Immunopathogenesis of Salmonellosis

Salmonella is an intracellular pathogenic, gram-negative, facultative anaerobe and non-spore-forming and usually a motile bacillus that leads to salmonellosis in the host. It is a common food-borne disease that ranges from local gastrointestinal inflammation and diarrhoea to life-threatening typhoid fever and presents usually a serious threat to public health due to its socio-economic value. Inadequate sanitation and impure water help in the propagation of this disease. Despite advancement in the sanitation standards, Salmonella enters the food chain and affects communities globally. There is an immediate need to develop improved vaccines to minimise Salmonella-related illnesses. Some Salmonella serovars infect a wide range of hosts, while others are known to be host restricted. Many different factors determine the adaptability and host specificity of Salmonella. The host-pathogen interactions play a unique role in Salmonella invasion and progression which needs to be studied in detail. This chapter shall focus on our current understanding of Salmonella invasion, pathogenesis and interactions with the host, host specificity and adaptability

Genetics of Disease Resistance in Chicken

Although poultry industry has gained momentum during the last few decades, there are still various impediments like improper infrastructure, unscientific management and above all various deadly infectious diseases which incur huge economic losses on poultry industry. These diseases include viral diseases like Avian Influenza, Marek’s Disease, New Castle disease and bacterial diseases like Colibacillosis, Pasteurellosis and Salmonellosis, etc. Development of disease resistant poultry has been found successful practice over the use of drugs or vaccines for disease control. Studies involving genome wide associations to figure out certain candidate genes that are involved in disease resistance have also been carried out. Single nucleotide polymorphism studies to unveil the mechanisms underlying disease resistance in chicken show that SNPs and other candidate gene approaches play a vital role in providing disease resistance. Also, understanding the genes and biological pathways that confer genetic resistance to various infections will lead towards the development of more resistant commercial poultry flocks or improved vaccines against various diseases. This chapter shall focus on various factors involved in disease resistance in chicken that interact with the pathogen and provide resistance against the pathogen

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Assessing changes in the above ground biomass and carbon stocks of Lidder valley, Kashmir Himalaya, India

The changes in the land use and land cover (LULC), above ground biomass (AGB) and the associated above ground carbon (AGC) stocks were assessed in Lidder Valley, Kashmir Himalaya using satellite data (1980–2013), allometric equations and phytosociological data. Change detection analysis of LULC, comprising of eight vegetation and five non-vegetation types, indicated that 6% (74.5 km2) of the dense evergreen forest has degraded. Degraded forest and settlement increased by 20 and 52.8 km2, respectively. Normalized difference vegetation index was assessed and correlated with the field-based biomass estimates to arrive at best-fit models for remotely sensed AGB estimates for 2005 and 2013. Total loss of 1.018 Megatons of AGB and 0.5 Megatons of AGC was estimated from the area during 33-year period which would have an adverse effect on the carbon sequestration potential of the area which is already facing the brunt of climate change

Epithelial to mesenchymal transition in mammary gland tissue fibrosis and insights into drug therapeutics

Background The epithelial-mesenchymal transition (EMT) is a multi-step morphogenetic process in which epithelial cells lose their epithelial properties and gain mesenchymal characteristics. The process of EMT has been shown to mediate mammary gland fibrosis. Understanding how mesenchymal cells emerge from an epithelial default state will aid in unravelling the mechanisms that control fibrosis and, ultimately, in identifying therapeutic targets to alleviate fibrosis. Methods The effects of EGF and high glucose (HG) on EMT in mammary epithelial cells, MCF10A and GMECs, as well as their pathogenic role, were studied. In-silico analysis was used to find interacting partners and protein-chemical/drug molecule interactions. Results On treatment with EGF and/or HG, qPCR analysis showed a significant increase in the gene expression of EMT markers and downstream signalling genes. The expression of these genes was reduced on treatment with EGF+HG combination in both cell lines. The protein expression of COL1A1 increased as compared to the control in cells treated with EGF or HG alone, but when the cells were treated with EGF and HG together, the protein expression of COL1A1 decreased. ROS levels and cell death increased in cells treated with EGF and HG alone, whereas cells treated with EGF and HG together showed a decrease in ROS production and apoptosis. In-silico analysis of protein-protein interactions suggest the possible role of MAPK1, actin alpha 2 (ACTA2), COL1A1, and NFκB1 in regulating TGFβ1, ubiquitin C (UBC), specificity protein 1 (SP1) and E1A binding protein P300 (EP300). Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment suggests advanced glycation end products-receptor for advanced glycation end products (AGE-RAGE) signalling pathway, relaxin signalling pathway and extra cellular matrix (ECM) receptor interactions underlying fibrosis mechanism. Conclusion This study demonstrates that EGF and HG induce EMT in mammary epithelial cells and may also have a role in fibrosis

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Not AvailableDeep RNA sequencing experiment was employed to detect putative single nucleotide polymorphisms (SNP) in mammary epithelial cells between two diverse cattle breeds (Jersey and Kashmiri) to understand the variations in the coding regions that reflect differences in milk production traits. The low milk-producing Kashmiri cattle are being replaced by crossbreeding practices with Jersey cattle with the aim of improving milk production. However, crossbred animals are prone to infections and various other diseases resulting in unsustainable milk production. In this study, we tend to identify high-impact SNPs from Jersey and Kashmiri cows (utilizing RNA-Seq data) to delineate key pathways mediating milk production traits in both breeds. A total of 607 (442 SNPs and 169 INDELs) and 684 (464 SNPs and 220 INDELs) high-impact variants were found specific to Jersey and Kashmir cattle, respectively. Based on our results, we conclude that in Jersey cattle, genes with high-impact SNPs were enriched in nucleotide excision repair pathway, ABC transporter, and metabolic pathways like glycerolipid metabolism, pyrimidine metabolism, and amino acid synthesis (glycine, serine, and threonine). Whereas, in Kashmiri cattle, the most enriched pathways include endocytosis pathway, innate immunity pathway, antigen processing pathway, insulin resistance pathway, and signaling pathways like TGF beta and AMPK which could be a possible defense mechanism against mammary gland infections. A varied set of SNPs in both breeds, suggests a clear differentiation at the genomic level; further analysis of high-impact SNPs are required to delineate their effect on these pathways.Not Availabl

Glacier thickness and volume estimation in the Upper Indus Basin using modeling and ground penetrating radar measurements

In the Himalaya, ice thickness data are limited, and field measurements are even scarcer. In this study, we employed the GlabTop model to estimate ice reserves in the Jhelum (1.9 ± 0.6 km3) and Drass (2.9 ± 0.9 km3) sub-basins of the Upper Indus Basin. Glacier ice thickness in the Jhelum ranged up to 187 ± 56 m with a mean of ~24 ± 7 m, while the Drass showed ice thickness up to 202 ± 60 m, with a mean of ~17 ± 5 m. Model results were validated using Ground Penetrating Radar measurements across four profiles in the ablation zone of the Kolahoi glacier in the Jhelum and nine profiles across the Machoi glacier in the Drass sub-basin. Despite underestimating ice-thickness by ~10%, the GlabTop model effectively captured glacier ice-thickness and spatial patterns in most of the profile locations where GPR measurements were taken. The validation showed high correlation coefficient of 0.98 and 0.87, low relative bias of ~ −13% and ~ −3% and a high Nash–Sutcliffe coefficient of 0.94 and 0.93 for the Kolahoi and Machoi glaciers, respectively, demonstrating the model's effectiveness. These ice-thickness estimates improve our understanding of glacio-hydrological, and glacial hazard processes over the Upper Indus Basin

Advances in genome editing for improved animal breeding: A review

Since centuries, the traits for production and disease resistance are being targeted while improving the genetic merit of domestic animals, using conventional breeding programs such as inbreeding, outbreeding, or introduction of marker-assisted selection. The arrival of new scientific concepts, such as cloning and genome engineering, has added a new and promising research dimension to the existing animal breeding programs. Development of genome editing technologies such as transcription activator-like effector nuclease, zinc finger nuclease, and clustered regularly interspaced short palindromic repeats systems begun a fresh era of genome editing, through which any change in the genome, including specific DNA sequence or indels, can be made with unprecedented precision and specificity. Furthermore, it offers an opportunity of intensification in the frequency of desirable alleles in an animal population through gene-edited individuals more rapidly than conventional breeding. The specific research is evolving swiftly with a focus on improvement of economically important animal species or their traits all of which form an important subject of this review. It also discusses the hurdles to commercialization of these techniques despite several patent applications owing to the ambiguous legal status of genome-editing methods on account of their disputed classification. Nonetheless, barring ethical concerns gene-editing entailing economically important genes offers a tremendous potential for breeding animals with desirable traits

Comparative transcriptome analysis of mammary epithelial cells at different stages of lactation reveals wide differences in gene expression and pathways regulating milk synthesis between Jersey and Kashmiri cattle.

Jersey and Kashmiri cattle are important dairy breeds that contribute significantly to the total milk production of the Indian northern state of Jammu and Kashmir. The Kashmiri cattle germplasm has been extensively diluted through crossbreeding with Jersey cattle with the goal of enhancing its milk production ability. However, crossbred animals are prone to diseases resulting to unsustainable milk production. This study aimed to provide a comprehensive transcriptome profile of mammary gland epithelial cells at different stages of lactation and to find key differences in genes and pathways regulating milk traits between Jersey and Kashmiri cattle. Mammary epithelial cells (MEC) isolated from milk obtained from six lactating cows (three Jersey and three Kashmiri cattle) on day 15 (D15), D90 and D250 in milk, representing early, mid and late lactation, respectively were used. RNA isolated from MEC was subjected to next-generation RNA sequencing and bioinformatics processing. Casein and whey protein genes were found to be highly expressed throughout the lactation stages in both breeds. Largest differences in differentially expressed genes (DEG) were between D15 vs D90 (1,805 genes) in Kashmiri cattle and, D15 vs D250 (3,392 genes) in Jersey cattle. A total of 1,103, 1,356 and 1,397 genes were differentially expressed between Kashmiri and Jersey cattle on D15, D90 and D250, respectively. Antioxidant genes like RPLPO and RPS28 were highly expressed in Kashmiri cattle. Differentially expressed genes in both Kashmiri and Jersey were enriched for multicellular organismal process, receptor activity, catalytic activity, signal transducer activity, macromolecular complex and developmental process gene ontology terms. Whereas, biological regulation, endopeptidase activity and response to stimulus were enriched in Kashmiri cattle and, reproduction and immune system process were enriched in Jersey cattle. Most of the pathways responsible for regulation of milk production like JAK-STAT, p38 MAPK pathway, PI3 kinase pathway were enriched by DEG in Jersey cattle only. Although Kashmiri has poor milk production efficiency, the present study suggests possible physicochemical and antioxidant properties of Kashmiri cattle milk that needs to be further explored

Long non-coding RNAs: Mechanism of action and functional utility

Recent RNA sequencing studies have revealed that most of the human genome is transcribed, but very little of the total transcriptomes has the ability to encode proteins. Long non-coding RNAs (lncRNAs) are non-coding transcripts longer than 200 nucleotides. Members of the non-coding genome include microRNA (miRNA), small regulatory RNAs and other short RNAs. Most of long non-coding RNA (lncRNAs) are poorly annotated. Recent recognition about lncRNAs highlights their effects in many biological and pathological processes. LncRNAs are dysfunctional in a variety of human diseases varying from cancerous to non-cancerous diseases. Characterization of these lncRNA genes and their modes of action may allow their use for diagnosis, monitoring of progression and targeted therapies in various diseases. In this review, we summarize the functional perspectives as well as the mechanism of action of lncRNAs. Keywords: LncRNA, X-chromosome inactivation, Genome imprinting, Transcription regulation, Cancer, Immunit