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Background: The population in Jiamusi has been reported to have the highest prevalence of colorectal cancer (CRC) in China. The genetic causal-effect for this occurrence among the residents remains unclear. Given the long cold seasons with people wearing more clothes and reduced UV exposure, we aimed to study the association between the vitamin D metabolism-related gene CYP24A1 polymorphism and CRC susceptibility. Method: A case-control study was conducted that included 168 patients with CRC and 710 age-matched healthy individuals as the control group. Plausible susceptible variations were sought and clinical phenotypic-genotype association analysis was performed. Results: Overall, two CYP24A1 polymorphisms, rs6013905 AX (P = 0.02, OR = 1.89, 95%CI: 1.09–3.29) and rs2762939 GX (P = 0.02, OR = 1.52, 95%CI: 1.08–2.13) were significantly associated with CRC in the Jiamusi population. In the female group, three CYP24A1 polymorphisms, rs6013905 AX (P = 0.04, OR = 2.59, 95%CI: 1.03–6.49), rs2762939 GX (P = 0.01, OR = 2.35, 95%CI: 1.25–4.42), and rs6068816 GG (P = 0.05, OR = 1.89, 95%CI: 0.99–3.59) carriers were significantly associated with CRC. In clinical phenotypic-genotype analysis, rs6013905 GG (P = 0.05, OR = 4.00, 95%CI: 0.92–17.48) and rs2762939 GX (P = 0.03, OR = 4.87, 95%CI: 1.00–23.69) carriers were significantly associated with poorly differentiated CRC, while CYP24A1 rs6068816 AX was significantly associated with the tumor type (P = 0.02, OR = 2.08, 95%CI: 1.10–3.96) and location (P = 0.04, OR = 2.24, 95%CI: 1.05–4.77). Conclusion: CYP24A1 gene polymorphism may be a genetic risk factor attributable to the highest prevalence of CRC in Jiamusi people. Individuals with CYP24A1 gene polymorphism may have an increased barrier for vitamin D absorption, thus contributing to the risk of CRC development. [ABSTRACT FROM AUTHOR]

Limited research exists regarding the relationship between fasting plasma C-peptide levels and sarcopenia. As a result, our study aimed to examine this association in elderly Chinese diabetic patients. This cross-sectional study included 288 elderly patients with diabetes mellitus from the Fourth People's Hospital in Guiyang who were enrolled prospectively between March 2020 and February 2023. The independent variable of interest was fasting plasma C-peptide, while the dependent variable was sarcopenia. Data on several covariates, including demographic factors, lifestyle habits, co-morbidities, anthropometric indicators, and laboratory indicators, were also collected. Of the 288 participants, 27.43% (79/288) had sarcopenia. After adjusting for potential confounding variables, we found a U-shaped association between fasting plasma C-peptide levels and sarcopenia, with inflection points identified at approximately 774 pmol/L and 939 mmol/L. Within the range of 50–744 pmol/L, each 100 pmol/L increase in CysC was associated with a 37% decrease in the odds of sarcopenia (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.49 to 0.83; P < 0.001). Additionally, within the range of 939–1694 pmol/L, each 100 pmol/L increase in fasting plasma C-peptide was associated with a 76% increase in the odds of sarcopenia (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.11 to 2.81; P = 0.017). Our study revealed a U-shaped association between fasting plasma C-peptide levels and the likelihood of sarcopenia, with lower risk in the range of 774–939 pmol/L. These findings may assist in the development of more effective prevention and treatment strategies for sarcopenia in elderly diabetic patients. [ABSTRACT FROM AUTHOR]

Climate change and variability are projected to alter the geographic suitability of lands for crops cultivation. Accurately predicting changes in the potential current and future land suitability distribution dynamics of wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) crops due to climate change scenarios is critical to adapting and mitigating the impacts of bioclimatic changes, and plays a significant role in securing food security in East Asia region. This study compiled large datasets of wheat, soybean and rice occurrence locations from GBIF and 19 bioclimatic variables obtained from the WorldClim database that affect crops growth. We recognized potential future suitable distribution regions for crops under the one socioeconomic pathway, (SSP585) for 2021–2040 and 2041–2060, using the MaxEnt model. The accuracy of the MaxEnt was highly significant with mean AUC values ranging from 0.833 to 0.882 for all models evaluated. The jackknife test revealed that for wheat, Bio4 and Bio12 contributed 17.6% and 12.6%, for soybean Bio10 and Bio12 contributed 15.6% and 49.5%, while for rice Bio12 and Bio14 contributed 12.9% and 36.0% to the MaxEnt model. In addition, cultivation aptitude for wheat, soybean, and rice increased in southeast China, North Korea, South Korea, and Japan, while decreasing in Mongolia and northwest China. Climate change is expected to increase the high land suitability for wheat, soybean, and rice in East Asia. Simulation results indicate an average decrease of unsuitable areas of -98.5%, -41.2% and -36.3% for wheat, soybean and rice from 2060 than that of current land suitability. In contrast, the high land suitable for wheat, soybean and rice cultivation is projected to increase by 75.1%, 68.5% and 81.9% from 2060 as compared with current. The findings of this study are of utmost importance in the East Asia region as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain crops distribution under future climates. Although the risks of wheat, soybean and rice cultivation may be significantly higher in the future because of high temperatures, heat waves, and droughts caused by climate change. [ABSTRACT FROM AUTHOR]

microRNAs (miRNAs) are small non-coding RNAs related to a number of complicated biological processes. A growing body of studies have suggested that miRNAs are closely associated with many human diseases. It is meaningful to consider disease-related miRNAs as potential biomarkers, which could greatly contribute to understanding the mechanisms of complex diseases and benefit the prevention, detection, diagnosis and treatment of extraordinary diseases. In this study, we presented a novel model named Graph Convolutional Autoencoder for miRNA-Disease Association Prediction (GCAEMDA). In the proposed model, we utilized miRNA-miRNA similarities, disease-disease similarities and verified miRNA-disease associations to construct a heterogeneous network, which is applied to learn the embeddings of miRNAs and diseases. In addition, we separately constructed miRNA-based and disease-based sub-networks. Combining the embeddings of miRNAs and diseases, graph convolution autoencoder (GCAE) is utilized to calculate association scores of miRNA-disease on two sub-networks, respectively. Furthermore, we obtained final prediction scores between miRNAs and diseases by adopting an average ensemble way to integrate the prediction scores from two types of subnetworks. To indicate the accuracy of GCAEMDA, we applied different cross validation methods to evaluate our model whose performance were better than the state-of-the-art models. Case studies on a common human diseases were also implemented to prove the effectiveness of GCAEMDA. The results demonstrated that GCAEMDA were beneficial to infer potential associations of miRNA-disease. Author summary: Numerous studies have demonstrated that miRNAs are closely related to several common human diseases, so observing unverified associations between miRNAs and diseases is conducive to the diagnose and treatment of complex diseases. Considerable models proposed to infer potential miRNA-disease associations have made the prediction more effective and productive. We constructed GCAEMDA model to acquire more accuracy prediction result by integrating graph convolutional network and autoencoder to make prediction based on multi-source miRNA and disease information. The five-fold cross validation and global leave-one-out cross validation were implemented to evaluate the performance of our model. Consequently, GCAEMDA reached AUCs of 0.9415 and 0.9505 respectively that were distinctly higher than AUCs of other comparative models. Furthermore, we carried out case studies on lung neoplasms and breast neoplasms to demonstrate the practical application of the model, 47 and 47 of top-50 candidate miRNAs were confirmed by experimental reports. In summary, GCAEMDA could be considered as an effective and accuracy model to reveal relationship of miRNAs and diseases. [ABSTRACT FROM AUTHOR]

miRNAs belong to small non-coding RNAs that are related to a number of complicated biological processes. Considerable studies have suggested that miRNAs are closely associated with many human diseases. In this study, we proposed a computational model based on Similarity Constrained Matrix Factorization for miRNA-Disease Association Prediction (SCMFMDA). In order to effectively combine different disease and miRNA similarity data, we applied similarity network fusion algorithm to obtain integrated disease similarity (composed of disease functional similarity, disease semantic similarity and disease Gaussian interaction profile kernel similarity) and integrated miRNA similarity (composed of miRNA functional similarity, miRNA sequence similarity and miRNA Gaussian interaction profile kernel similarity). In addition, the L2 regularization terms and similarity constraint terms were added to traditional Nonnegative Matrix Factorization algorithm to predict disease-related miRNAs. SCMFMDA achieved AUCs of 0.9675 and 0.9447 based on global Leave-one-out cross validation and five-fold cross validation, respectively. Furthermore, the case studies on two common human diseases were also implemented to demonstrate the prediction accuracy of SCMFMDA. The out of top 50 predicted miRNAs confirmed by experimental reports that indicated SCMFMDA was effective for prediction of relationship between miRNAs and diseases. Author summary: Considerable studies have suggested that miRNAs are closely associated with many human diseases, so predicting potential associations between miRNAs and diseases can contribute to the diagnose and treatment of diseases. Several models of discovering unknown miRNA-diseases associations make the prediction more productive and effective. We proposed SCMFMDA to obtain more accuracy prediction result by applying similarity network fusion to fuse multi-source disease and miRNA information and then utilizing similarity constrained matrix factorization to make prediction based on biological information. The global Leave-one-out cross validation and five-fold cross validation were applied to evaluate our model. Consequently, SCMFMDA could achieve AUCs of 0.9675 and 0.9447 that were obviously higher than previous computational models. Furthermore, we implemented case studies on significant human diseases including colon neoplasms and lung neoplasms, 47 and 46 of top-50 were confirmed by experimental reports. All results proved that SCMFMDA could be regard as an effective way to discover unverified connections of miRNA-disease. [ABSTRACT FROM AUTHOR]

Dysregulation of CDK8 (Cyclin-Dependent Kinase 8) and its regulatory partner CycC (Cyclin C), two subunits of the conserved Mediator (MED) complex, have been linked to diverse human diseases such as cancer. Thus, it is essential to understand the regulatory network modulating the CDK8-CycC complex in both normal development and tumorigenesis. To identify upstream regulators or downstream effectors of CDK8, we performed a dominant modifier genetic screen in Drosophila based on the defects in vein patterning caused by specific depletion or overexpression of CDK8 or CycC in developing wing imaginal discs. We identified 26 genomic loci whose haploinsufficiency can modify these CDK8- or CycC-specific phenotypes. Further analysis of two overlapping deficiency lines and mutant alleles led us to identify genetic interactions between the CDK8-CycC pair and the components of the Decapentaplegic (Dpp, the Drosophila homolog of TGFβ) signaling pathway. We observed that CDK8-CycC positively regulates transcription activated by Mad (Mothers against dpp), the primary transcription factor downstream of the Dpp/TGFβ signaling pathway. CDK8 can directly interact with Mad in vitro through the linker region between the DNA-binding MH1 (Mad homology 1) domain and the carboxy terminal MH2 (Mad homology 2) transactivation domain. Besides CDK8 and CycC, further analyses of other subunits of the MED complex have revealed six additional subunits that are required for Mad-dependent transcription in the wing discs: Med12, Med13, Med15, Med23, Med24, and Med31. Furthermore, our analyses confirmed the positive roles of CDK9 and Yorkie in regulating Mad-dependent gene expression in vivo. These results suggest that CDK8 and CycC, together with a few other subunits of the MED complex, may coordinate with other transcription cofactors in regulating Mad-dependent transcription during wing development in Drosophila. Author summary: CDK8 and its dedicated partner CycC are conserved subunits of the Mediator complex that bridges transcription factors with RNA Polymerase II in eukaryotes. Here we explore the function and regulation of the CDK8-CycC pair in Drosophila by performing a dominant modifier genetic screen based on wing vein patterning defects caused by specific alteration of CDK8-CycC activities. We have observed that multiple components of the Dpp/TGFβ signaling pathway genetically interact with CDK8-CycC. CDK8 and CycC positively regulate gene expression activated by Mad, the key transcription factor downstream of Dpp/TGFβ signaling, and CDK8 can directly interact with the linker region of the Mad protein. We also identify additional, but not all, subunits of the Mediator complex that play positive roles in regulating Mad-dependent gene expression. Given the fundamental role of Dpp/TGFβ signaling in regulating development and its misregulation in a variety of diseases, understanding how Mad/Smad interacts with the Mediator complex may have broad implications in understanding the pathogenesis of these diseases. [ABSTRACT FROM AUTHOR]

microRNAs are endogenous small regulatory RNAs that modulate myriad biological processes by repressing target gene expression in a sequence-specific manner. Here we show that the conserved miRNA miR-34 regulates innate immunity and ecdysone signaling in Drosophila. miR-34 over-expression activates antibacterial innate immunity signaling both in cultured cells and in vivo, and flies over-expressing miR-34 display improved survival and pathogen clearance upon Gram-negative bacterial infection; whereas miR-34 knockout animals are defective in antibacterial defense. In particular, miR-34 achieves its immune-stimulatory function, at least in part, by repressing the two novel target genes Dlg1 and Eip75B. In addition, our study reveals a mutual repression between miR-34 expression and ecdysone signaling, and identifies miR-34 as a node in the intricate interplay between ecdysone signaling and innate immunity. Lastly, we identify cis-regulatory genomic elements and trans-acting transcription factors required for optimal ecdysone-mediated repression of miR-34. Taken together, our study enriches the repertoire of immune-modulating miRNAs in animals, and provides new insights into the interplay between steroid hormone signaling and innate immunity. [ABSTRACT FROM AUTHOR]

Variation of soil organic carbon (SOC) and its major constraints in large spatial scale are critical for estimating global SOC inventory and projecting its future at environmental changes. By analyzing SOC and its environment at 210 sites in uncultivated land along a 3020km latitudinal transect in East Central Asia, we examined the effect of environmental factors on the dynamics of SOC. We found that SOC changes dramatically with the difference as high as 5 times in north China and 17 times in Mongolia. Regardless, C:N remains consistent about 12. Path analysis indicated that temperature is the dominant factor in the variation of SOC with a direct effect much higher than the indirect one, the former breaks SOC down the year round while the latter results in its growth mainly via precipitation in the winter half year. Precipitation helps accumulate SOC, a large part of the effect, however, is taken via temperature. NH4+-N and topography also affect SOC, their roles are played primarily via climatic factors. pH correlates significantly with SOC, the effect, however, is taken only in the winter months, contributing to the decay of SOC primarily via temperature. These factors explained as much as 79% of SOC variations, especially in the summer months, representing the major constraints on the SOC stock. Soil texture gets increasingly fine southward, it does not, however, constitute an apparent factor. Our results suggested that recent global warming should have been adversely affecting SOC stock in the mid-latitude as temperature dominates other factors as the constraint. [ABSTRACT FROM AUTHOR]

The steroid hormone ecdysone and its receptor (EcR) play critical roles in orchestrating developmental transitions in arthropods. However, the mechanism by which EcR integrates nutritional and developmental cues to correctly activate transcription remains poorly understood. Here, we show that EcR-dependent transcription, and thus, developmental timing in Drosophila, is regulated by CDK8 and its regulatory partner Cyclin C (CycC), and the level of CDK8 is affected by nutrient availability. We observed that cdk8 and cycC mutants resemble EcR mutants and EcR-target genes are systematically down-regulated in both mutants. Indeed, the ability of the EcR-Ultraspiracle (USP) heterodimer to bind to polytene chromosomes and the promoters of EcR target genes is also diminished. Mass spectrometry analysis of proteins that co-immunoprecipitate with EcR and USP identified multiple Mediator subunits, including CDK8 and CycC. Consistently, CDK8-CycC interacts with EcR-USP in vivo; in particular, CDK8 and Med14 can directly interact with the AF1 domain of EcR. These results suggest that CDK8-CycC may serve as transcriptional cofactors for EcR-dependent transcription. During the larval–pupal transition, the levels of CDK8 protein positively correlate with EcR and USP levels, but inversely correlate with the activity of sterol regulatory element binding protein (SREBP), the master regulator of intracellular lipid homeostasis. Likewise, starvation of early third instar larvae precociously increases the levels of CDK8, EcR and USP, yet down-regulates SREBP activity. Conversely, refeeding the starved larvae strongly reduces CDK8 levels but increases SREBP activity. Importantly, these changes correlate with the timing for the larval–pupal transition. Taken together, these results suggest that CDK8-CycC links nutrient intake to developmental transitions (EcR activity) and fat metabolism (SREBP activity) during the larval–pupal transition. [ABSTRACT FROM AUTHOR]

c-Met is over-expressed in hepatocellular carcinoma(HCC) but is absent or expressed at low levels in normal tissues. Therefore we generated a novel conjugate of a human anti-c-Met Fab fragment (MetFab) with doxorubicin (DOX) and assessed whether it had targeted antitumor activity against HCC and reduced the side-effects of DOX. The MetFab was screened from human phage library, conjugated with DOX via chemical synthesis, and the conjugation MetFab-DOX was confirmed by HPLC. The drug release patterns, the binding efficacy, and cellular distribution of MetFab-DOX were assessed. MetFab-DOX was stable at pH7.2 PBS while release doxorubicin quickly at pH4.0, the binding efficacy of MetFab-DOX was similarly as MetFab, and the cellular distribution of the MetFab-DOX is distinct from free DOX. The cytotoxicity of MetFab-DOX was analyzed by the MTT method and the nude mouse HCC model. The MetFab-DOX demonstrated cytotoxic effects on c-Met expressing-tumor cells, but not on the cells without c-Met expression. MetFab-DOX exerted anti-tumor effect and significantly reduced the side effect of free DOX in mice model. Furthermore, the localization of conjugate was confirmed by immunofluorescence staining of tumor tissue sections and optical tumor imaging, respectively, and the tissue-distribution of drug was compared between free DOX and MetFab-DOX treatment by spectrofluorometer. MetFab-DOX can localize to the tumor tissue, and the concentration of doxorubicin in the tumor was higher after MetFab-DOX administration than after DOX administration. In summary, MetFab-DOX can target c-Met expressing HCC cells effectively and have obvious antitumor activity with decreased side-effects in preclinical models of HCC. [ABSTRACT FROM AUTHOR]