In Utero Transplantation of Placenta-Derived Mesenchymal Stromal Cells for Potential Fetal Treatment of Hemophilia A.

Hemophilia A (HA) is an X-linked recessive disorder caused by mutations in the factor VIII ( FVIII) gene leading to deficient blood coagulation. The current standard of care is frequent infusions of plasma-derived FVIII or recombinant B-domain-deleted FVIII (BDD-FVIII). While this treatment is effective, many patients eventually develop FVIII inhibitors that limit the effectiveness of the infused FVIII. As a monogenic disorder, HA is an ideal target for gene or cell-based therapy. Several studies have investigated allogeneic stem cell therapy targeting in utero or postnatal treatment of HA but have not been successful in completely correcting HA. Autologous in utero transplantation of mesenchymal stem cells is promising for treatment of HA due to the naive immune status of the fetal environment as well as its potential to prevent transplant rejection and long-term FVIII inhibitor formation. HA can be diagnosed by chorionic villus sampling performed during the first trimester (10 to 13 wk) of gestation. In this study, we used an established protocol and isolated placenta-derived mesenchymal stromal cells (PMSCs) from first trimester chorionic villus tissue and transduced them with lentiviral vector encoding the BDD-FVIII gene. We show that gene-modified PMSCs maintain their immunophenotype and multipotency, express, and secrete high levels of active FVIII. PMSCs were then transplanted at embryonic day 14.5 (E14.5) into wild-type fetuses from time-mated pregnant mice. Four days after birth, pups were checked for engraftment, and varying levels of expression of human green fluorescent protein were found in the organs tested. This study shows feasibility of the approach to obtain PMSCs from first trimester chorionic villus tissue, genetically modify them with the FVIII gene, and transplant them in utero for cell-mediated gene therapy of HA. Future studies will involve evaluation of long-term engraftment, phenotypic correction in HA mice, and prevention of FVIII inhibitor development by this approach

Are Health Workers in Nigeria Prepared for the COVID-19 Pandemic? A Case Study of Selected Health Workers in Plateau State, Nigeria

Background: COVID-19 is a disease that has resulted in a worldwide pandemic. Health workers have been identified to be at a higher risk compared to the general population due to increased exposure primarily at the work place and having to deal with a novel disease whose epidemiology is still evolving. As health workers are vital to control efforts, their response will be influenced by what they know, their perception of the disease and their practices. This study therefore sought to assess the knowledge, perceptions and practices of health workers on COVID-19 in Plateau State, Nigeria. Method: It is a descriptive study that used a self-administered questionnaire to collect data on 105 health workers of Plateau State who were purposively selected. Data was collected on their knowledge, perceptions and practice of COVID-19 and analyzed using SPSS version 23 at a confidence interval of 95%. Results: Mean age of health workers was 42.5 ± 9.2 years.  Females made up 58% of the respondents, males were 42%.  Nurses made up 69% of the respondents.  More than 70% had worked for 10 – 29 years. Knowledge of COVID-19 was found to be inadequate in 57% of the health workers with social media being most frequent (69.5%) source of information. Most (86.6%) respondents had a good perception towards COVID-19 and 62.8% were willing to attend to a COVID-19 patient. There were consistent practices of hand hygiene and cough etiquette. Sixty percent had access to at least one form of personal protective equipment though 72.4% had never had training on putting on the full personal protective gear required for COVID-19. Conclusion: There is an urgent need for training of health care workers in Plateau State and provision of full personal protective gear to ensure their safety at work

Distribution of Human Papillomavirus Genotypes Among Women with Cervical Cancer in Nigeria

The prevalence of invasive cervical cancer (ICC) is high in Nigeria, with over 12,000 new cases responsible for over 8,000 deaths of women annually. This has been attributed to a large population of women with HIV infection who are 6 times at risk of developing ICC than women without HIV. We examined the distribution and prevalence of HPV genotypes among HIV-positive and HIV-negative women with ICC in Nigeria. We utilized baseline data and DNA samples from cervical tissue obtained from a prospective cohort study in Nigeria between March 2018 and September 2022. High-throughput next-generation amplicon sequencing of the HPV L-1 gene was used to identify and classify HPV genotypes from cervical samples. Logistic regression models were used to estimate associations between HIV and HPV infections. All statistical analyses were performed on Stata/BE 17.0 software. The study included 349 women (185 HIV-/ICC+, 64 HIV+/ICC+, 100 and HIV+/ICC-). The mean (SD) of HIV-positive women with ICC was 49.5 (10.9) years, compared to 47.0 (8.8) in HIV-positive women without ICC and 58.8 (12.9) in HIV-negative women with ICC, p <0.001. We tested 286 women (82.0%) for HPV and found HIV-positive women with ICC had a higher prevalence of HR-HPV, 77.6%, compared to 60.0% among HIV-negative women with ICC (p < 0.001). HIV-positive women showed the highest proportion of multiple HPV infections at 8.2%, compared to 1.4% among HIV-negative women with ICC and 2.1% without ICC (p < 0.001). HPV16 or HPV18 accounted for 65.1% (95% CI: 56.4, 72.9) of all HPV. The commonest HR-HPV detected included HPV16 (45.8%), HPV18 (19.4%), HPV45 (9.3%) and HPV35 (6.2%). Others Included HPV52 (5.4%), HPV59 (3.9%), and HPV58 (3.1%). LR-HPV genotypes had HPV11 (2.3%), HPV61 (1.6%), and HPV81 (1.6%). In multivariable models, the odds ratios comparing HIV-positive to HIV-negative women were 3.26 (95% CI: 1.44, 7.35; p = 0.004) for HR-HPV and 3.87 (95% CI: 2.71, 5.04; p < 0.001) for any HPV infections. In conclusion, HIV-positive women had the highest prevalence of HR-HPV and were associated with increased odds of acquiring HPV infection, highlighting the importance of understanding how long-term HIV infection may promote cervical cancer development

Forecasting Daily and Weekly Passenger Demand for Urban Rail Transit Stations Based on a Time Series Model Approach

Forecasting daily and weekly passenger demand is a key fundamental process used by existing urban rail transit (URT) station authorities to diagnose operational problems and make decisions about train schedule patterns to improve operational efficiency, increase revenue management, and improve driving safety. The accuracy of the forecast results will directly affect the operation planning of urban rail transit (URT). Therefore, based on the collected inbound historical passenger data, this study used the Box–Jenkins time series with the Facebook Prophet algorithm to analyze the characteristics of urban rail transit passenger demand and achieved better computational forecasting performance accuracy. After analyzing the periodicity, correlation, and stationarity, different time series models were constructed. The Akaike information criteria (AIC), Bayesian information criteria (BIC), mean squared error (MSE), and root mean squared error (RMSE) were used to evaluate the adequacy of the best forecast model from among several tested candidates’ models for the Box–Jenkins. The parameters of the daily and weekly models were estimated using statistical software. The experimental results of this study are of both theoretical and practical significance to the urban rail transit (URT) station authorities for an effective station planning system. The forecasting results signify that the SARIMA (5, 1, 3) (1, 0, 0)24 model performs better and is more stable in forecasting the daily passenger demand, and the ARMA (2, 1) model performs better in forecasting the weekly passenger demand. When comparing the SARIMA and ARMA models with the Facebook Prophet, results show that the Facebook Prophet model is superior to the SARIMA model for the daily time series, and the ARMA model is superior to the Facebook Prophet model for the weekly time series

Uric acid: A hypothetical cause of preeclampsia-eclampsia

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