eIF4A inhibitors suppress cell-cycle feedback response and acquired resistance to CDK4/6 inhibition in cancer

CDK4/6 inhibitors are FDA-approved drugs for estrogen receptor-positive (ER+) breast cancer and are being evaluated to treat other tumor types, including KRAS-mutant non-small cell lung cancer (NSCLC). However, their clinical utility is often limited by drug resistance. Here, we sought to better understand the resistant mechanisms and help devise potential strategies to overcome this challenge. We show that treatment with CDK4/6 inhibitors in both ER+ breast cancer and KRAS-mutant NSCLC cells induces feedback upregulation of cyclin D1, CDK4, and cyclin E1, mediating drug resistance. We demonstrate that rocaglates, which preferentially target translation of key cell-cycle regulators, effectively suppress this feedback upregulation induced by CDK4/6 inhibition. Consequently, combination treatment of CDK4/6 inhibitor palbociclib with the eukaryotic initiation factor (eIF) 4A inhibitor, CR-1-31-B, is synergistic in suppressing the growth of these cancer cells in vitro and in vivo Furthermore, ER+ breast cancer and KRAS-mutant NSCLC cells that acquired resistance to palbociclib after chronic drug exposure are also highly sensitive to this combination treatment strategy. Our findings reveal a novel strategy using eIF4A inhibitors to suppress cell-cycle feedback response and to overcome resistance to CDK4/6 inhibition in cancer.Accepted manuscrip

Ultra-fast self-assembly and stabilization of reactive nanoparticles in reduced graphene oxide films.

Nanoparticles hosted in conductive matrices are ubiquitous in electrochemical energy storage, catalysis and energetic devices. However, agglomeration and surface oxidation remain as two major challenges towards their ultimate utility, especially for highly reactive materials. Here we report uniformly distributed nanoparticles with diameters around 10 nm can be self-assembled within a reduced graphene oxide matrix in 10 ms. Microsized particles in reduced graphene oxide are Joule heated to high temperature (∼1,700 K) and rapidly quenched to preserve the resultant nano-architecture. A possible formation mechanism is that microsized particles melt under high temperature, are separated by defects in reduced graphene oxide and self-assemble into nanoparticles on cooling. The ultra-fast manufacturing approach can be applied to a wide range of materials, including aluminium, silicon, tin and so on. One unique application of this technique is the stabilization of aluminium nanoparticles in reduced graphene oxide film, which we demonstrate to have excellent performance as a switchable energetic material

Deep learning-based holographic polarization microscopy

Polarized light microscopy provides high contrast to birefringent specimen and is widely used as a diagnostic tool in pathology. However, polarization microscopy systems typically operate by analyzing images collected from two or more light paths in different states of polarization, which lead to relatively complex optical designs, high system costs or experienced technicians being required. Here, we present a deep learning-based holographic polarization microscope that is capable of obtaining quantitative birefringence retardance and orientation information of specimen from a phase recovered hologram, while only requiring the addition of one polarizer/analyzer pair to an existing holographic imaging system. Using a deep neural network, the reconstructed holographic images from a single state of polarization can be transformed into images equivalent to those captured using a single-shot computational polarized light microscope (SCPLM). Our analysis shows that a trained deep neural network can extract the birefringence information using both the sample specific morphological features as well as the holographic amplitude and phase distribution. To demonstrate the efficacy of this method, we tested it by imaging various birefringent samples including e.g., monosodium urate (MSU) and triamcinolone acetonide (TCA) crystals. Our method achieves similar results to SCPLM both qualitatively and quantitatively, and due to its simpler optical design and significantly larger field-of-view, this method has the potential to expand the access to polarization microscopy and its use for medical diagnosis in resource limited settings.Comment: 20 pages, 8 figure

Transfer-free, lithography-free and fast growth of patterned CVD graphene directly on insulators by using sacrificial metal catalyst

Chemical vapor deposited graphene suffers from two problems: transfer from metal catalysts to insulators, and photoresist induced degradation during patterning. Both result in macroscopic and microscopic damages such as holes, tears, doping, and contamination, translated into property and yield dropping. We attempt to solve the problems simultaneously. A nickel thin film is evaporated on SiO2 as a sacrificial catalyst, on which surface graphene is grown. A polymer (PMMA) support is spin-coated on the graphene. During the Ni wet etching process, the etchant can permeate the polymer, making the etching efficient. The PMMA/graphene layer is fixed on the substrate by controlling the surface morphology of Ni film during the graphene growth. After etching, the graphene naturally adheres to the insulating substrate. By using this method, transfer-free, lithography-free and fast growth of graphene realized. The whole experiment has good repeatability and controllability. Compared with graphene transfer between substrates, here, no mechanical manipulation is required, leading to minimal damage. Due to the presence of Ni, the graphene quality is intrinsically better than catalyst-free growth. The Ni thickness and growth temperature are controlled to limit the number of layers of graphene. The technology can be extended to grow other two-dimensional materials with other catalysts

Exogenously scavenged and endogenously synthesized heme are differentially utilized by Mycobacterium tuberculosis

Heme is both an essential cofactor and an abundant source of nutritional iron for the human pathogen Mycobacterium tuberculosis. While heme is required for M. tuberculosis survival and virulence, it is also potentially cytotoxic. Since M. tuberculosis can both synthesize and take up heme, the de novo synthesis of heme and its acquisition from the host may need to be coordinated in order to mitigate heme toxicity. However, the mechanisms employed by M. tuberculosis to regulate heme uptake, synthesis, and bioavailability are poorly understood. By integrating ratiometric heme sensors with mycobacterial genetics, cell biology, and biochemistry, we determined that de novo-synthesized heme is more bioavailable than exogenously scavenged heme, and heme availability signals the downregulation of heme biosynthetic enzyme gene expression. Ablation of heme synthesis does not result in the upregulation of known heme import proteins. Moreover, we found that de novo heme synthesis is critical for survival from macrophage assault. Altogether, our data suggest that mycobacteria utilize heme from endogenous and exogenous sources differently and that targeting heme synthesis may be an effective therapeutic strategy to treat mycobacterial infections. IMPORTANCE Mycobacterium tuberculosis infects ~25% of the world's population and causes tuberculosis (TB), the second leading cause of death from infectious disease. Heme is an essential metabolite for M. tuberculosis, and targeting the unique heme biosynthetic pathway of M. tuberculosis could serve as an effective therapeutic strategy. However, since M. tuberculosis can both synthesize and scavenge heme, it was unclear if inhibiting heme synthesis alone could serve as a viable approach to suppress M. tuberculosis growth and virulence. The importance of this work lies in the development and application of genetically encoded fluorescent heme sensors to probe bioavailable heme in M. tuberculosis and the discovery that endogenously synthesized heme is more bioavailable than exogenously scavenged heme. Moreover, it was found that heme synthesis protected M. tuberculosis from macrophage killing, and bioavailable heme in M. tuberculosis is diminished during macrophage infection. Altogether, these findings suggest that targeting M. tuberculosis heme synthesis is an effective approach to combat M. tuberculosis infections.Microbiology and Molecular Genetic

A High-Precision Machine Learning Algorithm to Classify Left and Right Outflow Tract Ventricular Tachycardia

Introduction: Multiple algorithms based on 12-lead ECG measurements have been proposed to identify the right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originate. However, a clinical-grade machine learning algorithm that automatically analyzes characteristics of 12-lead ECGs and predicts RVOT or LVOT origins of VT and PVC is not currently available. The effective ablation sites of RVOT and LVOT, confirmed by a successful ablation procedure, provide evidence to create RVOT and LVOT labels for the machine learning model. Methods: We randomly sampled training, validation, and testing data sets from 420 patients who underwent successful catheter ablation (CA) to treat VT or PVC, containing 340 (81%), 38 (9%), and 42 (10%) patients, respectively. We iteratively trained a machine learning algorithm supplied with 1,600,800 features extracted via our proprietary algorithm from 12-lead ECGs of the patients in the training cohort. The area under the curve (AUC) of the receiver operating characteristic curve was calculated from the internal validation data set to choose an optimal discretization cutoff threshold. Results: The proposed approach attained the following performance: accuracy (ACC) of 97.62 (87.44–99.99), weighted F1-score of 98.46 (90–100), AUC of 98.99 (96.89–100), sensitivity (SE) of 96.97 (82.54–99.89), and specificity (SP) of 100 (62.97–100). Conclusions: The proposed multistage diagnostic scheme attained clinical-grade precision of prediction for LVOT and RVOT locations of VT origin with fewer applicability restrictions than prior studies