Obesity and pain: a systematic review Chin, Shao-Hua; Huang, Wei-Lin; Akter, Sharmin ...
International Journal of Obesity,
05/2020, Volume:
44, Issue:
5
Journal Article
Peer reviewed
The current systematic review considered research published within the 10 years preceding June 2019, dealing with the topic of obesity and pain. Within the context of the complex biological and ...behavioral interrelationships among these phenomena, we sought to identify gaps in the literature and to highlight key targets for future transdisciplinary research. The overarching inclusion criteria were that the included studies could directly contribute to our understanding of these complex phenomena.
We searched PubMed/Medline/Cochrane databases dating back 10 years, using the primary search terms "obesity" and "pain," and for a secondary search we used the search terms "pain" and "diet quality."
Included studies (n = 70) are primarily human; however, some animal studies were included to enhance understanding of related basic biological phenomena and/or where human data were absent or significantly limited.
Our overall conclusions highlight (1) the mechanisms of obesity-related pain (i.e., mechanical, behavioral, and physiological) and potential biological and behavioral contributors (e.g., gender, distribution of body fat, and dietary factors), (2) the requirement for accurate and reliable objective measurement, (3) the need to integrate biological and behavioral contributors into comprehensive, well-controlled prospective study designs.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The human intestine hosts diverse microbial communities that play a significant role in maintaining gut-skin homeostasis. When the relationship between gut microbiome and the immune system is ...impaired, subsequent effects can be triggered on the skin, potentially promoting the development of skin diseases. The mechanisms through which the gut microbiome affects skin health are still unclear. Enhancing our understanding on the connection between skin and gut microbiome is needed to find novel ways to treat human skin disorders. In this review, we systematically evaluate current data regarding microbial ecology of healthy skin and gut, diet, pre- and probiotics, and antibiotics, on gut microbiome and their effects on skin health. We discuss potential mechanisms of the gut-skin axis and the link between the gut and skin-associated diseases, such as psoriasis, atopic dermatitis, acne vulgaris, rosacea, alopecia areata, and hidradenitis suppurativa. This review will increase our understanding of the impacts of gut microbiome on skin conditions to aid in finding new medications for skin-associated diseases.
Sulforaphane is an isothiocyanate compound that has been derived from cruciferous vegetables. It was shown in numerous studies to be active against multiple cancer types including pancreatic, ...prostate, breast, lung, cervical, and colorectal cancers. Sulforaphane exerts its therapeutics action by a variety of mechanisms, such as by detoxifying carcinogens and oxidants through blockage of phase I metabolic enzymes, and by arresting cell cycle in the G2/M and G1 phase to inhibit cell proliferation. The most striking observation was the ability of sulforaphane to potentiate the activity of several classes of anticancer agents including paclitaxel, docetaxel, and gemcitabine through additive and synergistic effects. Although a good number of reviews have reported on the mechanisms by which sulforaphane exerts its anticancer activity, a comprehensive review on the synergistic effect of sulforaphane and its delivery strategies is lacking. Therefore, the aim of the current review was to provide a summary of the studies that have been reported on the activity enhancement effect of sulforaphane in combination with other anticancer therapies. Also provided is a summary of the strategies that have been developed for the delivery of sulforaphane.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Coronavirus disease-19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is now a pandemic threat. This virus is supposed to be spread by human to human ...transmission. Cellular angiotensin-converting enzyme 2 (ACE2) is the receptor of SARS-CoV-2 which is identical or similar in different species of animals such as pigs, ferrets, cats, orangutans, monkeys, and humans. Moreover, a recent study predicted that dogs might be secondary hosts during the evolution of SARS-CoV-2 from bat to human. Therefore, there is a possibility of spreading SARS-CoV-2 through domestic pets. There are now many reports of SARS-CoV-2 positive cases in dogs, cats, tigers, lion, and minks. Experimental data showed ferrets and cats are highly susceptible to SARS-CoV-2 as infected by virus inoculation and can transmit the virus directly or indirectly by droplets or airborne routes. Based on these natural infection reports and experimental data, whether the pets are responsible for SARS-CoV-2 spread to humans; needs to be deeply investigated. Humans showing clinical symptoms of respiratory infections have been undergoing for the COVID-19 diagnostic test but many infected people and few pets confirmed with SARS-CoV-2 remained asymptomatic. In this review, we summarize the natural cases of SARS-CoV-2 in animals with the latest researches conducted in this field. This review will be helpful to think insights of SARS-CoV-2 transmissions, spread, and demand for seroprevalence studies, especially in companion animals.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this ...study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (
> 10%) and novel QTLs (viz.,
and
). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., "QTL Hotspot A", "QTL Hotspot B", "QTL Hotspot C", and "QTL Hotspot D" located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four "QTL Hotspots" were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz.,
and
, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Seed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying ...seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage.
In the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation.
Our findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In plants, lesion mimic mutants (LMMs) reveal spontaneous disease-like lesions in the absence of pathogen that constitutes powerful genetic material to unravel genes underlying programmed cell death ...(PCD), particularly the hypersensitive response (HR). However, only a few LMMs are reported in soybean, and no related gene has been cloned until now. In the present study, we isolated a new LMM named spotted leaf-1 (
) from NN1138-2 cultivar through ethyl methanesulfonate (EMS) treatment. The present study revealed that lesion formation might result from PCD and excessive reactive oxygen species (ROS) accumulation. The chlorophyll content was significantly reduced but antioxidant activities, viz., superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT), as well as the malondialdehyde (MDA) contents, were detected higher in
than in the wild-type. According to segregation analysis of mutant phenotype in two genetic populations, viz., W82×
and PI378692×
, the spotted leaf phenotype of
is controlled by a single recessive gene named
. The
locus governing mutant phenotype of
was first identified in 3.15 Mb genomic region on chromosome 04 through MutMap analysis, which was further verified and fine mapped by simple sequence repeat (SSR) marker-based genetic mapping. Genetic linkage analysis narrowed the genomic region (
locus) for mutant phenotype to a physical distance of ~76.23 kb. By searching against the Phytozome database, eight annotated candidate genes were found within the
region. qRT-PCR expression analysis revealed that, among these eight genes, only
showed highly significant expression levels in wild-type relative to the
mutant. However, sequencing data of the CDS region showed no nucleotide difference between
and its wild type within the coding regions of these genes but might be in the non-coding regions such as 5' or 3' UTR. Hence, the data of the present study are in favor of
being the possible candidate genes regulating the mutant phenotype of
. However, further validation is needed to prove this function of the gene as well as its role in PCD, which in turn would be helpful to understand the mechanism and pathways involved in HR disease resistance of soybean.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
We investigate the impact of international commodities trade on economic growth of five Asian countries including China over the last two decades. We examine the exports of eight commodity categories ...from 1995 to 2018. Firstly, we calculate trade entropy by considering the probability of exporting a product from one country to another. Our analysis reveals a significant increase in China’s trade entropy for manufactured goods primarily classified by material, compared to other products. The strong correlation between changes in gross domestic product (GDP) and trade volume in China indicates a remarkable contribution of manufactured goods to GDP during the studied period. Additionally, we establish a power law-scaling relation between GDP and product exports over time. Notably, the growth of manufactured goods from China exhibits a super-linear relationship with GDP.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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