Hub gene associated with prognosis in bladder cancer is a novel therapeutic target

Objective Bladder cancer is a clinical and social conundrum due to its high incidence and recurrence rate. It is urgent to find new targets for the diagnosis and treatment of bladder cancer and improve the prognosis and survival rate of bladder cancer patients. We sought a prognosis-related gene, built related models of evaluated bladder cancer and identified the function of the hub gene in bladder cancer. Methods We downloaded the data of bladder cancer patients from the TCGA database, and used differentially expressed genes (DEGs), copy number variation (CNV) and survival analysis to scan the hub genes associated with prognosis in bladder cancer. Then, multi-factor cox regression was used to obtain the bladder cancer prognosis correlation model. Then, we analyzed the relationship between the expression of hub gene and immune microenvironment of bladder cancer. The relationship between the expression of hub gene and prognosis in bladder cancer patients was verified by immunohistochemistry. Cell proliferation assay and drug sensitivity test in vivo were used to verify the inhibition of bladder cancer by targeted inhibitors. Results In bladder cancer, we screened seven hub genes (ACLY, CNP, NKIRAS2, P3H4, PDIA6, VPS25 and XPO1) associated with survival. Moreover, the multifactor regression model constructed with hub gene can well distinguish the prognosis of bladder cancer. Hub gene is mostly associated with immune microenvironment. Immunohistochemical results basically confirmed the importance of XPO1 in bladder cancer. Selinexor (an inhibitor of XPO1) could effectively inhibit the proliferation of bladder cancer in the cell proliferation experiments by CCK-8 assays and it could suppress the growth of bladder cancer in mouse bladder cancer model. Conclusions In this study, a prognostic model with seven hub genes has provided great help for the prognosis prediction of bladder cancer patients. And XPO1 is an important target affecting the prognosis of bladder cancer, and inhibition of XPO1 can effectively inhibit bladder cancer proliferation and growth

Superconductivity in a new layered cobalt oxychalcogenide Na6_{6}Co3_{3}Se6_{6}O3_{3} with a 3d5d^{5} triangular lattice

Unconventional superconductivity in bulk materials under ambient pressure is extremely rare among the 3$d$ transition-metal compounds outside the layered cuprates and iron-based family. It is predominantly linked to highly anisotropic electronic properties and quasi-two-dimensional (2D) Fermi surfaces. To date, the only known example of the Co-based exotic superconductor was the hydrated layered cobaltate, Na$_{x}$CoO$_{2}\cdot$ yH$_{2}$O, and its superconductivity is realized in the vicinity of a spin-1/2 Mott state. However, the nature of the superconductivity in these materials is still an active subject of debate, and therefore, finding new class of superconductors will help unravel the mysteries of their unconventional superconductivity. Here we report the discovery of unconventional superconductivity at $\sim$ 6.3 K in our newly synthesized layered compound Na$_{6}$Co$_{3}$Se$_{6}$O$_{3}$, in which the edge-shared CoSe$_{6}$ octahedra form [CoSe$_{2}$] layers with a perfect triangular lattice of Co ions. It is the first 3$d$ transition-metal oxychalcogenide superconductor with distinct structural and chemical characteristics. Despite its relatively low $T_{c}$, material exhibits extremely high superconducting upper critical fields, $\mu_{0}H_{c2}(0)$, which far exceeds the Pauli paramagnetic limit by a factor of 3 - 4. First-principles calculations show that Na$_{6}$Co$_{3}$Se$_{6}$O$_{3}$ is a rare example of negative charge transfer superconductor. This new cobalt oxychalcogenide with a geometrical frustration among Co spins, shows great potential as a highly appealing candidate for the realization of high-$T_{c}$ and/or unconventional superconductivity beyond the well-established Cu- and Fe-based superconductor families, and opened a new field in physics and chemistry of low-dimensional superconductors

A model worker: Multifaceted modulation of AUXIN RESPONSE FACTOR3 orchestrates plant reproductive phases

The key phytohormone auxin is involved in practically every aspect of plant growth and development. Auxin regulates these processes by controlling gene expression through functionally distinct AUXIN RESPONSE FACTORs (ARFs). As a noncanonical ARF, ARF3/ETTIN (ETT) mediates auxin responses to orchestrate multiple developmental processes during the reproductive phase. The arf3 mutation has pleiotropic effects on reproductive development, causing abnormalities in meristem homeostasis, floral determinacy, phyllotaxy, floral organ patterning, gynoecium morphogenesis, ovule development, and self-incompatibility. The importance of ARF3 is also reflected in its precise regulation at the transcriptional, posttranscriptional, translational, and epigenetic levels. Recent studies have shown that ARF3 controls dynamic shoot apical meristem (SAM) maintenance in a non-cell autonomous manner. Here, we summarize the hierarchical regulatory mechanisms by which ARF3 is regulated and the diverse roles of ARF3 regulating developmental processes during the reproductive phase

High-throughput estimation of plant height and above-ground biomass of cotton using digital image analysis and Canopeo

Plant height and above-ground biomass are important growth parameters that affect crop yield. Efficient and non-destructive technologies of crop phenotypic monitoring play crucial roles in intelligent farmland management. However, the feasibility of using these technologies to estimate cotton plant height and above-ground biomass has not been determined. This study proposed a low cost and high-throughput imaging method combined with Canopeo to extract the percentages of green color from high-definition digital images and establish a model to estimate the cotton plant height and above-ground biomass. The plant height and above-ground biomass field trials were conducted at two levels of irrigation (soil water content 70% ± 5% and 40%−45%, respectively) using 80 cotton genotypes. The linear fitting performed well across the different cotton genotypes (PH, R2 = 0.9829; RMSE = 2.4 cm; NRMSE = 11% and AGB, R2 = 0.9609; RMSE = 0.6 g / plant; and NRMSE = 5%), and two levels of irrigation (PH, R2 = 0.9604; RMSE = 2.15 cm; NRMSE = 6% and AGB, R2 = 0.9650; RMSE = 4.51 g/plant; and NRMSE = 17%). All reached a higher fitting degree. Additionally, the most comprehensive model to estimate the cotton plant height and above-ground biomass (Y = 0.4832*X + 11.04; Y = 0.4621*X − 0.3591) was determined using a simple linear regression modeling method. The percentages of green color positively correlated with plant height and above-ground biomass, and each model exhibited higher accuracy (R2 ≥ 0.8392, RMSE ≤ 0.0158, NRMSE ≤ 0.06%). Combining a high-definition digital camera with Canopeo enables the prediction of crop growth in the field. The simple linear regression modeling method and the most comprehensive model enable the rapid estimation of the cotton plant height and above-ground biomass. This method can also be used as a baseline to measure other important crop phenotypes

Long-term nitrogen fertilizer management for enhancing use efficiency and sustainable cotton (Gossypium hirsutum L.)

Optimal management of nitrogen fertilizer profoundly impacts sustainable development by influencing nitrogen use efficiency (NUE) and seed cotton yield. However, the effect of long-term gradient nitrogen application on the sandy loam soil is unclear. Therefore, we conducted an 8-year field study (2014–2021) using six nitrogen levels: 0 kg/hm2 (N0), 75 kg/hm2 (N1), 150 kg/hm2 (N2), 225 kg/hm2 (N3), 300 kg/hm2 (N4), and 375 kg/hm2 (N5). The experiment showed that 1) Although nitrogen application had insignificantly affected basic soil fertility, the soil total nitrogen (STN) content had decreased by 5.71%–19.67%, 6.67%–16.98%, and 13.64%–21.74% at 0-cm–20-cm, 20-cm–40-cm, and 40-cm–60-cm soil layers, respectively. 2) The reproductive organs of N3 plants showed the highest nitrogen accumulation and dry matter accumulation in both years. Increasing the nitrogen application rate gradually decreased the dry matter allocation ratio to the reproductive organs. 3) The boll number per unit area of N3 was the largest among all treatments in both years. On sandy loam, the most optional nitrogen rate was 190 kg/hm2–270 kg/hm2 for high seed cotton yield with minimal nitrogen loss and reduced soil environment pollution

Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China

The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization

Legislative Documents

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