Takotsubo Syndrome and COVID-19: Associations and Implications.

Incidence of cardiovascular complications has increased during the COVID-19 (Coronavirus disease 2019) pandemic, both population-wide and in patients diagnosed with the disease. This increase has presented complications in patient care, leading to increased hospitalizations, adverse outcomes, and medical costs. A condition of interest is takotsubo syndrome, which may be associated with the novel coronavirus. To understand this connection, a narrative review was performed by analyzing primary studies and case reports available. The findings showed increased incidence of takotsubo cardiomyopathy in both the general population and COVID-19 patients. Proposed mechanisms for the linkage include generalized increases in psychological distress, the cytokine storm, increased sympathetic responses in COVID-19 patients, and microvascular dysfunction. Moreover, natural disasters are noted as likely being associated with increases of takotsubo syndrome. As the pandemic continues, treating COVID-19 as a systemic condition is imperative, with the increase in takotsubo syndrome marking a significant impact of the novel coronavirus

Dynamic Capability and Strategic Corporate Social Responsibility Adoption: Evidence from China

An increasing number of studies have proposed that corporate social responsibility (CSR) performance depends on how firms apply their resources and capabilities to implement CSR. A firm’s ability to integrate, build, and reconfigure internal and external competencies to respond to environmental changes is its dynamic capability. Implementation of CSR at the strategic level, i.e., strategic CSR (SCSR) that requires alignment between activities and organizational configuration and structure will contribute to a firm’s sustainability. However, the research on how dynamic capabilities contribute to such alignment and SCSR adoption is incipient. This study investigates how dynamic capability influences the performance of SCSR in China. By analyzing 134 Chinese listed firms in the period 2017–2019, in this study, we found that firms with dynamic capabilities at a non-average-industrial level, i.e., higher or lower level than the average industrial level, were less likely to adopt SCSR practices, and had a low SCSR adoption performance. These results can help firms better understand dynamic capabilities and how dynamic capabilities contribute to SCSR adoption and firms’ sustainable development and operations. The policy implications of the study are also discussed

Targeted Assembly of Short Sequence Reads

As next-generation sequence (NGS) production continues to increase, analysis is becoming a significant bottleneck. However, in situations where information is required only for specific sequence variants, it is not necessary to assemble or align whole genome data sets in their entirety. Rather, NGS data sets can be mined for the presence of sequence variants of interest by localized assembly, which is a faster, easier, and more accurate approach. We present TASR, a streamlined assembler that interrogates very large NGS data sets for the presence of specific variants, by only considering reads within the sequence space of input target sequences provided by the user. The NGS data set is searched for reads with an exact match to all possible short words within the target sequence, and these reads are then assembled strin-gently to generate a consensus of the target and flanking sequence. Typically, variants of a particular locus are provided as different target sequences, and the presence of the variant in the data set being interrogated is revealed by a successful assembly outcome. However, TASR can also be used to find unknown sequences that flank a given target. We demonstrate that TASR has utility in finding or confirming ge-nomic mutations, polymorphism, fusion and integration events. Targeted assembly is a powerful method for interrogating large data sets for the presence of sequence variants of interest. TASR is a fast, flexible and easy to use tool for targeted assembly

Set-based State Estimation with Probabilistic Consistency Guarantee under Epistemic Uncertainty

Consistent state estimation is challenging, especially under the epistemic uncertainties arising from learned (nonlinear) dynamic and observation models. In this work, we propose a set-based estimation algorithm, named Gaussian Process-Zonotopic Kalman Filter (GP-ZKF), that produces zonotopic state estimates while respecting both the epistemic uncertainties in the learned models and aleatoric uncertainties. Our method guarantees probabilistic consistency, in the sense that the true states are bounded by sets (zonotopes) across all time steps, with high probability. We formally relate GP-ZKF with the corresponding stochastic approach, GP-EKF, in the case of learned (nonlinear) models. In particular, when linearization errors and aleatoric uncertainties are omitted and epistemic uncertainties are simplified, GP-ZKF reduces to GP-EKF. We empirically demonstrate our method's efficacy in both a simulated pendulum domain and a real-world robot-assisted dressing domain, where GP-ZKF produced more consistent and less conservative set-based estimates than all baseline stochastic methods.Comment: Published at IEEE Robotics and Automation Letters, 2022. Video: https://www.youtube.com/watch?v=CvIPJlALaFU Copyright: 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any media, including reprinting/republishing for any purposes, creating new works, for resale or redistribution, or reuse of any copyrighted component of this wor

Optimizing farmyard manure and cattle slurry applications for intensively managed grasslands based on UK-DNDC model simulations

Fertilizer applications can enhance soil fertility, pasture growth and thereby increase production. Nitrogen fertilizer has, however, been identified as a significant source of nitrous oxide (N2O) emissions fromagriculture if not used correctly and can thereby increase the environmental damage costs associatedwith agricultural production. The optimumuse of organic fertilizers requires an improved understanding of nutrient cycles and their controls. Against this context, the objective of this research was to evaluate the scope for reducing N2O emissions from grassland using a number of manure management practices including more frequent applications of smaller doses and differentmethods of application.We used amodified UK-DNDCmodel and N2O emissions from grasslands at Pwllpeiran (PW), UK during the calibration period in autumn, were 1.35 kg N/ha/y (cattle slurry) and 0.95 kgN/ha/y (farmyardmanure), and 2.31 kg N/ha/y (cattle slurry) and 1.08 kgN/ha/y (farmyardmanure) during validation period in spring, compared to 1.43 kg N/ha/y (cattle slurry) and 0.29 kgN/ha/y (farmyard manure) during spring at NorthWyke (NW), UK. The modelling results suggested that the time period between fertilizing and sampling (TPFA), rainfall and the daily average air temperature are key factors for N2O emissions. Also, the emission factor (EF) varies spatio-temporally (0–2%) compared to uniform 1% EF assumption of IPCC. Predicted N2O emissions were positively and linearly (R2≈1) related with N loadings under all scenarios. During the scenario analysis, the use of high frequency, lowdose fertilizer applications compared to a single one off application was predicted to reduce N2O peak fluxes and overall emissions for cattle slurry during the autumn and spring seasons at the PWand NW experimental sites by 17% and 15%, respectively. These results demonstrated that an optimized application regime using outputs from the modelling approach is a promising tool for supporting environmentally-friendly precision agriculture

Phagocytosis of mast cell granules results in decreased macrophage superoxide production

The mechanism by which phagocytosed mast cell granules (MCGs) inhibit macrophage superoxide production has not been defined. In this study, rat peritoneal macrophages were co-incubated with either isolated intact MCGs or MCG-sonicate, and their respiratory burst capacity and morphology were studied. Co-incubation of macrophages with either intact MCGs or MCG-sonicate resulted in a dose-dependent inhibition of superoxide- mediated cytochrome c reduction. This inhibitory effect was evident within 5 min of incubation and with MCG-sonicate was completely reversed when macrophages were washed prior to activation with PMA. In the case of intact MCGs, the inhibitory effect was only partially reversed by washing after a prolonged co-incubation time. Electron microscopic analyses revealed that MCGs were rapidly phagocytosed by macrophages and were subsequently disintegrated within the phagolysosomes. Assay of MCGs for superoxide dismutase (SOD) revealed the presence of significant activity of this enzyme. A comparison of normal macrophages and those containing phagocytosed MCGs did not reveal a significant difference in total SOD activity. It is speculated that, although there was no significant increase in total SOD activity in macrophages containing phagocytosed MCGs, the phagocytosed MCGs might cause a transient increase in SOD activity within the phagolysosomes. This transient rise in SOD results in scavenging of the newly generated superoxide. Alternatively, MCG inhibition of NADPH oxidase would explain the reported observations

Is left lobe adult-to-adult living donor liver transplantation ready for widespread use? The US experience (1998–2010)

AbstractObjectivesLiving donor liver transplantation (LDLT) is an accepted treatment for patients with end-stage liver disease. To minimize risk to the donor, left lobe (LL) LDLT may be an ideal option in adult LDLT.MethodsThis study assessed the outcomes of LL-LDLT compared with right lobe (RL) LDLT in adults (1998–2010) as reported to the United Network for Organ Sharing (UNOS) Organ Procurement and Transplantation Network (OPTN).ResultsA total of 2844 recipients of LDLT were identified. Of these, 2690 (94.6%) underwent RL-LDLT and 154 (5.4%) underwent LL-LDLT. A recent increase in the number of LL-LDLTs was noted: average numbers of LL-LDLTs per year were 5.2 during 1998–2003 and 19.4 during 2004–2010. Compared with RL-LDLT recipients, LL-LDLT recipients were younger (mean age: 50.5years vs. 47.0years), had a lower body mass index (BMI) (mean BMI: 24.5kg/m2 vs. 26.8kg/m2), and were more likely to be female (64.6% vs. 41.9%). Donors in LL-LDLT had a higher BMI (mean BMI: 29.4kg/m2 vs. 26.5kg/m2) and were less likely to be female (30.9% vs. 48.1%). Recipients of LL-LDLT had a longer mean length of stay (24.9days vs. 18.2days) and higher retransplantation rates (20.3% vs. 10.9%). Allograft survival in LL-LDLT was significantly lower than in RL-LDLT and there was a trend towards inferior patient survival. In Cox regression analysis, LL-LDLT was found to be associated with an increased risk for allograft failure [hazard ratio (HR): 2.39)] and inferior patient survival (HR: 1.86).ConclusionsThe number of LL-LDLTs has increased in recent years

QuDPy: A Python-Based Tool For Computing Ultrafast Non-linear Optical Responses

Nonlinear Optical Spectroscopy is a well-developed field with theoretical and experimental advances that have aided multiple fields including chemistry, biology and physics. However, accurate quantum dynamical simulations based on model Hamiltonians are need to interpret the corresponding multi-dimensional spectral signals properly. In this article, we present the initial release of our code, QuDPy (quantum dynamics in python) which addresses the need for a robust numerical platform for performing quantum dynamics simulations based on model systems, including open quantum systems. An important feature of our approach is that one can specify various high-order optical response pathways in the form of double-sided Feynman diagrams via a straightforward input syntax that specifies the time-ordering of ket-sided or bra-sided optical interactions acting upon the time-evolving density matrix of the system. We use the quantum dynamics capabilities of QuTip for simulating the spectral response of complex systems to compute essentially any n-th-order optical response of the model system. We provide a series of example calculations to illustrate the utility of our approach

Stochastic exciton-scattering theory of optical lineshapes: Renormalized many-body contributions

Spectral line-shapes provide a window into the local environment coupled to a quantum transition in the condensed phase. In this paper, we build upon a stochastic model to account for non-stationary background processes produced by broad-band pulsed laser stimulation. In particular, we consider the contribution of pair-fluctuations arising from the full bosonic many-body Hamiltonian within a mean-field approximation, treating the coupling to the system as a stochastic noise term. Using the It{\^o} transformation, we consider two limiting cases for our model which lead to a connection between the observed spectral fluctuations and the spectral density of the environment. In the first case, we consider a Brownian environment and show that this produces spectral dynamics that relax to form dressed excitonic states and recover an Anderson-Kubo-like form for the spectral correlations. In the second case, we assume that the spectrum is Anderson-Kubo like, and invert to determine the corresponding background. Using the Jensen inequality, we obtain an upper limit for the spectral density for the background. The results presented here provide the technical tools for applying the stochastic model to a broad range of problems