Association of gene polymorphisms with body weight changes in prediabetic patients

Recent research has demonstrated that Type 2 Diabetes (T2D) risk is influenced by a number of common polymorphisms, including MC4R rs17782313, PPARG rs1801282, and TCF7L2 rs7903146. Knowledge of the association between these single nucleotide polymorphisms (SNPs) and body weight changes in different forms of prediabetes treatment is still limited. The aim of this study was to investigate the association of polymorphisms within the MC4R, PPARG, and TCF7L2 genes on the risk of carbohydrate metabolism disorders and body composition changes in overweight or obese patients with early carbohydrate metabolism disorders. From 327 patients, a subgroup of 81 prediabetic female patients (48.7 ± 14.8 years) of Eastern European descent participated in a 3-month study comprised of diet therapy or diet therapy accompanied with metformin treatment. Bioelectrical impedance analysis and genotyping of MC4R rs17782313, PPARG rs1801282, and TCF7L2 rs7903146 polymorphisms were performed. The MC4R CC and TCF7L2 TT genotypes were associated with increased risk of T2D (OR = 1.46, p = 0.05 and OR = 2.47, p = 0.006, respectively). PPARG CC homozygotes experienced increased weight loss; however, no additional improvements were experienced with the addition of metformin. MC4R TT homozygotes who took metformin alongside dietary intervention experienced increased weight loss and reductions in fat mass (p < 0.05). We have shown that the obesity-protective alleles (MC4R T and PPARG C) were positively associated with weight loss efficiency. Furthermore, we confirmed the previous association of the MC4R C and TCF7L2 T alleles with T2D risk. [Abstract copyright: © 2022. The Author(s).

Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.Peer reviewe

Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe

Analysis of molecular phenotypes in normal mucosa and colorectal cancer in embryonic anatomical parts of the colon

Background: Differences in the embryonic development of the colonic mucosa determine the physiological embryonic-anatomical asymmetry of its structure and can manifest themselves via different molecular phenotypes (expression profiles) of the colon segments. These molecular characteristics are hypothesized to determine differences in the carcinogenesis mechanisms and influence the prognosis of right- or left-sided colorectal cancer (CRC). Studies of the tumors molecular phenotypes depending on their localization may be of interest for assessment of the prognosis and choice of treatment for CRC. Aim: To perform comparative analysis of molecular phenotypes of the normal colonic mucosa and adenocarcinoma CRC tissues depending on the natural embryonic anatomic asymmetry of the colon. Materials and methods: We performed a retrospective study of molecular phenotypes (mRNA expression of 61 genes) from different embryonic-anatomical parts of healthy colon and CRC. The normal group included 254 samples of mucosa from three different parts of the colon from 74 healthy donors who had no cancer and no organic abnormalities of the colon, including 90 samples from the right colon, 116 from the left colon, and 48 from the rectum. The CRC group consisted of 154 samples of localized stage T1–4N0–2M0 adenocarcinoma from 154 patients who had not received neoadjuvant radio- and chemotherapy, including 40 samples from the right colon, 54 from the left colon, and 60 from the rectum. The relative mRNA abundance of 61 genes was assessed by reverse-transcriptase polymerase chain reaction. In both groups, the resulting expression phenotypes were compared between the anatomical parts of the colon. Statistical management of the data included the discriminant analysis with stepwise inclusion of variables. Results: Based on the assessment of the mRNA level of the studied genes, a discriminant model was built that allows for classification of the normal group samples according to their anatomic origin in the colon with an accuracy of 95.8%. The most significant (p 0.05) for classification are the following 19 genes: CCND1, SCUBE2, TERT, BAG1, NDRG, IL1b, IL2Ra, IL7, ESR1, TGFb, IGF1, MMP9, MMP11, PAPPA, CD45, CD69, TLR2, TLR4, LIFR. The discriminant model built for the CRC group included 27 genes and made it possible to differentiate samples from three parts of colon with an accuracy of 75.2%. A statistically significant (p 0.05) contribution to the samples differentiation by the discriminant model was made by the COX-2, BIRC5, LIFR, TPA, IL1b, MMP11, MMP7, and P16INK4A genes. When combining samples from the two groups into one model in accordance with their embryonic-anatomical origin, there was a clear separation of tumor tissue samples and healthy colonic mucosa in the discriminant function space. Conclusion: The analysis of CRC gene expression profiles using the discriminant model showed that genetic changes in the colonic mucosa in CRC flatten the molecular phenotypic boundaries of the embryonic-anatomical parts. These changes are specific to CRC, forming a particular “pathological” molecular phenotype

Native Gold and Unique Gold–Brannerite Nuggets from the Placer of the Kamenny Stream, Ozerninsky Ore Cluster (Western Transbakalia, Russia) and Possible Sources

We carried out a comprehensive study of native gold (morphology, composition, intergrowths, and microinclusions) from alluvial deposits of the Kamenny stream (Ozerninsky ore cluster, Western Transbaikalia, Russia). The study showed that there were four types of native gold, which differed significantly in their characteristics and probably had different primary sources from which placers were formed: gold–quartz, oxidized gold–sulfide, gold–silver, and zones of listvenites with copper–gold and gold–brannerite (Elkon-type). Particular attention was paid to the study of unique, both in size and in composition, gold–brannerite nuggets of the Kamenny stream. It was established that the gold in the gold–brannerite nuggets (GBNs) had wide variations in chemical composition and mineral features. According to them, there were five different fineness types of native gold: 750–800‰; 850–880‰; 880–920‰; 930–960‰; and 980–1000‰. The data obtained indicated a multistage, possibly polygenic, and probably polychronous formation of GBN gold–uranium mineralization. The first stage was the formation of early quartz–nasturanium–gold–W–rutile–magnetite association (Middle–Late Paleozoic age). The second was the crystallization of brannerite and the replacement of an earlier pitchblende with brannerite (Late Triassic (T3)–Early Jurassic (J1) age). The third was the formation of the hematite–barite–rutile–gold association as a result of deformation–hydrothermal processes, which was associated with the appearance of zones of alteration in brannerite in contact with native gold with 8–15 wt.% Ag. The fourth was hypergene or the low-temperature hydrothermal alteration of minerals of early stages with the development of iron hydroxides (goethite) with impurities of manganese, tellurium, arsenic, phosphorus, and other elements. The carbon isotopic composition of an organic substance indicates the involvement of a biogenic carbon source. In the OOC area, there were signs that the composition of the GBNs and the quartz–chlorite–K–feldspar-containing rocks corresponded to Elkon-type deposits

State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells

A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC–MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC–MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (<i>R</i>² ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015–2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126