The Effects of Porphyromonas gingivalis on Atherosclerosis-Related Cells

Atherosclerosis (AS), one of the most common types of cardiovascular disease, has initially been attributed to the accumulation of fats and fibrous materials. However, more and more researchers regarded it as a chronic inflammatory disease nowadays. Infective disease, such as periodontitis, is related to the risk of atherosclerosis. Porphyromonas gingivalis (P. gingivalis), one of the most common bacteria in stomatology, is usually discovered in atherosclerotic plaque in patients. Furthermore, it was reported that P. gingivalis can promote the progression of atherosclerosis. Elucidating the underlying mechanisms of P. gingivalis in atherosclerosis attracted attention, which is thought to be crucial to the therapy of atherosclerosis. Nevertheless, the pathogenesis of atherosclerosis is much complicated, and many kinds of cells participate in it. By summarizing existing studies, we find that P. gingivalis can influence the function of many cells in atherosclerosis. It can induce the dysfunction of endothelium, promote the formation of foam cells as well as the proliferation and calcification of vascular smooth muscle cells, and lead to the imbalance of regulatory T cells (Tregs) and T helper (Th) cells, ultimately promoting the occurrence and development of atherosclerosis. This article summarizes the specific mechanism of atherosclerosis caused by P. gingivalis. It sorts out the interaction between P. gingivalis and AS-related cells, which provides a new perspective for us to prevent or slow down the occurrence and development of AS by inhibiting periodontal pathogens.

Risk evaluation at municipality level of a COVID-19 outbreak incorporating relevant geographic data: the study case of Galicia

The COVID-19 pandemic was an inevitable outcome of a globalized world in which a highly infective disease is able to reach every country in a matter of weeks. While lockdowns and strong mobility restrictions have proven to be efficient to contain the exponential transmission of the virus, its pervasiveness has made it impossible for economies to maintain this kind of measures in time. Understanding precisely how the spread of the virus occurs from a territorial perspective is crucial not only to prevent further infections but also to help with policy design regarding human mobility. From the large spatial differences in the behavior of the virus spread we can unveil which areas have been more vulnerable to it and why, and with this information try to assess the risk that each community has to suffer a future outbreak of infection. In this work we have analyzed the geographical distribution of the cumulative incidence during the first wave of the pandemic in the region of Galicia (north western part of Spain), and developed a mathematical approach that assigns a risk factor for each of the different municipalities that compose the region. This risk factor is independent of the actual evolution of the pandemic and incorporates geographic and demographic information. The comparison with empirical information from the first pandemic wave demonstrates the validity of the method. Our results can potentially be used to design appropriate preventive policies that help to contain the virus.

Artificial intelligence against COVID-19 Pandemic: A Comprehensive Insight

: COVID-19 is a pandemic initially identified in Wuhan, China, which is caused by a novel coronavirus, also recognized as the Severe Acute Respiratory Syndrome (SARS-nCoV-2). Unlike other coronaviruses, this novel pathogen may cause unusual contagious pain which results in viral pneumonia, serious heart problems, and even death. Researchers worldwide are continuously striving to develop a cure for this highly infective disease, yet there are no well-defined absolute treatments available at present. Several vaccination drives with emergency use authorisation vaccines are being done across many countries, however, their long term efficacy and side-effects study are yet to be done. The research community is analysing the situation by collecting the datasets from various sources. Healthcare professionals must thoroughly analyse the situation, devise preventive measures for this pandemic, and even develop possible drug combinations. Various analytical and statistical models have been developed, however, their outcome rate is prolonged. Thus, modern science stresses on the application of state-of-the-art methods in this combat against COVID-19. The application of Artificial intelligence (AI), and AI-driven tools are emerging as effective tools, especially with X-Ray and CT-Scan imaging data of infected subjects, infection trend predictions etc. The high efficacy of these AI systems can be observed in terms of highly accurate results, i.e. >95%, as reported in various studies. AI-driven tools are being used in COVID diagnostic, therapeutics, trend prediction, drug design and prevention to help fight against this pandemic. This paper aims to provide a deep insight into the comprehensive literature about AI and AI-driven tools in this battle against the COVID-19 pandemic. The extensive literature is divided into five sections, each describing the application of AI against COVID-19 viz. COVID-19 Prevention, diagnostic, infection spread trend prediction, therapeutic and drug repurposing.

A COMPENDIOUS REVIEW ARTICLE ON COVID-19 VACCINATION

A COVID-19 vaccine is a vaccine intended to provide acquired immunity aim to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). In Phase III trials, several COVID-19 vaccines have demonstrated effectiveness as high as 95% in preventing symptomatic COVID-19 infections. Almost twenty vaccines have been approved by at least one national regulatory authority for public use: nine conventional inactivated vaccines, two RNA vaccines, ve viral vector vaccines, and four protein subunit vaccines. At least nine different technology platforms are doing continuous research and development to create an effective as well as active vaccine against the deadlier infective disease COVID-19. Our immune system uses numerous tools to defend any kind of infection. Blood contains red blood cells, carries oxygen to tissues and organs, and white blood cells or immune cells helps to ght to defend infection. Different varieties of white blood cells defend infections in various ways. COVID-19 vaccines give assistance to our bodies to develop immunity against the coronavirus which causes COVID-19 without getting illness. It naturally takes few weeks to months after vaccination for the body to produce T-lymphocytes as well as Blymphocytes. Sometimes after vaccination also the process of building immunity can cause symptoms like fever, runny nose etc. These symptoms are usual indicating that the body is building immunity. After COVID vaccination the chances of getting a Corona infection will be only 10%. Through all available information, it is known that taking COVID vaccine is very essential.

Plague and Literature in Western Europe, from Giovanni Boccaccio to Albert Camus

In medieval times the plague hit Europe between 1330 and 1350. The Italian novelist Giovanni Boccaccio, one of the exponents of the cultural movement of Humanism, in the introduction (proem) of his “Decameron” described the devastating effects of the ‘black plague’ on the inhabitants of the city of Florence. The pestilence returned to Western Europe in several waves, between the 16th and 17th centuries. William Shakespeare in “Romeo and Juliet” and other tragedies, and Ben Jonson in “The Alchemist” made several references to the plague, but they did not offer any realistic description of that infective disease. Some decennials later Daniel Defoe, in his “A Journal of the Plague Year” (1719), gave a detailed report about the ‘Great Plague’ which hit England in 1660, based on documents of the epoch. In more recent times, Thomas S. Eliot, composing his poem “The Waste Land” was undoubtedly influenced by the spreading of another infective disease, the so-called “Spanish flu”, which affected him and his wife in December 1918. Some decennials later, the French writer and philosopher Albert Camus, in his novel “The Plague”, symbolized with a plague epidemic the war which devastated Europe, North Africa and the Far East from 1937 to 1945, extolling a death toll of over 50 million victims. Those literary works offered a sort of solace to the lovers of literature. To recall them is the purpose of the present paper, in these years afflicted by the spreading of the Covid-19 Pandemic.

Evaluation and Management of Septic Arthritis in Emergency Department “Narrative Review”

Septic arthritis (SA) is a secondary infective disease due to joints inflammation. It often appears with mono- or oligoarticular acute arthritis that frequently leads to an emergency department (ED) visit with need for prolonged hospitalization. SA is an orthopedic emergency that can threaten both life and limb due to its potential rapid destruction of the joint with fulminant sepsis, causing significant disability within hours to days. Delayed or poor treatment of septic arthritis can lead to irreversible joint damage with consequent disability in addition there to significant mortality rate. Management includes early detection and treatment with antibiotics, joint aspiration, and consultation for orthopedic surgery as potential operative management. This review aims to summarize current evidence regarding evaluation and management of septic arthritis in emergency department, and to highlight the difficulties of diagnosing and managing SA that face the healthcare providers to help overcome those difficulties and to recommend further studies to be done regarding those problems and their solutions.

Between-host dynamics (Epidemiology)

Epidemiology is the population dynamics of host–parasite systems. The spread of an infective disease is analysed with several tools. The SIR model (susceptible, infected, recovered hosts) is a standard model, with the basic reproductive number (R 0) as a characteristic. Diseases, in general, spread if R 0 > 1, which suggests a threshold size for host populations, and also for endemic maintenance or periodic outbreaks. Furthermore, spatial heterogeneity or the distribution of infections among hosts affects an epidemic. Individual-based models can follow the fate of infections more closely. Network analysis provides insights into transmission and contact rates. Models also describe the epidemics of vectored diseases, or of macroparasitic infections. Molecular epidemiology uses genetic markers or genomes to follow the spread of an infectious disease; phylodynamics reconstructs transmission chains, especially for viral diseases. Immunoepidemiology studies how immune defences affect an epidemic and identifies immunological markers for the study of infectious disease dynamics.

Anti-biofilm Approach in Infective Endocarditis Exposes New Treatment Strategies for Improved Outcome

Infective endocarditis (IE) is a life-threatening infective disease with increasing incidence worldwide. From early on, in the antibiotic era, it was recognized that high-dose and long-term antibiotic therapy was correlated to improved outcome. In addition, for several of the common microbial IE etiologies, the use of combination antibiotic therapy further improves outcome. IE vegetations on affected heart valves from patients and experimental animal models resemble biofilm infections. Besides the recalcitrant nature of IE, the microorganisms often present in an aggregated form, and gradients of bacterial activity in the vegetations can be observed. Even after appropriate antibiotic therapy, such microbial formations can often be identified in surgically removed, infected heart valves. Therefore, persistent or recurrent cases of IE, after apparent initial infection control, can be related to biofilm formation in the heart valve vegetations. On this background, the present review will describe potentially novel non-antibiotic, antimicrobial approaches in IE, with special focus on anti-thrombotic strategies and hyperbaric oxygen therapy targeting the biofilm formation of the infected heart valves caused by Staphylococcus aureus. The format is translational from preclinical models to actual clinical treatment strategies.

Impact of the Covid-19 Pandemic on Anxiety Levels of Medical Students in Pakistan

Covid-19 is a communicable infective disease and has been the major current health challenge since it emerged in China in late 2019. Although earlier data analyses of Dawei Wang etc. from 138 hospital of China had shown that its mortality rate is less than 5%, shown (4.3%), major concern is its widespread transmission. The Covid-19 pandemic has adversely affected economics and the mental health of millions worldwide. Fear is the one of the psychological outcomes of pandemic, but the psychological impact of the pandemic was overshadowed by financial and economic impact, which are interrelated. Conducted through an online questionnaire, this study evaluates the anxiety level of medical students of Nishtar Medical University and Multan and Quaid-e-Azam Medical College (QAMC) Bahawalpur in southern Punjab of Pakistan by using fear Covid-19 scale. The research employs the fear scale developed by Ahorsu et al. based on unidimensional 7 items, 5-point Likert scale. This scale is a valid and reliable tool and has been used to assess the fear for Covid-19 in general population. This scale has been used internationally by many researchers to measure anxiety levels. The research correlated the socio demographic variables, such as age, sex, education level and living surroundings, with anxiety levels that would help to redesign curriculum for education and to plan programs to enhance the knowledge of medical students for preventive measures against Covid-19. 577 male and female students from 1st to 5th year of bachelor’s in medicine and bachelor’s in surgery (MBBS) with ages ranging from 17 to 25 years participated in this study.

COVID-19 and Its Impact on Upper Gastrointestinal (GI) Cancer Management

Coronavirus disease 2019 (COVID-19), caused by the novel, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has left dramatic footprints on human health and economy. Cancer, whilst not an infective disease, is prevalent in epidemic proportions and cannot be pretermitted due to the impact of COVID-19. As we emanate from the second national lockdown in the UK with mixed feelings of hope and despair—due to vaccination and new COVID-19 variant, respectively—we reflect on the impact of the first wave on the provision on diagnosis and management of with upper gastrointestinal (UGI) cancers. This review provides a critical analysis of available literature on COVID-19 and its impact on cancer management in general and that of UGI cancers in particular.