An Integrative View of Mechanisms Underlying Generalized Spike-and-Wave Epileptic Seizures and Its Implication on Optimal Therapeutic Treatments

Many types of epileptic seizures are characterized by generalized spike-and-wave discharges. In the past, notable effort has been devoted to understanding seizure dynamics and various hypotheses have been proposed to explain the underlying mechanisms. In this paper, by taking an integrative view of the underlying mechanisms, we demonstrate that epileptic seizures can be generated by many different combinations of synaptic strengths and intrinsic membrane properties. This integrative view has important medical implications: the specific state of a patient characterized by a set of biophysical characteristics ultimately determines the optimal therapeutic treatment. Through the same view, we further demonstrate the potentiation effect of rational polypharmacy in the treatment of epilepsy and provide a new angle to resolve the debate on polypharmacy. Our results underscore the need for personalized medicine and demonstrate that computer modeling and simulation may play an important role in assisting the clinicians in selecting the optimal treatment on an individual basis

Effectiveness of BNT162b2 and CoronaVac vaccinations against SARS-CoV-2 omicron infection in people aged 60 years or above: a case–control study

BACKGROUND: In view of limited evidence that specifically addresses vaccine effectiveness (VE) in the older population, this study aims to evaluate the real-world effectiveness of BNT162b2 and CoronaVac in older adults during the Omicron BA.2 outbreak. METHODS: This case-control study analyzed data available between January and March 2022 from the electronic health databases in Hong Kong and enrolled individuals aged 60 or above. Each case was matched with up to 10 controls by age, sex, index date and Charlson Comorbidity Index for the four outcomes (COVID-19 infection, COVID-19-related hospitalization, severe complications, and all-cause mortality) independently. Conditional logistic regression was conducted to evaluate VE of BNT162b2 and CoronaVac against COVID-19-related outcomes within 28 days after COVID-19 infection among participants stratified by age groups (60-79, ≥80 years old). RESULTS: A dose-response relationship between the number of vaccine doses received and protection against severe or fatal disease was observed. Highest VE (95% CI) against COVID-19 infection was observed in individuals aged ≥80 who received three doses of BNT162b2 [75.5% (73.1-77.7%)] or three doses of CoronaVac [53.9% (51.0-56.5%)] compared to those in the younger age group who received three doses of BNT162b2 [51.1% (49.9-52.4%)] or three doses of CoronaVac [2.0% (-0.1-4.1%)]. VE (95% CI) was higher for other outcomes, reaching 91.9% (89.4-93.8%) and 86.7% (84.3-88.8%) against COVID-19-related hospitalization; 85.8% (61.2-94.8%) and 89.8% (72.4-96.3%) against COVID-19-related severe complications; and 96.4% (92.9-98.2%) and 95.0% (92.1-96.8%) against COVID-19-related mortality after three doses of BNT162b2 and CoronaVac in older vaccine recipients, respectively. A similar dose-response relationship was established in younger vaccine recipients and after stratification by sex and Charlson Comorbidity Index. CONCLUSION: Both BNT162b2 and CoronaVac vaccination were effective in protecting older adults against COVID-19 infection and COVID-19-related severe outcomes amidst the Omicron BA.2 pandemic, and VE increased further with the third dose

Vaccine Effectiveness of BNT162b2 and CoronaVac against SARS-CoV-2 Omicron BA.2 in CKD

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed increased risks of hospitalization and mortality in patients with underlying CKD. Current data on vaccine effectiveness of COVID-19 vaccines are limited to patients with CKD on dialysis and seroconversion in the non-dialysis population. Methods: A case–control study was conducted of adults with CKD using data extracted from the electronic health record database in Hong Kong. Adults with CKD and COVID-19 confirmed by PCR were included in the study. Each case was matched with up to ten controls attending Hospital Authority services without a diagnosis of COVID-19 on the basis of age, sex, and index date (within three calendar days). The vaccine effectiveness of BNT162b2 and CoronaVac in preventing COVID-19 infection, hospitalizations, and all-cause mortality was estimated using conditional logistic regression adjusted by patients' comorbidities and medication history during the outbreak from January to March 2022. Results: A total of 20,570 COVID-19 cases, 6604 COVID-19–related hospitalizations, and 2267 all-cause mortality were matched to 81,092, 62,803, and 21,348 controls, respectively. Compared with the unvaccinated group, three doses of BNT162b2 or CoronaVac were associated with a reduced risk of infection (BNT162b2: 64% [95% confidence interval (CI), 60 to 67], CoronaVac: 42% [95% CI, 38 to 47]), hospitalization (BNT162b2: 82% [95% CI, 77 to 85], CoronaVac: 80% [95% CI, 76 to 84]), and mortality (BNT162b2: 94% [95% CI, 88 to 97], CoronaVac: 93% [95% CI, 88 to 96]). Vaccines were less effective in preventing infection and hospitalization in the eGFR <15 and 15–29 ml/min per 1.73 m2 subgroups as compared with higher GFR subgroups. However, receipt of vaccine, even for one dose, was effective in preventing all-cause mortality, with estimates similar to the higher eGFR subgroups, as compared with unvaccinated. Conclusions: A dose-response relationship was observed between the number of BNT162b2 or CoronaVac doses and the effectiveness against COVID-19 infection and related comorbidity in the CKD population

Advanced Non-Krylov Subspace Model Order Reduction Techniques for Interconnect Circuits

Model order reduction (MOR) is an efficient technique to reduce the complexity of dynamical systems while producing a good approximation of the input and output behavior. Classical MOR approaches such as Krylov subspace and truncated balanced realization methods have been well developed in the areas of system, control, and applied math for general systems in state-space equations. In recent years, MOR techniques using Krylov subspace algorithm have been studied intensively in the field of electronic design automation (EDA) for interconnect analysis. Interconnects in integrated circuits (IC) can be extracted as RLC circuits, which are described by a class of state-space equations with special structure properties such as symmetry, positive semi-definiteness and sparsity. As a result, to reduce the complexity of interconnect circuits, we can take advantage of the special structures to simplify the classical MOR methods. On the other hand, there are also some special requirements for interconnect reduction: scalability to large problems, passivity and structure preserving, and application to circuits with massive ports. In this thesis, we present several non-Krylov subspace MOR techniques for interconnect analysis.First, we present new methods based on classical balanced truncation for interconnect analysis: we generalize the simultaneous diagonalization algorithm for first-order balanced truncation to overcome the high computing costs; we also propose a passive second-order balanced truncation technique (and its fast version) to preserve both passivity and structure information inherent to circuit formulation. Second, we propose two new methods to perform passive reduction: we present new algorithm based on the Caratheodory extension, which has a similar computational cost as the Krylov subspace based methods but ensures the passivity of reduced model without any restriction on the internal structure of state-space equation; we also propose the concept of conditional passivity and a method to generate frequency band-limited passive reduced models.Finally, we work on long-standing problem of reducing interconnect circuits with massive ports. We propose a decentralized MOR scheme, where a multi-input multi-output (MIMO) system is decoupled into a number of subsystems in terms of outputs. The decoupling process and terminal reduction are based on the relative gain array (RGA), which measures the degree of interaction of each input-output pair. The reduction scheme can lead to passive reduction and is suitable for resistive coupling dominatant networks like power grids and substrate networks

Advanced Non-Krylov Subspace Model Order Reduction Techniques for Interconnect Circuits

Model order reduction (MOR) is an efficient technique to reduce the complexity of dynamical systems while producing a good approximation of the input and output behavior. Classical MOR approaches such as Krylov subspace and truncated balanced realization methods have been well developed in the areas of system, control, and applied math for general systems in state-space equations. In recent years, MOR techniques using Krylov subspace algorithm have been studied intensively in the field of electronic design automation (EDA) for interconnect analysis. Interconnects in integrated circuits (IC) can be extracted as RLC circuits, which are described by a class of state-space equations with special structure properties such as symmetry, positive semi-definiteness and sparsity. As a result, to reduce the complexity of interconnect circuits, we can take advantage of the special structures to simplify the classical MOR methods. On the other hand, there are also some special requirements for interconnect reduction: scalability to large problems, passivity and structure preserving, and application to circuits with massive ports. In this thesis, we present several non-Krylov subspace MOR techniques for interconnect analysis.First, we present new methods based on classical balanced truncation for interconnect analysis: we generalize the simultaneous diagonalization algorithm for first-order balanced truncation to overcome the high computing costs; we also propose a passive second-order balanced truncation technique (and its fast version) to preserve both passivity and structure information inherent to circuit formulation. Second, we propose two new methods to perform passive reduction: we present new algorithm based on the Caratheodory extension, which has a similar computational cost as the Krylov subspace based methods but ensures the passivity of reduced model without any restriction on the internal structure of state-space equation; we also propose the concept of conditional passivity and a method to generate frequency band-limited passive reduced models.Finally, we work on long-standing problem of reducing interconnect circuits with massive ports. We propose a decentralized MOR scheme, where a multi-input multi-output (MIMO) system is decoupled into a number of subsystems in terms of outputs. The decoupling process and terminal reduction are based on the relative gain array (RGA), which measures the degree of interaction of each input-output pair. The reduction scheme can lead to passive reduction and is suitable for resistive coupling dominatant networks like power grids and substrate networks

Tunable fractional-order photonic differentiator based on the inverse Raman scattering in a silicon microring resonator

A novel photonic fractional-order temporal differentiator is proposed based on the inverse Raman scattering (IRS) in the side-coupled silicon microring resonator. By controlling the power of the pump light-wave, the intracavity loss is adjusted and the coupling state of the microring resonator can be changed, so the continuously tunable differentiation order is achieved. The influences of input pulse width on the differentiation order and the output deviation are discussed. Due to the narrow bandwidth of IRS in silicon, the intracavity loss can be adjusted on a specific resonance while keeping the adjacent resonances undisturbed. It can be expected that the proposed scheme has the potential to realize different differentiation orders simultaneously at different resonant wavelengths