A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess ...of either pro-inflammatory or anti-inflammatory pathways that can lead to widespread inflammation, tissue damage, and organ failure. A dysregulated immune response can manifest as changes in differentiated immune cell populations and concentrations of circulating biomarkers. To propose an early diagnostic system that enables differentiation and identifies the severity of immune-dysregulated syndromes, we built an artificial intelligence tool that uses input data from single-cell RNA sequencing. In our results, single-cell transcriptomics successfully distinguished between mild and severe sepsis and COVID-19 infections. Moreover, by interpreting the decision patterns of our classification system, we identified that different immune cells upregulating or downregulating the expression of the genes CD3, CD14, CD16, FOSB, S100A12, and TCRɣδ can accurately differentiate between different degrees of infection. Our research has identified genes of significance that effectively distinguish between infections, offering promising prospects as diagnostic markers and providing potential targets for therapeutic intervention.
On 31 December 2019 the Wuhan Health Commission reported a cluster of atypical pneumonia cases that was linked to a wet market in the city of Wuhan, China. The first patients began experiencing ...symptoms of illness in mid-December 2019. Clinical isolates were found to contain a novel coronavirus with similarity to bat coronaviruses. As of 28 January 2020, there are in excess of 4,500 laboratory-confirmed cases, with > 100 known deaths. As with the SARS-CoV, infections in children appear to be rare. Travel-related cases have been confirmed in multiple countries and regions outside mainland China including Germany, France, Thailand, Japan, South Korea, Vietnam, Canada, and the United States, as well as Hong Kong and Taiwan. Domestically in China, the virus has also been noted in several cities and provinces with cases in all but one provinence. While zoonotic transmission appears to be the original source of infections, the most alarming development is that human-to-human transmission is now prevelant. Of particular concern is that many healthcare workers have been infected in the current epidemic. There are several critical clinical questions that need to be resolved, including how efficient is human-to-human transmission? What is the animal reservoir? Is there an intermediate animal reservoir? Do the vaccines generated to the SARS-CoV or MERS-CoV or their proteins offer protection against 2019-nCoV? We offer a research perspective on the next steps for the generation of vaccines. We also present data on the use of in silico docking in gaining insight into 2019-nCoV Spike-receptor binding to aid in therapeutic development. Diagnostic PCR protocols can be found at https://www.who.int/health-topics/coronavirus/laboratory-diagnostics-for-novel-coronavirus.
Post-acute sequelae of COVID-19 (PASC) or the continuation of COVID-19 (Coronavirus disease 2019) symptoms past 12 weeks may affect as many as 30% of people recovering from a SARS-CoV-2 (severe acute ...respiratory coronavirus 2) infection. The mechanisms regulating the development of PASC are currently not known; however, hypotheses include virus reservoirs, pre-existing conditions, microblood clots, immune dysregulation, as well as poor antibody responses. Importantly, virus neutralizing antibodies are essential for COVID-19 recovery and protection from reinfection but there is currently limited information on these immune regulators and associated cytokines in PASC patients. Understanding the key drivers of general and specific symptoms associated with Long COVID and the presence of virus neutralizing antibodies in PASC will aid in the development of therapeutics, diagnostics, and vaccines which currently do not exist. We designed a cross-sectional study to investigate systemic antibody and cytokine responses during COVID-19 recovery and PASC. In total, 195 participants were recruited in one of four groups: (1) Those who never had COVID-19 (No COVID); (2) Those in acute COVID-19 recovery (Acute Recovery) (4-12 weeks post infection); (3) Those who recovered from COVID-19 (Recovered) (+ 12 weeks from infection); and (4) those who had PASC (PASC) (+ 12 weeks from infection). Participants completed a questionnaire on health history, sex, gender, demographics, experiences with COVID-19 acute and COVID-19 recovery/continuing symptoms. Serum samples collected were evaluated for antibody binding to viral proteins, virus neutralizing antibody titers, and serum cytokine levels using Ella SimplePlex Immunoassay™ panels. We found participants with PASC reported more pre-existing conditions (e.g. such as hypertension, asthma, and obesity), and PASC symptoms (e.g. fatigue, brain fog, headaches, and shortness of breath) following COVID-19 than COVID-19 Recovered individuals. Importantly, we found PASC individuals to have significantly decreased levels of neutralizing antibodies toward both SARS-CoV-2 and the Omicron BA.1 variant. Sex analysis indicated that female PASC study participants had sustained antibody levels as well as levels of the inflammatory cytokines GM-CSF and ANG-2 over time following COVID-19. Our study reports people experiencing PASC had lower levels of virus neutralizing antibodies; however, the results are limited by the collection time post-COVID-19 and post-vaccination. Moreover, we found females experiencing PASC had sustained levels of GM-CSF and ANG-2. With lower levels of virus neutralizing antibodies, this data suggests that PASC individuals not only have had a suboptimal antibody response during acute SARS-CoV-2 infection but may also have increased susceptibility to subsequent infections which may exacerbate or prolong current PASC illnesses. We also provide evidence suggesting GM-CSF and ANG-2 to play a role in the sex-bias of PASC. Taken together, our findings maybe important for understanding immune molecular drivers of PASC and PASC subgroups.
The COVID-19 pandemic, caused by the SARS-CoV-2 coronavirus, is responsible for over 400 million cases and over 5. 5 million deaths worldwide. In response to widespread SARS-CoV-2 infection, ...immunization of the global population has approached 60% one dose and 54% full dose vaccination status. Emerging data indicates decreasing circulating antibody levels as well as decreases in other immune correlates in vaccinated individuals. Complicating the determination of vaccine effectiveness is the concomitant emergence of novel SARS-CoV-2 variants with substantial antigenic differences from the ancestral D614G strain. The Omicron variant (B.1.1.529) spike protein has over 30 mutations compared with the D614G spike protein, which was used to design most SARS-CoV-2 vaccines in use today. Therefore, breakthrough cases of SARS-CoV-2 infections or severe disease in fully vaccinated individuals must be interpreted with caution taking into consideration vaccine waning and the degree of vaccine variant-mismatch resulting in adaptive immune evasion by novel emerging SARS-CoV-2 variants.
Millions of deaths worldwide are a result of sepsis (viral and bacterial) and septic shock syndromes which originate from microbial infections and cause a dysregulated host immune response. These ...diseases share both clinical and immunological patterns that involve a plethora of biomarkers that can be quantified and used to explain the severity level of the disease. Therefore, we hypothesize that the severity of sepsis and septic shock in patients is a function of the concentration of biomarkers of patients.
In our work, we quantified data from 30 biomarkers with direct immune function. We used distinct Feature Selection algorithms to isolate biomarkers to be fed into machine learning algorithms, whose mapping of the decision process would allow us to propose an early diagnostic tool.
We isolated two biomarkers, i.e., Programmed Death Ligand-1 and Myeloperoxidase, that were flagged by the interpretation of an Artificial Neural Network. The upregulation of both biomarkers was indicated as contributing to increase the severity level in sepsis (viral and bacterial induced) and septic shock patients.
In conclusion, we built a function considering biomarker concentrations to explain severity among sepsis, sepsis COVID, and septic shock patients. The rules of this function include biomarkers with known medical, biological, and immunological activity, favoring the development of an early diagnosis system based in knowledge extracted from artificial intelligence.
Mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome continue to threaten the global landscape of the coronavirus disease 2019 (COVID-19) pandemic. The Omicron variant ...(B.1.1.529) rapidly displaced previous ‘variants of concern’ (VoC) in 2021 due to its high rate of transmissibility and multitude of mutations. This global influx of infections saturated healthcare systems, overwhelmed testing capacity and case reporting, and increased the COVID-19 death toll. Global health leaders are now being faced with the most transmissible COVID-19 variants yet, the Omicron sublineages BA.4 and BA.5, which contain additional spike protein (S) mutations from previous Omicron and VoC serotypes. With universally observed antibody waning, increasing vaccine-variant mismatch, and resuming international travel, the stage is set for unprecedented levels of breakthrough infections and superspreading events. In this paper, we raise awareness to these novel variants and provide context for the high likelihood of an upcoming wave of infection capable of inflicting significant disease burden on a global scale.
After the initial onset of the SARS-CoV-2 pandemic, the government of Canada and provincial health authorities imposed restrictive policies to limit virus transmission and mitigate disease burden. In ...this study, the pandemic implications in the Canadian province of Nova Scotia (NS) were evaluated as a function of the movement of people and governmental restrictions during successive SARS-CoV-2 variant waves (i.e., Alpha through Omicron).
Publicly available data obtained from community mobility reports (Google), the Bank of Canada Stringency Index, the "COVID-19 Tracker" service, including cases, hospitalizations, deaths, and vaccines, population mobility trends, and governmental response data were used to relate the effectiveness of policies in controlling movement and containing multiple waves of SARS-CoV-2.
Our results indicate that the SARS-CoV-2 pandemic inflicted low burden in NS in the initial 2 years of the pandemic. In this period, we identified reduced mobility patterns in the population. We also observed a negative correlation between public transport (-0.78), workplace (-0.69), retail and recreation (-0.68) and governmental restrictions, indicating a tight governmental control of these movement patterns. During the initial 2 years, governmental restrictions were high and the movement of people low, characterizing a 'seek-and-destroy' approach. Following this phase, the highly transmissible Omicron (B.1.1.529) variant began circulating in NS at the end of the second year, leading to increased cases, hospitalizations, and deaths. During this Omicron period, unsustainable governmental restrictions and waning public adherence led to increased population mobility, despite increased transmissibility (26.41-fold increase) and lethality (9.62-fold increase) of the novel variant.
These findings suggest that the low initial burden caused by the SARS-CoV-2 pandemic was likely a result of enhanced restrictions to contain the movement of people and consequently, the spread of the disease. Easing public health restrictions (as measured by a decline in the BOC index) during periods of high transmissibility of circulating COVID-19 variants contributed to community spread, despite high levels of immunization in NS.
The severe form of COVID-19 can cause a dysregulated host immune syndrome that might lead patients to death. To understand the underlying immune mechanisms that contribute to COVID-19 disease we have ...examined 28 different biomarkers in two cohorts of COVID-19 patients, aiming to systematically capture, quantify, and algorithmize how immune signals might be associated to the clinical outcome of COVID-19 patients.
The longitudinal concentration of 28 biomarkers of 95 COVID-19 patients was measured. We performed a dimensionality reduction analysis to determine meaningful biomarkers for explaining the data variability. The biomarkers were used as input of artificial neural network, random forest, classification and regression trees, k-nearest neighbors and support vector machines. Two different clinical cohorts were used to grant validity to the findings.
We benchmarked the classification capacity of two COVID-19 clinicals studies with different models and found that artificial neural networks was the best classifier. From it, we could employ different sets of biomarkers to predict the clinical outcome of COVID-19 patients. First, all the biomarkers available yielded a satisfactory classification. Next, we assessed the prediction capacity of each protein separated. With a reduced set of biomarkers, our model presented 94% accuracy, 96.6% precision, 91.6% recall, and 95% of specificity upon the testing data. We used the same model to predict 83% and 87% (recovered and deceased) of unseen data, granting validity to the results obtained.
In this work, using state-of-the-art computational techniques, we systematically identified an optimal set of biomarkers that are related to a prediction capacity of COVID-19 patients. The screening of such biomarkers might assist in understanding the underlying immune response towards inflammatory diseases.
Critically ill COVID-19 patients start developing single respiratory organ failure that often evolves into multiorgan failure. Understanding the immune mechanisms in severe forms of an infectious ...disease (either critical COVID-19 or bacterial septic shock) would help to achieve a better understanding of the patient's clinical trajectories and the success of potential therapies. We hypothesized that a dysregulated immune response manifested by the abnormal activation of innate and adaptive immunity might be present depending on the severity of the clinical presentation in both COVID-19 and bacterial sepsis. We found that critically ill COVID-19 patients demonstrated a different clinical endotype that resulted in an inflammatory dysregulation in mild forms of the disease. Mild cases (COVID-19 and bacterial non severe sepsis) showed significant differences in the expression levels of CD8 naïve T cells, CD4 naïve T cells, and CD4 memory T cells. On the other hand, in the severe forms of infection (critical COVID-19 and bacterial septic shock), patients shared immune patterns with upregulated single-cell transcriptome sequencing at the following levels: B cells, monocyte classical, CD4 and CD8 naïve T cells, and natural killers. In conclusion, we identified significant gene expression differences according to the etiology of the infection (COVID-19 or bacterial sepsis) in the mild forms; however, in the severe forms (critical COVID-19 and bacterial septic shock), patients tended to share some of the same immune profiles related to adaptive and innate immune response. Severe forms of the infections were similar independent of the etiology. Our findings might promote the implementation of co-adjuvant therapies and interventions to avoid the development of severe forms of disease that are associated with high mortality rates worldwide.
Surgical Site Infections (SSIs) are infections of incision or deep tissue at operation sites. These infections prolong hospitalization, delay wound healing, and increase the overall cost and ...morbidity.
This study aimed to investigate anaerobic and aerobic bacteria prevalence in surgical site infections and determinate antibiotic susceptibility pattern in these isolates.
One hundred SSIs specimens were obtained by needle aspiration from purulent material in depth of infected site. These specimens were cultured and incubated in both aerobic and anaerobic condition. For detection of antibiotic susceptibility pattern in aerobic and anaerobic bacteria, we used disk diffusion, agar dilution, and E-test methods.
A total of 194 bacterial strains were isolated from 100 samples of surgical sites. Predominant aerobic and facultative anaerobic bacteria isolated from these specimens were the members of Enterobacteriaceae family (66, 34.03%) followed by Pseudomonas aeruginosa (26, 13.4%), Staphylococcus aureus (24, 12.37%), Acinetobacter spp. (18, 9.28%), Enterococcus spp. (16, 8.24%), coagulase negative Staphylococcus spp. (14, 7.22%) and nonhemolytic streptococci (2, 1.03%). Bacteroides fragilis (26, 13.4%), and Clostridium perfringens (2, 1.03%) were isolated as anaerobic bacteria. The most resistant bacteria among anaerobic isolates were B. fragilis. All Gram-positive isolates were susceptible to vancomycin and linezolid while most of Enterobacteriaceae showed sensitivity to imipenem.
Most SSIs specimens were polymicrobial and predominant anaerobic isolate was B. fragilis. Isolated aerobic and anaerobic strains showed high level of resistance to antibiotics.