Non-invasive prenatal rhesus D genotyping using cell-free foetal DNA.

Background & objectives: Non-invasive prenatal diagnosis (NIPD) of rhesus D (RHD) genotype using cell-free foetal DNA is extensively used in many developed countries. Studies on NIPD from India are scarce. The aim of the present study was to evaluate the performance of non-invasive foetal RHD genotyping by targeting exon 10 of the RHD gene using cell-free DNA. Methods: DNA was extracted from the maternal plasma of alloimmunized and non-alloimmunized women between 7 and 34 wk of gestation. RHD sequence was determined by quantitative real time polymerase chain reaction (PCR). Results were compared with RhD phenotype obtained from cord blood samples of neonates. Results: A total of 135 samples from RhD-negative pregnant women were collected. The foetal RHD status was conclusive in all 135 (100%) cases. The highest number of cases reported for RHD genotyping were from Punjab (38.5%) followed by Haryana (24.4%), Himachal Pradesh (17.0%) and Chandigarh Union Territory (13.3%). The non-invasive test correctly predicted the foetal RhD phenotype in 133 of 135 cases, making the accuracy of the test as 98.51 per cent [95% confidence interval (CI): 97.90-99.50%]. The overall sensitivity and specificity of the test were 99.18 per cent (95% CI: 95.52-99.98%) and 92.31 per cent (95% CI: 63.97-99.81%), respectively, with negative and positive predictive values of 99.80 per cent (95% CI: 94.85-99.87%) and 96.31 per cent (95% CI: 62.87-98.84%), respectively. Interpretation & conclusions: Non-invasive foetal RHD determination by single-exon quantitative PCR exhibited high accuracy and could be used in routine clinical practice after confirmatory studies are done.

Seasonal deviation effects foliar endophyte assemblage and diversity in Asparagus racemosus and Hemidesmus indicus.

BACKGROUND: Fungal endophytes are the living symbionts which cause no apparent damage to the host tissue. The distribution pattern of these endophytes within a host plant is mediated by environmental factors. This study was carried out to explore the fungal endophyte community and their distribution pattern in Asparagus racemosus and Hemidesmus indicus growing in the study area. RESULTS: Foliar endophytes were isolated for 2 years from A. racemosus and H. indicus at four different seasons (June-August, September-November, December-February, March-May). A total of 5400 (675/season/year) leaf segments harbored 38 fungal species belonging to 17 genera, 12 miscellaneous mycelia sterile from 968 isolates and 13 had yeast like growth. In A. racemosus, Acremonium strictum and Phomopsis sp.1, were dominant with overall relative colonization densities (RCD) of 7.11% and 5.44% respectively, followed by Colletotrichum sp.3 and Colletotrichum sp.1 of 4.89% and 4.83% respectively. In H. indicus the dominant species was A. strictum having higher overall RCD of 5.06%, followed by Fusarium moniliforme and Colletotrichum sp.2 with RCD of 3.83% and 3%, respectively. Further the overall colonization and isolation rates were higher during the wet periods (September-November) in both A. racemosus (92.22% and 95.11%) and H. indicus (82% and 77.11%). CONCLUSION: Study samples treated with 0.2% HgCl2 and 75% EtOH for 30 s and 1 min, respectively, confirmed most favorable method of isolation of the endophytes. Owing to high mean isolation and colonization rates, September-November season proved to be the optimal season for endophyte isolation in both the study plants. Assessing the bioactive potential of these endophytes, may lead to the isolation of novel natural products and metabolites.

A Theoretical Exploration of Artificial Intelligence's Impact on Feto-Maternal Health from Conception to Delivery.

The implementation of Artificial Intelligence (AI) in healthcare is enhancing diagnostic accuracy in clinical setups. The use of AI in healthcare is steadily increasing with advancing technology, extending beyond disease diagnosis to encompass roles in feto-maternal health. AI harnesses Machine Learning (ML), Natural Language Processing (NLP), Artificial Neural Networks (ANN), and computer vision to analyze data and draw conclusions. Considering maternal health, ML analyzes vast datasets to predict maternal and fetal health outcomes, while NLP interprets medical texts and patient records to assist in diagnosis and treatment decisions. ANN models identify patterns in complex feto-maternal medical data, aiding in risk assessment and intervention planning whereas, computer vision enables the analysis of medical images for early detection of feto-maternal complications. AI facilitates early pregnancy detection, genetic screening, and continuous monitoring of maternal health parameters, providing real-time alerts for deviations, while also playing a crucial role in the early detection of fetal abnormalities through enhanced ultrasound imaging, contributing to informed decision-making. This review investigates into the application of AI, particularly through predictive models, in addressing the monitoring of feto-maternal health. Additionally, it examines potential future directions and challenges associated with these applications.

Prevalence of ABO and Rhesus (D) Blood Group and Allelic Frequency at Blood Bank of Nigist Eleni Mohammed Hospital, Ethiopia.

Background: The purpose of this cross-sectional study was to determine the pattern of the ABO and rhesus D (RhD) blood group distribution among voluntary blood donors attending five blood donation centers at Nigist Eleni Mohammed General Hospital in Hossana, Ethiopia. Methods: A total of 1,120 participants who fulfilled the "who can give blood" criteria of the World Health Organization were selected randomly. Blood samples were collected, transported to the laboratory, and analyzed for ABO and RhD typing. The data was analyzed using descriptive statistics and chi-square correlation analysis. Results: The study found that the O blood group was the most prevalent (39.0%), followed by A (32.2%), B (22.5%), and AB (6.4%). When considering both the ABO and Rh blood groups together, 92.9% of blood donors were RhD positive, while only 7.1% were RhD negative. The distribution pattern of the ABO blood groups in Gurage Zone, Hadiya Zone, Kembata Zone, and Silte Zone showed that the O blood group was the most prevalent, followed by A, B, and AB, in that order. Conversely, the ABO blood group distribution pattern in Halaba Zone was A > O > B > AB. Civil servants from different occupational statuses were the most dominant voluntary blood donors, accounting for 53.2%, followed by students from different high schools and universities (41.9%), self-employed individuals (4.1%), and others (0.7%). The ABO blood group system had observed allele frequencies significantly different from the expected frequencies (p = 0.007), while the RhD system did not (p = 0.037). Allele frequencies for A, B, and O in the ABO system were 0.3531, 0.2576, and 0.3893, respectively. Observed frequencies for RhD-positive and RhD-negative alleles were 0.9647 and 0.0531, respectively. Conclusion: This study highlights the regional ABO and RhD blood group variations in Ethiopia, noting disparities from expected ABO allele frequencies, and identifies the O blood group predominance among donors with a high RhD-positive prevalence.

Reappraisal of evolving methods in non-invasive prenatal screening: Discovery, biology and clinical utility.

Non-invasive prenatal screening (NIPS) offers an opportunity to screen or determine features associated with the fetus. Earlier, prenatal testing was done with cytogenetic procedures like karyotyping or fluorescence in-situ hybridization, which necessitated invasive methods such as fetal blood sampling, chorionic villus sampling or amniocentesis. Over the last two decades, there has been a paradigm shift away from invasive prenatal diagnostic methods to non-invasive ones. NIPS tests heavily rely on cell-free fetal DNA (cffDNA). This DNA is released into the maternal circulation by placenta. Like cffDNA, fetal cells such as nucleated red blood cells, placental trophoblasts, leukocytes, and exosomes or fetal RNA circulating in maternal plasma, have enormous potential in non-invasive prenatal testing, but their use is still limited due to a number of limitations. Non-invasive approaches currently use circulating fetal DNA to assess the fetal genetic milieu. Methods with an acceptable detection rate and specificity such as sequencing, methylation, or PCR, have recently gained popularity in NIPS. Now that NIPS has established clinical significance in prenatal screening and diagnosis, it is critical to gain insights into and comprehend the genesis of NIPS de novo. The current review reappraises the development and emergence of non-invasive prenatal screen/test approaches, as well as their clinical application, with a focus, on the scope, benefits, and limitations.

RHD exon 5, 7 and 10 targeted non-invasive prenatal screening of fetal Rhesus-D (RhD) in selected RhD negative pregnant women in Ethiopia.

BACKGROUND: A majority of non-invasive prenatal screening studies determining fetal RhD status have been tested on Caucasian and Asian populations, but limited or no studies have been conducted on the Ethiopian population. In the current study, we carried non-invasive prenatal screening of fetal RHD genotype in selected RhD negative Ethiopian pregnant women. METHODS: Cell-free DNA was extracted from the plasma samples of 117 RhD pregnant women between 9 and 38 weeks of gestation. Fetal RHD genotypes were detected by targeting exons 5, 7 and 10 of the RHD gene by using real-time PCR assay. RHD genotypic results were confirmed by neonatal cord blood serology. RESULTS: Fetal RHD genotyping was conclusive in all 117 subjects. RHD genotype was correctly predicted in 115 of 117 cases, thus the test yielded 98.3% accuracy (95%CI: 97.3-99.1%). Among 115 cases, 105 were genotyped as RHD positive and 12 were genotyped as RHD negative. The sensitivity and specificity of the test were 99.1% (95% CI: 94.8-99.9%) and 91.7% (95%CI: 61.5-99.7%) respectively. The negative and positive predictive values were 99.9% (95%CI: 99.2-99.9%) and 54.0% (95% CI: 15.2-88.4%) respectively. SRY genotyping results were in complete concordance with fetal sex. CONCLUSION: Multi exon targeted non-invasive prenatal screening test for fetal RhD determination exhibited high accuracy and sensitivity. A confirmatory study with a bigger size of study subjects is warranted before enabling clinical implementation.

Prevalence of Khat (Catha edulis) Chewing and Its Determinants: A Respondent-Driven Survey from Hossana, Ethiopia.

BACKGROUND: Ethiopia is a leading khat producer in East Africa, and almost all regions are involved in khat production. Hossana, a small town in Southern Ethiopia, is also actively involved in khat production and its use. However, very few studies have been conducted to investigate the habit of khat chewing in this area. This study was conducted to assess the prevalence and predictors of khat chewing among Hossana residents. METHODS: The study was conducted on 1700 individuals in Hossana town from March 2018 to June 2019. A structured pre-tested self-administered questionnaire was designed and used for data collection. Descriptive statistics and logistic regression were carried out to study the prevalence and predictors of khat chewing in the study area. RESULTS: The overall prevalence of khat chewing among the respondents was 58.0% (95% CI 53.4-63.3) of which 68.4% were daily khat users and 31.5% used it occasionally. About 24.7% of females and 75.2% of males had chewed khat. Muslim religion (AOR 2.37; 95% CI 1.58-4.32), male gender (AOR 3.48; 95% CI 2.16-5.61), Older age (AOR 1.36; 95% CI 0.84-2.21), participants having habitual khat chewing friends or a khat chewer family associate (OR 1.70; 95% CI 1.17-2.20) were found to be independent predictors of chewing. CONCLUSION: Significant portion of the population in the study area chew khat. Khat use is significantly associated with the Muslim religion, gender, age, and habit of family and friends. Further studies with larger demographic area are warranted from the study area to reproduce these findings.

Genetic markers: Potential candidates for cardiovascular disease.

The effective prevention of cardiovascular disease depends upon the ability to recognize the high-risk individuals at an early stage of the disease or long before the development of adverse events. Evolving technologies in the fields of proteomics, metabolomics, and genomics have played a significant role in the discovery of cardiovascular biomarkers, but so far these methods have achieved the modest success. Hence, there is a crucial need for more reliable, suitable, and lasting diagnostic and therapeutic markers to screen the disease well in time to start the clinical aid to the patients. Gene polymorphisms associated with the cardiovascular disease play a decisive role in the disease onset. Therefore, the genetic marker evaluation to classify high-risk patients from low-risk patients trends an effective approach to patient management and care. Currently, there are no genetic markers available for extensive adoption as risk factors for coronary vascular disease, yet, there are numerous promising, biologically acceptable candidates. Many of these gene biomarkers, alone or in combination, can play an essential role in the prediction of cardiovascular risk. The present review highlights some putative emerging genetic biomarkers that could facilitate more authentic and fast diagnosis of CVD. This review also briefly describes few technological approaches employed in the biomarker search.

Aqueous Terminalia arjuna extract modulates expression of key atherosclerosis-related proteins in a hypercholesterolemic rabbit: A proteomic-based study.

PURPOSE: The present study evaluates the effect of an aqueous extract of Terminalia arjuna (aqTAE) on protein expression in aortic plaques of hypercholesterolemic rabbits using a proteomic approach. EXPERIMENTAL DESIGN: Thirty male New Zealand rabbits (n = 6) were employed as Gp1 (stock diet); Gp2 (high-fat diet [HFD]); Gp3 (stock diet + aqTAE); Gp4 (HFD + aqTAE); and Gp5 (HFD + atorvastatin) and followed for 6 months. Protein lysates of aortic tissues were separated by 2DE and proteins were identified by MALDI-TOF/MS. RESULTS: Serum lipids were found to be significantly increased by an HFD and reduced by aqTAE both at 3 and 6 months (Gp4 vs. Gp2; p < 0.05). Total 79 spots were differentially expressed, among which 60 individual proteins were identified, 31 grouped as atherosclerosis-related proteins and 29 classified as others. aqTAE significantly attenuated the protein expression of tumor necrosis factor α, cyclooxygenase-2, MMP-9, HSP60, ICAM-5, Endothelin-3, Vimentin, Protein S100-A9 besides others. Many of the observed proteins are known to be consistently associated with endothelial dysfunction, inflammation, plaque rupture, and immune imbalance. CONCLUSIONS AND CLINICAL RELEVANCE: Strong hypolipidemic effects of aqTAE and attenuation of these signature atherogenic biomarkers using proteomics highlights the fact that aqTAE may be useful in the prevention and management of atherosclerosis.

The Most Favourable Procedure for the Isolation of Cell-Free DNA from the Plasma of Iso-Immunized RHD-Negative Pregnant Women.

BACKGROUND: The ability to achieve quality recovery of cell-free foetal DNA is important for making non-invasive prenatal diagnoses. In this study, we performed quantitative and qualitative analyses of isolated DNA from maternal plasma, using different DNA-isolation methods. METHOD: DNA was isolated from 30 iso-immunized women via the QIAamp column-based method, using four different elution volumes and two conventionally based methods. Real-time polymerase chain-reaction quantification of RHD and ß-globin genes was performed in order to determine foetal-specific sequences and total genome equivalents, respectively. RESULTS: The column-based method at a 3 µl elution volume yielded the highest quality and quantity of total DNA (67.0±0.6 ng/µL). At a 3 µl elution volume, the ß-globin and RHD-gene sequences were estimated to be the highest among all isolation procedures, with 2778.13±1.5 and 66.9±0.6 GEq/mL, respectively, and a 100% sensitivity for RHD-gene sequence detection. Among the two conventional manual methods, the boiling lysis method yielded a higher DNA concentration (53.8±0.8 ng/µL) and purity (1.73±0.05). In addition, the method's sensitivity for foetal-detection sequences was only 80%, whereas the salting-out method's sensitivity was just 70%. CONCLUSIONS: This study confirms the theory that the QIAamp method is a specific and sensitive approach for purifying and quantifying plasma DNA, when used in the minimum elution volume.