Malaria is a major health problem in various parts of the world especially affecting the tropical countries. It affects the vital organs causing severe complicated malaria. Clinical syndromes like severe cerebral anaemia, coagulation abnormalities, respiratory distress and severe anaemia can increase the mortality of malaria infected cases. Variation in individual susceptibility and severity and type of clinical presentations of malaria raises the need for study of both the parasite and host immune reactions as well as the contribution of inflammatory cytokines in malaria pathogenesis. This study explored the immunopathological basis and advances of severe malaria and their importance in pathogenesis of malaria and its complications. Previous and ongoing studies indicate that changes in endothelium during the sequestration of parasites in organs causes disruption of endothelial barrier function leading to serious effects of malaria. Parasite and host factors contribute to disturbance of cytokine regulation and escape of parasites from the immune system of the host. Immunopathological changes and dysregulation of cytokine production play central role in pathogenesis and disease severity in malaria.
This paper presents the outcome of a laboratory investigation on mix design, resilient modulus, moisture susceptibility and rutting resistance of Stone Mastic Asphalt (SMA) and Dense Graded Asphalt (AC) that is incorporated with Nanosilica (NS) modified binder. Penetration Grade 60-70 (PEN60-70) types of binder were mixed with nanoparticles (NS) using concentration of 0wt%, 2wt%, 4wt% and 6wt% by weight of asphalt binder. The mixtures were tested for resilient modulus, indirect tensile strength and rutting, in order to evaluate the performance of NS-SMA and NS-AC. The results show that the existence of NS is capable of enhancing the performance of both asphalt mixtures, and the addition of NS decreases the susceptibility of moisture damage and provides better resistance against permanent deformation. Furthermore, the addition of 4wt% NS appears to be the most effective amount for the performance enhancement in AC and SMA mixtures.
In the literatures, discussions on the accuracy of different models for landslide analysis have been discussed widely.
However, to date, arguments on the type of input data (landslides in the form of point or polygon) and how they affect
the accuracy of these models can hardly be found. This study assesses how different types of data (point or polygon)
applied to the same model influence the accuracy of the model in determining areas susceptible to landsliding. A total
of 137 landslides was digitised as polygon (areal) units and then transformed into points; forming two separate datasets
both representing the same landslides within the study area. These datasets were later separated into training and
validation datasets. The polygon unit dataset uses the area density technique reported as percentage, while the point
data uses the landslide density technique, as means of assigning weighting to landslide factor maps to generate the
landslide susceptibility map that is based on the analytical hierarchy process (AHP) model. Both data groups show striking
differences in terms of mapping accuracy for both training and validation datasets. The final landslide susceptibility
map using area density (polygon) as input only has 48% (training) and 35% (validation) accuracy. The accuracy for
the susceptibility map using the landslide density as input data achieved 89% and 82% for both training and validation
datasets, respectively. This result showed that the selection of the type of data for landslide analysis can be critical in
producing an acceptable level of accuracy for the landslide susceptibility map. The authors hope that the finding of this
research will assist landslide investigators to determine the appropriateness of the type of landslide data because it will
influence the accuracy of the final landslide potential map.
Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of "lifestyle" diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be "mismatched" and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions, with different health effects in "ancestral" versus "modern" environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the "matched" to "mismatched" spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.
Previous models of disease spread involving delay have used basic SIR (susceptible--infectious--recovery) formulae and approaches. This paper demonstrates how time-varying SEIRS (S--exposed--I - R - S) models can be extended with delay to produce wave propagations that simulate periodic wave fronts of disease spread in the context of population movements. The model also takes into account the natural mortality associated with the disease spread. Understanding the delay of an infectious disease is critical when attempting to predict where and how fast the disease will propagate. We use cellular automata to model the delay and its effect on the spread of infectious diseases where population movement occurs. We illustrate an approach using wavelet transform analysis to understand the impact of the delay on the spread of infectious diseases. The results indicate that including delay provides novel ways to understand the effects of migration and population movement on disease spread.
The susceptibility of Culex sitiens to Japanese Encephalitis (JE) virus was examined in the laboratory. Cx. sitiens became infected with JE virus on day 8 and subsequently it is able to transmit the virus when it takes a blood meal. Both parts of the experiment were carried out using artificial membrane feeding technique.
Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to simulate the infectious trend and trajectory of COVID-19 to understand the severity of the disease and determine the approximate number of days required for the trend to decline. The number of confirmed positive infectious cases [as reported by Ministry of Health, Malaysia (MOH)] were used from January 25, 2020 to March 31, 2020. This study simulated the infectious count for the same duration to assess the predictive capability of the Susceptible-Infectious-Recovered (SIR) model. The same model was used to project the simulation trajectory of confirmed positive infectious cases for 80 days from the beginning of the outbreak and extended the trajectory for another 30 days to obtain an overall picture of the severity of the disease in Malaysia. The transmission rate, β also been utilized to predict the cumulative number of infectious individuals. Using the SIR model, the simulated infectious cases count obtained was not far from the actual count. The simulated trend was able to mimic the actual count and capture the actual spikes approximately. The infectious trajectory simulation for 80 days and the extended trajectory for 110 days depicts that the inclining trend has peaked and ended and will decline towards late April 2020. Furthermore, the predicted cumulative number of infectious individuals tallies with the preparations undertaken by the MOH. The simulation indicates the severity of COVID-19 disease in Malaysia, suggesting a peak of infectiousness in mid-March 2020 and a probable decline in late April 2020. Overall, the study findings indicate that outbreak control measures such as the Movement Control Order (MCO), social distancing and increased hygienic awareness is needed to control the transmission of the outbreak in Malaysia.
This work is the consideration of a fractal fractional mathematical model on the transmission and control of corona virus (COVID-19), in which the total population of an infected area is divided into susceptible, infected and recovered classes. We consider a fractal-fractional order
SIR
type model for investigation of Covid-19. To realize the transmission and control of corona virus in a much better way, first we study the stability of the corresponding deterministic model using next generation matrix along with basic reproduction number. After this, we study the qualitative analysis using "fixed point theory" approach. Next, we use fractional Adams-Bashforth approach for investigation of approximate solution to the considered model. At the end numerical simulation are been given by matlab to provide the validity of mathematical system having the arbitrary order and fractal dimension.
Infectious bronchitis virus (IBV) infection is highly infectious respiratory disease in poultry industry with significant economic importance. The prevalence of IBV in quail industry in Malaysia was not well documented; therefore, its actual role in the epidemiology of the disease is relatively unknown. This study was to determine the susceptibility of Japanese quail, as one of the species in commercial poultry industry, toward IBV. In addition, it will also give a potential impact on the overall health management in the quail industry even though it had been established that quail are resistant to diseases affecting poultry. Moreover, to the best of our knowledge, it is the first experimental study on IBV inoculation in quail. In this experimental study, 20 quails were divided into 4 groups (n = 5 for group A, B, and C, n = 5 for control group). The quails in group A, B, and C were infected via intraocular and intranasal routes with 0.2 mL of 10 × 5 EID50 of the virus. Clinical signs, gross lesions, positive detection of virus, and trachea histopathological scoring were used to assess the susceptibility of these Japanese quails. The results have indicated mild ruffled feathers and watery feces in these inoculated birds. Trachea, lung, and kidney were subjected to one-step reverse transcription polymerase chain reaction for virus detection. The virus was found from trachea and lung samples, whereas it was absent from all kidney samples. Only 3 quails were found with gross lesions. There was a significant difference of tracheal lesion by 0.009 ± 0.845 (P < 0.05) within the treatment groups. In summary, Japanese quails might be susceptible to IBV.
Introduction: Hypertension related morbidities and mortalities around the world show a gradual increase and early detection and prevention are advocated. The Database of Genomic Variants (DGV) has associated variation in DNA sequences called copy number variation (CNV) with susceptibility to common diseases. However, little is known about CNV role in essential hypertension. Thus, this study aimed to characterize the CNV esv27061 among prehypertensive and hypertensive young adults in Malaysia. Materials and method: In this comparative cross-sectional study, 104 subjects living in Kuantan who gave voluntary consent to participate are recruited and divided into three groups; control (43 subjects), prehypertensive (38 subjects) and mild hypertensive (23 subjects). An optimized droplet digital polymerase chain reaction (ddPCR) was used in the determination of CNV esv27061 in this study. Results: All subjects in the control (n=38; 88.4% gain), prehypertensive (n=33; 86.8% gain) and mild hypertensive (n=21; 91.3% gain) groups had CNV gain (copy number > 2) while 11.6% of control, 13.2% of prehypertensive and 8.7% of mild hypertensive subjects exhibited normal copies (copy number = 2). Conclusion: The present preliminary finding was consistent with the Database of Genomic Variants (DGV) which stated that CNV esv27061 showed more gain than loss.
The effects of methanolic extract of Javanese turmeric (Curcuma xanthorrhiza Roxb.) at different level of concentrations on the inactivation of Bacillus cereus, Escherichia coli, Pseudomonas spp. and Staphylococcus aureus in oyster mushroom (Pleurotus sajor-caju) were investigated. This study was conducted principally for the achievement on the best combination between the
susceptibility of C. xanthorrhiza extract on natural microflora and foodborne pathogenic bacteria with the sensory acceptability of the soaked oyster mushroom. Three different concentrations (g/ml), 0.05%, 0.50% and 5.00%, of C. xanthorrhiza extract prepared with dilution method were designed as sanitizing agent in treating the oyster mushroom at 5 minutes and 10 minutes.
There was significance reduction in the survival of microbial load between the untreated fresh oyster mushroom and those soaked with 0.05%, 0.50% and 5.00% rhizome extract (P
Copy number variation (CNV) caused by changes in DNA sequences of 1000
or more bases is implicated with susceptibility to common diseases. A study on CNV
esv27061 among hypertensive Australian adults reported association with high blood
pressure (BP). In Malaysia, no study on CNV among hypertensive young adults is
available. Thus, this investigation aimed to assess the CNV esv27061 of young Malaysian
adults with high blood pressure using optimized ddPCR. (Copied from article).
Different probiotic strains are incorporated into cultured-milk drinks by respective manufacturers with the common aim of providing health benefits to the consumers. Four common cultured-milk products (brands N, S, V and Y) were evaluated for their quality of probiotic strains used, based on the susceptibility of the probiotics to various pH levels simulated to mimic the gastrointestinal system. Results showed that brands Y and V have higher initial probiotic inoculum compared to brands N and S although probiotics from brands N and S were more tolerant to pH 3. Generally, all probiotic strains preferred higher pH with highest viability of Lactobacillus spp., Bifidobacterium spp., and Streptococcus thermophilus observed at pH 8.1. Our study also discovered that among the four brands tested, brand V contained probiotic strains which are most likely to remain viable after passage through the gastrointestinal system.
The stress catabolism state predisposes critically ill patients to a high risk of malnutrition. This, coupled with inadequate or delayed nutrition provision, will lead to further deterioration of nutrition status. Preexisting malnutrition and iatrogenic underfeeding are associated with increased risk of adverse complications. Therefore, accurate detection of patients who are malnourished and/or with high nutrition risk is important for timely and optimal nutrition intervention. Various tools have been developed for nutrition screening and assessment for hospitalized patients, but not all are studied or validated in critically ill populations. In this review article, we consider the pathophysiology of malnutrition in critical illness and the currently available literature to develop recommendations for nutrition screening and assessment. We suggest the use of the (modified) Nutrition Risk in the Critically Ill (mNUTRIC) for nutrition risk screening and the subjective global assessment (SGA) together with other criteria relevant to the critically ill patients, such as gastrointestinal function, risk of aspiration, determination of sarcopenia and frailty, and risk of refeeding syndrome for nutrition assessment. Further research is needed to identify suitable nutrition monitoring indicators to determine the response to the provision of nutrition.
Disease frequency is used to measure the situation of the disease with reference to the population size and time period
which is in a fractional form. The lower part of the fraction, known as denominator is the important part as it was used
to calculate a rate or ratio. Since the disease frequency is based on a ratio estimator, the results are highly dependent
upon the value of denominator. Therefore, the main aim of this paper was to propose a new method in calculating the
denominator for the relative risk equation with the application to chikungunya disease data from Malaysia. The new
method of calculating the denominator of the relative risk equation includes the use of discrete time-space stochastic
SIR-SI (susceptible-infective-recovered for human population and susceptible-infective for vector population) disease
transmission model instead of the total disease counts. The results of the analysis showed that the estimation of expected
disease counts based on total posterior means can overcome the problem of expected counts estimation based on the total
number of disease especially when there is no observed disease count in certain regions. The proposed new approach to
calculate the denominator for the relative risk equation is suitable for the case of rare disease in which it offers a better
method of expected disease counts estimation.
Recent advancements in the understanding of how sperm develop into offspring have shown complex interactions between environmental influences and genetic factors. The past decade, marked by a research surge, has not only highlighted the profound impact of paternal contributions on fertility and reproductive outcomes but also revolutionized our comprehension by unveiling how parental factors sculpt traits in successive generations through mechanisms that extend beyond traditional inheritance patterns. Studies have shown that offspring are more susceptible to environmental factors, especially during critical phases of growth. While these factors are broadly detrimental to health, their effects are especially acute during these periods. Moving beyond the immutable nature of the genome, the epigenetic profile of cells emerges as a dynamic architecture. This flexibility renders it susceptible to environmental disruptions. The primary objective of this review is to shed light on the diverse processes through which environmental agents affect male reproductive capacity. Additionally, it explores the consequences of paternal environmental interactions, demonstrating how interactions can reverberate in the offspring. It encompasses direct genetic changes as well as a broad spectrum of epigenetic adaptations. By consolidating current empirically supported research, it offers an exhaustive perspective on the interwoven trajectories of the environment, genetics, and epigenetics in the elaborate transition from sperm to offspring.
Viruses are obligate parasites known to interact with a wide variety of host proteins at different stages of infection. Current antiviral treatments target viral proteins and may be compromised due to the emergence of drug resistant viral strains. Targeting viral-host interactions is now gaining recognition as an alternative approach against viral infections. Recent research has revealed that heterogeneous ribonucleoprotein A1, an RNA-binding protein, plays an essential functional and regulatory role in the life cycle of many viruses. In this review, we summarize the interactions between heterogeneous ribonucleoprotein A1 (hnRNPA1) and multiple viral proteins during the life cycle of RNA and DNA viruses. hnRNPA1 protein levels are modulated differently, in different viruses, which further dictates its stability, function, and intracellular localization. Multiple reports have emphasized that in Sindbis virus, enteroviruses, porcine endemic diarrhea virus, and rhinovirus infection, hnRNPA1 enhances viral replication and survival. However, in others like hepatitis C virus and human T-cell lymphotropic virus, it exerts a protective response. The involvement of hnRNPA1 in viral infections highlights its importance as a central regulator of host and viral gene expression. Understanding the nature of these interactions will increase our understanding of specific viral infections and pathogenesis and eventually aid in the development of novel and robust antiviral intervention strategies.
Based on clinical observations, women with polycystic ovarian syndrome (PCOS) are prone to developing several other diseases, such as metabolic and cardiovascular diseases. However, the molecular association between PCOS and these diseases remains poorly understood. Recent studies showed that the information from protein-protein interaction (PPI) network analysis are useful in understanding the disease association in detail. This study utilized this approach to deepen the knowledge on the association between PCOS and other diseases. A PPI network for PCOS was constructed using PCOS-related proteins (PCOSrp) obtained from PCOSBase. MCODE was used to identify highly connected regions in the PCOS network, known as subnetworks. These subnetworks represent protein families, where their molecular information is used to explain the association between PCOS and other diseases. Fisher's exact test and comorbidity data were used to identify PCOS-disease subnetworks. Pathway enrichment analysis was performed on the PCOS-disease subnetworks to identify significant pathways that are highly involved in the PCOS-disease associations. Migraine, schizophrenia, depressive disorder, obesity, and hypertension, along with twelve other diseases, were identified to be highly associated with PCOS. The identification of significant pathways, such as ribosome biogenesis, antigen processing and presentation, and mitophagy, suggest their involvement in the association between PCOS and migraine, schizophrenia, and hypertension.
INTRODUCTION: routine rubella antibody screening is not done for antenatal mothers in community health clinics in Malaysia. However, congenital rubella syndrome has persisted with its associated health burden.
OBJECTIVES: to determine the prevalence of rubella susceptibility among pregnant mothers and its associated risk factors.
METHODOLOGY: a cross-sectional study was carried out in the Petaling district, Selangor, Malaysia, where 500 pregnant mothers were recruited, and face-to-face interviews were conducted. Rubella IgG tests were performed.
RESULTS: the prevalence of rubella susceptibility among pregnant mothers was 11.4%. Using logistic regression, a history of not having received rubella vaccination or having unknown rubella vaccination status was found to be a significant predictor for mothers to be rubella susceptible (odds ratio = 2.691; 95% confidence interval = 1.539-4.207).
CONCLUSIONS: routine rubella IgG screening tests need to be offered to all antenatal mothers in view of the high prevalence found.
Study site: Antenatal clinics (klinik kesihatan), Petaling, Selangor, Malaysia