Clinical significance and biological function of interferon regulatory factor 1 in non-small cell lung cancer

The clinical application and biological function of interferon regulatory factor 1 (IRF1) in non-small cell lung cancer (NSCLC) patients undergoing chemoimmunotherapy remain elusive. The aim of this study was to investigate the predictive and prognostic significance of IRF1 in NSCLC patients. We employed the cBioPortal database to predict frequency changes in IRF1 and explore its target genes. Bioinformatic methods were utilized to analyze the relationship between IRF1 and immune regulatory factors. Retrospective analysis of clinical samples was conducted to assess the predictive and prognostic value of IRF1 in chemoimmunotherapy. Additionally, A549 cells with varying IRF1 expression levels were constructed to investigate its effects on NSCLC cells, while animal experiments were performed to study the role of IRF1 in vivo. Our findings revealed that the primary mutation of IRF1 is deep deletion and it exhibits a close association with immune regulatory factors. KRAS and TP53 are among the target genes of IRF1, with interferon and IL-2 being the predominantly affected pathways. Clinically, IRF1 levels significantly correlate with the efficacy of chemoimmunotherapy. Patients with high IRF1 levels exhibited a median progression-free survival (mPFS) of 9.5 months, whereas those with low IRF1 levels had a shorter mPFS of 5.8 months. IRF1 levels positively correlate with PD-L1 distribution and circulating IL-2 levels. IL-2 enhances the biological function of IRF1 and recapitulates its role in vivo in the knockdown group. Therefore, IRF1 may possess predictive and prognostic value for chemoimmunotherapy in NSCLC patients through the regulation of the IL-2 inflammatory pathway

Evolution and Association Analysis of Ghd7 in Rice

Plant height, heading date, and yield are the main targets for rice genetic improvement. Ghd7 is a pleiotropic gene that controls the aforementioned traits simultaneously. In this study, a rice germplasm collection of 104 accessions (Oryza sativa) and 3 wild rice varieties (O.rufipogon) was used to analyze the evolution and association of Ghd7 with plant height, heading date, and yield. Among the 104 accessions, 76 single nucleotide polymorphisms (SNPs) and six insertions and deletions were found within a 3932-bp DNA fragment of Ghd7. A higher pairwise π and θ in the promoter indicated a highly diversified promoter of Ghd7. Sixteen haplotypes and 8 types of Ghd7 protein were detected. SNP changes between haplotypes indicated that Ghd7 evolved from two distinct ancestral gene pools, and independent domestication processes were detected in indica and japonica varietals respectively. In addition to the previously reported premature stop mutation in the first exon of Ghd7, which caused phenotypic changes of multiple traits, we found another functional C/T mutation (SNP S_555) by structure-based association analysis. SNP S_555 is located in the promoter and was related to plant height probably by altering gene expression. Moreover, another seven SNP mutations in complete linkage were found to be associated with the number of spikelets per panicle, regardless of the photoperiod. These associations provide the potential for flexibility of Ghd7 application in rice breeding programs

Gains in QTL Detection Using an Ultra-High Density SNP Map Based on Population Sequencing Relative to Traditional RFLP/SSR Markers

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs

Can Arable Land Alone Ensure Food Security? The Concept of Arable Land Equivalent Unit and Its Implications in Zhoushan City, China

The requisition–compensation balance of farmlands (RCBF) is a strict Chinese policy that aims to ensure food security. However, the process of supplementing arable land has substantially damaged the ecological environment through the blind development of grasslands, woodlands, and wetlands to supplement arable land. Can arable land alone ensure food security? To answer this question, this study introduced the concepts of arable land equivalent unit (ALEU) and food equivalent unit (FEU) based on the idea of food security. Zhoushan City in Zhejiang Province, China was selected as the research area. This study analyzed the ALEU supply and demand capabilities in the study area and presented the corresponding policy implications for the RCBF improvement. The results showed that the proportion of ALEU from arable land and waters for aquaculture is from 46:54 in 2009 to 31:69 in 2015, thereby suggesting that aquaculture waters can also be important in food security. Under three different living standards (i.e., adequate food and clothing, well-off, and affluence), ALEU from arable land can barely meet the needs of the permanent resident population in the study area. However, ALEU from aquaculture waters can provide important supplementation. Therefore, we suggest that food supply capability from land types other than the arable land be taken seriously. Furthermore, RCBF can be improved with ALEU as core of the balance

What Drives Farmers to Participate in Rural Environmental Governance? Evidence from Villages in Sandu Town, Eastern China

Understanding farmers’ participation is crucial for achieving an effective impact on rural living environmental governance and promoting sustainable development. Taking Sandu Town in eastern China as a case study, in-depth semi-structured interviews with farmers, village cadres, and town managers were conducted in this study. Then, a conceptual framework incorporating comprehensive factors is presented to analyze the driving factors and mechanisms of farmer participation in rural domestic waste management. The results show that farmers’ participation in pro-environmental actions is a response to an integrated network of both internal and external factors. Life inertia, loss of personal interests, and objective conditions are the barriers to farmers deciding to participate. Meanwhile, environmental awareness can increase farmers’ internal motivations, and factors such as household benefits, social-cultural influences, and appraisal systems, including household possession protection, very low economic costs, better life experiences, demonstrations from society, “following the crowd”, peer pressure, and reward and criticism measures, are the external forces that mobilize farmers to participate in rural environmental governance. Policy recommendations are proposed based on the findings

Mapping Cropland Abandonment in Mountainous Areas in China Using the Google Earth Engine Platform

Knowledge about the spatial-temporal pattern of cropland abandonment is the premise for the management of abandoned croplands. Traditional mapping approaches of abandoned croplands usually utilize a multi-date classification-based land cover change trajectory. It requires quality training samples for land cover classification at each epoch, which is challenging in regions of smallholder agriculture in the absence of high-resolution imagery. Facing these challenges, a theoretical model is proposed to recognize abandoned croplands based on post-abandonment secondary succession. It applies the continuous change detection and classification (CCDC) temporal segmentation algorithm to Landsat time series (1986~2021) to obtain disjoint segments, representing croplands’ status. The post-abandonment secondary succession showing a greening trend is recognized using NDVI-based harmonic analysis, so as to capture its preceding abandonment. This algorithm is applied to a mountainous area in southwest China, where cropland abandonments are widespread. Validation based on stratified random samples referenced by a vegetation index time series and satellite images shows that the detected abandoned croplands have user accuracy, producer accuracy and an F1 score ranging from 43% to 71%, with variation among abandonment year. The study area has a potential cropland extent of 22,294 km2, within which 9252 km2 of the cropland was abandoned. The three peak years of abandonment were 1994, 2000, and 2011. The algorithm is suitable to be applied to large-scale mapping due to its automatic manner

What Drives Farmers to Participate in Rural Environmental Governance? Evidence from Villages in Sandu Town, Eastern China

Understanding farmers’ participation is crucial for achieving an effective impact on rural living environmental governance and promoting sustainable development. Taking Sandu Town in eastern China as a case study, in-depth semi-structured interviews with farmers, village cadres, and town managers were conducted in this study. Then, a conceptual framework incorporating comprehensive factors is presented to analyze the driving factors and mechanisms of farmer participation in rural domestic waste management. The results show that farmers’ participation in pro-environmental actions is a response to an integrated network of both internal and external factors. Life inertia, loss of personal interests, and objective conditions are the barriers to farmers deciding to participate. Meanwhile, environmental awareness can increase farmers’ internal motivations, and factors such as household benefits, social-cultural influences, and appraisal systems, including household possession protection, very low economic costs, better life experiences, demonstrations from society, “following the crowd”, peer pressure, and reward and criticism measures, are the external forces that mobilize farmers to participate in rural environmental governance. Policy recommendations are proposed based on the findings

Generation of an induced pluripotent stem cell lines NSHDMUi001-A from patients with type 2 diabetes

Type 2 diabetes mellitus (T2DM) is common in China, and its aetiology and pathogenesis are still unclear. We reprogrammed pEP4EO2SEN2K and pEP4EO2SET2K, pCEP4-M2L was electrotransfected in T2DM patients with pEP4EO2SEN2K, and pCEP4-M2L was electrotransfected in T2DM patients expressing the OCT4, SOX2, NANOG, LIN28, c-MYC, KLF4, and SV40LT transcription factors to obtain induced pluripotent stem cells (iPSCs). The obtained iPSCs have been verified to have pluripotency, normal karyotype and differentiation potential; therefore, these cells can be used in the study of disease pathophysiology and drug development to create new therapeutic targets for T2DM and associated central nervous system damage

Changes in crop mix and the effects on agricultural carbon emissions in China

Changes in crop mix significantly affect the carbon emissions from cropping systems, thus underscoring their importance in achieving sustainable agriculture development. This article aims to offer new insights into the relationship between crop mix changes and carbon emissions from cropping systems. Based on provincial statistical data on crop production, this study analyzed the spatiotemporal dynamics of crop mix and the subsequent effect on the carbon emissions from cropping systems in China from 2005 to 2020. The crop-mix type identification rules, emission-factor approach, and grey incidence analysis were applied. The results showed clear changes in crop mix and obvious transitions from grain crops to cash crops in southern provinces. Among crops, the abundance of maize, vegetables, and melons increased remarkably. Besides, the carbon emission intensity (CI) from cropping systems generally showed an upward trend in most provinces, with a spatial pattern of gradual decrease from southeast to northwest. The changes in CI were most closely correlated with rice, maize, vegetables, and melon, with coefficients of 0.808, 0.773, 0.814, and 0.792, respectively. Additionally, the growth of maize and vegetables ratios played a significant role in the CI increases in most provinces. To optimize crop cultivation and mitigate carbon emissions, possible strategies including rational crop production layout, land transfer, and clean production technologies were proposed.</p