Genetic Variation Between and Within Three Varieties of Domesticated Tiger Barb (Puntius Tetrazona) Using Rapd Markers

Tiger barb (Puntius tetrazona) is one of the popular ornamental fish species cultured and is a significant component of the aquarium fish industry in Malaysia This study was conducted to assess genetic variation between and within three varieties of domesticated Tiger barb using random amplified polymorphic DNA (RAPD) markers. Genetic markers are important to selective breeding programmes and as a supportive research in order to minimise incorrect identification and stock contamination. Fifty random individuals of each variety (normal, green and yellow) were obtained from Perak and Johor, which are the main producers of Tiger barb i

Microbiota composition data for wild and captive bluestreak cleaner wrasse Labroides dimidiatus (Valenciennes, 1839

The Labroides dimidiatus is known as the “doctor fish” because of its role in removing parasites and infectious pathogens from the body of other fishes. This important role played both in wild and captive conditions could represent a novel form of parasitic transmission process mediated by the cleaning activity of the fish. Yet, there is a paucity of data on the microflora associated with this fish which is important for tracking disease infection and generally monitoring the health status of the fish. This article, therefore, represents the first dataset for the microbiota composition of wild and captive L. dimidiatus. Wild fish samples and carriage water were gotten in Terengganu Malaysia around the corals of the Karah Island. The captive sample, however, was obtained from well-known ornamental fish suppliers in Terengganu Malaysia. Thereafter, bacteria present on the skin, in the stomach and the aquarium water were enumerated using culture-independent approaches and Next Generation Sequencing (NGS) technology. Data obtained from the three metagenomic libraries using NGS analysis gave 1,426,740 amplicon sequence reads which are composed of 508 operational taxonomic units (OTUs) for wild samples and 3,238,564 valid reads and 828 OTUs for captive samples. All sequence reads were deposited in the GeneBank (Accession numbers SAMN14260247, SAMN14260248, SAMN14260249, SAMN14260250, SAMN14260251, and SAMN14260252). The dataset presented is associated with the research article “16S rDNA-Based Metagenomic Analysis of Microbial Communities Associated with Wild Labroides dimidiatus From Karah Island, Terengganu, Malaysia”. The microbiota data presented in this article can be used to monitor the health and wellbeing of the ornamental fish, especially under captivity, hence preventing possible cross-infectio

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

16S rRNA-Based metagenomic analysis of microbial communities associated with wild Labroides dimidiatus from Karah Island, Terengganu, Malaysia

This study was designed to evaluate the bacterial composition of the Labroides dimidiatus and its surrounding water. Fish and carriage water samples were obtained from corals of the Karah Island in Terengganu Malaysia. DNA was extracted and the bacteria communities on the skin mucus and stomach as well as water sample were classified (to family level) using the 16S rRNA-based metagenomics analysis. 1,426,740 amplicon sequence reads corresponding to 508 total operational taxonomic units were obtained from the three metagenomics libraries in this study. The Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria and Fusobacteria were the most dominant bacterial phyla in all samples. A total of 36 different classes and 132 families were identified, many of which had shared presence in all samples while others were exclusive to different sample. Thirty-three of these were identified as pathogenic zoonotic bacterial. The results obtained indicate a strong influence of host environment on the composition of its microbiota. Knowing the composition of the microbiota is the first step toward exploring proper management of this ornamental fish in captivity. Keywords: Bluestreak cleaner wrasse, Skin mucus, Bacterial community, Microbiot

Morphometric Variations Between Triploid and Diploid Clarias gariepinus (Burchell, 1822)

Several scientific methods have been described in the identification of triploid fish. However, many of these methods are not applicable for routine management purposes due to their complexity and cost. In this study, the possibility of using morphological variation as a least cost and less complex method of distinguishing triploid and diploid African catfish Clarias gariepinus (Burchell, 1822) was examined. Triploid catfish were produced by cold shock of fertilized eggs in 5°C for 20 mins (at approximately 3 mins after fertilization). The fish were incubated, hatched and raised for 3 months. Ploidy levels of the fish were then ascertained by observing the erythrocyte shape. Triploid erythrocyte was ellipsoidal in shape while diploid was round. Morphological characterization was then carried out on 100 samples each of triploid and diploid African catfish. Although significant differences were observed in many parameters, the principal morphometric difference between triploid and diploid African catfish could not be clearly distinguished. It was therefore concluded that morphological characteristics is not ideal for discriminating triploids and diploids of African catfish. The used of erythrocyte characteristics still remains the cheapest and relatively effective method for triploid and diploid determination in African catfish

MORPHOMETRIC VARIATIONS BETWEEN TRIPLOID AND DIPLOID Clarias gariepinus (Burchell, 1822)

Nekoliko znanstvenih metoda ranije je opisano za prepoznavanje triploidnih riba. Međutim, mnoge od tih metoda nisu primjenjive u svrhu rutinskog upravljanja radi njihove složenosti i troškova. U ovom radu istraživana je mogućnost korištenja morfoloških varijacija kao jeftine i jednostavne metode razlikovanja triploidnih i diploidnih afričkih somova Clarias gariepinus (Burchell, 1822). Triploidski somovi su proizvedeni metodom hladnog šoka oplođenih jaja na 5°C tijekom 20 minuta (približno 3 min. nakon oplodnje). Ribe su bile inkubirane, izvaljene i uzgajane tijekom 3 mjeseca. Plodnost riba utvrđena je promatranjem oblika eritrocita. Triploidni eritrocit bio je elipsoidnog oblika dok je diploidi bio okrugli. Morfološka karakterizacija je provedena na 100 uzoraka triploidnih i na 100 uzoraka diploidnih afričkih somova. Iako su značajne razlike zabilježene u mnogim parametrima, glavna morfometrijska razlika između triploidnih i diploidnih afričkih somova nije se mogla jasno razlikovati. Stoga je zaključeno da morfološka svojstva nisu idealna za razlikovanje triploida i diploida afričkog soma. Upotreba eritrocitnih karakteristika i dalje je najjeftiniji i relativno učinkovit način za triploido i diploidno određivanje afričkih somova.Several scientific methods have been described in the identification of triploid fish. However, many of these methods are not applicable for routine management purposes due to their complexity and cost. In this study, the possibility of using morphological variation as a least cost and less complex method of distinguishing triploid and diploid African catfish Clarias gariepinus (Burchell, 1822) was examined. Triploid catfish were produced by cold shock of fertilized eggs in 5°C for 20 mins (at approximately 3 mins after fertilization). The fish were incubated, hatched and raised for 3 months. Ploidy levels of the fish were then ascertained by observing the erythrocyte shape. Triploid erythrocyte was ellipsoidal in shape while diploid was round. Morphological characterization was then carried out on 100 samples each of triploid and diploid African catfish. Although significant differences were observed in many parameters, the principal morphometric difference between triploid and diploid African catfish could not be clearly distinguished. It was therefore concluded that morphological characteristics is not ideal for discriminating triploids and diploids of African catfish. The used of erythrocyte characteristics still remains the cheapest and relatively effective method for triploid and diploid determination in African catfish

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.MethodsThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.FindingsThe leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.InterpretationLong-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere