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Biallelic loss of cyclin-dependent kinase 12 (CDK12) defines a metastatic castration-resistant prostate cancer (mCRPC) subtype. It remains unclear, however, whether CDK12 loss drives prostate cancer (PCa) development or uncovers pharmacologic vulnerabilities. Here, we show Cdk12 ablation in murine prostate epithelium is sufficient to induce preneoplastic lesions with lymphocytic infiltration. In allograft-based CRISPR screening, Cdk12 loss associates positively with Trp53 inactivation but negatively with Pten inactivation. Moreover, concurrent Cdk12/Trp53 ablation promotes proliferation of prostate-derived organoids, while Cdk12 knockout in Pten-null mice abrogates prostate tumor growth. In syngeneic systems, Cdk12/Trp53-null allografts exhibit luminal morphology and immune checkpoint blockade sensitivity. Mechanistically, Cdk12 inactivation mediates genomic instability by inducing transcription-replication conflicts. Strikingly, CDK12-mutant organoids and patient-derived xenografts are sensitive to inhibition or degradation of the paralog kinase, CDK13. We therein establish CDK12 as a bona fide tumor suppressor, mechanistically define how CDK12 inactivation causes genomic instability, and advance a therapeutic strategy for CDK12-mutant mCRPC.

Objective To investigate the changes of retinal nerve fiber layer (RNFL) thickness and superficial vascular density in patients with Parkinson's disease (PD), and analyze the correlation between the changes and disease severity. Methods Total 43 patients (76 eyes) with PD admitted to the Affiliated Hospital of North Sichuan Medical College from June 2021 to March 2022, and 45 patients (90 eyes) with normal neurological and visual functions from their family members were recruited as the control group. Optical coherence tomography angiography (OCTA) was used to measure RNFL thickness, retinal blood vessel length density and perfusion density, and the area and circumference of foveal avascular zone (FAZ). Disease severity was evaluated by modified Hoehn - Yahr staging, and motor function was evaluated by Unified Parkinson's Disease Rating Scale Ⅲ (UPDRS Ⅲ) in PD group. Pearson and partial correlation analyses were used to investigate the correlation between retinal parameters and PD severity. Results Comparison of OCTA related parameters between the 2 groups: RNFL thickness (t = - 6.424, P = 0.000), central length density (t = - 3.629, P = 0.000), inner ring length density (Z = - 2.846, P = 0.004) and central perfusion density (Z = - 2.703, P = 0.007) in the PD group were lower than those in the control group. Correlation analysis showed that RNFL thickness was negatively correlated with UPDRSⅢ score (r = - 0.625, P = 0.000). Conclusions RNFL thickness may be a potential indicator for early diagnosis and evaluation of the severity of PD.

At present, environmental issues are of concern to all countries, especially for developing countries, and education on waste sorting is urgent. However, it remains a challenge to improve students' learning achievement and engagement in environmental education. Researchers have pointed out the potential of digital games for promoting students' learning motivation. In addition, the two-tier testing mechanism has been recognized as an effective tool for correcting students' misconceptions and promoting their in-depth thinking. Therefore, this study proposed a two-tier testing-based digital gaming approach. To verify the effectiveness of the approach, a digital game was developed and a quasi-experiment was conducted. The participants were two classes of fifth graders, with one class as the experimental group using the two-tier test-based digital game and the other class as the control group learning with the conventional digital game. The results showed that the digital game-based learning with two-tier testing model was conducive to students' improved academic performance compared with the conventional digital game-based learning model, especially for students in the low-level group, who were able to make greater progress. In addition, the approach was effective in terms of reducing students' cognitive load and improving their flow experience.

In recent years,brain functional networks analysis using the resting state functional magnetic resonance imaging data has been widely used in computer-aided diagnosis tasks of various brain diseases.The graph convolutional network framework integrating clinical phenotypic measurements and brain functional networks improves the applicability of intelligent medical disease diagnosis models to the real world.However,the trustworthiness study is an important but still widely neglected component of disease diagnosis models based on brain functional networks.Adversarial attack techniques in medical machine learning can deceive models,which further leads to the security and trust issues of the model applied in clinical practice.Based on this,this paper proposes an adversarial attack method BFGCNattack on graph convolutional network for brain disease diagnosis,constructs a disease diagnosis model integrating clinical phenotypic measurements,and evaluates the robustness of brain functional networks-based disease diagnosis model in the face of adversarial attacks.Experimental results on the autism brain imaging data exchange dataset suggest that the models constructed using graph convolutional networks are vulnerable to the proposed adversarial attack.Even if only a small number(10%) of perturbations are performed,the model’s accuracy and classification margin significantly decrease,while the fooling rate significantly increases.

In order to provide accurate meteorological services for grain storage and ensure the safety of grain storage, based on the grain situation data of three grain depot in Jiamusi and the observation data of local meteorological stations from 2017 to 2020, the temperature, relative humidity and their correlation inside and outside the station and the granary were explored and analyzed by using mathematical statistics method. The results showed that the real-time temperature of meteorological stations was mostly lower than that outside the granary, and the two showed synchronous oscillation changes with little difference. R was above 0.996. The relative humidity of meteorological stations was higher than that outside the granary, and the two basically showed consistent changes. The relative humidity inside the granary was generally controlled below 70%. The daily maximum temperature of meteorological stations had a good correlation with the temperature in the warehouse and the maximum grain temperature in the surface layer, and R reached above 0.90. The change of warehouse temperature and the maximum grain temperature in the surface layer lagged behind the change of daily maximum temperature for about 1 d and 30 d, respectively. The regression equations of the daily maximum temperature of meteorological stations with the warehouse temperature and the maximum grain temperature in the surface layer were all positively correlated, and increased with the increase of the daily maximum temperature. The maximum grain temperature in other layers was less affected by temperature. According to the regression equation, the warehouse temperature and the maximum grain temperature in each layer were predicted, and the high temperature index of meteorological service in large warehouses was 28 ℃, and the ventilation and humidity service index was less than 70%.