BACKGROUND: Since the novel coronavirus emerged in late 2019, the scientific and public health community around the world have sought to better understand, surveil, treat, and prevent the disease, COVID-19. In sub-Saharan Africa (SSA), many countries responded aggressively and decisively with lockdown measures and border closures. Such actions may have helped prevent large outbreaks throughout much of the region, though there is substantial variation in caseloads and mortality between nations. Additionally, the health system infrastructure remains a concern throughout much of SSA, and the lockdown measures threaten to increase poverty and food insecurity for the subcontinents poorest residents. The lack of sufficient testing, asymptomatic infections, and poor reporting practices in many countries limit our understanding of the viruss impact, creating a need for better and more accurate surveillance metrics that account for underreporting and data contamination. OBJECTIVE: The goal of this study is to improve infectious disease surveillance by complementing standardized metrics with new and decomposable surveillance metrics of COVID-19 that overcome data limitations and contamination inherent in public health surveillance systems. In addition to prevalence of observed daily and cumulative testing, testing positivity rates, morbidity, and mortality, we derived COVID-19 transmission in terms of speed, acceleration or deceleration, change in acceleration or deceleration (jerk), and 7-day transmission rate persistence, which explains where and how rapidly COVID-19 is transmitting and quantifies shifts in the rate of acceleration or deceleration to inform policies to mitigate and prevent COVID-19 and food insecurity in SSA. METHODS: We extracted 60 days of COVID-19 data from public health registries and employed an empirical difference equation to measure daily case numbers in 47 sub-Saharan countries as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Kenya, Ghana, Nigeria, Ethiopia, and South Africa have the most observed cases of COVID-19, and the Seychelles, Eritrea, Mauritius, Comoros, and Burundi have the fewest. In contrast, the speed, acceleration, jerk, and 7-day persistence indicate rates of COVID-19 transmissions differ from observed cases. In September 2020, Cape Verde, Namibia, Eswatini, and South Africa had the highest speed of COVID-19 transmissions at 13.1, 7.1, 3.6, and 3 infections per 100,0000, respectively; Zimbabwe had an acceleration rate of transmission, while Zambia had the largest rate of deceleration this week compared to last week, referred to as a jerk. Finally, the 7-day persistence rate indicates the number of cases on September 15, 2020, which are a function of new infections from September 8, 2020, decreased in South Africa from 216.7 to 173.2 and Ethiopia from 136.7 to 106.3 per 100,000. The statistical approach was validated based on the regression results; they determined recent changes in the pattern of infection, and during the weeks of September 1-8 and September 9-15, there were substantial country differences in the evolution of the SSA pandemic. This change represents a decrease in the transmission model R value for that week and is consistent with a de-escalation in the pandemic for the sub-Saharan African continent in general. CONCLUSIONS: Standard surveillance metrics such as daily observed new COVID-19 cases or deaths are necessary but insufficient to mitigate and prevent COVID-19 transmission. Public health leaders also need to know where COVID-19 transmission rates are accelerating or decelerating, whether those rates increase or decrease over short time frames because the pandemic can quickly escalate, and how many cases today are a function of new infections 7 days ago. Even though SSA is home to some of the poorest countries in the world, development and population size are not necessarily predictive of COVID-19 transmission, meaning higher income countries like the United States can learn from African countries on how best to implement mitigation and prevention efforts. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/21955

We investigated the feasibility of linear salpingotomy with suturing for ampullary tubal pregnancy via single incision laparoscopic surgery (SILS). Three patients underwent SILS between April and May 2010 at our hospital due to ampullary tubal pregnancy. A multichannel port was inserted into the umbilicus via a 2.5-cm incision to accommodate a 5-mm flexible laparoscope and a disposable articulating forceps. The linearly incised Fallopian tube was intracorporeally sutured using an articulating suturing device dedicated to SILS. The mean surgical duration was 54 minutes. Tubal preservation by linear salpingotomy was accomplished for all patients without up-conversion to conventional laparoscopy. Serum -hCG values of all patients immediately decreased and further medical treatment was unnecessary.

Axonal plasticity allows neurons to control their output, which critically determines the flow of information in the brain. Axon diameter can be regulated by activity, yet how morphological changes in an axon impact its function remains poorly understood. Axonal swellings have been found on Purkinje cell axons in the cerebellum both in healthy development and in neurodegenerative diseases, and computational models predicts that axonal swellings impair axonal function. Here we report that in young Purkinje cells, axons with swellings propagated action potentials with higher fidelity than those without, and that axonal swellings form when axonal failures are high. Furthermore, we observed that healthy young adult mice with more axonal swellings learn better on cerebellar-related tasks than mice with fewer swellings. Our findings suggest that axonal swellings underlie a form of axonal plasticity that optimizes the fidelity of action potential propagation in axons, resulting in enhanced learning.

It is well established that cancer patients are more susceptible to infection because of the immunosuppressive status caused by both disease itself and anticancer treatment, including surgery and chemoradiation Head and neck cancer (HNC) patients are generally at high-risk for coronavirus disease 2019 (COVID-19) infection and serious adverse outcomes Although there is an urgent need for guidance in the delivery of safe, quality oncologic care, no international consented recommendation addressed the management of HNC patients in COVID-19 due to limited data In this review, we summarized the consideration for head and neck oncologic care in the context of the COVID-19 pandemic, based on the data and the very recent recommendations from the Korean Cancer Association and National Cancer Center COVID-19 should be taken into consideration in the comprehensive management of HNC patients, and multidisciplinary evaluation of multilevel surgical-risks, discussion of optimized strategy, and shared-decision-making with the patient are needed to maximize both the safety from infectious pandemic and outcome of surgical and oncologic care

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), an infectious disease characterized by strong induction of inflammatory cytokines, progressive lung inflammation and potentially multi-organ dysfunction. It remains unclear whether SARS-CoV-2 is sensed by pattern recognition receptors (PRRs) leading to immune activation. Several studies suggest that the Spike (S) protein of SARS-CoV-2 might interact with Toll-like receptor 4 (TLR4) and thereby activate immunity. Here we have investigated the role of TLR4 in SARS-CoV-2 infection and immunity. Neither exposure of isolated S protein, SARS-CoV-2 pseudovirus nor a primary SARS-CoV-2 isolate induced TLR4 activation in a TLR4-expressing cell line. Human monocyte-derived dendritic cells (DCs) express TLR4 but not ACE2, and DCs were not infected by a primary SARS-CoV-2 isolate. Notably, neither S protein nor the primary SARS-CoV-2 isolate induced DC maturation or cytokines, indicating that both S protein and SARS-CoV-2 virus particles do not trigger extracellular TLRs, including TLR4. Ectopic expression of ACE2 in DCs led to efficient infection by SARS-CoV-2. Strikingly, infection of ACE2-positive DCs induced type I IFN and cytokine responses, which was inhibited by antibodies against ACE2. These data strongly suggest that not extracellular TLRs but intracellular viral sensors are key players in sensing SARS-CoV-2. These data imply that SARS-CoV-2 escapes direct sensing by TLRs, which might underlie the lack of efficient immunity to SARS-CoV-2 early during infection. Author summaryThe immune system needs to recognize pathogens such as SARS-CoV-2 to initiate antiviral immunity. Dendritic cells (DCs) are crucial for inducing antiviral immunity and are therefore equipped with both extracellular and intracellular pattern recognition receptors to sense pathogens. However, it is unknown if and how SARS-CoV-2 activates DCs. Recent research suggests that SARS-CoV-2 is sensed by extracellular Toll-like receptor 4 (TLR4). We have previously shown that DCs do not express ACE2, and are therefore not infected by SARS-CoV-2. Here we show that DCs do not become activated by exposure to viral Spike proteins or SARS-CoV-2 virus particles. These findings suggest that TLR4 and other extracellular TLRs do not sense SARS-CoV-2. Next, we expressed ACE2 in DCs and SARS-CoV-2 efficiently infected these ACE2-positive DCs. Notably, infection of ACE2-positive DCs induced an antiviral immune response. Thus, our study suggests that infection of DCs is required for induction of immunity, and thus that intracellular viral sensors rather than extracellular TLRs are important in sensing SARS-CoV-2. Lack of sensing by extracellular TLRs might be an escape mechanism of SARS-CoV-2 and could contribute to the aberrant immune responses observed during COVID-19.

Social networking services played a crucial role in the management of previous outbreaks around the world. African populations are increasingly using social networks and this may have benefits but also harmful consequences, especially at this time of coronavirus disease 2019 pandemic. This paper concisely discusses of these consequences which include the propagation of fake news and the misinterpretation of messages pertaining to the prevention and the treatment of the disease. Moreover, our commentary provides some ways to alleviate them, chiefly represented by a framed and practical communication by health authorities. We suggest for instance the systematic sharing of correct messages through official Facebook and Twitter accounts and the conception of tailored web tools dedicated to the verification of circulating information.

We demonstrate that universal scaling behavior is observed in the current coronavirus (COVID-19) spread in various countries. We analyze the numbers of infected people in selected eleven countries (Japan, USA, Russia, Brazil, China, Italy, Indonesia, Spain,South Korea, UK, and Sweden). By using the double exponential function called the Gompertz function, fG(x)=exp(-e-x), the number of infected people is well described as N(t)=N0 fG({gamma}(t-t0)), where N0, {gamma} and t0 are the final total number of infected people, the damping rate of the infection probability and the peak time of dN(t)/dt, respectively. The scaled data of infected people in most of the analyzed countries are found to collapse onto a common scaling function fG(x) with x={gamma}(t-t0) in the range of fG(x) {+/-} 0.05. The recently proposed indicator so-called the K value, the increasing rate of infected people in one week, is also found to show universal behavior. The mechanism for the Gompertz function to appear is discussed from the time dependence of the produced pion numbers in nucleus-nucleus collisions, which is also found to be described by the Gompertz function.

As part of the urgent need to respond to the COVID-19 pandemic, governments, healthcare providers, and businesses have looked to applications of Artificial Intelligence (AI) to compensate for the unavailability of human workers. This interest has renewed the debate regarding the use of AI for the automation of work, which has been described as Intelligent Automation (IA). A new dimension to this debate is whether COVID-19 will be the catalyst for higher IA adoption levels. This article reviews arguments in favour of COVID-19 increasing the level of IA adoption and possible counter-arguments. Key arguments in favour of increased IA adoption include consumer preferences changing to favour IA, increasing familiarity of IA technologies, and increased business confidence in IA. Counter-arguments include big data availability and reliability limitations, many tasks still favouring human skills over IA, the narrow capabilities of IA technologies, and a high availability of human workers. The article also discusses the implications of this debate for information management research and practice.

OBJECTIVE: Otological complications are considered early symptoms of severe acute respiratory syndrome coronavirus-2; however, it is unknown how long these symptoms last and whether the virus leaves any hearing disorders post-recovery. METHODS: This prospective cohort study comprised 31 mild or moderate confirmed coronavirus disease 2019 patients and 26 age-matched control peers (21C50 years old). Patients were questioned about their otological symptoms, and their hearing status was assessed during one month post-diagnosis. RESULTS: Patients showed a significantly higher rate of otological symptoms (hearing loss, ear fullness, ear pain, dizziness or vertigo, communication difficulties, and hyperacusis) versus the control group (p 0.022). The symptoms resolved early, between 2 and 8 days after their appearance. No significant differences were observed between the two groups in pure tone and extended high-frequency audiometry, transient evoked otoacoustic emissions, distortion product otoacoustic emissions, or auditory brainstem response following recovery. CONCLUSION: The findings indicate that, in mild to moderate coronavirus disease 2019 cases, otological symptoms resolve within a week, and the virus has no lasting impact on the auditory system.

Background: The ability to predict likely prognosis and infectiousness for patients with COVID-19 would aid patient management decisions. Diagnosis is usually via real-time PCR and it is unclear whether the semi-quantitative capability of this method, determining viral load through cycle threshold (Ct) values, can be leveraged. Objectives: We aim to review available knowledge on correlations between SARS-COV-2 Ct values and patient- or healthcare-related outcomes to determine whether Ct values provide useful clinical information. Sources A PubMed search was conducted on 1st June 2020 based on a search strategy of (Ct value OR viral load) AND SARS-CoV-2. Data was extracted from studies reporting on the presence or absence of an association between Ct values, or viral loads determined via Ct value, and clinical outcomes. Content Data from 18 studies were relevant for inclusion. One study reported on the correlation between Ct values and mortality and one study reported on the correlation between Ct values and progression to severe disease;both reported a significant association (p < 0.001 and p = 0.008, respectively). Fourteen studies reported on the correlation between Ct value or viral loads determined via Ct value and disease severity and an association was observed in 8 (57%) studies. Studies reporting on the correlation of viral load with biochemical and haematological markers showed an association with at least one marker, including increased lactate dehydrogenase ( n = 4), decreased lymphocytes ( n = 3) and increased high-sensitivity troponin I ( n = 2). Two studies reporting on the correlation with infectivity showed that lower Ct values were associated with higher viral culture positivity. Implications Data suggest that lower Ct values may be associated with worse outcomes, and that Ct values may be useful in predicting the clinical course and prognosis of patients with COVID-19;however, further studies are warranted to confirm clinical value.

The pandemic caused by the new SARS-CoV-2 coronavirus has created a climate of uncertainty. The application of the precautionary principle is therefore justified for some of the measures taken by the competent authorities. In Spain, these measures have been aimed, on the one hand, at stopping its spread by means of a state of alarm for the restriction of daily activities. On the other hand, they aimed at recommending the most appropriate treatment according to scientific research developments, as well as containment measures based on the use of health care products. These latest measures have led to an extraordinary increase in the use of medicines and health care products, which compromises their supply. Thus, authorities were forced to regulate certain actions in the legal supply chain of medicines and healthcare products, such as procurement and dispensing.

The upper airway C which consists mainly of the naso- and oro-pharynx - is the first point of contact between the respiratory system and microbial organisms that are ubiquitous in the environment. It has evolved highly specialised functions to address these constant threats whilst facilitating seamless respiratory exchange with the lower respiratory tract. Dysregulation of its critical homeostatic and defence functions can lead to ingress of pathogens into the lower respiratory tract, potentially leading to serious illness. Systems-wide proteomic tools may facilitate a better understanding of mechanisms in the upper airways in health and disease. In this study, we aimed to develop a mass spectrometry based proteomics method for characterizing the upper airways proteome. Naso- and oropharyngeal swab samples used in all our experiments had been eluted in the Universal Transport Media (UTM) containing significantly high levels of bovine serum albumin. Our proteomic experiments tested the optimal approach to characterize airway proteome on swab samples eluted in UTM based on the number of proteins identified without BSA depletion (Total proteome: Protocol A) and with its depletion using a commercial kit; Allprep, Qiagen (cellular proteome: Protocol B, Ci, and Cii). Observations and lessons drawn from protocol A, fed into the design and implementation of protocol B, and from B to protocol Ci and finally Cii. Label free proteome quantification was used in Protocol A (n = 6) and B (n = 4) while commercial TMT 10plex reagents were used for protocols Ci and ii (n = 83). Protocols Ci and ii were carried out under similar conditions except for the elution gradient: 3 h and 6 h respectively. Swab samples tested in this study were from infants and children with and without upper respiratory tract infections from Kilifi County Hospital on the Kenyan Coast. Protocol A had the least number of proteins identified (215) while B produced the highest number of protein identifications (2396). When Protocol B was modified through sample multiplexing with TMT to enable higher throughput (Protocol Ci), the number of protein identified reduced to 1432. Modification of protocol Ci by increasing the peptide elution time generated Protocol Cii that substantially increased the number of proteins identified to 1875. The coefficient of variation among the TMT runs in Protocol Cii was <20%. There was substantial overlap in the identity of proteins using the four protocols. Our method was were able to identify marker proteins characteristically expressed in the upper airway. We found high expression levels of signature nasopharyngeal and oral proteins, including BPIFA1/2 and AMY1A, as well as a high abundance of proteins related to innate and adaptive immune function in the upper airway. We have developed a sensitive systems-level proteomic assay for the systematic quantification of naso-oro-pharyngeal proteins. The assay will advance mechanistic studies of respiratory pathology, by providing an untargeted and hypothesis-free approach of examining the airway proteome.

In the period of Corona Virus Disease 2019 (COVID-19), millions of people participate in the discussion of COVID-19 on the Internet, which can easily trigger public opinion and threaten social stability. This paper creatively proposes a multi-stage risk grading model of Internet public opinion for public health emergencies. On the basis of general public opinion risk grading analysis, the model continuously pays attention to the risk level of Internet public opinion based on the time scale of regular or major information updates. This model combines Analytic Hierarchy Process Sort II (AHPSort II) and Swing Weighting (SW) methods and proposes a new Multi-Criteria Decision Making (MCDM) method C AHPSort II-SW. Intuitionistic fuzzy number and linguistic fuzzy number are introduced into the model to evaluate the criteria that cannot be quantified. The multi-stage model is tested using more than 2,000 textual data about COVID-19 collected from Microblog, a leading social media platform in China. Seven public opinion risk assessments were conducted from January 23 to April 8, 2020. The empirical results show that in the early COVID-19 outbreak, the risk of public opinion is more serious on macroscopic view. In details, the risk of public opinion decreases slowly with time, but the emergence of important events may still increase the risk of public opinion. The analysis results are in line with the actual situation and verify the effectiveness of the method. Comparative analysis indicates the improved method is proved to be superior and effective, sensitivity analysis confirms its stability. Finally, management suggestions was provided, this study contributes to the literature on public opinion risk assessment and provides implications for practice.

At the end of 2019, respiratory coronavirus diseases 2019 (COVID\19) appeared and spread rapidly in the world. Besides several mutations, the outcome of this pandemic was the death up to 15% of hospitalized patients. Mesenchymal stromal cell therapy as a therapeutic strategy seemed successful in treatment of several diseases. Not only mesenchymal stromal cells of several tissues, but also their secreted extracellular vesicles and even secretome indicated beneficial therapeutic function. All of these three options were studied for treatment of COVID\19 as well as those respiratory diseases that have similar symptom. Fortunately, most of the outcomes were promising and optimistic. In this paper, we review in\vivo and clinical studies which have been used different sources of mesenchymal stromal cell, secreted extracellular vesicles, and secretome to improve and treat symptoms of COVID\19 and similar lung diseases.

John Finch, an independent journalist specialising in legal and ethical aspects of clinical practice, has previously examined the fundamentals of consent to treatment In this article, he focuses on testing for medical conditions, including suspected transmissible disease The alarming and rapid spread of COVID-19 has highlighted the larger question of whether and to what extent consent by a person to be tested, as well knowledge as to the precise reason for the test, is a legal requirement Taking a broader view of clinical testing, this article examines the legal basis of consent and places it in context by briefly examining the law relating to negligence and the nature of assault and battery

The deterioration of tissue structure and decline in physiological function during aging are accompanied by alterations to the gut microbiota. The elderly has higher risks of various diseases and chronic diseases. However, inter\individual differences are more apparent in elderly than younger, and a proportion of individuals have a delayed onset or even avoid developing chronic diseases. This difference in health status is influenced by both heredity and Lifestyle and environmental factors. During the process of aging, the gut microbiota is also affected by the external environment, and provides a buffer to external challenge, and thus the gut microbiota reflects an individual's personal experience. Moreover, the immune system undergoes a series of changes with age, which are related to chronic inflammation in the elderly. The formation, maturation and senescence of the intestinal immune system is closely related to the gut microbiota. Additionally, changes in the gut microbiota of elderly individuals may modulate the immune system, which may in turn affect health status. Herein, we summarize the correlations between the gut microbiota with individual health status in the elderly and explore the related mechanisms, which may provide a basis to maintain or enhance the health of the elderly though interventions targeting the gut microbiota.

The outbreak of the coronavirus disease (COVID-19) pandemic has become a worldwide health catastrophe instigated by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Countries are battling to slow the spread of this virus by testing and treating patients, along with other measures such as prohibiting large gatherings, maintaining social distance, and frequent, thorough hand washing, as no vaccines or medicines are available that could effectively treat infected people for different types of SARS-CoV-2 variants. However, the testing procedure to detect this virus is lengthy. This study proposes a surface plasmon resonance-based biosensor for fast detection of SARS-CoV-2. The sensor employs a multilayered configuration consisting of TiO(2)CAgCMoSe(2) graphene with a BK7 prism. AntigenCantibody interaction was considered the principle for this virus detection. Immobilized CR3022 antibody molecules for detecting SARS-CoV-2 antigens (S-glycoprotein) are used for this sensor. It was found that the proposed sensors sensitivity (194/RIU), quality factor (54.0390 RIU(?1)), and detection accuracy (0.2702) outperformed those of other single and multilayered structures. This study could be used as a theoretical base and primary step in constructing an actual sensor.

What happens when the outside world begins to affect the classroom? Is the classroom supposed to be neutral, objective, and devoid of feelings? Or is it a space where students and teacher meet for healing, understanding, and critical thinking? From news reports of police brutality to highly publicized acts of racial aggression, students are inundated with examples of intolerance, hatred, and racial inequality. Those committed to critical pedagogy and social justice invite, embrace, and use these events to enhance classroom materials. What happens, however, when pedagogy is painful for both the student and the teacher? Several articles address the teachers experience and others the student experience. This article is dedicated to synthesizing and discussing both experiences from one course, Race and Ethnicity, at a height of racial tensions in the United States and on campus and providing the personal and pedagogical strategies that developed from the course.

This study explores the prevalent Machine and Deep Learning approaches for the control of COVID-19. It reveals the impact of Artificial Intelligence in the case prediction, analysis, diagnosis, and treatment of the disease. Apart from discussing four (4) knowledge areas where Machine Learning and Deep Learning approaches were employed in the fight against the pandemic, we proposed a Generalized Artificial Intelligence Response Framework using those areas. We observed that most of the works seeking Artificial Intelligence scientific solutions to the pandemic were employing the use of chest X-ray images and chest computed tomography scans for prognosis and diagnosis while applying different Machine and Deep Learning approaches using available data dashboards. However, a production-ready landmark contribution towards the control of the disease through Artificial Intelligence is still at the moment a work in progress. Hence, the need for a response framework to give researchers and practitioners a working guide to finding solutions to the pandemic using computing techniques. ? 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

This project aimed to determine the impact of and needs from physician members of the Canadian Association of Physical Medicine and Rehabilitation (CAPMR) during the early response to the COVID-19 global pandemic. The purpose of this project was to develop a framework for addressing the pandemic tailored to the needs of Canadian physiatrists. A convergent mixed-methods design was used for this needs assessment quality project. A total of 136 responses were obtained with an overall response rate of 34%. Three major themes were identified relating to the impact of COVID-19 on physicians: 1) changes to direct patient care, 2) changes to non-clinical aspects of physicians practices, and 3) impacts on personal and family well-being. Three requests for CAPMR support during the pandemic were: 1) collaborative sharing of information and resources, 2) advocacy for both patients and providers, and 3) avenues for social connection and wellness. This project provided insight into the impact of COVID-19 and current needs of CAPMR physicians. The results were used to develop a solutions framework including guidance on use of virtual care and holding education webinars on high-yield topics. Next steps include a follow-up survey on change in preparedness and member satisfaction with the CAPMR response.