Although KRAS
inhibitors have shown promising activity in lung adenocarcinomas harbouring KRAS
, acquired resistance to these therapies eventually occurs in most patients. Re-expression of KRAS is ...thought to be one of the main causes of acquired resistance. However, the mechanism through which cancer cells re-express KRAS is not fully understood. Here, we report that the Hedgehog signal is induced by KRAS
inhibitors and mediates KRAS re-expression in cancer cells treated with a KRAS
inhibitor. Further, KRAS
inhibitors induced the formation of primary cilia and activated the Hedgehog-GLI-1 pathway. GLI-1 binds to the KRAS promoter region, enhancing KRAS promoter activity and KRAS expression. Inhibition of GLI using siRNA or the smoothened (Smo) inhibitor suppressed re-expression of KRAS in cells treated with a KRAS
inhibitor. In addition, we demonstrate that KRAS
inhibitors decreased Aurora kinase A (AURKA) levels in cancer cells, and inhibition of AURKA using siRNA or inhibitors led to increased expression levels of GLI-1 and KRAS even in the absence of KRAS inhibitor. Ectopic expression of AURKA attenuated the effect of KRAS
inhibitors on the expression of GLI-1 and re-expression of KRAS. Together, these findings demonstrate the important role of AURKA, primary cilia, and Hedgehog signals in the re-expression of KRAS and therefore the induction of acquired resistance to KRAS
inhibitors, and provide a rationale for targeting Hedgehog signalling to overcome acquired resistance to KRAS
inhibitors.
In patients with Parkinson's disease (PD), stem cells can serve as therapeutic agents to restore or regenerate injured nervous system. Here, we differentiated two types of stem cells; mouse embryonic ...stem cells (mESCs) and protein-based iPS cells (P-iPSCs) generated by non-viral methods, into midbrain dopaminergic (mDA) neurons, and then compared the efficiency of DA neuron differentiation from these two cell types. In the undifferentiated stage, P-iPSCs expressed pluripotency markers as ES cells did, indicating that protein-based reprogramming was stable and authentic. While both stem cell types were differentiated to the terminally-matured mDA neurons, P-iPSCs showed higher DA neuron-specific markers' expression than ES cells. To investigate the mechanism of the superior induction capacity of DA neurons observed in P-iPSCs compared to ES cells, we analyzed histone modifications by genome-wide ChIP sequencing analysis and their corresponding microarray results between two cell types. We found that Wnt signaling was up-regulated, while SFRP1, a counter-acting molecule of Wnt, was more suppressed in P-iPSCs than in mESCs. In PD rat model, transplantation of neural precursor cells derived from both cell types showed improved function. The present study demonstrates that P-iPSCs could be a suitable cell source to provide patient-specific therapy for PD without ethical problems or rejection issues.
Network quantization is an essential procedure in deep learning for development of efficient fixed-point inference models on mobile or edge platforms. However, as datasets grow larger and privacy ...regulations become stricter, data sharing for model compression gets more difficult and restricted. In this paper, we consider data-free network quantization with synthetic data. The synthetic data are generated from a generator, while no data are used in training the generator and in quantization. To this end, we propose data-free adversarial knowledge distillation, which minimizes the maximum distance between the outputs of the teacher and the (quantized) student for any adversarial samples from a generator. To generate adversarial samples similar to the original data, we additionally propose matching statistics from the batch normalization layers for generated data and the original data in the teacher. Furthermore, we show the gain of producing diverse adversarial samples by using multiple generators and multiple students. Our experiments show the state-of-the-art data-free model compression and quantization results for (wide) residual networks and MobileNet on SVHN, CIFAR-10, CIFAR-100, and Tiny-ImageNet datasets. The accuracy losses compared to using the original datasets are shown to be very minimal.
The specific objective of developing neural interfaces is to analyze the electrophysiological signals associated with neural activities within the body, with the aim of providing early diagnosis for ...diseases related to the neural system. One example is the electrocardiogram (ECG) that assesses the functionality of the heart, identifying arrhythmias and potentially pinpointing the location of any malfunction. Conventional clinical protocols require cardiac electrical signal measurements to be conducted during a stationary phase, with an emphasis on minimizing noise interference as much as possible. While this holds true in clinical scenarios, such motion artifacts can be valuable sources of information for motion tracking. In this study, we present a methodology where we demonstrate the simultaneous monitoring and computation of both heart rate and motion using a wireless ECG sensing system with a three-electrode configuration.
Recently, the digital X‐ray detector (DXD) technology requires high quality and high frame rate dynamic images, so efforts are being made to apply an oxide semiconductor (OS) thin film transistor ...(TFT) to the DXD backplane as a switching device instead of an amorphous Si (a‐Si) TFT. In order for the OS TFT to be used as a switching device of the X‐ray detector, it is necessary to study about the degradation parameters of the OS TFT under X‐ray irradiation. We confirmed that the threshold voltage (Vth) of the InGaZnO (IGZO) TFTs shifted negatively without s‐factor degradation according to X‐ray exposure. To understand these characteristics, we evaluated the X‐ray degradation characteristics of various methods.
Abstract
Glioblastoma (GBM) is one of the most lethal human tumors with a highly infiltrative phenotype. Although invasiveness is related to poor prognosis, no therapeutic intervention targeting ...invasion is available for treatment of GBM patient, partially due to the diversity and redundancy of invasion machinery genes. In this regard, additional identification of deterministic and causative targets for invasion is required. Invasiveness of GBM patients and matched tumorspheres (TSs) was quantified using MR images and collagen-based 3D invasion assays, respectively. Transcriptome of GBM samples were obtained using microarrays. The knockdown effects of invasion-deterministic transcription factors (TFs) were evaluated using western blot and mouse orthotopic xenograft model. This study is aimed to identify novel transcriptional regulatory networks, which can collectively modulate invasion-involved genes in GBM. After classification of 23 GBM patient-derived TSs into low and high invasion groups, we applied single sample gene set enrichment analysis using TF target gene sets. According to enrichment scores, TFs responsible for low (PCBP1) and high (STAT3 and SRF) invasiveness were identified. Consistently with computational prediction, knockdown of PCBP1 significantly increased invasion area, whereas knockdown of STAT3 or SRF significantly suppressed invasive properties in all tested TSs. Notably, MR images showed coherent patterns with invasion of originated TS, and high invasiveness was associated with poor prognosis. In addition, mouse orthotopic xenograft model using TSs with down-regulated STAT3 or SRF showed significantly prolonged survival time compared to control. We identified invasion-deterministic TFs in glioblastoma using integrative transcriptome analysis. Owing to relationship among these transcriptional regulatory networks, invasive phenotype, and prognosis, we suggest that these TFs as novel drug targets for GBM.
Over the past decade, a number of studies have demonstrated the resistance of cancer cells to conventional drugs and have recognized this as a major challenge in cancertherapy. While attempting to ...understand the underlying mechanisms of chemoresistance, several studies have suggested that the presence of cancer stem cells (CSCs) in tumors is one of the major pathways contributing toward resistance. Chemoresistance leads to cancer treatment failure and worsens the prognosis of patients. Natural herbal compounds are gaining attention as an alternative treatment strategy for cancer. These compounds may be effective against chemoresistant cells either alone or synergistically alongside conventional drugs, sensitizing cancer cells and enhancing the therapeutic efficacy. BRM270 is a natural compound made from seven herbal plant (Saururus chinensis, Citrus unshiu Markovich, Aloe vera, Arnebia euchroma, Portulaca oleracea, Prunella vulgaris var. lilacina and Scutellaria bacicalensis) extracts used in Asian traditional medicine and has the potential to target CSCs. Several studies have demonstrated the positive effects of BRM270 against chemoresistant cancer and its synergy alongside existing cancer drugs, including paclitaxel and gefitinib. These effects have been observed against various cancer types, including resistant non-small cell lung cancer (NSCLC), glioblastoma, multi-drug resistant osteosarcoma, cervical cancer, pancreatic cancer and hepatocarcinoma. The present review discusses the effects of BRM270 treatment against CSC-associated chemoresistance in common types of cancer.
Here, we report a resistance mechanism that is induced through the modulation of 16S ribosomal RNA (rRNA) processing on the exposure of Escherichia coli cells to aminoglycoside antibiotics. We ...observed decreased expression levels of RNase G associated with increased RNase III activity on rng mRNA in a subgroup of E. coli isolates that transiently acquired resistance to low levels of kanamycin or streptomycin. Analyses of 16S rRNA from the aminoglycoside-resistant E. coli cells, in addition to mutagenesis studies, demonstrated that the accumulation of 16S rRNA precursors containing 3-8 extra nucleotides at the 5' terminus, which results from incomplete processing by RNase G, is responsible for the observed aminoglycoside resistance. Chemical protection, mass spectrometry analysis and cell-free translation assays revealed that the ribosomes from rng-deleted E. coli have decreased binding capacity for, and diminished sensitivity to, streptomycin and neomycin, compared with wild-type cells. It was observed that the deletion of rng had similar effects in Salmonella enterica serovar Typhimurium strain SL1344. Our findings suggest that modulation of the endoribonucleolytic activity of RNase III and RNase G constitutes a previously uncharacterized regulatory pathway for adaptive resistance in E. coli and related gram-negative bacteria to aminoglycoside antibiotics.
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