Vaccination against SARS-CoV-2: a human enhancement story

Background Vaccination is an essential strategy for mitigating the COVID-19 pandemic. Besides its significance as a public health measure, vaccination is a sophisticated example of modern biotechnology. Since vaccination gives the human body an ability that it does not naturally possess, the question arises as to its classification as Human Enhancement. Main Body Exemplified on a selection of different definitions, we conclude that vaccinations may indeed be classified and treated as a form of Human Enhancement. This raises some ethical issues that are notorious in the broad field of Human Enhancement. A study with N = 67 participants revealed that vaccinations are perceived neither as a clear nor poor example of Human Enhancement. Conclusion We argue that qualifying vaccination technology as Human Enhancement does not provide convincing arguments to reject vaccination. By examining the Human Enhancement debate and the similarities to the issue of vaccination shown here, policymakers can learn valuable lessons regarding mass vaccination programs’ current and future handling.

Association between angiotensinogen (AGT), angiotensin-converting enzyme (ACE) and angiotensin-II receptor 1 (AGTR1) polymorphisms and COVID-19 infection in the southeast of Iran: a preliminary case-control study

Background The COVID-19 pandemic remains an emerging public health crisis with serious adverse effects. The disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV--2) infection, targeting angiotensin-converting enzyme-2 (ACE2) receptor for cell entry. However, changes in the renin-angiotensin system (RAS) balance alter an individual’s susceptibility to COVID-19 infection. We aimed to evaluate the association between AGT rs699 C > T, ACE rs4646994 I/D, and AGTR1 rs5186 C > A variants and the risk of COVID-19 infection and the severity in a sample of the southeast Iranian population. Methods A total of 504 subjects, including 258 COVID-19 positives, and 246 healthy controls, were recruited. Genotyping of the ACE gene rs4646994, and AGT rs699, and AGTR1 rs5186 polymorphisms was performed by polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism (PCR-RFLP), respectively. Results Our results showed that the II genotype of ACE rs4646994 and the I allele decreased the risk of COVID-19 infection. Moreover, we found that the TC genotype and C allele of AGT rs699 increased the risk of COVID-19 infection. The AGTR1 rs5186 was not associated with COVID-19 infection. Also, we did not find any association between these polymorphisms and the severity of the disease. However, we found a significantly higher age and prevalence of diabetes and hypertension in patients with severe disease than a non-severe disease. Conclusions These findings suggest that ACE rs4646994 and AGT rs699 polymorphisms increase the risk of COVID-19 infection in a southeast Iranian population.

Safety and efficacy of autologous non-hematopoietic enriched stem cell nebulization in COVID-19 patients: a randomized clinical trial, Abu Dhabi 2020

Background The novel SARS-CoV-2 has caused the coronavirus disease 2019 (COVID-19) pandemic. Currently, with insufficient worldwide vaccination rates, identifying treatment solutions to reduce the impact of the virus is urgently needed. Method An adaptive, multicentric, open-label, and randomized controlled phase I/II clinical trial entitled the “SENTAD-COVID Study” was conducted by the Abu Dhabi Stem Cells Center under exceptional conditional approval by the Emirates Institutional Review Board (IRB) for COVID-19 Research Committee from April 4th to July 31st, 2020, using an autologous peripheral blood non-hematopoietic enriched stem cell cocktail (PB-NHESC-C) administered by compressor (jet) nebulization as a complement to standard care therapy. The primary endpoints include safety and efficacy assessments, adverse events, the mortality rate within 28 days, and the time to clinical improvement as measured by a 2-point reduction on a seven-category ordinal scale or discharge from the hospital whichever occurred first. Results The study included a total of 139 randomized COVID-19 patients, with 69 in the experimental group and 70 in the control group (standard care). Overall survival was 94.20% for the cocktail-treated group vs. 90.27% for the control group. Adverse events were reported in 50 (72.46%) patients receiving PB-NHESC-C and 51 (72.85%) in the control group (p = 0.9590), with signs and symptoms commonly found in COVID-19. After the first 9 days of the intervention, 67.3% of cocktail-treated patients recovered and were released from hospitals compared to 53.1% (RR = 0.84; 95% CI, 0.56–1.28) in the control group. Improvement, i.e., at least a 2-point reduction in the severity scale, was more frequently observed in cocktail-treated patients (42.0%) than in controls (17.0%) (RR = 0.69; 95% CI, 0.56–0.88). Conclusions Cocktail treatment improved clinical outcomes without increasing adverse events. Thus, the nebulization of PB-NHESC-C was safe and effective for treatment in most of these patients. Trial registration ClinicalTrials.gov. NCT04473170. It was retrospectively registered on July 16th, 2020.

A novel method for maintaining the stability of freshly cultured Mesenchymal stem cells in clinical grade injection ready state without cryopreservation

Background Mesenchymal Stem Cells (MSCs) are multipotent cells with low immuonogenecity, and dynamic tissue repair potential, which explains the overwhelming attention they have attracted in regenerative therapy. One notable challenge in MSCs therapy is the bench to bed timeline of freshly cultured MSCs; it does not exceed 24 h. For use after 24 h, MSC need to be cryopreserved - which can preserve the cells for years - but it is a costly and damaging process. Here we introduce a method to extend the bench to bed lifetime of MSCs up to 4 days without the high cost and cell damaging effects of cryopreservation. Our method is based on preserving the MSCs in human plasma. Methods MSCs of 12 tissue samples - 4 adipose, 4 bone marrow and 4 Wharton’s jelly- were cultured and expanded in standard conditions. Cells harvested from passage 2 or 3 were washed, centrifuged, pelleted, and re-suspended in human plasma. Cell suspensions were refrigerated (5 ± 3 °C) or stored at room temperature (22 ± 3 °C) in a sterile, temperature controlled room. During the next 7 days, two tubes (one from each group) were examined every 24 h to assess MSCs viability and growth potential. On day 3, we assessed MSC cell surface markers and its differentiation potential to adipocyte and osteocyte tissues. Results were analyzed by computing the overall mean and applying the independent-samples t-test to those means. Results The sample means for both cell expansion and cell viability were compared between the two “refrigerator” and “room temperature” groups. Although there was a gradual decrease in cell growth potential between the cells stored for 1 day to those stored for 7 days, we show more than 80% of the cells remain alive for up to 4 days of storage in both groups. The cells reached 80% confluency in under 20 days for all samples stored up to 4 days. No significant differences were observed between the two groups (room temperature and refrigerator stored). The differentiation potential to adipocyte and osteocyte tested on day 3 were positive in all samples. The analysis of cell surface markers tested on day 3 were positive for CD90, CD105, CD73 and negative for CD34, CD45 and HLA-DR. Conclusion We present a method of MSC culture medium using human plasma that can preserve their viability and growth potential for up to 4 days in both room and refrigerator temperatures without losing their stemness characteristics (we recommend use of 5 ± 3 °C). This novel method will allow rapid expansion and therapeutic use of MSCs. Since the cells can be maintained in clinical grade, injection ready state for several days, they can be transported across the globe.

PhiΦBreast & theory of spiral cancer new diagnostic techniques for breast cancer detection

Background Today, breast cancer is one of the most aggressive cancers in women and new cases continue to increase worldwide. The incidence of this tumor is kept under control especially with surgery. In order to reduce mortality we need to detect this life threatening disease at an earlier stage. For two years, we have conducted a study for the identification and characterization of suspicious breast lesions using a new diagnostic technique applied to ultrasonography and mammography called “PhiΦBreast.” Methods Identification and characterization of category C4-C5 lesions of the breast with high Predictive Positive PPV value, with a new innovative method called “PhiΦBreast” using the Golden Ratio (Phi, or Φ 1.618...) Fibonacci sequence and a Predictive Algorithm, applied to the ultrasonography and mammography with subsequent deepening with cytological examination using fine needle aspiration (FNAC), according to evaluation criteria of the Breast Imaging Report Data System (BI-RADS) and the American College of Radiology (ACR). Usefulness of this research and the use of this new diagnostic tecnique is to detect the breast cancer in early stage. In addition to develop a classification model of the histological type identified in the section areas and the percentage of probability in relation between the golden spiral and Fibonacci sequence. This amazing intuition and research has given contribution to the new Theory of Spiral Cancer. Results With the use of Golden Ratio and Fibonacci sequence, applied to ultrasonography and mammography, we have experimented and developed a diagnostic map with characteristics of high probability of identifying suspicious lesions at an early stage. We examined 987 women, 55 lesions detected with PhiΦBreast pattern were classified according to BI-RADS descriptors for US-imaging, including morphologic features that had a high predictive value for the malignancy (p <0.001). This innovative diagnostic technique has shown a sensitivity of 95%, a specificity of 97%, a positive predictive value of 97%, and negative predictive value of 96%. The discriminating capacity of PhiΦBreast was significantly better than normal ultrasonography (P < 0,05). Furthermore with a predictive algorithm associated with malignant cytology after FNAC, we have classified different types of potentially life threatening cancers for patients. Conclusion PhiΦBreast could be an important new model diagnostic technique to be applied ultrasound and mammography for detection of malignant lesions of category C4-C5. In diagnostic imaging beyond the identification of a lesion and classification according to the BI-RADS category and the evaluation criteria of the ACR is fundamental to recognize predictively the characteristics of a potentially aggressive tumor. Everything mentioned above, reinforces the concept that the early diagnosis is essential because it allows to remove small tumors and therefore capable of producing more limited metastases than the potential of the most voluminous neoplasm. This way, we could plan an effective cure for the patient. This new model (PhiΦBreast) could represent the cornerstone as an important contribution for early diagnosis of breast cancer.

The protective role of statins in COVID-19 patients: a retrospective observational study

Background To evaluate and determine the protective role of statins in COVID-19 patients. Methods This is a retrospective cohort study conducted across five hospitals in India. Patients diagnosed with COVID-19 and hospitalized with existing and valid medical documentation were included. Results This study comprised 3252 COVID-19 patients, of whom 1048 (32.2%) were on statins, with 52.4% being males. The comorbidity prevalence of hypertension was 75%, followed by diabetes 62.51% and coronary artery disease being 47.5%. At the time of hospitalization, statin users had a higher incidence of dyspnea, cough, and fatigue (95.8, 93.3, and 92.7%). The laboratory results revealed a lower mean of WBC count (7.8 × 103/μL), D-dimer (2.4 μg/mL), and C-reactive protein (103 mg/L) among statin users. They also had lower mortality rates (17.1%), a lesser requirement for mechanical ventilation (20%), and hemodialysis (5.4%). Conclusion This observation study elaborates on the beneficial effects of statins in COVID-19 patients. However, the inferences from this study should be viewed with caution due to the impending effect of confounding factors on its statistical results.

Application of a composite measure of product adherence, protocol compliance, and semen exposure to a phase III microbicide HIV prevention trial

Background Strict adherence to antiretroviral-based microbicide use is important for effective HIV prevention. We previously developed a composite measure of product adherence, protocol compliance, and semen exposure for determining vaginal use of tenofovir (TFV) 1% gel applicators through biomarkers and residual drug analyses. In this study, we tested the ability of the composite measure in vaginally used TFV gel applicators from a Phase III HIV prevention clinical trial. Methods Used vaginal gel applicators from the FACTS 001 study were swabbed for detection of vaginal bacterial markers (vaginal insertion), semen DNA markers (semen exposure), and residual TFV gel (product use). Results Of 1,098 evaluable TFV and placebo applicators, 80% had detectable vaginal insertion biomarkers and 52% had semen biomarkers. Ninety-nine percent of vaginally inserted applicators TFV applicators had detectable residual TFV as measured by liquid chromatography with tandem mass spectroscopy (LC–MS/MS). Residual TFV levels were also successfully detected using Fourier Transform Infrared (FTIR)-based spectroscopy. Conclusions Vaginal insertion and semen exposure biomarkers were detectable on used TFV 1% gel applicators. Residual TFV on these gel applicators was detectable by LC–MS/MS and FTIR-based spectroscopy, which has potential to be a more convenient and quicker method for detecting drug use. With continual improvements, this composite measure of product adherence, protocol compliance, and semen exposure has potential to assess use of not only TFV gel but also other topical microbicides or products.

Clinical progression of patients with COVID-19 in Lagos State, Nigeria

Background The majority of COVID-19 research has been devoted to characterizing the epidemiology and early clinical aspects of the virus. In Lagos, Nigeria, we looked at the temporal progression of COVID-19 patients. We included 1337 confirmed COVID-19 cases in our study from February 27th to March 27th 2020. Of the 1337 patients enrolled, the median age was 50 years old, and 800 (59.83%) were male while 537 (40.16%) were female. Method In symptomatic patients, the time from the beginning of signs to admission was 4 (2–7) days. Fever occurred in 217 (16.2%) while cough occurred in 211(15.78%) patients respectively. Patients were given 5–6 treatment, including nutrition support, supplementary oxygen, and antiviral medicines (e.g., Remdesivir, dexamethasone) in a limited percentage of cases. The assessed median period of infection in all patients was 10 days after the start of symptoms (95 confidential intervals [CIs]: 8–11 days). The duration of fever was slightly longer in patients admitted to intensive care units (ICU) than in those who were not (31 days versus 9 days, respectively, P < 0.003). Results On day 7 after the onset of symptoms, radiological deterioration of the original picture was found in 500 (37.39%) patients. On day 13, 154 of these patients (94.5%) showed signs of radiological improvement. The average time it took for upper respiratory tract samples to test negative for reverse transcriptase PCR was 10 days (90 percent confidence interval: 10–12 days). Virus clearance was more significant in ICU patients than in non-ICU patients (P < 0.003). Conclusions Community members should continue to adhere to the recommended methods of preventing the spread of COVID-19 infection and patients should seek care early to reduce the risk of mortality associated with the infection as rapidly as possible.

Predictive model and feature importance for early detection of type II diabetes mellitus

Background Accurate prediction and early recognition of type II diabetes (T2DM) will lead to timely and meaningful interventions, while preventing T2DM associated complications. In this context, machine learning (ML) is promising, as it can transform vast amount of T2DM data into clinically relevant information. This study compares multiple ML techniques for predictive modelling based on different T2DM associated variables in an African population, Ghana. Methods The study involved 219 T2DM patients and 219 healthy individuals who were recruited from the hospital and the local community, respectively. Anthropometric and biochemical information including glycated haemoglobin (HbA1c), body mass index (BMI), blood pressure, fasting blood sugar (FBS), serum lipids [(total cholesterol (TC), triglycerides (TG), high and low-density lipoprotein cholesterol (HDL-c and LDL-c)] were collected. From this data, four ML classification algorithms including Naïve-Bayes (NB), K-Nearest Neighbor (KNN), Support Vector Machines (SVM) and Decision Tree (DT) were used to predict T2DM. Precision, Recall, F1-Scores, Receiver Operating Characteristics (ROC) scores and the confusion matrix were computed to determine the performance of the various algorithms while the importance of the feature attributes was determined by recursive feature elimination technique. Results All the classifiers performed beyond the acceptable threshold of 70% for Precision, Recall, F-score and Accuracy. After building the predictive model, 82% of diabetic test data was detected by the NB classifier, of which 93% were accurately predicted. The SVM classifier was the second-best performing classifier which yielded an overall accuracy of 84%. The non-T2DM test data yielded an accurate prediction score of 75% from the 98% of the proportion of the non-T2DM test data. KNN and DT yielded accuracies of 83% and 81%, respectively. NB had the best performance (AUC = 0.87) followed by SVM (AUC = 0.84), KNN (AUC = 0.85) and DT (AUC = 0.81). The best three feature attributes, in order of importance, were HbA1c, TC and BMI whereas the least three importance of the features were Age, HDL-c and LDL-c. Conclusion Based on the predictive performance and high accuracy, the study has shown the potential of ML as a robust forecasting tool for T2DM. Our results can be a benchmark for guiding policy decisions in T2DM surveillance in resource and medical expertise limited countries such as Ghana.

Idiotype/anti-idiotype antibodies: as a glorious savior in COVID-19 pandemics

The idiotype network is experimentally modified to provide protective immunity against various microbial pathogens. Both internal and non-internal image-idiotype antibodies can trigger specific immune responses to antigens. The current outbreak of Severe Acute Respiratory Syndrome 2 (SARS-2) has provided a great opportunity to take advantage of idiotype / anti-idiotype antibodies as a protective regimen when no approved vaccine is available on earth. The current review identifies successful applications of idiotype/ anti-idiotype antibodies in various viral diseases and highlights their importance in COVID-19 pandemics. In the absence of vaccines and targeted therapies, polyclonal idiotype/ anti-idiotype antibodies against the viral structure may be a potential approach to the prevention and treatment of COVID-19 patients.