Optimization Algorithms for Computational Systems Biology

Computational systems biology aims at integrating biology and computational methods to gain a better understating of biological phenomena. It often requires the assistance of global optimization to adequately tune its tools. This review presents three powerful methodologies for global optimization that fit the requirements of most of the computational systems biology applications, such as model tuning and biomarker identification. We include the multi-start approach for least squares methods, mostly applied for fitting experimental data. We illustrate Markov Chain Monte Carlo methods, which are stochastic techniques here applied for fitting experimental data when a model involves stochastic equations or simulations. Finally, we present Genetic Algorithms, heuristic nature-inspired methods that are applied in a broad range of optimization applications, including the ones in systems biology

Mechanistic models of α\alpha-synuclein homeostasis for Parkinson's disease: A blueprint for therapeutic intervention

Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide, yet there is no disease-modifying therapy up to this date. The biological complexity underlying PD hampers the investigation of the principal contributors to its pathogenesis. In this context, mechanistic models grounded in molecular-level knowledge provide virtual labs to uncover the primary events triggering PD onset and progression and suggest promising therapeutic targets. Multiple modeling efforts in PD research have focused on the pathological role of $\alpha$-synuclein ($\alpha$syn), a presynaptic protein that emerges from the intricate molecular network as a crucial driver of neurodegeneration. Here, we collect the advances in mathematical modeling of $\alpha$syn homeostasis, focusing on aggregation and degradation pathways, and discussing potential modeling improvements and possible implications in PD therapeutic strategy design

B cell rich meningeal inflammation associates with increased spinal cord pathology in multiple sclerosis

Increased inflammation in the cerebral meninges is associated with extensive subpial cortical grey matter pathology in the forebrain and a more severe disease course in a substantial proportion of secondary progressive multiple sclerosis (SPMS) cases. It is not known whether this relationship extends to spinal cord pathology. We assessed the contribution of meningeal and parenchymal immune infiltrates to spinal cord pathology in SPMS cases characterised by the presence (F+) or absence (F-) of lymphoid-like structures in the forebrain meninges. Transverse cryosections of cervical, thoracic and lumbar cord of 22 SPMS and 5 control cases were analysed for CD20+ B cells, CD4+ and CD8+ T cells, microglia/macrophages (IBA-1+), demyelination (myelin oligodendrocyte glycoprotein+) and axon density (neurofilament-H+). Lymphoid-like structures containing follicular dendritic cell networks and dividing B cells were seen in the spinal meninges of three out of 11 F+SPMS cases. CD4+ and CD20+ cell counts were increased in F+SPMS compared to F-SPMS and controls, whilst axon loss was greatest in motor and sensory tracts of the F+SPMS cases (p<0.01). The density of CD20+ B cells of the spinal leptomeninges correlated with: CD4+ T cells and total B and T cells of the meninges; with the density of white matter perivascular CD20+ and CD4+ lymphocytes (p<0.05); with white matter lesion area (p<0.05); and the extent of axon loss (p<0.05) in F+SPMS cases only. We show that the presence of lymphoid-like structures in the forebrain is associated with a profound spinal cord pathology, and local B cell rich meningeal inflammation associates with the extent of cord pathology. Our work supports a principal role for B cells in sustaining inflammation and tissue injury throughout the CNS in the progressive disease stage

Narrowband, mid-infrared, seeded optical parametric generator based on non-critical CdSiP2 pumped by 120-ps, single longitudinal mode 1,064 nm pulses

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A Novel Insulin/Glucose Model after a Mixed-Meal Test in Patients with Type 1 Diabetes on Insulin Pump Therapy

Current closed-loop insulin delivery methods stem from sophisticated models of the glucose-insulin (G/I) system, mostly based on complex studies employing glucose tracer technology. We tested the performance of a new minimal model (GLUKINSLOOP 2.0) of the G/I system to characterize the glucose and insulin dynamics during multiple mixed meal tests (MMT) of different sizes in patients with type 1 diabetes (T1D) on insulin pump therapy (continuous subcutaneous insulin infusion, CSII). The GLUKINSLOOP 2.0 identified the G/I system, provided a close fit of the G/I time-courses and showed acceptable reproducibility of the G/I system parameters in repeated studies of identical and double-sized MMTs. This model can provide a fairly good and reproducible description of the G/I system in T1D patients on CSII, and it may be applied to create a bank of "virtual" patients. Our results might be relevant at improving the architecture of upcoming closed-loop CSII systems

Laser system generating 250-mJ bunches of 5-GHz repetition rate, 12-ps pulses.

We report on a high-energy solid-state laser based on a master-oscillator power-amplifier system seeded by a 5-GHz repetition-rate mode-locked oscillator, aimed at the excitation of the dynamic Casimir effect by optically modulating a microwave resonator. Solid-state amplifiers provide up to 250 mJ at 1064 nm in a 500-ns (macro-)pulse envelope containing 12-ps (micro-)pulses, with a macro/micropulse format and energy resembling that of near-infrared free-electron lasers. Efficient second-harmonic conversion allowed synchronous pumping of an optical parametric oscillator, obtaining up to 40 mJ in the range 750-850 nm

Sub-nanosecond, 1-10 kHz, low-threshold, non-critical OPOs based on periodically poled KTP crystal pumped at 1,064 nm

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Mechanistic models of α-synuclein homeostasis for Parkinson's disease: A blueprint for therapeutic intervention

Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide, yet there is no disease-modifying therapy up to this date. The biological complexity underlying PD hampers the investigation of the principal contributors to its pathogenesis. In this context, mechanistic models grounded in molecular-level knowledge provide virtual labs to uncover the primary events triggering PD onset and progression and suggest promising therapeutic targets. Multiple modeling efforts in PD research have focused on the pathological role of α-synuclein (αsyn), a presynaptic protein that emerges from the intricate molecular network as a crucial driver of neurodegeneration. Here, we collect the advances in mathematical modeling of αsyn homeostasis, focusing on aggregation and degradation pathways, and discussing potential modeling improvements and possible implications in PD therapeutic strategy design

Diode-pumped Nd: BaY 2 F 8 picosecond laser mode-locked with carbon nanotube saturable absorbers

Picosecond pulse generation near 1-m wavelength has been achieved with a Nd: BaY 2 F 8 (Nd:BaYF) laser mode-locked using a single-walled carbon nanotube saturable absorber (SWCNT-SA). The laser was operated at its main 1049-nm transition, generating 8.5-ps pulses with Ϸ70-mW output power for Ϸ570-mW absorbed pump power. This is the first demonstration of cw mode-locking in the picosecond regime with Nd-doped crystals and SWCNT-SAs. The requirements on the SWCNT-SA for successful mode-locking in relatively narrowband neodymium lasers are reviewed and their implications are discussed