DSK1, a novel kinesin-related protein from the diatom Cylindrotheca fusiformis that is involved in anaphase spindle elongation.

We have identified an 80-kD protein that is involved in mitotic spindle elongation in the diatom Cylindrotheca fusiformis. DSK1 (Diatom Spindle Kinesin 1) was isolated using a peptide antibody raised against a conserved region in the motor domain of the kinesin superfamily. By sequence homology, DSK1 belongs to the central motor family of kinesin-related proteins. Immunoblots using an antibody raised against a non-conserved region of DSK1 show that DSK1 is greatly enriched in mitotic spindle preparations. Anti-DSK1 stains in diatom central spindle with a bias toward the midzone, and staining is retained in the spindle midzone during spindle elongation in vitro. Furthermore, preincubation with anti-DSK1 blocks function in an in vitro spindle elongation assay. This inhibition of spindle elongation can be rescued by preincubating concurrently with the fusion protein against which anti-DSK1 was raised. We conclude that DSK1 is involved in spindle elongation and is likely to be responsible for pushing hal-spindles apart in the spindle midzone

Monotone Control of Queueing and Production/Inventory Systems

Weber and Stidham (1987) used submodularity to establish transition monotonicity (a service completion at one station cannot reduce the service rate at another station) for Markovian queueing networks that meet certain regularity conditions and are controlled to minimize service and queueing costs. We give an extension of monotonicity to other directions in the state space, such as arrival transitions, and to arrival routing problems. The conditions used to establish monotonicity, which deal with the boundary of the state space, are easily verified for many queueing systems. We also show that, without service costs, transition-monotone controls can be described by simple control regions and switching functions, extending earlier results. The theory is applied to production/inventory systems with holding costs at each stage and finished goods backorder costs

Optimal Control of Two-Station Tandem Production/Inventory System

A manufacturing facility consisting of two stations in tandem operates in a maketo-stock mode: after production, items are placed in a finished goods inventory that services an exogenous demand. Demand that cannot be met from inventory is backordered. Each station is modelled as a queue with controllable production rate, and the problem is to control these rates to minimize inventory holding and backordering costs. Optimal controls are computed using dynamic programming and compared with kanban and buffer control mechanisms, popular in manufacturing, and with the base stock mechanism popular in inventory/distribution systems. Conditions are found under which certain simple controls are optimal using stochastic coupling arguments. Insights are gained into when to hold work-in-process and finished goods inventory, comparable to previous studies of production lines in make-to-order and unlimited demand ("push") environments

Schnurri-3 (KRC) Interacts with c-Jun to Regulate the IL-2 Gene in T Cells

The activator protein 1 (AP-1) transcription factor is a key participant in the control of T cell proliferation, cytokine production, and effector function. In the immune system, AP-1 activity is highest in T cells, suggesting that a subset of T cell–specific coactivator proteins exist to selectively potentiate AP-1 function. Here, we describe that the expression of Schnurri-3, also known as κ recognition component (KRC), is induced upon T cell receptor signaling in T cells and functions to regulate the expression of the interleukin 2 (IL-2) gene. Overexpression of KRC in transformed and primary T cells leads to increased IL-2 production, whereas dominant-negative KRC, or loss of KRC protein in KRC-null mice, results in diminished IL-2 production. KRC physically associates with the c-Jun transcription factor and serves as a coactivator to augment AP-1–dependent IL-2 gene transcription

Detecting Bioterror Attacks by Screening Blood Donors: A Best-Case Analysis

To assess whether screening blood donors could provide early warning of a bioterror attack, we combined stochastic models of blood donation and the workings of blood tests with an epidemic model to derive the probability distribution of the time to detect an attack under assumptions favorable to blood donor screening. Comparing the attack detection delay to the incubation times of the most feared bioterror agents shows that even under such optimistic conditions, victims of a bioterror attack would likely exhibit symptoms before the attack was detected through blood donor screening. For example, an attack infecting 100 persons with a noncontagious agent such as Bacillus anthracis would only have a 26% chance of being detected within 25 days; yet, at an assumed additional charge of $10 per test, donor screening would cost$139 million per year. Furthermore, even if screening tests were 99.99% specific, 1,390 false-positive results would occur each year. Therefore, screening blood donors for bioterror agents should not be used to detect a bioterror attack

Detecting Bioterror Attacks by Screening Blood Donors: A Best-Case Analysis

To assess whether screening blood donors could provide early warning of a bioterror attack, we combined stochastic models of blood donation and the workings of blood tests with an epidemic model to derive the probability distribution of the time to detect an attack under assumptions favorable to blood donor screening. Comparing the attack detection delay to the incubation times of the most feared bioterror agents shows that even under such optimistic conditions, victims of a bioterror attack would likely exhibit symptoms before the attack was detected through blood donor screening. For example, an attack infecting 100 persons with a noncontagious agent such as Bacillus anthracis would only have a 26% chance of being detected within 25 days; yet, at an assumed additional charge of $10 per test, donor screening would cost$139 million per year. Furthermore, even if screening tests were 99.99% specific, 1,390 false-positive results would occur each year. Therefore, screening blood donors for bioterror agents should not be used to detect a bioterror attack

Geometry: The leading parameter for the Poisson’s ratio of bending-dominated cellular solids

Control over the deformation behaviour that a cellular structure shows in response to imposed external forces is a requirement for the effective design of mechanical metamaterials, in particular those with negative Poisson’s ratio. This article sheds light on the old question of the relationship between geometric microstructure and mechanical response, by comparison of the deformation properties of bar-and-joint-frameworks with those of their realisation as a cellular solid made from linear-elastic material. For ordered planar tessellation models, we find a classification in terms of the number of degrees of freedom of the framework model: first, in cases where the geometry uniquely prescribes a single deformation mode of the framework model, the mechanical deformation and Poisson’s ratio of the linearly-elastic cellular solid closely follow those of the unique deformation mode; the result is a bending-dominated deformation with negligible dependence of the effective Poisson’s ratio on the underlying material’s Poisson’s ratio and small values of the effective Young’s modulus. Second, in the case of rigid structures or when geometric degeneracy prevents the bending-dominated deformation mode, the effective Poisson’s ratio is material-dependent and the Young’s modulus View the MathML sourceE˜cs large. All analysed structures of this type have positive values of the Poisson’s ratio and large values of View the MathML sourceE˜cs. Third, in the case, where the framework has multiple deformation modes, geometry alone does not suffice to determine the mechanical deformation. These results clarify the relationship between mechanical properties of a linear-elastic cellular solid and its corresponding bar-and-joint framework abstraction. They also raise the question if, in essence, auxetic behaviour is restricted to the geometry-guided class of bending-dominated structures corresponding to unique mechanisms, with inherently low values of the Young’s modulus

Mathematical modeling of the dynamics of the bladder cancer and the immune response applied to a patient: Evolution and short-term prediction

[EN] Bladder cancer is one of the most common malignant diseases in the urinary system and a highly aggressive neoplasm. The prognosis is not favorable usually, and its evolution for particular patients is very difficult to find out. In this paper, we propose a dynamic mathematical model that describes the bladder tumor growth and the immune response evolution. This model is customized for a single patient, determining appropriate model parameter values via model calibration. Due to the uncertainty of the tumor evolution, using the calibrated model parameters, we predict the tumor size and the immune response evolution over the next few months assuming three different scenarios: favorable, neutral, and unfavorable. In the former, it is not expected any trace of the cancer in the middle of September 2018 (after 16 mo). In the neutral scenario, at the same date, a 7- to 8-mm tumor is expected. In the worst case, a 40-mm tumor is expected. The patient was cited on 10 September 2018 to check the tumor size, and according to the doctors, there was no sign of recurrence. It seems that we are in the favorable scenario. The patient will be called again for follow-up in mid-2019.This work has been supported by the Ministerio de Economía, Industria y Competitividad grant MTM2017-89664-P.Burgos-Simon, C.; García-Medina, N.; Martínez-Rodríguez, D.; Villanueva Micó, RJ. (2019). Mathematical modeling of the dynamics of the bladder cancer and the immune response applied to a patient: Evolution and short-term prediction. Mathematical Methods in the Applied Sciences. 42(17):5746-5757. https://doi.org/10.1002/mma.5536S574657574217Official Site for Spanish Medic Oncology Society.https://www.seom.org. Accessed: 25/09/2018.Greenlee, R. T., Hill-Harmon, M. B., Murray, T., & Thun, M. (2001). Cancer Statistics, 2001. CA: A Cancer Journal for Clinicians, 51(1), 15-36. doi:10.3322/canjclin.51.1.15Holmang, S., Hedelin, H., Anderstrom, C., & Johansson, S. L. (1995). The Relationship Among Multiple Recurrences, Progression and Prognosis of Patients with Stages TA and T1 Transitional Cell Cancer of the Bladder Followed for at least 20 years. Journal of Urology, 153(6), 1823-1827. doi:10.1016/s0022-5347(01)67321-xRedelman-Sidi, G., Glickman, M. S., & Bochner, B. H. (2014). The mechanism of action of BCG therapy for bladder cancer—a current perspective. Nature Reviews Urology, 11(3), 153-162. doi:10.1038/nrurol.2014.15Bladder Cancer Treatment (PDQ)‐Health Professional Version.https://www.cancer.gov/types/bladder/hp/bladder-treatment-pdq. Accessed: 25/09/2018.Bladder Cancer Treatment (PDQ)‐Patient Version.https://www.cancer.gov/types/bladder/patient/bladder-treatment-pdq. Accessed: 25/09/2018.Official Site for Hospital Universitari i Politècnic La Fe Valencia Spain.http://www.hospital-lafe.com. Accessed: 25/09/2018.Hanahan, D., & Weinberg, R. A. (2011). Hallmarks of Cancer: The Next Generation. Cell, 144(5), 646-674. doi:10.1016/j.cell.2011.02.013Dong, H., Strome, S. E., Salomao, D. R., Tamura, H., Hirano, F., Flies, D. B., … Chen, L. (2002). Tumor-associated B7-H1 promotes T-cell apoptosis: A potential mechanism of immune evasion. Nature Medicine, 8(8), 793-800. doi:10.1038/nm730Fernandez, N. C., Lozier, A., Flament, C., Ricciardi-Castagnoli, P., Bellet, D., Suter, M., … Zitvogel, L. (1999). Dendritic cells directly trigger NK cell functions: Cross-talk relevant in innate anti-tumor immune responses in vivo. Nature Medicine, 5(4), 405-411. doi:10.1038/7403Factsheet of OncoTICE 2 − 8 × 108UFC powder for suspension intravesical (in Spanish).https://www.aemps.gob.es/cima/pdfs/es/ft/61377/61377_ft.pdf. Accessed: 25/09/2018