GARNL3 identified as a crucial target for overcoming temozolomide resistance in EGFRvIII-positive glioblastoma.

OBJECT: Amplification of the epidermal growth factor receptor (EGFR) and its active mutant type III (EGFRvIII), frequently occurr in glioblastoma (GBM), contributing to chemotherapy and radiation resistance in GBM. Elucidating the underlying molecular mechanism of temozolomide (TMZ) resistance in EGFRvIII GBM could offer valuable insights for cancer treatment. METHODS: To elucidate the molecular mechanisms underlying EGFRvIII-mediated resistance to TMZ in GBM, we conducted a comprehensive analysis using Gene Expression Omnibus and The cancer genome atlas (TCGA) databases. Initially, we identified common significantly differentially expressed genes (DEGs) and prioritized those correlating significantly with patient prognosis as potential downstream targets of EGFRvIII and candidates for drug resistance. Additionally, we analyzed transcription factor expression changes and their correlation with candidate genes to elucidate transcriptional regulatory mechanisms. Using estimate method and databases such as Tumor IMmune Estimation Resource (TIMER) and CellMarker, we assessed immune cell infiltration in TMZ-resistant GBM and its relationship with candidate gene expression. In this study, we examined the expression differences of candidate genes in GBM cell lines following EGFRvIII intervention and in TMZ-resistant GBM cell lines. This preliminary investigation aimed to verify the regulatory impact of EGFRvIII on candidate targets and its potential involvement in TMZ resistance in GBM. RESULTS: Notably, GTPase Activating Rap/RanGAP Domain Like 3 (GARNL3) emerged as a key DEG associated with TMZ resistance and poor prognosis, with reduced expression correlating with altered immune cell profiles. Transcription factor analysis suggested Epiregulin (EREG) as a putative upstream regulator of GARNL3, linking it to EGFRvIII-mediated TMZ resistance. In vitro experiments confirmed EGFRvIII-mediated downregulation of GARNL3 and decreased TMZ sensitivity in GBM cell lines, further supported by reduced GARNL3 levels in TMZ-resistant GBM cells. CONCLUSION: GARNL3 downregulation in EGFRvIII-positive and TMZ-resistant GBM implicates its role in TMZ resistance, suggesting modulation of EREG/GARNL3 signaling as a potential therapeutic strategy.

6-mm shunt transjugular intrahepatic portosystemic shunt in patients with severe liver atrophy and variceal bleeding.

OBJECTIVES: We proposed a strategy for the creation of a 6-mm transjugular intrahepatic portosystemic shunt (TIPS) and to assess its effectiveness compared to a conventional 8-mm shunt for TIPS-induced hepatic encephalopathy (HE). METHODS: Patients were reviewed retrospectively using propensity score matching (1:1) and divided into 6-mm and 8-mm shunt groups based on shunt diameter. The stent patency, HE incidence, and rebleeding rate between the two groups were then compared. RESULTS: From January 2018 to June 2021, both 6-mm shunt group and 8-mm shunt group included 58 patients. The 6-mm shunt group had significantly smaller liver volumes (879.3 ± 237.1 vs. 1008.8 ± 293.0; p = 0.010), and the median stent patency times were 30.7 and 33.8 months in the 6-mm and 8-mm groups, respectively (p = 0.124). No statistically significant difference was found between the two groups in the 1-year (8.6% vs. 3.4%; p = 0.242) and 2-year (17.2% vs. 12.1%; p = 0.242) rebleeding rates. The 1-year cumulative incidences of overt HE were 12.1% and 27.6% in the 6-mm and 8-mm groups, respectively (p = 0.040), and the 2-year cumulative overt HE incidences in these groups were 19.0% and 36.2%, respectively (p = 0.038). Notably, patients with a 6-mm shunt also experienced less hepatic impairment. CONCLUSIONS: For patients with variceal bleeding and a small liver volume, the 6-mm shunt significantly reduced the incidence of overt HE, protected perioperative liver function, and did not affect stent patency or rebleeding rate. CLINICAL RELEVANCE STATEMENT: For patients with variceal bleeding with small liver volume, the 6-mm transjugular intrahepatic portosystemic shunt (TIPS) significantly reduced the incidence of overt hepatic encephalopathy after TIPS, protected perioperative liver function, and did not affect stent patency and rebleeding rate. KEY POINTS: • A strategy for the creation of a 6-mm transjugular intrahepatic portosystemic shunt for patients with variceal bleeding and a small liver volume was proposed. • The 6-mm transjugular intrahepatic portosystemic shunt significantly reduced the incidence of overt hepatic encephalopathy. • The 6-mm transjugular intrahepatic portosystemic shunt did not affect stent patency or rebleeding rate.

Leader-Following Consensus of Heterogeneous Linear Multiagent Systems With Communication Time-Delays via Adaptive Distributed Observers.

This article investigates the leader-following consensus problem of heterogeneous linear multiagent systems under switching and directed topologies. It is assumed that the communication between agents suffers from time-varying delays and only the neighboring agents of the leader are able to get access to the information of the leader agent, including its agent matrices. A key technical lemma on the input to state stability of time-delayed systems is first established with which the main results of this article can be obtained. An adaptive distributed observer, taking into consideration of communication time delays, is proposed for each follower to estimate the leader's system matrices and its state. Then, a distributed controller based on this adaptive observer is developed. We show that the resulting closed-loop multiagent system achieves the leader-following output consensus. Two examples are finally given to illustrate the effectiveness of the proposed controller.

Deep Learning Based Monitoring of Spatter Behavior by the Acoustic Signal in Selective Laser Melting.

As one of the most promising metal additive manufacturing (AM) technologies, the selective laser melting (SLM) process has high expectations ofr its use in aerospace, medical, and other fields. However, various defects such as spatter, crack, and porosity seriously hinder the applications of the SLM process. In situ monitoring is a vital technique to detect the defects in advance, which is expected to reduce the defects. This work proposed a method that combined acoustic signals with a deep learning algorithm to monitor the spatter behaviors. The acoustic signals were recorded by a microphone and the spatter information was collected by a coaxial high-speed camera simultaneously. The signals were divided into two types according to the number and intensity of spatter during the SLM process with different combinations of processing parameters. Deep learning models, one-dimensional Convolutional Neural Network (1D-CNN), two-dimensional Convolutional Neural Network (2D-CNN), Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) were trained to establish the relationships between the acoustic signals and characteristics of spatter. After K-fold verification, the highest classification confidence of models is 85.08%. This work demonstrates that it is feasible to use acoustic signals in monitoring the spatter defect during the SLM process. It is possible to use cheap and simple microphones instead of expensive and complicated high-speed cameras for monitoring spatter behaviors.