Computational modeling of the effects of autophagy on amyloid-β peptide levels

Autophagy is an evolutionarily conserved intracellular process that is used for delivering proteins and organelles to the lysosome for degradation. For decades, autophagy has been speculated to regulate amyloid-β peptide (Aβ) accumulation, which is involved in Alzheimers disease (AD); however, specific autophagic effects on the Aβ kinetics only have begun to be explored. We develop a mathematical model for autophagy with respect to Aβ kinetics and perform simulations to understand the quantitative relationship between Aβ levels and autophagy activity. In the case of an abnormal increase in the Aβ generation, the degradation, secretion, and clearance rates of Aβ are significantly changed, leading to increased levels of Aβ. When the autophagic Aβ degradation is defective in addition to the increased Aβ generation, the Aβ-regulation failure is accompanied by elevated concentrations of autophagosome and autolysosome, which may further clog neurons. The model predicts that modulations of different steps of the autophagy pathway (i.e., Aβ sequestration, autophagosome maturation, and intralysosomal hydrolysis) have significant step-specific and combined effects on the Aβ levels and thus suggests therapeutic and preventive implications of autophagy in AD.K.H. acknowledges support by the Intramural Research Program of the NIH, National Heart, Lung and Blood Institute. K.H. was supported in part by a grant from the KRIBB Research Initiative Program (Korean Biomedical Scientist Fellowship Program), Korea Research Institute of Bioscience and Biotechnology, Republic of Korea. MYC acknowledges support from the National Research Foundation of Korea through the Basic Science Research Program (Grant No. 2019R1F1A1046285)

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide1, 2. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis3, 4, 5, several of which are currently in clinical trials6, 7, 8. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis

Guide-Path Design for Automated Guided Vehicles

AGVS(Automated Guided Vehicle Systems) in material handling have been used widely since late 1970s. Implementation of an AGVS generally requires substantial study to optimize the design and performance of guide-paths. Traditional mathematical approaches have been used with limited success to analyze AGVS. These approaches, however, do not provide a practical tool for guide-path designers. This paper presents a new approach based on rules in designing and assessing AGV guide-paths to improve the design of a closed-loop layout. A framework for the integrated approach is proposed, problem solving procedures are explained, and a case study is reported to demonstrate the framework. Deletion of seldom used guide-paths, and addition of bypasses to solve the congestion problem, are conducted interactively and iteratively through simulation experiments. To visualize the results, a graphic control program is developed and integrated with the AutoMod/AutoGram simulation package.clos

Rule-based Approach for the Design of AGV Path in CIMS

Implementation of AGVS (Automated Guided Vehicle System) in CIMS (Computer Integrated Manufacturing System) generally requires substantial study to optimize design and performance of the guide path. Traditional mathematical approaches have been used with limited success to analyze AGVS. These approaches, however, do not provide a practical opportunity to use by path designers. This paper presents a new approach based on Jules in designing and assessing AGV path to have better design of the closed-loop layout. A framework for the approach is proposed and a case study is reported to demonstrate the framework. Deletion of seldom used paths and addition of bypasses to solve the congestion problem are conducted automatically through simulation expefiments. To visualize die results a graphic control program is developed and integrated with AutoMod/AutoGram simulation package

Autophagy mediates phase transitions from cell death to life

Autophagy is a lysosomal degradation pathway, which is critical for maintaining normal cellular functions. Despite considerable advances in defining the specific molecular mechanism governing the autophagy pathway during the last decades, we are still far from understanding the underlying principle of the autophagy machinery and its complex role in human disease. As an alternative attempt to reinvigorate the search for the principle of the autophagy pathway, we in this study make use of the computer-aided analysis, complementing current molecular-level studies of autophagy. Specifically, we propose a hypothesis that autophagy mediates cellular phase transitions and demonstrate that the autophagic phase transitions are essential to the maintenance of normal cellular functions and critical in the fate of a cell, i.e., cell death or survival. This study should provide valuable insight into how interactions of sub-cellular components such as genes and protein modules/complexes regulate autophagy and then impact on the dynamic behaviors of living cells as a whole, bridging the microscopic molecular-level studies and the macroscopic cellular-level and physiological approaches

Effects of BIM-Based Construction of Prefabricated Steel Framework from the Perspective of SMEs

Small- and medium-sized enterprises (SMEs) are part of the building construction industry. Although many effect analyses of applying building information modeling (BIM) to projects have been conducted, analyses from the perspective of SMEs are lacking. We propose a BIM-based construction of prefabricated steel framework from the perspective of SMEs. We derive the essential functions of the system from the viewpoint of SMEs and verify the qualitative effect through a case analysis of prefabricated steel frame construction that is based on BIM. The following system functions and qualitative effects are analyzed according to project stages that are based on interviews of working groups participating in system development and case projects. (1) Preconstruction stage: extraction of fabrication drawing and review of shop drawing, (2) fabrication stage: prefabrication review, steel member removal, and field loading review, and (3) construction phase: integrated management of cost and schedule and quality management. The expected effects of applying the system are qualitatively and quantitatively analyzed through expert group interviews and surveys. For the quantitative analysis, an evaluation index is used for the end-user computing satisfaction survey. Further analysis of the finishing and installation work is required. Future research should also analyze the effect of system application on human resource management

Limited coagulation-diffusion dynamics in inflating spaces

We consider the one-dimensional coagulation–diffusion problem on a dynamical expanding linear lattice, in which the effect of the coagulation process is balanced by the dilatation of the distance between particles. Distances x(t) follow the general law ẋ (t) ∕ x (t) = α (1 + αt ∕ β) -1 with growth rate α and exponent β, describing both algebraic and exponential (β = ∞) growths. In the space continuous limit, the particle dynamics is known to be subdiffusive, with the diffusive length varying like t1∕2−β for β 1∕2. We interpret and characterize quantitatively this phenomenon as a second order phase transition between an absorbing state and a localized state where particles are not reactive. We furthermore investigate the case when space is discrete and use a generating function method to solve the time differential equation associated with the survival probability. This model is then compared with models of growth on geometrically constrained two-dimensional domains, and with the theory of fractional diffusion in the subdiffusive case. We found in particular a duality relation between the diffusive lengths in the inflating space and the fractional theory