Analysis of Genetic Diversity in Some Rice Varieties and Their Performance in Bangladesh

This study was conducted to evaluate the genetic diversity for several rice features and their association with yields, as well as to identify genotypes of short-duration rice. The experiment was conducted in the field in a natural environment, and data were collected on several plant parameters for each genotype at various phases of plant development. Twenty genotypes of rice were examined based on their morphological and physiological characteristics. From July through December of 2020, the experiment was conducted at the Bangladesh Rice Research Institute's regional station in Shyampur, Rajshahi. There was significant diversity among the twenty rice genotypes for all characteristics tested. The genotype BRRI dhan57 displayed the shortest days to flowering. In terms of days to maturity, the genotype BRRI dhan57 was the earliest, with a maturity time of 107.33 days, followed by BRRI dhan56 and BRRI dhan39. The days to blooming had the highest heritability (99.75%), followed by the days to maturity (99.58%), grain yield (85.30%), thousand grain weight (85.22%), grains per panicle (84.91%), plant height (82.21%), and tillers per hill (21.61%). High heritability scores indicated that the researched qualities were less influenced by the surrounding environment. As a percentage of the mean, the genetic gain was greatest for grain yield (36.33%) and lowest for tillers per hill (6.60%) among the yield-contributing factors. In days to flowering, days to maturity, grains per panicle, and plant height, high heritability and genetic progress were seen. According to the principal component analysis (PCA), the Eigen values of the first four components of the total variance accounted for 89.46% of the total variance, indicating that these components were mostly responsible for the genetic diversity of the current materials. It was the largest cluster, containing seven rice genotypes. Clusters II and V contained five and four genotypes of rice, respectively. Clusters III and IV were the smallest, with only two genotypes apiece. The pattern of distribution of genotypes among various clusters demonstrated the significant genetic variety present in the genotypes, which may be the result of adaptation of these genotypes to certain environmental conditions. The largest value of intercluster distance indicated that cluster III genotypes were extremely distinct from cluster IV genotypes. Negative values in both vectors for tillers per hill suggested that this feature contributed the least to the total diversity. The number of panicles per hill, panicle length, weight per thousand grains, and grain yield were all positive in both directions. According to these statistics, these four characteristics contributed the most to the variety. View Article DOI: 10.47856/ijaast.2022.v09i12.00

ESTIMATION OF COMBINING ABILITY AND HETEROSIS IN WHEAT

The study used a half-diallel mating fashion to identify combining ability (GCA and SCA) and heterosis of six wheat (Triticum aestivum L.) genotypes and their 15 F1 hybrids for morpho-physiological, yield, and yield-contributing traits. The present study was carried out in a randomized complete block design with three replications. The studied characters are heading days, maturity days, chlorophyll content, Plant height, Effective tillers plant-1, Total tillers plant-1, Spikes plant-1, Spike length, Filled spikelets spike-1, Unfilled spikelets spike-1, Grains spike-1, Thousand grain weight, Grain yield plant-1, Biological yield plant-1, and Harvest index Highly significant differences were observed among genotypes (parents and F1 hybrids) for all characters studied. The results also showed that the mean squares due to general (GCA) and specific (SCA) combining abilities were highly significant for all studied characters except harvest index, indicating the magnitude of both additive and non-additive gene effects in governing these traits. GCA/SCA ratios were greater than one for all characters except filled spikelets spike-1 and harvests index, indicating the dominance of additive gene effects, which play important roles in the inheritance of these characters. While the non-additive effect of the gene predominated in the inheritance of filled spikelets (spike-1) and harvests index, The parent BARI GOM-30 emerged as the best general combiner for total tillers plant-1, filled spikelets spike-1, grains spike-1, thousand-grain weight, grain yield plant-1, and harvest index. Bari Gom-28 was the best general combiner for heading days and maturity days, and Sourav was the best for effective tillers plant-1, spikes plant-1, and biological yield plant-1. The cross BARI GOM-30  SOURAV was the best specific combiner for effective tillers plant-1, total tillers plant-1, spikes plant-1, and PRODIP  SOURAV for filled spikelets spike-1. Bari GOM-33   Sourav emerged as the best specific combiner for grain yield plant-1 and Prodip    Ayt-5 for grain spike-1. Concerning heterotic effects in comparison to the midparent, the F1 hybrid BARI GOM-28  BARI GOM-33 showed maximum significant positive heterosis for chlorophyll content and biological yield plant-1 and BARI GOM-33  SOURAV for effective tillers plant-1, spikes plant-1, and grain yield plant-1. These parents and cross combinations could be used for the breeding program of wheat for potential yield. View Article DOI: 10.47856/ijaast.2022.v09i12.00

Estimation of Genetic Variability, Heritability and Genetic Advances for Short Duration and High Yielding Rice Genotypes

The goal of the study was to find genotypes of 18 different rice varieties that would yield a lot of rice in a short amount of time. With this in mind, the study genotypes' field performance as well as the relationships between various morpho-physiological and yield-contributing traits among the genotypes was assessed. The experiments were conducted from July to December 2018 at the Agronomy Field, Department of Agronomy and Agricultural Extension, Faculty of Agriculture, Rajshahi University. In genotype BRRI dhan 51, the maximum number of days to 50% flowering was discovered. The genotype BRRI dhan 56 had the lowest number of days required for 50% flowering. Genotypes showed a wide range of days to maturity (92.00–109.00), with an average of 98.96 days. The genotypes DRR 46, BINA 7, and DRR 44 are followed by the genotypes BRR1 dhan 66, BRR1 dhan 56, and BRR1 dhan 57, which have shorter maturity periods (i.e., 92.00 days), indicating earliness. The traits investigated in this study showed high heritabilities, with estimates ranging from 67.00 to 96.00 percent. Days to flowering and unfilled grain panicle-1 had the highest heritability among the traits (96.00%).The presence of high heritability values suggests that the expression of the traits under study is less influenced by the external environment. The unfilled grain panicle-1 had the highest genetic advance as a percentage of the mean (144.80%), while panicle length had the lowest genetic advance (10.48%) among the traits that affected yield. View Article DOI: 10.47856/ijaast.2022.v09i10.00

The Study of Genetic Divergence in Rice (Oryza Sativa L.) Genotypes with Grain Yield and Different Morpho-Physiological Traits using Mahalanobis’ D2 Analysis

The current study attempted to study genetic divergence in rice (Oryza sativa L.) genotypes with grain yield and different morpho-physiological traits among 18 rice varieties using Mahalanobis' D2 analysis. Keeping this in mind, the performance of the studied genotypes, as well as the association between various morpho-physiological and yield contributing traits among the genotypes, were evaluated in the field. The experiments were conducted from July to December 2018 at the Agronomy Field, Department of Agronomy and Agricultural Extension, Faculty of Agriculture, Rajshahi University. In terms of grain yield and other morpho-physiological traits, the genotypes differed significantly. The genotypes were classified into five clusters using Mahalonobis' D2 statistics and Tocher's method (Table 3). Cluster IV was the smallest of the clusters. Cluster l is the largest, with six genotypes. Clusters II and lV each contained three and two genotypes. The pattern of genotype distribution among various clusters reflected the significant genetic variability present in the genotypes, which may be due to adaptation of these genotypes to specific environmental conditions. Genotypes from different clusters are expected (inter-cluster). The intra (bold) and inter-cluster distances from D2 analysis (Table 4). Cluster I has the greatest intra cluster distance (0.956), while Cluster IV has the smallest (0.3583). The greatest inter-cluster distance is observed between cluster IV and (8.190), while the smallest inter-cluster distance is observed between cluster II and IV (2.924). In both vectors, the average inter-cluster distances were greater than the average intra-cluster distances, indicating the presence of greater genetic diversity among genotypes from different clusters than those from the same cluster. These findings indicated that these five traits contributed the most to the divergence among the eighteen rice genotypes. The results revealed that the clusters were remarkably distinct for the majority of the traits, indicating proper clustering. The most effective tiller, grain panicle, effective grain panicle, and days to maturity were found in Cluster V. The intra-cluster mean for grain yield was the lowest in this cluster. Cluster III had the lowest grain yield per acre. This was the cluster with the lowest initial grain yield. The intra-cluster mean for effective tiller and days to maturity was highest in this cluster. Cluster II had the smallest grain yield and the second smallest thousand grain weight. Cluster V had the shortest panicle length intra-cluster. View Article DOI: 10.47856/ijaast.2022.v09i10.00

Candida albicans skin infection in diabetic patients: An updated review of pathogenesis and management

Candida species, commensal residents of human skin, are recognized as the cause of cutaneous candidiasis across various body surfaces. Individuals with weakened immune systems, particularly those with immunosuppressive conditions, are significantly more susceptible to this infection. Diabetes mellitus, a major metabolic disorder, has emerged as a critical factor inducing immunosuppression, thereby facilitating Candida colonization and subsequent skin infections. This comprehensive review examines the prevalence of different types of Candida albicans-induced cutaneous candidiasis in diabetic patients. It explores the underlying mechanisms of pathogenicity and offers insights into recommended preventive measures and treatment strategies. Diabetes notably increases vulnerability to oral and oesophageal candidiasis. Additionally, it can precipitate vulvovaginal candidiasis in females, Candida balanitis in males, and diaper candidiasis in young children with diabetes. Diabetic individuals may also experience candidal infections on their nails, hands and feet. Notably, diabetes appears to be a risk factor for intertrigo syndrome in obese individuals and periodontal disorders in denture wearers. In conclusion, the intricate relationship between diabetes and cutaneous candidiasis necessitates a comprehensive understanding to strategize effective management planning. Further investigation and interdisciplinary collaborative efforts are crucial to address this multifaceted challenge and uncover novel approaches for the treatment, management and prevention of both health conditions, including the development of safer and more effective antifungal agents

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

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

A Survey on SDN and SDCN Traffic Measurement: Existing Approaches and Research Challenges

The Software-Defined Network (SDN) is a next-generation network that uses OpenFlow to decouple the control plane from the data plane of forwarding devices. Other protocols for southbound interfaces include ForCES and POF. However, some security issues might be in action on the SDN, so that attackers can take control of the SDN control plane. Since live video calling, QoS control, high bandwidth needs, and resource management are inevitable in any SDN/Software-Defined Cellular Network (SDCN), traffic monitoring is an integral approach for safeguarding against DDoS, heavy hitters, and superspreaders. In such a scenario, SDN traffic measurement comes into action. Thus, we survey SDN traffic measurement solutions to assess how these solutions can make a secure, efficient, and robust SDN/SDCN architecture. This research classifies SDN traffic measurement solutions according to network application behavior and compares several ML approaches. Furthermore, we find out the challenges related to SDN/SDCN traffic measurement and the future scope of research, which will guide the design and development of more advanced traffic measurement solutions for a scalable, heterogeneous, hierarchical, and widely deployed SDN/SDCN architecture. In more detail, we list different kinds of practical machine learning (ML) approaches to analyze how we can improve traffic measurement performances. We conclude that using ML in SDN traffic measurement solutions will help secure SDNs/SDCNs in complementary ways

Evaluations of crude protein and amino acid contents from the scales of four mullet species (Mugilidae) collected from Karachi fish harbour, Pakistan

724-731<span style="font-size:9.0pt;font-family: " times="" new="" roman","serif";mso-fareast-font-family:"ms="" mincho";mso-font-kerning:="" 0pt;mso-ansi-language:en-us;mso-fareast-language:en-us;mso-bidi-language:ar-sa"="" lang="EN-US">The present study was aimed to determine the crude protein and amino acid contents in the scales of four mullet species namely Liza macrolepis, Liza melinoptera, Mugil cephalus and <span style="mso-bidi-font-style: italic">Valamugil speigleri found in the Pakistan coast. <span style="font-size:9.0pt; font-family:" times="" new="" roman","serif";mso-fareast-font-family:"ms="" mincho";="" mso-font-kerning:0pt;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:ar-sa"="" lang="EN-GB">The moisture content of scales ranged from 42.8% in L. macrolepis to 58.3% in M. cephalus. The values of crude protein content in dry matter of the scales were found to be in order of 78.07% in Liza melinoptera, 76.45% in Mugil cephalus, <span style="font-size:9.0pt; font-family:" times="" new="" roman","serif";mso-fareast-font-family:"ms="" mincho";="" mso-font-kerning:0pt;mso-ansi-language:en-us;mso-fareast-language:ja;="" mso-bidi-language:ar-sa"="" lang="EN-US">70.36 Liza macrolepis<span style="font-size: 9.0pt;font-family:" times="" new="" roman","serif";mso-fareast-font-family:"ms="" mincho";="" mso-font-kerning:0pt;mso-ansi-language:en-us;mso-fareast-language:en-us;="" mso-bidi-language:ar-sa;mso-bidi-font-style:italic"="" lang="EN-US">, 62.28% in Valamugil speigleri, respectively. Both glycine and proline contents were found to be high as compare to the remaining amino acids, however, cysteine, methionine and tryptophan were not detected. Hence, the result of the present study revealed that like other materials obtained from the fish, scales could also be considered as a rich source of protein and various essential amino acids, thence, they could also be used to produce various materials including skin moisturizing creams, anti-aging creams, wrinkles removers creams etc. and biomedical materials in <span style="font-size: 9.0pt;font-family:" times="" new="" roman","serif";mso-fareast-font-family:"ms="" mincho";="" mso-font-kerning:0pt;mso-ansi-language:en-us;mso-fareast-language:en-us;="" mso-bidi-language:ar-sa"="" lang="EN-US">pharmaceutical and cosmetics industries.</span

Population-based sero-epidemiological investigation of SARS-CoV-2 infection in Somalia

Objectives: To explore the burden of coronavirus disease 2019 (COVID-19) in Somalia by measuring the seroprevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the general population. Methods: We recruited a convenience sample of 2751 participants from among individuals attending outpatient and inpatient departments of public health facilities, or their accompanying family members. Participants were interviewed to collect sociodemographic data and provided a blood sample. We calculated seropositivity rates overall and by sex, age group, state, residence, education and marital status. We used logistic regression analysis – odds ratios and 95% confidence intervals (CI) – to investigate sociodemographic correlates of seropositivity. Results: The overall seropositivity rate was 56.4% (95% CI 54.5–58.3%), while 8.8% of participants reported being previously diagnosed with COVID-19 by July 2021. In the regression analysis, after controlling for covariates, urban residence was significantly asscoiated with seropositivity: OR = 1.74 (95% CI: 1.19–2.55). Conclusions: Our results show a high seroprevalence rate of SARS-CoV-2 in the Somali population (56.4%), and indicate that many infections have not been captured by the country’s surveillance system resulting in considerable under-reporting