Network Pharmacology and Bioinformatics Analysis to Identify the Molecular Targets and its Biological Mechanisms of Sciadopitysin against Glioblastoma.

Glioblastoma multiform (GBM) is categorized as the most malignant subtype of gliomas, which comprise nearly 75% of malignant brain tumors in adults. Increasing evidence suggests that network pharmacology will be a novel method for identifying the systemic mechanism of therapeutic compounds in diseases like cancer. The present study aimed to use a network pharmacology approach to establish the predictive targets of sciadopitysin against GBM and elucidate its biological mechanisms. Firstly, targets of sciadopitysin were obtained from the SwissTargetPrediction database, and genes associated with the pathogenesis of GBM were identified from the DiGeNET database. Sixty-four correlative hits were identified as anti-glioblastoma targets of sciadopitysin. Functional enrichment and pathway analysis revealed significant biological mechanisms of the targets. Interaction of protein network and cluster analysis using STRING resulted in two crucial interacting hub genes, namely, HSP90 and AKT1. Additionally, the in vitro cytotoxic potential of sciadopitysin was assessed on GBM U87 cells. The findings indicate that the pharmacological action of sciadopitysin against GBM might be associated with the regulation of two core targets: HSP90 and AKT1. Thus, the network pharmacology undertaken in the current study established the core active targets of sciadopitysin, which may be extensively applied with further validations for treatment in GBM.

Molecular insights and clinical implications for the tumor suppressor role of SCFFBXW7 E3 ubiquitin ligase.

FBXW7 is one of the most well-characterized F-box proteins, serving as substrate receptor subunit of SKP1-CUL1-F-box (SCF) E3 ligase complexes. SCFFBXW7 is responsible for the degradation of various oncogenic proteins such as cyclin E, c-MYC, c-JUN, NOTCH, and MCL1. Therefore, FBXW7 functions largely as a major tumor suppressor. In keeping with this notion, FBXW7 gene mutations or downregulations have been found and reported in many types of malignant tumors, such as endometrial, colorectal, lung, and breast cancers, which facilitate the proliferation, invasion, migration, and drug resistance of cancer cells. Therefore, it is critical to review newly identified FBXW7 regulation and tumor suppressor function under physiological and pathological conditions to develop effective strategies for the treatment of FBXW7-altered cancers. Since a growing body of evidence has revealed the tumor-suppressive activity and role of FBXW7, here, we updated FBXW7 upstream and downstream signaling including FBXW7 ubiquitin substrates, the multi-level FBXW7 regulatory mechanisms, and dysregulation of FBXW7 in cancer, and discussed promising cancer therapies targeting FBXW7 regulators and downstream effectors, to provide a comprehensive picture of FBXW7 and facilitate the study in this field.

A prognostic signature of fatty acid metabolism-related genes for predicting survival of gastric cancer patients.

To analyze the expression profile of fatty acid metabolism (FAM)-related genes, identify a prognostic signature, and evaluate its clinical value for gastric cancer (GC) patients. The mRNA expression profiles of 493 FAM-related genes were obtained from TCGA database. Differentially expressed genes (DEGs) between cancer and non-cancer samples were identified, and their relationships with overall survival (OS) of GC patients were evaluated. A prognostic signature of FAM-related genes was identified by the LASSO regression model, and its predictive performance was tested by an independent external cohort. Ninety-three DEGs were identified, of which 44 were downregulated and 49 were upregulated. After optimizing risk characteristics, a prognostic signature of four FAM-related genes (ACBD5, AVPR1A, ELOVL4, and FAAH) were developed. All patients were divided into high-risk (>1.020) and low-risk groups (≤1.020) on the basis of the median risk score. Survival analysis indicated that high-risk patients had a shorter OS than low-risk patients (5-year OS rate, 26.3% vs. 45.0%, p < 0.001). The AUC values for the prediction of 3-year and 5-year OS were 0.664 and 0.624, respectively. In the GSE62254 data set, the 5-year OS rate of high-risk and low-risk patients were 44.7% versus 61.5%, respectively (p = 0.003). The AUC values were 0.632 and 0.627 at 3-year and 5-year prediction. The prognostic signature of FAM-related genes was an independent predictor of OS (hanzard ratio [HR] for TCGA cohort: 1.851, 95% confidence interval [CI]: 1.394-2.458, p < 0.001; HR for GSE62254: 1.549, 95% CI: 1.098-2.185, p = 0.013). The risk signature of four FAM-related genes was a valuable prognostic tool, and it might be helpful for clinical management and therapeutic decision of gastric cancer patients.

Research on Computing Resource Measurement and Routing Methods in Software Defined Computing First Network.

Computing resource measurement and computing routing are essential technologies in the computing first network (CFN), serving as its foundational elements. This paper introduces a Software Defined Computing First Network (SD-CFN) architecture. Building upon this framework, a Dynamic-Static Integrated Computing Resource Measurement Mechanism (DCRMM) is proposed, incorporating methods such as the entropy weight method and K-Means clustering. The DCRMM algorithm outperforms the Maximum-closest Static Algorithm (MSA) and Maximum Closest Dynamic Algorithm (MDA) in terms of node stability, node utilization, and node matching accuracy. Additionally, a Reinforcement Learning and Software Defined Computing First Networking Routing (RSCR) algorithm is presented as a software-defined computing routing solution within the SD-CFN. RSCR introduces a knowledge plane responsible for computing routing calculations. It comprehensively considers factors such as link latency, available bandwidth, and packet loss rate. Simulation experiments conducted on the GÉANT topology demonstrate that RSCR outperforms the OSPF algorithm in terms of link latency, packet loss rate, and throughput. DCRMM and RSCR offer innovative solutions for computing resource measurement and computing routing in computing first networks.

Which is the appropriate surgical procedure for appendiceal adenocarcinoma: appendectomy, partial colectomy or right hemicolectomy?

Objective The purpose of this study was to explore the appropriate surgical procedure and clinical decision for appendiceal adenocarcinoma. Methods A total of 1,984 appendiceal adenocarcinoma patients from 2004 to 2015 were retrospectively identified from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were divided into three groups based on the extent of surgical resection: appendectomy (N = 335), partial colectomy (N = 390) and right hemicolectomy (N = 1,259). The clinicopathological features and survival outcomes of three groups were compared, and independent prognostic factors were assessed. Results The 5-year OS rates of patients who underwent appendectomy, partial colectomy and right hemicolectomy were 58.3%, 65.5% and 69.1%, respectively (right hemicolectomy vs appendectomy, P < 0.001; right hemicolectomy vs partial colectomy, P = 0.285; partial colectomy vs appendectomy, P = 0.045). The 5-year CSS rates of patients who underwent appendectomy, partial colectomy and right hemicolectomy were 73.2%, 77.0% and 78.7%, respectively (right hemicolectomy vs appendectomy, P = 0.046; right hemicolectomy vs partial colectomy, P = 0.545; partial colectomy vs appendectomy, P = 0.246). The subgroup analysis based on the pathological TNM stage indicated that there was no survival difference amongst three surgical procedures for stage I patients (5-year CSS rate: 90.8%, 93.9% and 98.1%, respectively). The prognosis of patients who underwent an appendectomy was poorer than that of those who underwent partial colectomy (5-year OS rate: 53.5% vs 67.1%, P = 0.005; 5-year CSS rate: 65.2% vs 78.7%, P = 0.003) or right hemicolectomy (5-year OS rate: 74.2% vs 53.23%, P < 0.001; 5-year CSS rate: 65.2% vs 82.5%, P < 0.001) for stage II disease. Right hemicolectomy did not show a survival advantage over partial colectomy for stage II (5-year CSS, P = 0.255) and stage III (5-year CSS, P = 0.846) appendiceal adenocarcinoma (AU)

Lemierre Syndrome: Report of a Case with an Innovative Diagnostic Method and Literature Review.

Objective: To understand the clinical features, diagnosis and treatment of Lemierre syndrome (LS), a high-risk and low-prevalence infectious disease. Methods: We present the severe LS case that was diagnosed using metagenomic next-generation sequencing (mNGS) in our hospital, and systematically summarized the diagnosis and treatment strategies of patients that reported LS from 2006 to 2022. Results: The 24-year-old patient in our hospital suffered from cranial nerve paralysis, a neurological complication rarely seen in LS cases. The causative agent (Fusobacterium necrophorum, Fn) of this patient was only detected by mNGS tests, and the reads number of Fn detected by plasma mNGS tests was decrease as the patients gradually improved, indicating plasma mNGS is valuable in monitoring treatment efficacy. Although most of the cases retrieved from the literature showed typical symptoms, such as a history of sore throat, septic emboli, and internal jugular vein thrombosis, clinical manifestations were still relatively heterogeneous (eg, diversity of predisposing factors and pathogens, differences in pulmonary imaging features). Conclusion: We summarized the clinical presentation, diagnosis, treatment, and regression of 17 symptomatic cases reported LS to provide clinicians with knowledge about this rare but fatal disease. mNGS assays should be considered as early as possible to identify the responsible pathogens for acute and critically ill patients with suspected infections in order to implement accurate and effective treatment.

USP29 activation mediated by FUBP1 promotes AURKB stability and oncogenic functions in gastric cancer.

BACKGROUND: Gastric cancer is a highly prevalent cancer type and the underlying molecular mechanisms are not fully understood. Ubiquitin-specific peptidase (USP) 29 has been suggested to regulate cell fate in several types of cancer, but its potential role in gastric carcinogenesis remains unclear. METHODS: The expression of USP29 in normal and gastric cancer tissues was analyzed by bioinformatics analysis, immunohistochemistry and immunoblot. Gene overexpression, CRISPR-Cas9 technology, RNAi, and Usp29 knockout mice were used to investigate the roles of USP29 in cell culture, xenograft, and benzo[a]pyrene (BaP)-induced gastric carcinogenesis models. We then delineated the underlying mechanisms using mass spectrometry, co-immunoprecipitation (Co-IP), immunoblot, ubiquitination assay, chromatin immunoprecipitation (ChIP), quantitative real-time PCR (qRT-PCR), and luciferase assays. RESULTS: In this study, we found that USP29 expression was significantly upregulated in gastric cancers and associated with poor patient survival. Ectopic expression of USP29 promoted, while depletion suppressed the tumor growth in vitro and in vivo mouse model. Mechanistically, transcription factor far upstream element binding protein 1 (FUBP1) directly activates USP29 gene transcription, which then interacts with and stabilizes aurora kinase B (AURKB) by suppressing K48-linked polyubiquitination, constituting a FUBP1-USP29-AURKB regulatory axis that medicates the oncogenic role of USP29. Importantly, systemic knockout of Usp29 in mice not only significantly decreased the BaP-induced carcinogenesis but also suppressed the Aurkb level in forestomach tissues. CONCLUSIONS: These findings uncovered a novel FUBP1-USP29-AURKB regulatory axis that may play important roles in gastric carcinogenesis and tumor progression, and suggested that USP29 may become a promising drug target for cancer therapy.

Which is the appropriate surgical procedure for appendiceal adenocarcinoma: appendectomy, partial colectomy or right hemicolectomy?

OBJECTIVE: The purpose of this study was to explore the appropriate surgical procedure and clinical decision for appendiceal adenocarcinoma. METHODS: A total of 1,984 appendiceal adenocarcinoma patients from 2004 to 2015 were retrospectively identified from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were divided into three groups based on the extent of surgical resection: appendectomy (N = 335), partial colectomy (N = 390) and right hemicolectomy (N = 1,259). The clinicopathological features and survival outcomes of three groups were compared, and independent prognostic factors were assessed. RESULTS: The 5-year OS rates of patients who underwent appendectomy, partial colectomy and right hemicolectomy were 58.3%, 65.5% and 69.1%, respectively (right hemicolectomy vs appendectomy, P < 0.001; right hemicolectomy vs partial colectomy, P = 0.285; partial colectomy vs appendectomy, P = 0.045). The 5-year CSS rates of patients who underwent appendectomy, partial colectomy and right hemicolectomy were 73.2%, 77.0% and 78.7%, respectively (right hemicolectomy vs appendectomy, P = 0.046; right hemicolectomy vs partial colectomy, P = 0.545; partial colectomy vs appendectomy, P = 0.246). The subgroup analysis based on the pathological TNM stage indicated that there was no survival difference amongst three surgical procedures for stage I patients (5-year CSS rate: 90.8%, 93.9% and 98.1%, respectively). The prognosis of patients who underwent an appendectomy was poorer than that of those who underwent partial colectomy (5-year OS rate: 53.5% vs 67.1%, P = 0.005; 5-year CSS rate: 65.2% vs 78.7%, P = 0.003) or right hemicolectomy (5-year OS rate: 74.2% vs 53.23%, P < 0.001; 5-year CSS rate: 65.2% vs 82.5%, P < 0.001) for stage II disease. Right hemicolectomy did not show a survival advantage over partial colectomy for stage II (5-year CSS, P = 0.255) and stage III (5-year CSS, P = 0.846) appendiceal adenocarcinoma. CONCLUSIONS: Right hemicolectomy may not always be necessary for appendiceal adenocarcinoma patients. An appendectomy could be sufficient for therapeutic effect of stage I patients, but limited for stage II patients. Right hemicolectomy was not superior to partial colectomy for advanced stage patients, suggesting omission of standard hemicolectomy might be feasible. However, adequate lymphadenectomy should be strongly recommended.

Orthodontic force/torque modeling and experiment of Kitchon root-controlled auxiliary archwire.

The incidence of oral malocclusion is increasing and is seriously damaging the oral health of human beings. The Kitchon root-controlled auxiliary archwire is an individualized orthodontic arch. It is used clinically for the treatment of tooth-lingual tilt/root-lip tilt phenomenon of the central incisors. However, the bending parameters of the Kitchon root-controlled auxiliary archwire used in different patients are based on the clinical experience of the dentists. Therefore, this orthodontic treatment has a high risk and unpredictability. In this paper, the loading performance and orthodontic process of Kitchon root-controlled auxiliary archwire are analyzed. And the prediction model of support resistance and correction torque are established. The bending parameters of the Kitchon root-controlled auxiliary archwire, as well as the effect of the bending parameters on the support resistance and the correction torque, are all quantified. And the prediction models for the support resistance and the correction torque are calculated separately. The correlation coefficients of calculated data and experimental data are ξT1 > .97 and ξA1 > .96, respectively; the correlation coefficients of simulated data and experimental data are ξT2 > .96 and ξA2 > .96, respectively. The accuracy and reliability of the established prediction models are verified. It provides an effective theoretical guide for dentists to safely and efficiently perform root-controlled rotation orthodontic treatment on patients' central incisors.

Reducing Flow Table Update Costs in Software-Defined Networking.

In software-defined networking (SDN), the traffic forwarding delay highly depends on the latency associated with updating the forwarding rules in flow tables. With the increase in fine-grained flow control requirements, due to the flexible control capabilities of SDN, more rules are being inserted and removed from flow tables. Moreover, the matching fields of these rules might overlap since multiple control domains might generate different rules for similar flows. This overlap implies dependency relationships among the rules, imposing various restrictions on forwarding entries during updates, e.g., by following update orders or storing entries at specified locations, especially in flow tables implemented using ternary content addressable memory (TCAM); otherwise, mismatching or packet dropping will occur. It usually takes a while to resolve and maintain dependencies during updates, which hinders high forwarding efficiency. To reduce the delay associated with updating dependent rules, in this paper, we propose an updating algorithm for TCAM-based flow tables. We formulate the TCAM maintenance process as an NP-hard problem and analyze the inefficiency of existing moving approaches. To solve the problem, we propose an optimal moving chain for single rule updates and provide theoretical proof for its minimum moving steps. For multiple rules arriving at a switch simultaneously, we designed a dynamic approach to update concurrent entries; it is able to update multiple rules heuristically within a restricted TCAM region. As the update efficiency concerns dependencies among rules, we evaluate our flow table by updating algorithms with different dependency complexities. The results show that our approach achieves about 6% fewer moving steps than existing approaches. The advantage is more pronounced when the flow table is heavily utilized and rules have longer dependency chains.

USP2 inhibition prevents infection with ACE2-dependent coronaviruses in vitro and is protective against SARS-CoV-2 in mice.

Targeting angiotensin-converting enzyme 2 (ACE2) represents a promising and effective approach to combat not only the COVID-19 pandemic but also potential future pandemics arising from coronaviruses that depend on ACE2 for infection. Here, we report ubiquitin specific peptidase 2 (USP2) as a host-directed antiviral target; we further describe the development of MS102, an orally available USP2 inhibitor with viable antiviral activity against ACE2-dependent coronaviruses. Mechanistically, USP2 serves as a physiological deubiquitinase of ACE2, and targeted inhibition with specific small-molecule inhibitor ML364 leads to a marked and reversible reduction in ACE2 protein abundance, thereby blocking various ACE2-dependent coronaviruses tested. Using human ACE2 transgenic mouse models, we further demonstrate that ML364 efficiently controls disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as evidenced by reduced viral loads and ameliorated lung inflammation. Furthermore, we improved the in vivo performance of ML364 in terms of both pharmacokinetics and antiviral activity. The resulting lead compound, MS102, holds promise as an oral therapeutic option for treating infections with coronaviruses that are reliant on ACE2.

ddPCR provides a sensitive test compared with GeneXpert MTB/RIF and mNGS for suspected Mycobacterium tuberculosis infection.

Introduction: The Metagenomics next-generation sequencing (mNGS) and GeneXpert MTB/RIF assay (Xpert) exhibited a sensitivity for tuberculosis (TB) diagnostic performance. Research that directly compared the clinical performance of ddPCR analysis, mNGS, and Xpert in mycobacterium tuberculosis complex (MTB) infection has not been conducted. Methods: The study aimed to evaluate the diagnostic performance of ddPCR compared to mNGS and Xpert for the detection of MTB in multiple types of clinical samples. The final clinical diagnosis was used as the reference standard. Results: Out of 236 patients with suspected active TB infection, 217 underwent synchronous testing for tuberculosis using ddPCR, Xpert, and mNGS on direct clinical samples. During follow-up, 100 out of 217 participants were diagnosed with MTB infection. Compared to the clinical final diagnosis, ddPCR produced the highest sensitivity of 99% compared with mNGS (86%) and Xpert (64%) for all active MTB cases. Discussion: Twenty-two Xpert-negative samples were positive in mNGS tests, which confirmed the clinical diagnosis results from ddPCR and clinical manifestation, radiologic findings. Thirteen mNGS-negative samples were positive in ddPCR assays, which confirmed the clinical final diagnosis.ddPCR provides a higher sensitive compared to Xpert and mNGS for MTB diagnosis, as defined by the high concordance between ddPCR assay and clinical final diagnosis.

Pyroptosis-related gene signature: A predictor for overall survival, immunotherapy response, and chemosensitivity in patients with pancreatic adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is a lethal malignancy with high levels of heterogeneity. Pyroptosis is thought to influence the development of various tumors. Nevertheless, the role of pyroptosis-related genes (PRGs) in prognostic risk stratification and therapeutic guidance for PAAD remains ambiguously. Methods: Transcriptome profile and clinical information of PAAD patients were retrieved from The Cancer Genome Atlas (TCGA) as well as Gene Expression Omnibus (GEO) databases, followed by differential analysis. Patients were divided into distinct pyroptosis phenotype subtypes based on the characteristic of differently expressed PRGs (DEPRGs). Then a PRG signature was established through univariate analysis and LASSO algorithm in the training set to assess the prognostic risk, and its reliability was verified in the validation set using receiver operating characteristic(ROC) curve. The correlation of risk score with tumor microenvironment(TME), TMB and chemotherapeutic drug sensitivity were also analyzed. In addition, a nomogram was constructed to promote better clinical application. Results: A total of 28 DEPRGs were determined in the integrated TCGA-GEO datasets. Patients were divided into three pyroptosis phenotype subtypes, Kaplan-Meier curve suggested patients in cluster B had a worse prognosis than those in cluster A and C. Then a price signature comprised of 8 PRGs was generated. TME analysis suggested that the low-risk subgroup displayed potential stronger antitumor immune effect and might respond better to immune checkpoint inhibitors (ICIs) therapy. Furthermore, PRG signature exhibited favorable discriminatory ability for TMB status and the sensitivity of multiple conventional chemotherapeutic agents including paclitaxel. Ultimately, we constructed a promising nomogram according to the risk score and N stage with good predictive accuracy compared with the actual overall survival (OS) probabilities. Conclusion: We established an 8-gene signature that could be regarded as an independent prognostic risk factor for PAAD patients. The 8-gene signature could provide rationale for immunotherapy and chemotherapy, which might help clinicians make precise individualized treatment regimens.

Identifying a Risk Signature of Methylation-Driven Genes as a Predictor of Survival Outcome for Colon Cancer Patients.

Aberrant expression of gene is driven by its promoter methylation and is the key molecular basis of carcinogenic processes. This study aimed at identifying a risk signature of methylation-driven (MD) genes and evaluating its prognostic value for colon cancer (CC) patients. The expression profiles of methylation and mRNA in CC samples were obtained from the TCGA database, and the MethylMix algorithm was used to identify MD genes. The relationships between their expression levels and overall survival (OS) of CC patients were analyzed, and a prognostic signature of MD genes was established. The risk score of gene signature was calculated, and the median was used to divide all patients into high (H) and low (L) risk groups. The prognostic value of gene signature was tested by the TCGA cohort and an independent validation cohort (GSE17538 dataset). In total, 69 MD genes were identified, and 7 were associated with OS of CC patients. Ultimately, 4 (TWIST1, LDOC1, EPHX3, and STC2) were screened out to establish a risk signature. The H-risk patients (>0.923) had a worse OS than L-risk patients (≤0.923) in both the TCGA (5-year cumulative survival: 52.9% vs 72.0%, P=0.005) and GSE17538 cohort (49.4% vs 69.3%, P=0.004). The AUC values of MD genes signature for the prediction of 3- and 5-year OS were 0.648 and 0.643 in the TCGA dataset and 0.634 and 0.624 in the GSE17538 dataset, respectively. The risk signature of four MD genes was identified as an independent predictor of OS for CC patients (HR for TCGA dataset: 2.071, 95% CI=1.196-3.586, P=0.009; HR for GSE17538 dataset: 2.021, 95% CI=1.290-3.166, P=0.002). The risk signature of four MD genes might be a useful prognostic tool and help doctors improve the clinical management of CC patients.

Secondary Infection Surveillance with Metagenomic Next-Generation Sequencing in COVID-19 Patients: A Cross-Sectional Study.

Background: Metagenomic next-generation sequencing (mNGS) is a promising tool for improving antimicrobial therapy and infection control decision-making in complex infections. Secondary infection surveillance using mNGS in COVID-19 patients has rarely been reported. Methods: Respiratory pathogen and antibiotic resistance prediction were evaluated by BALF mNGS for 192 hospitalized COVID-19 patients between December 2022 and February 2023. Results: Secondary infection was confirmed in 83.3% (160/192) of the COVID-19 patients, with bacterial infections (45%, 72/160) predominating, followed by mixed bacterial and fungal infections (20%, 32/160), and fungal infections (17.5%, 28/160). The incidence of bacterial or viral secondary infection was significantly higher in patients who were admitted to the ICU, received mechanical ventilation, or developed severe pneumonia (all p<0.05). Klebsiella pneumoniae (n=30, 8.4%) was the most prevalent pathogen associated with secondary infection followed by Acinetobacter baumannii (n=29, 8.1%), Candida albicans (n=29, 8.1%), Aspergillus fumigatus (n=27, 7.6%), human herpes simplex virus type 1 (n=23, 6.4%), Staphylococcus aureus (n=20, 5.6%) and Pneumocystis jiroveci (n=14, 3.9%). The overall concordance between the resistance genes detected by mNGS and the reported phenotypic resistance in 69 samples containing five clinically important pathogens (ie, K. pneumoniae, A. baumannii, S. aureus, P. aeruginosa and E. coli) that caused secondary infection was 85.5% (59/69). Conclusion: mNGS can detect pathogens causing secondary infection and predict antimicrobial resistance for COVID19 patients. This is crucial for initiating targeted treatment and rapidly detect unsuspected spread of multidrug-resistant pathogens.

QGD-Net: A Lightweight Model Utilizing Pixels of Affinity in Feature Layer for Dermoscopic Lesion Segmentation.

RESPONSE: Pixels with location affinity, which can be also called "pixels of affinity," have similar semantic information. Group convolution and dilated convolution can utilize them to improve the capability of the model. However, for group convolution, it does not utilize pixels of affinity between layers. For dilated convolution, after multiple convolutions with the same dilated rate, the pixels utilized within each layer do not possess location affinity with each other. To solve the problem of group convolution, our proposed quaternion group convolution uses the quaternion convolution, which promotes the communication between to promote utilizing pixels of affinity between channels. In quaternion group convolution, the feature layers are divided into 4 layers per group, ensuring the quaternion convolution can be performed. To solve the problem of dilated convolution, we propose the quaternion sawtooth wave-like dilated convolutions module (QS module). QS module utilizes quaternion convolution with sawtooth wave-like dilated rates to effectively leverage the pixels that share the location affinity both between and within layers. This allows for an expanded receptive field, ultimately enhancing the performance of the model. In particular, we perform our quaternion group convolution in QS module to design the quaternion group dilated neutral network (QGD-Net). Extensive experiments on Dermoscopic Lesion Segmentation based on ISIC 2016 and ISIC 2017 indicate that our method has significantly reduced the model parameters and highly promoted the precision of the model in Dermoscopic Lesion Segmentation. And our method also shows generalizability in retinal vessel segmentation.

A novel miRNA-based signature as predictive tool of survival outcome of colorectal cancer patients.

It is great significance of identifying valuable biomarkers for early diagnosis and prognostic prediction of colorectal cancer (CRC) patients. This study aimed at developing and validating a miRNAs-based signature as prognostic tool for CRC patients. The miRNA expression profile of 624 CRC samples (613 tumor tissues and 11 normal tissues) was analyzed, and 523 differentially expressed miRNAs (DEmiRNAs) were identified, in which 191 were downregulated and 332 were upregulated. All patients were randomly divided into a training cohort (N = 308) and an internal validation cohort (N = 200). Using the least absolute shrinkage and selection operator (LASSO) and Cox regression model, a prognostic signature of 10 miRNAs (hsa-miR-149-5p, hsa-miR-193b-5p, hsa-miR-193a-3p, hsa-miR-3677-3p, hsa-miR-29a-3p, hsa-miR-200c-5p, hsa-miR-200a-5p, hsa-miR-6854-5p, hsa-miR-216a-5p and hsa-miR-891a-5p) was developed in the training cohort. The risk score was calculated by the product of the expression level and the coefficients of each miRNA. The prognostic value of 10 miRNAs-based signature for CRC patients was tested and validated. Survival analysis indicated that high-risk patients (> 1.10) had a worse overall survival (OS) than low-risk (≤ 1.10) patients (5-year OS rate for training cohort: 59.3% vs. 78.9%, p < .001; validation cohort: 48.3% vs. 69.3%, p = .011). The miRNA-based signature was an independent prognostic factor for CRC patients (HR for training cohort:2.476, 95% CI:1.202-5.098, p = .014; HR for validation cohort:2.050, 95% CI:1.087-3.869, p = .027). The AUC values for 3-year and 5-year OS prediction were 0.718 and 0.784 in the training cohort, 0.659 and 0.614 in the validation cohort, respectively. The 10 miRNAs-based signature provided a proper prognostic stratification for CRC patients, and it might be a promising tool for survival prediction.

Prolonged hypoxia alleviates prolyl hydroxylation-mediated suppression of RIPK1 to promote necroptosis and inflammation.

The prolyl hydroxylation of hypoxia-inducible factor 1α (HIF-1α) mediated by the EGLN-pVHL pathway represents a classic signalling mechanism that mediates cellular adaptation under hypoxia. Here we identify RIPK1, a known regulator of cell death mediated by tumour necrosis factor receptor 1 (TNFR1), as a target of EGLN1-pVHL. Prolyl hydroxylation of RIPK1 mediated by EGLN1 promotes the binding of RIPK1 with pVHL to suppress its activation under normoxic conditions. Prolonged hypoxia promotes the activation of RIPK1 kinase by modulating its proline hydroxylation, independent of the TNFα-TNFR1 pathway. As such, inhibiting proline hydroxylation of RIPK1 promotes RIPK1 activation to trigger cell death and inflammation. Hepatocyte-specific Vhl deficiency promoted RIPK1-dependent apoptosis to mediate liver pathology. Our findings illustrate a key role of the EGLN-pVHL pathway in suppressing RIPK1 activation under normoxic conditions to promote cell survival and a model by which hypoxia promotes RIPK1 activation through modulating its proline hydroxylation to mediate cell death and inflammation in human diseases, independent of TNFR1.

Metabolic orchestration of cell death by AMPK-mediated phosphorylation of RIPK1.

Adenosine monophosphate-activated protein kinase (AMPK) activity is stimulated to promote metabolic adaptation upon energy stress. However, sustained metabolic stress may cause cell death. The mechanisms by which AMPK dictates cell death are not fully understood. We report that metabolic stress promoted receptor-interacting protein kinase 1 (RIPK1) activation mediated by TRAIL receptors, whereas AMPK inhibited RIPK1 by phosphorylation at Ser415 to suppress energy stress-induced cell death. Inhibiting pS415-RIPK1 by Ampk deficiency or RIPK1 S415A mutation promoted RIPK1 activation. Furthermore, genetic inactivation of RIPK1 protected against ischemic injury in myeloid Ampkα1-deficient mice. Our studies reveal that AMPK phosphorylation of RIPK1 represents a crucial metabolic checkpoint, which dictates cell fate response to metabolic stress, and highlight a previously unappreciated role for the AMPK-RIPK1 axis in integrating metabolism, cell death, and inflammation.

PRMT1 methylates METTL14 to modulate its oncogenic function.

N6-methyladenosine (m6A), the most abundant mRNA modification in mammalian cells, is responsible for mRNA stability and alternative splicing. The METTL3-METTL14-WTAP complex is the only methyltransferase for the m6A modification. Thus, regulation of its enzymatic activity is critical for the homeostasis of mRNA m6A levels in cells. However, relatively little is known about the upstream regulation of the METTL3-METTL14-WTAP complex, especially at the post-translational modification level. The C-terminal RGG repeats of METTL14 are critical for RNA binding. Therefore, modifications on these residues may play a regulatory role in its function. Arginine methylation is a post-translational modification catalyzed by protein arginine methyltransferases (PRMTs), among which PRMT1 preferentially methylates protein substrates with an arginine/glycine-rich motif. In addition, PRMT1 functions as a key regulator of mRNA alternative splicing, which is associated with m6A modification. To this end, we report that PRMT1 promotes the asymmetric methylation of two major arginine residues at the C-terminus of METTL14, and the reader protein SPF30 recognizes this modification. Functionally, PRMT1-mediated arginine methylation on METTL14 is likely essential for its function in catalyzing the m6A modification. Moreover, arginine methylation of METTL14 promotes cell proliferation that is antagonized by the PRMT1 inhibitor MS023. These results indicate that PRMT1 likely regulates m6A modification and promotes tumorigenesis through arginine methylation at the C-terminus of METTL14.