional order and time.

In this manuscript, by means of the technique of measures of weak noncompactness, we prove some fixed set results for the sum and the product of (p+1) multi-valued mappings Pp i=1 A Bi; acting on Banach algebras satisfying a certain sequential condition (P) under weak topology. In addition, by using a new definition of the multi-valued mapping I A ; we get new fixed set theorems for the mappings of the form I A 1 Pni =1 Bi under some suitable conditions on the operators A; B1; : : : ; Bp in Banach algebras. Applications to the theory of self-similarity are also given.

In the present scientific article, an efficient operational matrix based on the famous Bernstein polynomials is applied for the numerical solution of two-dimensional non-linear variable order reaction-diffusion equation in porous media with given initial and boundary conditions. An operational matrix is constructed for fractional variable order differentiation w.r.to space variable x,y and time t, so that our proposed model is converted into a system of non-linear algebraic equations with the help of collocation method, which can be solved employing the Newton-Iteration method. The salient features of the article are finding the stability analysis and error bounds of the proposed method and also the validation and the effectiveness of the method through the RMS, L∞ and L2 errors. The physical presentation of the these errors for considered twodimensional non-linear variable order reaction-diffusion with their exact solutions shows the method is too good for finding the solution of these kind of problems.