We consider a finite system of interacting point processes with memory of variable length modeling a finite but large network of spiking neurons with two different leakage mechanisms. Associated to ...each neuron there are two point processes, describing its successive spiking and leakage times. For each neuron, the rate of the spiking point process is an exponential function of its membrane potential, with the restriction that the rate takes the value 0 when the membrane potential is 0. At each spiking time, the membrane potential of the neuron resets to 0, and simultaneously, the membrane potentials of the other neurons increase by one unit. The leakage can be modeled in two different ways. In the first way, at each occurrence time of the leakage point process associated to a neuron, the membrane potential of that neuron is reset to 0, with no effect on the other neurons. In the second way, if the membrane potential of the neuron is strictly positive, at each occurrence time of the leakage point process associated to that neuron, its membrane potential decreases by one unit, with no effect on the other neurons. In both cases, the leakage point process of the neurons has constant rate. For both models, we prove that the system has a metastable behavior as the population size diverges. This means that the time at which the system gets trapped by the list of null membrane potentials suitably re-scaled converges to a mean one exponential random time.
Dosage of local anesthetics (LAs) used for regional anesthesia in children is not well determined. In order to evaluate and come to a consensus regarding some of these controversial topics, The ...European Society of Regional Anaesthesia and Pain Therapy (ESRA) and the American Society of Regional Anesthesia and Pain Medicine (ASRA) developed a Joint Committee Practice Advisory on Local Anesthetics and Adjuvants Dosage in Pediatric Regional Anesthesia.
Representatives from both ASRA and ESRA composed the joint committee practice advisory. Evidence-based recommendations were based on a systematic search of the literature. In cases where no literature was available, expert opinion was elicited.
Spinal anesthesia with bupivacaine can be performed with a dose of 1 mg/kg for newborn and/or infant and a dose of 0.5 mg/kg in older children (>1 year of age). Tetracaine 0.5% is recommended for spinal anesthesia (dose, 0.07-0.13 mL/kg). Ultrasound-guided upper-extremity peripheral nerve blocks (eg, axillary, infraclavicular, interscalene, supraclavicular) in children can be performed successfully and safely using a recommended LA dose of bupivacaine or ropivacaine of 0.5 to 1.5 mg/kg. Dexmedetomidine can be used as an adjunct to prolong the duration of peripheral nerve blocks in children.
High-level evidence is not yet available to guide dosage of LA used in regional blocks in children. The ASRA/ESRA recommendations intend to provide guidance in order to reduce the large variability of LA dosage currently observed in clinical practice.
Duguetia pycnastera Sandwith (Annonaceae) is a tropical tree that can be found in the Guyanas, Bolivia, Venezuela, and Brazil. In Brazil, it is popularly known as “ata”, “envira”, “envira-preta”, and ...“envira-surucucu”. In the present work, we investigated the in vitro and in vivo HepG2 cell growth inhibition capacity of D. pycnastera leaf essential oil (EO). The chemical composition of the EO was determined by GC−MS and GC−FID analyses. The alamar blue assay was used to examine the in vitro cytotoxicity of EO in cancer cell lines and non-cancerous cells. In EO-treated HepG2 cells, DNA fragmentation was measured by flow cytometry. The in vivo antitumor activity of the EO was assessed in C.B-17 SCID mice xenografted with HepG2 cells treated with the EO at a dosage of 40 mg/kg. Chemical composition analysis displayed the sesquiterpenes α-gurjunene (26.83%), bicyclogermacrene (24.90%), germacrene D (15.35%), and spathulenol (12.97%) as the main EO constituents. The EO exhibited cytotoxicity, with IC50 values ranging from 3.28 to 39.39 μg/mL in the cancer cell lines SCC4 and CAL27, respectively. The cytotoxic activity of the EO in non-cancerous cells revealed IC50 values of 16.57, 21.28, and >50 μg/mL for MRC-5, PBMC, and BJ cells, respectively. An increase of the fragmented DNA content was observed in EO-treated HepG2 cells. In vivo, EO displayed tumor mass inhibition activity by 47.76%. These findings imply that D. pycnastera leaf EO may have anti-liver cancer properties.
We explore the predictions for detectable gravitational-wave signals from merging binary black holes formed through chemically homogeneous evolution in massive short-period stellar binaries. We find ...that ∼500 events per year could be detected with advanced ground-based detectors operating at full sensitivity. We analyse the distribution of detectable events, and conclude that there is a very strong preference for detecting events with nearly equal components (mass ratio >0.66 at 90 per cent confidence in our default model) and high masses (total source-frame mass between 57 and 103 M⊙ at 90 per cent confidence). We consider multiple alternative variations to analyse the sensitivity to uncertainties in the evolutionary physics and cosmological parameters, and conclude that while the rates are sensitive to assumed variations, the mass distributions are robust predictions. Finally, we consider the recently reported results of the analysis of the first 16 double-coincident days of the O1 LIGO (Laser Interferometer Gravitational-wave Observatory) observing run, and find that this formation channel is fully consistent with the inferred parameters of the GW150914 binary black hole detection and the inferred merger rate.
The development of accurate forecasting systems can be challenging in real-world applications. The modeling of real-world time series is a particularly difficult task because they are generally ...composed of linear and nonlinear patterns that are combined in some form. Several hybrid systems that combine linear and nonlinear techniques have obtained relevant results in terms of accuracy in comparison with single models. However, the best combination function of the forecasting of the linear and nonlinear patterns is unknown, which makes this modeling an open question. This work proposes a hybrid system that searches for a suitable function to combine the forecasts of linear and nonlinear models. Thus, the proposed system performs: (i) linear modeling of the time series; (ii) nonlinear modeling of the error series; and (iii) a data-driven combination that searches for: (iii.a) the most suitable function, between linear and nonlinear formalisms, and (iii.b) the number of forecasts of models (i) and (ii) that maximizes the performance of the combination. Two versions of the hybrid system are evaluated. In both versions, the ARIMA model is used in step (i) and two nonlinear intelligent models – Multi-Layer Perceptron (MLP) and Support Vector Regression (SVR) – are used in steps (ii) and (iii), alternately. Experimental simulations with six real-world complex time series that are well-known in the literature are evaluated using a set of popular performance metrics. Our results show that the proposed hybrid system attains superior performance when compared with single and hybrid models in the literature.
Abstract
SARS-CoV-2 is considered a global emergency, resulting in an exacerbated crisis in the health public in the world. Although there are advances in vaccine development, it is still limited for ...many countries. On the other hand, an immunological response that mediates protective immunity or indicates that predict disease outcome in SARS-CoV-2 infection remains undefined. This work aimed to assess the antibody levels, avidity, and subclasses of IgG to RBD protein, in symptomatic patients with severe and mild forms of COVID-19 in Brazil using an adapted in-house RBD-IgG ELISA. The RBD IgG-ELISA showed 100% of specificity and 94.3% of sensibility on detecting antibodies in the sera of hospitalized patients. Patients who presented severe COVID-19 had higher anti-RBD IgG levels compared to patients with mild disease. Additionally, most patients analyzed displayed low antibody avidity, with 64.4% of the samples of patients who recovered from the disease and 84.6% of those who died in this avidity range. Our data also reveals an increase of IgG1 and IgG3 levels since the 8th day after symptoms onset, while IgG4 levels maintained less detectable during the study period. Surprisingly, patients who died during 8–14 and 15–21 days also showed higher anti-RBD IgG4 levels in comparison with the recovered (P < 0.05), suggesting that some life-threatening patients can elicit IgG4 to RBD antibody response in the first weeks of symptoms onset. Our findings constitute the effort to clarify IgG antibodies' kinetics, avidity, and subclasses against SARS-CoV-2 RBD in symptomatic patients with COVID-19 in Brazil, highlighting the importance of IgG antibody avidity in association with IgG4 detection as tool laboratory in the follow-up of hospitalized patients with more significant potential for life-threatening.
We show that the predictions of commonly used spatially smeared particle detectors coupled to quantum fields are not generally covariant outside the pointlike limit. This lack of covariance manifests ...itself as an ambiguity in the time-ordering operation. We analyze how the breakdown of covariance affects typical detector models in quantum field theory such as the Unruh–DeWitt model. Specifically, we show how the violations of covariance depend on the state of the detectors-field system, the shape and state of motion of the detectors, and the spacetime geometry. Furthermore, we provide the tools to explicitly evaluate the magnitude of the violation and identify the regimes where the predictions of smeared detectors are either exactly or approximately covariant in perturbative analyses, thus providing limits of validity of smeared particle detector models.
Photodynamic therapy (PDT) is a clinically approved cancer therapy, based on a photochemical reaction between a light activatable molecule or photosensitizer, light, and molecular oxygen. When these ...three harmless components are present together, reactive oxygen species are formed. These can directly damage cells and/or vasculature, and induce inflammatory and immune responses. PDT is a two-stage procedure, which starts with photosensitizer administration followed by a locally directed light exposure, with the aim of confined tumor destruction. Since its regulatory approval, over 30 years ago, PDT has been the subject of numerous studies and has proven to be an effective form of cancer therapy. This review provides an overview of the clinical trials conducted over the last 10 years, illustrating how PDT is applied in the clinic today. Furthermore, examples from ongoing clinical trials and the most recent preclinical studies are presented, to show the directions, in which PDT is headed, in the near and distant future. Despite the clinical success reported, PDT is still currently underutilized in the clinic. We also discuss the factors that hamper the exploration of this effective therapy and what should be changed to render it a more effective and more widely available option for patients.
Tuberculosis, caused by
Mycobacterium tuberculosis
(
M. tuberculosis
), is still responsible for a large number of fatal cases, especially in developing countries with alarming rates of incidence and ...prevalence worldwide.
Mycobacterium tuberculosis
has a remarkable ability to develop new resistance mechanisms to the conventional antimicrobials treatment. Because of this, there is an urgent need for novel bioactive compounds for its treatment. The dehydroquinate dehydratase II (DHQase II) is considered a key enzyme of shikimate pathway, and it can be used as a promising target for the design of new bioactive compounds with antibacterial action. The aim of this work was the construction of QSAR models to aid the design of new potential DHQase II inhibitors. For that purpose, various molecular modeling approaches, such as activity cliff, QSAR models and computer-aided ligand design were utilized. A predictive
in silico
4D-QSAR model was built using a database comprising 86 inhibitors of DHQase II, and the model was used to predict the activity of the designed ligands. The obtained model proved to predict well the DHQase II inhibition for an external validation dataset (
Q
ext
2
= 0.72). Also, the Activity Cliff analysis shed light on important structural features applied to the ligand design.
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