Down syndrome (DS) is a genetic condition resulting from triplication of human chromosome (HSA)21. Besides intellectual disability, DS is frequently associated with hypotonia. Satellite cells are the resident cells that provides robust and remarkable regenerative capacity to the skeletal muscles, and its population size has been reported to be disease-associated. However, little is known about the population size of satellite cells in DS and the association of its intrinsic cellular functionality and hypotonia seen in DS. Here, we studied the Ts1Cje mouse, a DS murine model displays the muscle weakness characteristic. Satellite cell populations were immunostained with Pax7 and myonuclei numbers in the Ts1Cje extensor digitorum longus muscle were assessed. Their cellular function was further determined via in vitro assay in high-serum conditioned medium. Subsequently, the in vitro self-renewal, proliferative, and differentiation activities of these myogenic precursor cells were assessed after 24, 48, and 72h using Pax7, MyoD, and Ki67 immunomarkers. Our results showed that the population and functionality of Ts1Cje satellite cell did not differ significantly when compared to the wildtype cells isolated from disomic littermates. In conclusion, our findings indicated that intrinsic cellular functionality of the satellite cells, do not contribute to muscle weakness in Ts1Cje mouse.
Metisa plana (Walker) is a leaf defoliating pest that is able to cause staggering economical losses to oil palm cultivation. Considering the economic devastation that the pest could bring, an early warning system to predict its outbreak is crucial. The state of art of satellite technologies are now able to derive environmental factors such as relative humidity (RH) that may influence pest population's fluctuations in rapid, harmless, and cost-effective manners. This study examined the relationship between the presence of Metisa plana at different time lags and remote sensing (RS) derived RH by using statistical and machine learning approaches. Metisa plana census data of cumulated larvae instar 1, 2, 3, and 4 were collected biweekly in 2014 and 2015 in an oil palm plantation in Muadzam Shah, Pahang, Malaysia. Relative humidity values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were apportioned to 6 time lags; 1 week (T1), 2 weeks (T2), 3 week (T3), 4 weeks (T4), 5 week (T5) and 6 weeks (T6) and paired with the respective census data. Pearson's correlation was carried out to analyse the relationship between Metisa plana and RH at different time lags. Regression analyses and artificial neural network (ANN) were also conducted to develop the best prediction model of Metisa plana's outbreak. The results showed relatively high correlations, positively or negatively, between the presences of Metisa plana with RH ranging from 0.46 to 0.99. ANN was found to be superior to regression models with the adjusted coefficient of determination (R2) between the actual and predicted Metisa plana values ranging from 0.06 to 0.57 versus 0.00 to 0.05. The analysis on the best time lags illustrated that the multiple time lags were more influential on the Metisa plana population than the individual time lags. The best Metisa plana prediction model was derived from T1, T2 and T3 multiple time lags modelled using the ANN algorithm with R2 value of 0.57, errors below 1.14 and accuracies above 93%. Based on the result of this study, the elucidation of Metisa plana's landscape ecology was possible with the utilization of RH as the predictor variable in consideration of the time lag effects of RH on the pest's population.
The objective of the study is to examine the impact of environmental indicators and air pollution on "health" and "wealth" for the low-income countries. The study used a number of promising variables including arable land, fossil fuel energy consumption, population density, and carbon dioxide emissions that simultaneously affect the health (i.e., health expenditures per capita) and wealth (i.e., GDP per capita) of the low-income countries. The general representation for low-income countries has shown by aggregate data that consist of 39 observations from the period of 1975-2013. The study decomposes the data set from different econometric tests for managing robust inferences. The study uses temporal forecasting for the health and wealth model by a vector error correction model (VECM) and an innovation accounting technique. The results show that environment and air pollution is the menace for low-income countries' health and wealth. Among environmental indicators, arable land has the largest variance to affect health and wealth for the next 10-year period, while air pollution exerts the least contribution to change health and wealth of low-income countries. These results indicate the prevalence of war situation, where environment and air pollution become visible like "gun" and "bullet" for low-income countries. There are required sound and effective macroeconomic policies to combat with the environmental evils that affect the health and wealth of the low-income countries.
This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.
Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.
The origins of linguistic diversity remain controversial. Studies disagree on whether group features such as population size or social structure accelerate or decelerate linguistic differentiation. While some analyses of between-group factors highlight the role of geographical isolation and reduced linguistic exchange in differentiation, others suggest that linguistic divergence is driven primarily by warfare among neighbouring groups and the use of language as marker of group identity. Here we provide the first integrated test of the effects of five historical sociodemographic and geographic variables on three measures of linguistic diversification among 50 Austronesian languages: rates of word gain, loss and overall lexical turnover. We control for their shared evolutionary histories through a time-calibrated phylogenetic sister-pairs approach. Results show that languages spoken in larger communities create new words at a faster pace. Within-group conflict promotes linguistic differentiation by increasing word loss, while warfare hinders linguistic differentiation by decreasing both rates of word gain and loss. Finally, we show that geographical isolation is a strong driver of lexical evolution mainly due to a considerable drift-driven acceleration in rates of word loss. We conclude that the motor of extreme linguistic diversity in Austronesia may have been the dispersal of populations across relatively isolated islands, favouring strong cultural ties amongst societies instead of warfare and cultural group marking.
Genome sequences from diverse human groups are needed to understand the structure of genetic variation in our species and the history of, and relationships between, different populations. We present 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. Analyses of these genomes reveal an excess of previously undocumented common genetic variation private to southern Africa, central Africa, Oceania, and the Americas, but an absence of such variants fixed between major geographical regions. We also find deep and gradual population separations within Africa, contrasting population size histories between hunter-gatherer and agriculturalist groups in the past 10,000 years, and a contrast between single Neanderthal but multiple Denisovan source populations contributing to present-day human populations.
Small populations are often exposed to high inbreeding and mutational load that can increase the risk of extinction. The Sumatran rhinoceros was widespread in Southeast Asia, but is now restricted to small and isolated populations on Sumatra and Borneo, and most likely extinct on the Malay Peninsula. Here, we analyse 5 historical and 16 modern genomes from these populations to investigate the genomic consequences of the recent decline, such as increased inbreeding and mutational load. We find that the Malay Peninsula population experienced increased inbreeding shortly before extirpation, which possibly was accompanied by purging. The populations on Sumatra and Borneo instead show low inbreeding, but high mutational load. The currently small population sizes may thus in the near future lead to inbreeding depression. Moreover, we find little evidence for differences in local adaptation among populations, suggesting that future inbreeding depression could potentially be mitigated by assisted gene flow among populations.
Large areas of tropical forest now exist as remnants scattered across agricultural landscapes, and so understanding the impacts of forest fragmentation is important for biodiversity conservation. We examined species richness and nestedness among tropical forest remnants in birds (meta-analysis of published studies) and insects (field data for fruit-feeding Lepidoptera (butterflies and moths) and ants). Species-area relationships were evident in all four taxa, and avian and insect assemblages in remnants typically were nested subsets of those in larger areas. Avian carnivores and nectarivores and predatory ants were more nested than other guilds, implying that the sequential loss of species was more predictable in these groups, and that fragmentation alters the trophic organization of communities. For butterflies, the ordering of fragments to achieve maximum nestedness was by fragment area, suggesting that differences among fragments were driven mainly by extinction. In contrast for moths, maximum nestedness was achieved by ordering species by wing length; species with longer wings (implying better dispersal) were more likely to occur at all sites, including low diversity sites, suggesting that differences among fragments were driven more strongly by colonization. Although all four taxa exhibited high levels of nestedness, patterns of species turnover were also idiosyncratic, and thus even species-poor sites contributed to landscape-scale biodiversity, particularly for insects.
Phlebotomine sand flies were collected using CO2 baited CDC light trap in 2000 and 2001 in limestone areas and caves of western Malaysia. A total of 1,548 specimens were collected comprising 18 species from two genera: Phlebotomus (6 spp) and Sergentomyia (12 spp). Phlebotomus major major (38.9%) was the predominant species followed by Sergentomyia perturbans (20.1%), P. stantoni (15.3%) and others. Biting activity of the sand flies at the Gua Senyum caves, Gua Kota Gelanggi, Batu caves and Gua Kelam were observed using the bare leg landing catch (BLC) technique. Four Phlebotomus spp at Gua Senyum were found to bite humans with a unimodal biting peak (between 01:00 and 04:00 AM). At Gua Kota Gelanggi P. major major was observed to bite humans, but at Batu Caves and Gua Kelam no sand flies were observed to bite humans. Sergentomyia spp did not feed on humans even though high numbers were caught in light traps. The populations of phleobotomine sand flies fluctuated, with several peaks especially among P. major major which peaked in December and was low in February and August. Phlebotomus stantoni was abundant throughout 2001. Most species populations were weakly related to rainfall because they inhabited caves.
Using the cow-baited trap (CBT) method, 1,845 Anopheles mosquitos, comprising 14 species, were caught in malaria-endemic area of Hulu Perak district, Peninsular Malaysia. The two dominant species were An. barbirostris (18.59%) and An. aconitus (18.86%). Anopheles maculatus, the main malaria vector, constituted 9.11% of the total number of mosquitos sampled. Three hundred and seventy-seven Anopheles larvae, comprising 8 species, were sampled using the North Carolina Biological Station dipper. Anopheles barbirostris larvae amounted to 64.69% of the total number of larvae; An. aconitus accounted for 10.65% of larvae. Seven habitats were identified as breeding places of Anopheles. Most species were found to breed in paddies, fishponds, and rivers. Other less popular habitats were temporary pools, mountain streams, and spring wells.
Mosquito collections were carried out for a period of one year from January to December 1992 in a pig farm in Sungai Pelek, Selangor, Malaysia. A total of 41,022 mosquitos belonging to 52 species and 20 genera were collected. Culex tritaeniorhynchus and Cx. gelidus, the important vectors, comprised 63% of all mosquitos collected. Both these species were collected in large numbers during the wet months of May and December. The other predominant species in that area were Cx. fuscocephala, Cx. quinquefasciatus, Cx. sitiens, Aedes butleri, and Armigeres subalbatus.
"The present paper attempts to provide an analytical profile of development and human resources in [12] selected [Islamic] countries." The countries--Bangladesh, Somalia, Pakistan, Indonesia, Egypt, Turkey, Malaysia, Algeria, Iraq, Saudi Arabia, Kuwait, and United Arab Emirates--vary in income levels from low to high and in population size from 1 million to 159 million. Using data from the World Bank and the Population Council, comparisons are made on the basis of mortality and fertility levels, family size, income, urbanization, labor force size and growth, education, nutrition, and health. Governmental policy changes and future directions are discussed.
Dengue fever (DF) is a major vector-borne disease in Malaysia. The incidences of DF in Malaysia are caused by viruses transmitted through the bites of infected female Aedes albopictus and Ae. aegypti mosquitoes. This study aims to establish the spatial density of mosquito population or breteau index (BI) in the areas of Kuala Lumpur using geographic information system (GIS), remote sensing (RS) and spatial statistical tools.
We investigate the geographical and historical context of diversification in a complex of mutualistic Crematogaster ants living in Macaranga trees in the equatorial rain forests of Southeast Asia. Using mitochondrial DNA from 433 ant colonies collected from 32 locations spanning Borneo, Malaya and Sumatra, we infer branching relationships, patterns of genetic diversity and population history. We reconstruct a time frame for the ants' diversification and demographic expansions, and identify areas that might have been refugia or centres of diversification. Seventeen operational lineages are identified, most of which can be distinguished by host preference and geographical range. The ants first diversified 16-20 Ma, not long after the onset of the everwet forests in Sundaland, and achieved most of their taxonomic diversity during the Pliocene. Pleistocene demographic expansions are inferred for several of the younger lineages. Phylogenetic relationships suggest a Bornean cradle and major axis of diversification. Taxonomic diversity tends to be associated with mountain ranges; in Borneo, it is greatest in the Crocker Range of Sabah and concentrated also in other parts of the northern northwest coast. Within-lineage genetic diversity in Malaya and Sumatra tends to also coincide with mountain ranges. A series of disjunct and restricted distributions spanning northern northwest Borneo and the major mountain ranges of Malaya and Sumatra, seen in three pairs of sister lineages, further suggests that these regions were rain-forest refuges during drier climatic phases of the Pleistocene. Results are discussed in the context of the history of Sundaland's rain forests.
Dengue fever is a recurring public health problem afflicting thousands of Malaysians annually. In this paper, the risk map for dengue fever in the peninsular Malaysian states of Selangor and Kuala Lumpur was modelled based on co-kriging and geographical information systems. Using population density and rainfall as the model's only input factors, the area with the highest risk for dengue infection was given as Gombak and Petaling, two districts located on opposite sides of Kuala Lumpur city that was also included in the risk assessment. Comparison of the modelled risk map with the dengue case dataset of 2010, obtained from the Ministry of Health of Malaysia, confirmed that the highest number of cases had been found in an area centred on Kuala Lumpur as predicted our risk profiling.
Efforts to stamp dengue in many dengue endemic countries has met little success. There is a need to re-examine and understand how the public at large view the dengue prevention efforts. This study aimed to examine the demographic factors, theoretical constructs of the Health Belief Model and knowledge about dengue and how these influence the practice of dengue prevention.
It is important to obtain frequent measurements of the abundance, distribution, and seasonality of mosquito vectors to determine the risk of disease transmission. The number of cases of dengue infection has increased in recent years on Penang Island, Malaysia, with recurring epidemics. However, ongoing control attempts are being critically hampered by the lack of up-to-date information regarding the vectors. To overcome this problem, we examined the current situation and distribution of dengue vectors on the island. Residences throughout the urban, suburban, and rural areas were inspected through wet and dry seasons between February 2009 and February 2010. Two vectors were encountered in the survey, with Aedes aegypti present in especially high numbers mostly in urban areas. Similar observations were noted for Ae. albopictus in rural areas. The former species was more abundant in outdoor containers, while the latter showed almost equivalent abundance both outdoors and indoors. The dengue virus was active in both urban and rural areas, and the number of cases of infection was higher in areas where Ae. aegypti was predominant. The abundance of immature Ae. albopictus was positively correlated with rainfall (r2 = 0.461; P < 0.05), but this was not the case for Ae. aegypti. For both species, the size of immature populations tended to increase with increasing intensity of rain, but heavy rains resulted in population loss. In addition to updating data regarding the larval habitats and locations (outdoors and indoors), this study highlighted the importance of spatial vector control stratification, which has the potential to reduce costs in control programs.