Notes

Overview of migraine inherited genes: get together genomic and transcriptomic aspects.
The lower abdominal tissue is still the most common donor site used for free autologous breast reconstruction. If this site is not available, multiple secondary choices exist. The transverse upper gracilis flap is a valuable choice and it can be used alone or in combination with other flaps. We present a case of a 49-year-old patient who underwent delayed unilateral breast reconstruction by using a double transverse upper gracilis flap. Due to venous thrombosis, the flap inserted in the lower pole was lost. We managed the complication tailoring a latissimus dorsi flap to close the defect. We reported the advantages of the latissimus dorsi flap as a rescue solution and its superior aesthetic result in this particular case. Breast reconstruction with transverse upper gracilis flap in addition to the latissimus dorsi flap allowed us to obtain an adequate breast volume avoiding the use of breast implants as desired by the patient. We thought that the double free transverse upper gracilis flap for delayed, or immediate unilateral reconstruction of small to moderate breast could be a valuable option to avoid the use of implants and when abdominal tissue is not available. However, it should be taken into consideration the shortness of the transverse upper gracilis pedicle, the necessity to perform a retrograde flow anastomosis at the level of the internal mammary, and the discrepancy of skin color tones with the receiving site. The latissimus dorsi flap was an excellent rescue solution and put in evidence the aesthetic superiority of this flap compared to the transverse upper gracilis flap.In this article, we are studying fractional-order COVID-19 model for the analytical and computational aspects. The model consists of five compartments including; ` ` S c ″ which denotes susceptible class, ` ` E c ″ represents exposed population, ` ` I c ″ is the class for infected people who have been developed with COVID-19 and can cause spread in the population. The recovered class is denoted by ` ` R c ″ and ` ` V c ″ is the concentration of COVID-19 virus in the area. Staurosporine manufacturer The computational study shows us that the spread will be continued for long time and the recovery reduces the infection rate. The numerical scheme is based on the Lagrange's interpolation polynomial and the numerical results for the suggested model are similar to the integer order which gives us the applicability of the numerical scheme and effectiveness of the fractional order derivative.Against the backdrop of a global pandemic, this study investigates how U.S. higher education leaders have centered their crisis management on values and guiding ethical principles. We conducted 55 in-depth interviews with leaders from 30 U.S. higher education institutions, with most leaders participating in two interviews. We found that crisis plans created prior to the COVID-19 pandemic were inadequate due to the long duration and highly uncertain nature of the crisis. Instead, higher education leaders applied guiding principles on the fly to support their decision-making. If colleges and universities infuse shared values into their future crisis plans, they will not have to develop a moral compass on the fly for the next pandemic. This paper suggests the following somewhat universal shared values (1) engage in accuracy, transparency, and accountability; (2) foster deliberative dialog; (3) prioritize safety; (4) support justice, fairness, and equity; and (5) engage in an ethic of care. To navigate ethics tensions, leaders need to possess crisis-relevant expertise or ensure that such expertise is present among crisis management team members. Standing up formal ethics committees composed of diverse stakeholders also is instrumental in navigating tensions inherent in crises. The next pandemic is already on the horizon according to experts. Through infusing values into future crisis plans, higher education leaders can be confident that their responses will be grounded in their communities' shared values.Awareness about the occurrence of viral infectious (or other) tail risks can influence their socioeconomic inter-temporal impacts. In this regard, a branch of the literature finds that personal experiences with significant shocks can have long-lasting effects on risk-taking attitudes and the perceived probability about the occurrence of extreme, negative shocks. In this paper, we proxy the level of societal experience (awareness) in the face of the COVID-19 outbreak by past exposure of a country to epidemics, and other catastrophic events. We show that in a large cross-section of more than 150 countries, more aware societies suffered a less intense impact of the COVID-19 disease, in terms of loss of lives and, to some extent, economic damage.The world is going through a critical period due to a new respiratory disease called coronavirus disease 2019 (COVID-19). This disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Mathematical modeling is one of the most important tools that can speed up finding a drug or vaccine for COVID-19. COVID-19 can lead to death especially for patients having chronic diseases such as cancer, AIDS, etc. We construct a new within-host SARS-CoV-2/cancer model. The model describes the interactions between six compartments nutrient, healthy epithelial cells, cancer cells, SARS-CoV-2 virus particles, cancer-specific CTLs, and SARS-CoV-2-specific antibodies. We verify the nonnegativity and boundedness of its solutions. We outline all possible equilibrium points of the proposed model. We prove the global stability of equilibria by constructing proper Lyapunov functions. We do some numerical simulations to visualize the obtained results. According to our model, lymphopenia in COVID-19 cancer patients may worsen the outcomes of the infection and lead to death. Understanding dysfunctions in immune responses during COVID-19 infection in cancer patients could have implications for the development of treatments for this high-risk group.The fast pandemics of coronavirus disease (COVID-19) has led to a devastating influence on global public health. In order to treat the disease, medical imaging emerges as a useful tool for diagnosis. However, the computed tomography (CT) diagnosis of COVID-19 requires experts' extensive clinical experience. Therefore, it is essential to achieve rapid and accurate segmentation and detection of COVID-19. This paper proposes a simple yet efficient and general-purpose network, called Sequential Region Generation Network (SRGNet), to jointly detect and segment the lesion areas of COVID-19. SRGNet can make full use of the supervised segmentation information and then outputs multi-scale segmentation predictions. Through this, high-quality lesion-areas suggestions can be generated on the predicted segmentation maps, reducing the diagnosis cost. Simultaneously, the detection results conversely refine the segmentation map by a post-processing procedure, which significantly improves the segmentation accuracy. The superiorities of our SRGNet over the state-of-the-art methods are validated through extensive experiments on the built COVID-19 database.
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