TRIM24 is critical for the cellular response to DNA double-strand breaks through regulating the recruitment of MRN complex

The MRE11-RAD50-NBS1 (MRN) complex plays a crucial role in DNA double-strand breaks (DSBs) sensing and initiation of signaling cascades. However, the precise mechanisms by which the recruitment of MRN complex is regulated has yet to be elucidated. Here, we identified TRIpartite motif-containing protein 24 (TRIM24), a protein considered as an oncogene overexpressed in cancers, as a novel signaling molecule in response to DSBs. TRIM24 is essential for DSBs-induced recruitment of MRN complex and activation of downstream signaling. In the absence of TRIM24, MRN mediated DSBs repair is remarkably diminished. Mechanistically, TRIM24 is phosphorylated by ataxia-telangiectasia mutated (ATM) and then recruited to DSBs sites, facilitating the accumulation of the MRN components to chromatin. Depletion of TRIM24 sensitizes human hepatocellular carcinoma cells to cancer therapy agent-induced apoptosis and retards the tumor growth in a subcutaneous xenograft tumor mouse model. Together, our data reveal a novel function of TRIM24 in response to DSBs through regulating the MRN complex, which suggests that TRIM24 may be a potential therapeutic molecular target for tumor treatment.

Perturbed autophagy intervenes systemic lupus erythematosus by active ingredients of traditional Chinese medicine

Systemic lupus erythematosus (SLE) is a common multisystem, multiorgan heterozygous autoimmune disease. The main pathological features of the disease are autoantibody production and immune complex deposition. Autophagy is an important mechanism to maintain cell homeostasis. Autophagy functional abnormalities lead to the accumulation of apoptosis and induce the autoantibodies that result in immune disorders. Therefore, improving autophagy may alleviate the development of SLE. For SLE, glucocorticoids or immunosuppressive agents are commonly used in clinical treatment, but long-term use of these drugs causes serious side effects in humans. Immunosuppressive agents are expensive. Traditional Chinese medicines (TCMs) are widely used for immune diseases due to their low toxicity and few side effects. Many recent studies found that TCM and its active ingredients affected the pathological development of SLE by regulating autophagy. This article explains how autophagy interferes with immune system homeostasis and participates in the occurrence and development of SLE. It also summarizes several studies on TCM-regulated autophagy intervention in SLE to generate new ideas for basic research, the development of novel medications, and the clinical treatment of SLE.

A mechanism-based fate model of pesticide solutions on the plant surface under aerial application

Pesticide residues on plant surfaces are a primary source of pesticide bioaccumulation in crops. In this context, we propose a mechanism-based model for understanding the pesticide fate on the plant surface following aerial application, taking into account fate modelling of the pesticide spray solution on the plant surface. Using chlorothalonil as an example, the simulation results revealed that the spray solution dissipated rapidly after aerial application, resulting in the formation of a saturated pesticide solution, which facilitated the diffusion process of the pesticide residue from the plant surface into the peel tissue. The proposed model generated higher simulated residue concentrations in the peel or pulp than the current model, owing to the proposed model's assumption of rapid dissipation of the spray solution. This indicated that the proposed model specified the influence of the spray solution on the plant's exposure to residues via the surface deposition pathway, whereas the current modelling approach presented a generic estimate of the residue dissipation on the plant surface that linked to the residue's fate in the soil.

A Tiny Model for Fast and Precise Ship Detection via Feature Channel Pruning

It is of great significance to accurately detect ships on the ocean. To obtain higher detection performance, many researchers use deep learning to identify ships from images instead of traditional detection methods. Nevertheless, the marine environment is relatively complex, making it quite difficult to determine features of ship targets. In addition, many detection models contain a large amount of parameters, which is not suitable to deploy in devices with limited computing resources. The two problems restrict the application of ship detection. In this paper, firstly, an SAR ship detection dataset is built based on several databases, solving the problem of a small number of ship samples. Then, we integrate the SPP, ASFF, and DIOU-NMS module into original YOLOv3 to improve the ship detection performance. SPP and ASFF help enrich semantic information of ship targets. DIOU-NMS can lower the false alarm. The improved YOLOv3 has 93.37% mAP, 4.11% higher than YOLOv3 on the self-built dataset. Then, we use the MCP method to compress the improved YOLOv3. Under the pruning ratio of 80%, the obtained compressed model has only 6.7 M parameters. Experiments show that MCP outperforms NS and ThiNet. With the size of 26.8 MB, the compact model can run at 15 FPS on an NVIDIA TX2 embedded development board, 4.3 times faster than the baseline model. Our work will contribute to the development and application of ship detection on the sea.

Deep Reinforcement Learning for the Detection of Abnormal Data in Smart Meters

The rapidly growing power data in smart grids have created difficulties in security management. The processing of large-scale power data with the use of artificial intelligence methods has become a hotspot research topic. Considering the early warning detection problem of smart meters, this paper proposes an abnormal data detection network based on Deep Reinforcement Learning, which includes a main network and a target network composed of deep learning networks. This work uses the greedy policy algorithm to find the action of the maximum value of Q based on the Q-learning method to obtain the optimal calculation policy. It also uses the reward value and discount factor to optimize the target value. In particular, this study uses the fuzzy c-means method to predict the future state information value, which improves the computational accuracy of the Deep Reinforcement Learning model. The experimental results show that compared with the traditional smart meter data anomaly detection method, the proposed model improves the accuracy of meter data anomaly detection.

Development and validation of a prognostic nomogram for patients with stage II colon mucinous adenocarcinoma

PURPOSE

Mucinous histology is generally considered as a risk factor of prognosis in stage II colon cancer, but there is no appropriate model for prognostic evaluation and treatment decision in patients with stage II colon mucinous adenocarcinoma (C-MAC) Thus, it is urgent to develop a comprehensive, individualized evaluation tool to reflect the heterogeneity of stage II C-MAC.

METHODS

Patients with stage II C-MAC who underwent surgical treatment in the Surveillance, Epidemiology, and End Results Program were enrolled and randomly divided into training cohort (70%) and internal validation cohort (30%). Prognostic predictors which were determined by univariate and multivariate analysis in the training cohort were included in the nomogram. The calibration curves, decision curve analysis, X-tile analysis, and Kaplan-Meier curve of the nomogram were validated in the internal validation cohort.

RESULTS

Three thousand seven hundred sixty-two patients of stage II C-MAC were enrolled. The age, pathological T (pT) stage, tumor number, serum carcinoembryonic antigen (CEA), and perineural invasion (PNI) were independent predictors of overall survival (OS), which were used to establish a nomogram. Calibration curves of the nomogram indicated good consistency between nomogram prediction and actual survival for 1-, 3- and 5-year OS. Besides, patients with stage II C-MAC could be divided into high-, middle-, and low-risk subgroups by the nomogram. Further subgroup analysis indicated that patients in the high-risk group could have a survival benefit from chemotherapy after surgical treatment.

CONCLUSIONS

We established the first nomogram to accurately predict the survival of stage II C-MAC patients who underwent surgical treatment. In addition, the nomogram identified low-, middle-, and high-risk subgroups of patients and found chemotherapy might improve survival in the high-risk subgroup of stage II C-MAC patients.

A synopsis of global frontiers in fertility preservation

Since 2007, the Oncofertility Consortium Annual Conference has brought together a diverse network of individuals from a wide range of backgrounds and professional levels to disseminate emerging basic and clinical research findings in fertility preservation. This network also developed enduring educational materials to accelerate the pace and quality of field-wide scientific communication. Between 2007 and 2019, the Oncofertility Consortium Annual Conference was held as an in-person event in Chicago, IL. The conference attracted approximately 250 attendees each year representing 20 countries around the world. In 2020, however, the COVID-19 pandemic disrupted this paradigm and precluded an in-person meeting. Nevertheless, there remained an undeniable demand for the oncofertility community to convene. To maintain the momentum of the field, the Oncofertility Consortium hosted a day-long virtual meeting on March 5, 2021, with the theme of "Oncofertility Around the Globe" to highlight the diversity of clinical care and translational research that is ongoing around the world in this discipline. This virtual meeting was hosted using the vFairs ® conference platform and allowed over 700 people to participate, many of whom were first-time conference attendees. The agenda featured concurrent sessions from presenters in six continents which provided attendees a complete overview of the field and furthered our mission to create a global community of oncofertility practice. This paper provides a synopsis of talks delivered at this event and highlights the new advances and frontiers in the fields of oncofertility and fertility preservation around the globe from clinical practice and patient-centered efforts to translational research.

Phosphorylated STYK1 restrains the inhibitory role of EGFR in autophagy initiation and EGFR-TKIs sensitivity

Epidermal growth factor receptor (EGFR) plays critical roles in cell proliferation and tumorigenesis. Autophagy has emerged as a potential mechanism involved in the acquired resistance to anti-EGFR treatments, however, the molecular mechanisms has not been fully addressed. In this study, we identified EGFR interacts with STYK1, a positive autophagy regulator, in EGFR kinase activity dependent manner. We found that EGFR phosphorylates STYK1 at Y356 site and STYK1 inhibits activated EGFR mediated Beclin1 tyrosine phosphorylation and interaction between Bcl2 and Beclin1, thus enhances PtdIns3K-C1 complex assembly and autophagy initiation. We also demonstrated that STYK1 depletion increased the sensitivity of NSCLC cells to EGFR-TKIs in vitro and in vivo. Moreover, EGFR-TKIs induced activation of AMPK phosphorylates STYK1 at S304 site. STYK1 S304 collaborated with Y356 phosphorylation to enhance the EGFR-STYK1 interaction and reverse the inhibitory effects of EGFR to autophagy flux. Collectively, these data revealed new roles and cross-talk between STYK1 and EGFR in autophagy regulation and EGFR-TKIs sensitivity in NSCLC.

Identification of Ferroptosis-related molecular model and immune subtypes of hepatocellular carcinoma for individual therapy

BACKGROUND

Excessive iron accumulation and lipid peroxidation are primary characteristics of ferroptosis in hepatocellular carcinoma (HCC). Ferroptosis inducer combined with immunotherapy has become a new hope for HCC patients. Therefore, the construction and validation of subtype-specific sensitivity to ferroptosis inducer will be helpful for hierarchical management and precise individual therapy.

METHODS

RNA-seq transcriptome and clinical data of HCC patients were extracted from International Cancer Genome Consortium (ICGC) dataset and The Cancer Genome Atlas (TCGA) dataset. Consistency matrix and data clustering of the both cohorts were constructed by 'ConsensusClusterPlus' package. Single-sample gene set enrichment analysis (ssGSEA) analysis was performed to evaluate immune infiltration. Cox analysis was utilized to construct a ferroptosis phenotype-related prognostic model (FRPM) in HCC. The predictive efficiency of the constructed FRPM was evaluated through Kaplan Meier (K-M) survival analyses and Receiver Operating Characteristic (ROC) curves. The expression levels of candidate genes were detected and validated by Real-Time PCR between liver cancer tissues and adjacent non-tumor liver tissues.

RESULTS

45 differentially expressed ferroptosis-related genes (FRGs) were identified between HCC tissues and non-tumor liver tissues. Furthermore, four ferroptosis-associated clusters (FACs) of HCC were established via consensus clustering. Subsequently, we established a FRPM, consisting of four prognostic genes (SLC7A11, SLC1A5, GCLM and SAT1), to evaluate the survival of HCC patients, based on which, patients were divided into high-risk group and low-risk group. The high-risk group exhibited worse survival compared to low-risk group (p < 0.0001 both in TCGA and ICGC cohorts). Patients belong to different FACs or different risk scores showed distinct clinical characteristics. Moreover, in the validation experiment, the transcriptional expression levels of the four prognostic genes were consistent with the results drew from datasets.

CONCLUSION

We revealed a novel FRGs signature, which may provide the molecular characteristic data for effectively prognostic evaluation and potential personalized therapy for HCC patients.

Notch is an alternative splicing gene in brown planthopper, Nilaparvata lugens

Much research has assumed that Notch codes one protein. Then the protein will be cleaved into two parts and regenerates a heterodimers receptor to construct Notch signal pathways to regulate development in the past three decades. Here, we show that Notch in brown planthopper is a complex alternatively spliced gene has at least three transcriptional start sites, four exon skips, and 21 transcriptional endpoints that uses these to form variants and codes a series of proteins. When used dsRNAs to suppression different regions of the full-length variant NlNF resulted in a similar phenotype. Insects were molting after treatment, sensation circles on antennas near to root decayed, bristles on wings shortened, thickened or disappeared, accompanied by thickening veins and blades of fore-wing apex regions thickened. These results suggested that Notch influenced developmental of sensation circles, bristles, veins, and blades in nymph late periods. This study has deepened our understanding of Notch.

O-167 Microfluidics to mimic female reproductive tract

The female reproductive tract (FRT) consists of major organs of the ovary, the female gonad, and downstream fallopian tube, uterus, and cervix. There are intimate relationships between cells in each reproductive organ as well as between each organ to sustain women’s menstrual cycle and fertility. So far, there are few effective in vitro or ex vivo models that both faithfully recapitulate the hallmarks of female reproduction and possess scalability. In this presentation, I will first introduce how we used an alginate hydrogel-based 3D encapsulated in vitro follicle growth (eIVFG) system to engineer a mini-ovary, which can recapitulate key ovarian functions as occurring in vivo, including gonadotropin-dependent folliculogenesis, oocyte maturation, ovarian steroidogenesis, ovulation, and luteinization. Next, I will introduce how we used the emerging microfluidic technology to engineer an FRT-on-a-chip. The FRT-on-a-chip allows organ-organ integration of hormonal signaling, which simulates women’s 28-day menstrual cycle and also the pregnancy-like endocrine loops. In summary, the engineered mini-ovary and FRT-on-a-chip are new powerful tools for studying female reproductive biology, disease, contraception, drug development, and toxicology.

Mucinous histology is associated with poor prognosis in locally advanced colorectal adenocarcinoma treated with postoperative first-line adjuvant chemotherapy: A systematic review and meta-analysis

PURPOSE

Postoperative adjuvant chemotherapy followed surgery is the standard management for localized advanced colorectal carcinoma (CRC). Mucinous adenocarcinoma (MAC) is a peculiar histological subtype of CRC, but the prognosis of MAC patients is controversial. The objective of this study is to assess the implication of MAC in survival of patients treated with surgery and firs-line adjuvant chemotherapy.

METHODS

Studies describing outcomes for advanced MAC and non-specific adenocarcinoma (AC) of CRC patients treated with first-line postoperative adjuvant chemotherapy followed surgery were searched in PubMed, Embase, Medline, EBSCO, Wiley, and Cochrane Library (January 1963-August 2021). Hazard ratios (HRs) of overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS) for MAC to AC were extracted. Random-effects model was used for calculating the pooled HRs and 95% confidence interval (CI).

RESULTS

This meta-analysis is comprised of 8 studies involving a total of 124,303 CRC patients treated with first-line adjuvant chemotherapy followed surgery. The pooled HR for MAC was 1.23 (95% CI, 1.07-1.41, p < 0.01, I² = 80%), and the DFS (HR, 2.95, 95% CI, 1.22-7.14) of MAC patients were significantly poorer than AC patients. Similar results were also observed in stage III and FOLFOX regimen subgroups.

CONCLUSION

MAC was a risk factor for prognosis of localized advanced CRC patients treated with postoperative first-line adjuvant chemotherapy. Thus, the role of first-line adjuvant chemotherapy regimens should be further studied in these MAC patients.

Enriching Facial Anti-Spoofing Datasets via an Effective Face Swapping Framework

In the era of rapid development of the Internet of things, deep learning, and communication technologies, social media has become an indispensable element. However, while enjoying the convenience brought by technological innovation, people are also facing the negative impact brought by them. Taking the users’ portraits of multimedia systems as examples, with the maturity of deep facial forgery technologies, personal portraits are facing malicious tampering and forgery, which pose a potential threat to personal privacy security and social impact. At present, the deep forgery detection methods are learning-based methods, which depend on the data to a certain extent. Enriching facial anti-spoofing datasets is an effective method to solve the above problem. Therefore, we propose an effective face swapping framework based on StyleGAN. We utilize the feature pyramid network to extract facial features and map them to the latent space of StyleGAN. In order to realize the transformation of identity, we explore the representation of identity information and propose an adaptive identity editing module. We design a simple and effective post-processing process to improve the authenticity of the images. Experiments show that our proposed method can effectively complete face swapping and provide high-quality data for deep forgery detection to ensure the security of multimedia systems.

Camrelizumab in combination with concurrent chemoradiotherapy as first-line treatment for nonoperative head and neck cancer: A comparative study

6063

Background: We hypothesized that concurrent chemoradiotherapy (CCRT) plus concurrent and adjuvant camrelizumab as first-line treatmentwas associated with improved survival compared with concurrent chemoradiotherapy alone for nonoperative locoregionally advanced head and neck squamous cell carcinoma (HNSCC). The purpose of this comparative study was to compare the efficacy and toxicity of CCRT plus concurrent and adjuvant camrelizumab versus CCRT alone in nonoperative locoregionally advanced HNSCC. Methods: One hundred and eighty patients with nonoperative locoregionally advanced HNSCC (cancer of the oral cavity, oropharyngeal cancer, hypopharyngeal cancer and laryngeal cancer) received either CCRT plus concurrent and adjuvant camrelizumab (camrelizumab + CCRT group, n = 90) or CCRT alone (CCRT alone group, n = 90). Patients in both groups received curative cisplatin-based concurrent chemoradiotherapy. The radiation dose was 70 Gy (2.0 Gy/fraction). In camrelizumab + CCRT group, concurrent camrelizumab (200mg/day on days 1, 22, 43) was added to CCRT, followed by adjuvant camrelizumab (200mg, every 3 weeks for 6 months or until disease progression, unacceptable adverse events or withdrawal of consent). Results: Compared with CCRT alone, the addition of concurrent and adjuvant camrelizumab significantly improved complete response (CR) rates (92.2% vs. 80.0%; P = 0.018), 3-year disease free survival (DFS, 72.2% vs. 56.7%; P = 0.029), locoregional recurrence-free survival (LRRFS, 76.7% vs. 61.1%; P = 0.024), and overall survival (OS, 78.9% vs. 63.3%; P = 0.033). Reactive cutaneous capillary endothelial proliferation was higher in the camrelizumab + CCRT group (6.7% vs. 0.0%; P = 0.013). No statistically significant differences in other acute (mucositis, leukopenia, thrombocytopenia, anemia, etc.) and late toxic effects (mucosal necrosis, trismus, cranial nerve palsy, etc.) were observed between the two groups. The addition of camrelizumab (CCRT plus camrelizumab vs. CCRT alone) was a significant independent prognostic factor for 3-year DFS, LRRFS and OS (P = 0.038, P = 0.032, and P = 0.048, respectively). Conclusions: Concurrent chemoradiotherapy plus concurrent and adjuvant camrelizumab as first-line treatment is associated with a considerable survival benefit, with acceptable adverse events, as compared with concurrent chemoradiotherapy alone, among patients with nonoperative locoregionally advanced head and neck squamous cell carcinoma. Our ongoing prospective clinical trial (registered with chictr.org.cn, number ChiCTR2200056298) will further investigate the efficacy of camrelizumab in combination with chemoradiotherapy for HNSCC.

Bias correction framework for satellite precipitation products using a rain/no rain discriminative model

Despite the benefits of global coverage with high spatiotemporal resolutions, satellite precipitation products (SPPs) still suffer from inadequate accuracy in natural hazard forecasts, hydrology, and water resources management. Rain/no-rain (R/NR) detection error significantly affects the accuracy of daily SPPs, which has attracted increasing attention in recent years. This paper proposed a precipitation bias correction framework (PBCF) to improve the accuracy of daily SPPs, focusing on improving the ability of SPPs to detect the occurrence of the precipitation based on a R/NR discriminative model. Multiple land and climate variables derived from ERA5-Land reanalysis dataset were used to construct the R/NR discriminative model using the artificial neural network (ANN) method. A case study on the bias correction of daily precipitation of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) over Hanjiang River Basin (HRB) was conducted for the period 2004-2018. Daily precipitation of 64 meteorological stations in HRB were spatially and randomly divided into two groups: 44 stations were used for training, validating and testing the constructed R/NR discriminative model, and the other 20 stations were used to evaluate the performance of the R/NR discriminative model in different topographic areas. The results indicate that the proposed PBCF could reduce the bias of IMERG, with the correlation coefficient (R) increased by 19.4%, the root mean square error (RMSE) and the mean absolute error (MAE) decreased by 19.0% and 29.8% on the daily scale, respectively. The constructed R/NR discriminative model could improve the ability of IMERG for detecting the precipitation occurrence, with a classification accuracy of about 86.5% and the equitable threat score (ETS) increased from 0.15 to 0.58. Further analyses showed that the proposed PBCF was more efficient than the cumulative distribution function mapping method in correcting IMERG. This study provides a novel insight for the correction of daily SPPs.

Radiofrequency coblation assisted transoral excision of lingual thyroglossal duct cyst

Radiofrequency coblation (RFC) is a relatively new device that has been used in several transoral procedures. Currently, clinical data on its use for excising lingual thyroglossal duct cyst (LTGDC) are lacking. Herein, we conducted this retrospective case series to explore the feasibility and efficacy of RFC-assisted transoral surgery (RFC-TOS) in excising LTGDC. A total of 12 LTGDC patients between 2013 and 2020 were retrospectively studied. The cysts of these patients were all fully removed along the boundary to the depth of the hyoid using RFC wands. All surgeries were completed within 30 minutes. Only one patient had an intraoperative blood loss of more than 10 ml. All patients started oral feeding on the day of operation. The mean postoperative hospital stay was only 3.3 days (range 1-8 days). No surgical-related short-term and long-term complications were observed. One patient was lost to follow up, and no recurrences occurred during a mean follow-up period of 52.7 months among the other 11 patients. Therefore, we believe that RFC is a reliable tool in transoral operation for treating LTGDC. LTGDC patients who underwent RFC-TOS showed quick recovery, low risks of complications, and excellent clinical and functional outcomes.