Spread, circulation, and evolution of the Middle East respiratory syndrome coronavirus

The Middle East respiratory syndrome coronavirus (MERS-CoV) was first documented in the Kingdom of Saudi Arabia (KSA) in 2012 and, to date, has been identified in 180 cases with 43% mortality. In this study, we have determined the MERS-CoV evolutionary rate, documented genetic variants of the virus and their distribution throughout the Arabian peninsula, and identified the genome positions under positive selection, important features for monitoring adaptation of MERS-CoV to human transmission and for identifying the source of infections. Respiratory samples from confirmed KSA MERS cases from May to September 2013 were subjected to whole-genome deep sequencing, and 32 complete or partial sequences (20 were ≥99% complete, 7 were 50 to 94% complete, and 5 were 27 to 50% complete) were obtained, bringing the total available MERS-CoV genomic sequences to 65. An evolutionary rate of 1.12 × 10−3 substitutions per site per year (95% credible interval [95% CI], 8.76 × 10−4; 1.37 × 10−3) was estimated, bringing the time to most recent common ancestor to March 2012 (95% CI, December 2011; June 2012). Only one MERS-CoV codon, spike 1020, located in a domain required for cell entry, is under strong positive selection. Four KSA MERS-CoV phylogenetic clades were found, with 3 clades apparently no longer contributing to current cases. The size of the population infected with MERS-CoV showed a gradual increase to June 2013, followed by a decline, possibly due to increased surveillance and infection control measures combined with a basic reproduction number (R0) for the virus that is less than 1

Deletion of low molecular weight protein tyrosine phosphatase (Acp1) protects against stress-induced cardiomyopathy.

The low molecular weight protein tyrosine phosphatase (LMPTP), encoded by the ACP1 gene, is a ubiquitously expressed phosphatase whose in vivo function in the heart and in cardiac diseases remains unknown. To investigate the in vivo role of LMPTP in cardiac function, we generated mice with genetic inactivation of the Acp1 locus and studied their response to long-term pressure overload. Acp1(-/-) mice develop normally and ageing mice do not show pathology in major tissues under basal conditions. However, Acp1(-/-) mice are strikingly resistant to pressure overload hypertrophy and heart failure. Lmptp expression is high in the embryonic mouse heart, decreased in the postnatal stage, and increased in the adult mouse failing heart. We also show that LMPTP expression increases in end-stage heart failure in humans. Consistent with their protected phenotype, Acp1(-/-) mice subjected to pressure overload hypertrophy have attenuated fibrosis and decreased expression of fibrotic genes. Transcriptional profiling and analysis of molecular signalling show that the resistance of Acp1(-/-) mice to pathological cardiac stress correlates with marginal re-expression of fetal cardiac genes, increased insulin receptor beta phosphorylation, as well as PKA and ephrin receptor expression, and inactivation of the CaMKIIδ pathway. Our data show that ablation of Lmptp inhibits pathological cardiac remodelling and suggest that inhibition of LMPTP may be of therapeutic relevance for the treatment of human heart failure

Accelerating biomedical image segmentation using equilibrium optimization with a deep learning approach

Biomedical image segmentation is a vital task in the analysis of medical imaging, including the detection and delineation of pathological regions or anatomical structures within medical images. It has played a pivotal role in a variety of medical applications, involving diagnoses, monitoring of diseases, and treatment planning. Conventionally, clinicians or expert radiologists have manually conducted biomedical image segmentation, which is prone to human error, subjective, and time-consuming. With the advancement in computer vision and deep learning (DL) algorithms, automated and semi-automated segmentation techniques have attracted much research interest. DL approaches, particularly convolutional neural networks (CNN), have revolutionized biomedical image segmentation. With this motivation, we developed a novel equilibrium optimization algorithm with a deep learning-based biomedical image segmentation (EOADL-BIS) technique. The purpose of the EOADL-BIS technique is to integrate EOA with the Faster RCNN model for an accurate and efficient biomedical image segmentation process. To accomplish this, the EOADL-BIS technique involves Faster R-CNN architecture with ResNeXt as a backbone network for image segmentation. The region proposal network (RPN) proficiently creates a collection of a set of region proposals, which are then fed into the ResNeXt for classification and precise localization. During the training process of the Faster RCNN algorithm, the EOA was utilized to optimize the hyperparameter of the ResNeXt model which increased the segmentation results and reduced the loss function. The experimental outcome of the EOADL-BIS algorithm was tested on distinct benchmark medical image databases. The experimental results stated the greater efficiency of the EOADL-BIS algorithm compared to other DL-based segmentation approaches

Population pharmacokinetics of vancomycin in very low birth weight neonates

IntroductionVancomycin dosing in very low birth weight (VLBW) neonates is challenging. Compared with the general neonatal population, VLBW neonates are less likely to achieve the vancomycin therapeutic targets. Current dosing recommendations are based on studies of the general neonatal population, as only a very limited number of studies have evaluated vancomycin pharmacokinetics in VLBW neonates. The main aim of this study was to develop a vancomycin population pharmacokinetic model to optimize vancomycin dosing in VLBW neonates.MethodsThis multicenter study was conducted at six major hospitals in Saudi Arabia. The study included VLBW neonates who received vancomycin and had at least one vancomycin serum trough concentration measurement at a steady state. We developed a pharmacokinetic model and performed Monte Carlo simulations to develop an optimized dosing regimen for VLBW infants. We evaluated two different targets: AUC0–24 of 400–600 or 400–800 µg. h/mL. We also estimated the probability of trough concentrations >15 and 20 µg/mL.ResultsIn total, we included 236 neonates, 162 in the training dataset, and 74 in the validation dataset. A one-compartment model was used, and the distribution volume was significantly associated only with weight, whereas clearance was significantly associated with weight, postmenstrual age (PMA), and serum creatinine (Scr).DiscussionWe developed dosing regimens for VLBW neonates, considering the probability of achieving vancomycin therapeutic targets, as well as different toxicity thresholds. The dosing regimens were classified according to PMA and Scr. These dosing regimens can be used to optimize the initial dose of vancomycin in VLBW neonates

Seroprevalence of antibodies to SARS-CoV-2 among blood donors in the early month of the pandemic in Saudi Arabia

Background: Serologic testing provides better understanding of SARS-CoV-2 prevalence and its transmission. This study was an investigation of the prevalence of antibodies to SARS-CoV-2 among blood donors in Saudi Arabia. Objective: To estimate the seroprevalence of anti-SARS-CoV-2 antibodies among blood donors in Saudi Arabia during the early phase of the COVID-19 pandemic. Methods: Serology results and epidemiological data were analyzed for 837 adult blood donors, with no confirmed SARS-CoV-2 infection, in Saudi Arabia from 20th to 25th May 2020. Seroprevalence was determined using electrochemical immunoassay to detect anti-SARS-CoV-2 antibodies. Results: The overall seroprevalence of anti-SARS-CoV-2 antibodies was 1.4% (12/837). Non-citizens had higher seroprevalence compared with citizens (OR 13.6, p = 0.001). Secondary education was significantly associated with higher seroprevalence compared with higher education (OR 6.8, p = 0.005). The data showed that the highest seroprevalence was in Makkah (8.1%). Uisng Makkah seroprevalence as the reference, the seroprevalence in other areas was: Madinah 4.1% (OR 0.48, 95% CI 0.12-1.94), Jeddah 2.3% (OR 0.27, 95% CI 0.31-2.25), and Qassim 2.9 % (OR 0.34, 95% CI 0.04-2.89) and these were not statistically different from seroprevalence in the Makkah region. Conclusions: At the early months of the COVID-19 pandemic in Saudi Arabia, the seroprevalence of antibodies to SARS-CoV-2 among blood donors was low, but was higher among non-citizens. These findings may indicate that non-citizens and less educated individuals may be less attentive to preventive measures. Monitoring seroprevalence trends over time require repeated sampling

Assessment of knowledge, attitude and practice of diabetic people in Najran, Kingdom of Saudi Arabia

Background: This cross-sectional hospital based study aimed at determining the level of knowledge, attitude and practice of diabetes among local people of Najran, Saudi Arabia.Methods: We aimed to investigate the levels of knowledge, attitude and practice among diabetic people in Najran area.Results: 10% of the participants scored >7, 28% scored >5 and 62% scored 5 and less in Knowledge questionnaire. None [0.00%] of the participants scored 7 or more out of the attitude questionnaire. 100% of the participants scored 5 and less out of 12. 100% of the participants scored >6 and 0% scored 12 or more in the practice questionnaire.Conclusions: Our study revealed that the level of knowledge, attitude and practice of diabetes in the area of Najran is very poor. We suggest that a structured educational program to be adopted by the health authorities in Saudi Arabia

Viral shedding and antibody response in 37 patients with MERS-coronavirus infection

Background. The Middle East respiratory syndrome (MERS) coronavirus causes isolated cases and outbreaks of severe respiratory disease. Essential features of the natural history of disease are poorly understood. Methods. We studied 37 adult patients infected with MERS coronavirus for viral load in the lower and upper respiratory tracts (LRT and URT, respectively), blood, stool, and urine. Antibodies and serum neutralizing activities were determined over the course of disease. Results. One hundred ninety-nine LRT samples collected during the 3 weeks following diagnosis yielded virus RNA in 93% of tests. Average (maximum) viral loads were 5 × 106 (6 × 1010) copies/mL. Viral loads (positive detection frequencies) in 84 URT samples were 1.9 × 104 copies/mL (47.6%). Thirty-three percent of all 108 serum samples tested yielded viral RNA. Only 14.6% of stool and 2.4% of urine samples yielded viral RNA. All seroconversions occurred during the first 2 weeks after diagnosis, which corresponds to the second and third week after symptom onset. Immunoglobulin M detection provided no advantage in sensitivity over immunoglobulin G (IgG) detection. All surviving patients, but only slightly more than half of all fatal cases, produced IgG and neutralizing antibodies. The levels of IgG and neutralizing antibodies were weakly and inversely correlated with LRT viral loads. Presence of antibodies did not lead to the elimination of virus from LRT. Conclusions. The timing and intensity of respiratory viral shedding in patients with MERS closely matches that of those with severe acute respiratory syndrome. Blood viral RNA does not seem to be infectious. Extrapulmonary loci of virus replication seem possible. Neutralizing antibodies do not suffice to clear the infection

Prevalence of Endocrine Disorders Among Down Syndrome Individuals in Ksa: A Cross-Sectional Study

Objective: To determine the prevalence of endocrine disorders among individuals with Down Syndrome in KSA. Methods: This research employs a cross-sectional study design to investigate the prevalence of endocrine disorders among individuals with Down Syndrome in the Kingdom of Saudi Arabia (KSA). A cross-sectional approach allows us to collect data at a single point in time from a diverse group of participants, providing a snapshot of the prevalence and characteristics of endocrine disorders within the study population. Results: The study included 686 participants. The participants asked if they had a child with Down syndrome. Most of them answered no (n= 576, 84%) followed by yes (n= 110, 16%). The most frequent child age who has Down syndrome among study participants was 7-10 years (n= 45, 40.9%) followed by 3-6 years (n= 30, 27.3%). The most frequent child gender who has Down syndrome among study participants was female (n= 57, 51.8%) followed by male (n= 53, 48.2%). Father's educational level among study participants with most of them having a university (n= 82, 74.5%). Mother's educational level among study participants with most of them having a university (n= 77, 70%). Participants were asked if there was a first-degree relationship between the parents. There 55 had a first-degree relationship with (50%), and 55 didn’t have a first-degree relationship between parents with (50%). Participants were asked the female about two diseases polycystic ovary disease there were 12 had it (10.9%), 62 didn’t have it (56.4%), and the second disease was Turner syndrome 22 had it (20%) and 53 participants didn’t have it (47.3%). Conclusion: Study results showed that most of the study participants don’t have Down Syndrome according to the parent's answers. Half of the participants have a first-degree relationship between their parents. The most educational level for parents was the university