Unmasking the interplay between mTOR and Nox4: novel insights into the mechanism connecting diabetes and cancer.

Cancer was recently annexed to diabetic complications. Furthermore, recent studies suggest that cancer can increase the risk of diabetes. Consequently, diabetes and cancer share many risk factors, but the cellular and molecular pathways correlating diabetes and colon and rectal cancer (CRC) remain far from understood. In this study, we assess the effect of hyperglycemia on cancer cell aggressiveness in human colon epithelial adenocarcinoma cells in vitro and in an experimental animal model of CRC. Our results show that Nox (NADPH oxidase enzyme) 4-induced reactive oxygen species (ROS) production is deregulated in both diabetes and CRC. This is paralleled by inactivation of the AMPK and activation of the mammalian target of rapamycin (mTOR) C1 signaling pathways, resulting in 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) accumulation, induction of DNA damage, and exacerbation of cancer cell aggressiveness, thus contributing to the genomic instability and predisposition to increased tumorigenesis in the diabetic milieu. Pharmacologic activation of AMPK, inhibition of mTORC1, or blockade of Nox4 reduce ROS production, restore the homeostatic signaling of 8-oxoguanine DNA glycosylase/8-oxodG, and lessen the progression of CRC malignancy in a diabetic milieu. Taken together, our results identify the AMPK/mTORC1/Nox4 signaling axis as a molecular switch correlating diabetes and CRC. Modulating this pathway may be a strategic target of therapeutic potential aimed at reversing or slowing the progression of CRC in patients with or without diabetes.-Mroueh, F. M., Noureldein, M., Zeidan, Y. H., Boutary, S., Irani, S. A. M., Eid, S., Haddad, M., Barakat, R., Harb, F., Costantine, J., Kanj, R., Sauleau, E.-A., Ouhtit, A., Azar, S. T., Eid, A. H., Eid, A. A. Unmasking the interplay between mTOR and Nox4: novel insights into the mechanism connecting diabetes and cancer.

Efficient noise mitigation technique for quantum computing.

Quantum computers have enabled solving problems beyond the current machines' capabilities. However, this requires handling noise arising from unwanted interactions in these systems. Several protocols have been proposed to address efficient and accurate quantum noise profiling and mitigation. In this work, we propose a novel protocol that efficiently estimates the average output of a noisy quantum device to be used for quantum noise mitigation. The multi-qubit system average behavior is approximated as a special form of a Pauli Channel where Clifford gates are used to estimate the average output for circuits of different depths. The characterized Pauli channel error rates, and state preparation and measurement errors are then used to construct the outputs for different depths thereby eliminating the need for large simulations and enabling efficient mitigation. We demonstrate the efficiency of the proposed protocol on four IBM Q 5-qubit quantum devices. Our method demonstrates improved accuracy with efficient noise characterization. We report up to 88% and 69% improvement for the proposed approach compared to the unmitigated, and pure measurement error mitigation approaches, respectively.

A Portable Non-Invasive Electromagnetic Lesion-Optimized Sensing Device for the Diagnosis of Skin Cancer (SkanMD).

The article presented herein proposes an alternative skin cancer screening method that delivers non-invasive diagnosis and monitoring of skin lesions by leveraging electromagnetic waves with radio frequency technology and circuits. The proposed handheld device, named SkanMD, comprises a sensitive electromagnetic sensor, customized radio frequency wave analyzer circuits, and machine learning algorithms. The device is used in clinical studies that are performed on a total of 46 individuals that are composed of 18 patients with pre-diagnosed skin cancer, 10 individuals with benign nevi, 7 patients with arbitrary diseases, and 11 healthy individuals. These studies included the measurement of the reflection coefficient, S11, on multiple skin regions and recording the obtained complex values to build a Support Vector Machine (SVM)-based classification model. Due to the lesion-optimized sensor and the unified cross-patient classifier, our results differentiate between cancerous and non-cancerous skin lesions with a sensitivity that exceeds 92% and a specificity that exceeds 81.4%. These reported results are based on a limited population size study. They also demonstrate that SkanMD is a promising solution that could augment conventional diagnosis methods to greatly improve patient comfort and enable instantaneous and accurate diagnosis.

Wearable flexible body matched electromagnetic sensors for personalized non-invasive glucose monitoring.

This work introduces novel body-matched, vasculature-inspired, quasi-antenna-arrays that act as electromagnetic sensors to instantaneously, continuously, and wirelessly sense glucose variations in the bloodstream. The proposed sensors are personalized, leverage electromagnetic waves, and are coupled with a custom machine-learning-based signal-processing module. These sensors are flexible, and embedded in wearable garments such as socks, which provide conformity to curved skin surfaces and movement resilience. The entire wearable system is calibrated against temperature, humidity, and movement resulting in high accuracy in glucose variations tracking. In-Vivo experiments on diabetic rats and pigs exhibit a 100% diagnostic accuracy over a wide range of glucose variations. Human trials on patients with diabetes and healthy individuals reveal a clinical accuracy of continuous glucose monitoring of 99.01% in twenty-eight subjects who underwent Oral Glucose Tolerance Tests. Hence, our approach ensures the continuous tracking of glucose variations from hypo-to-hyper glycemic levels with great fidelity.

Noninvasive, wearable, and tunable electromagnetic multisensing system for continuous glucose monitoring, mimicking vasculature anatomy.

Painless, needle-free, and continuous glucose monitoring sensors are needed to enhance the life quality of diabetic patients. To that extent, we propose a first-of-its-kind, highly sensitive, noninvasive continuous glycemic monitoring wearable multisensor system. The proposed sensors are validated on serum, animal tissues, and animal models of diabetes and in a clinical setting. The noninvasive measurement results during human trials reported high correlation (>0.9) between the system's physical parameters and blood glucose levels, without any time lag. The accurate real-time responses of the sensors are attributed to their unique vasculature anatomy-inspired tunable electromagnetic topologies. These wearable apparels wirelessly sense hypo- to hyperglycemic variations with high fidelity. These components are designed to simultaneously target multiple body locations, which opens the door for the development of a closed-loop artificial pancreas.