Recent Progress in the Use of Glucagon and Glucagon Receptor Antagonists in the Treatment of Diabetes Mellitus

Glucagon is an important pancreatic hormone, released into blood circulation by alpha cells of the islet of Langerhans. Glucagon induces gluconeogenesis and glycogenolysis in hepatocytes, leading to an increase in hepatic glucose production and subsequently hyperglycemia in susceptible individuals. Hyperglucagonemia is a constant feature in patients with T2DM. A number of bioactive agents that can block glucagon receptor have been identified. These glucagon receptor antagonists can reduce the hyperglycemia associated with exogenous glucagon administration in normal as well as diabetic subjects. Glucagon receptor antagonists include isoserine and beta-alanine derivatives, bicyclic 19-residue peptide BI-32169, Des-His1-[Glu9] glucagon amide and related compounds, 5-hydroxyalkyl-4-phenylpyridines, N-[3-cano-6- (1,1 dimethylpropyl)-4,5,6,7-tetrahydro-1-benzothien-2-yl]-2-ethylbutamide, Skyrin and NNC 250926. The absorption, dosage, catabolism, excretion and medicinal chemistry of these agents are the subject of this review. It emphasizes the role of glucagon in glucose homeostasis and how it could be applied as a novel tool for the management of diabetes mellitus by blocking its receptors with either monoclonal antibodies, peptide and non-peptide antagonists or gene knockout techniques

Targeted profiling of human extrachromosomal DNA by CRISPR-CATCH

Extrachromosomal DNA (ecDNA) is a common mode of oncogene amplification but is challenging to analyze. Here, we adapt CRISPR-CATCH, in vitro CRISPR-Cas9 treatment and pulsed field gel electrophoresis of agarose-entrapped genomic DNA, previously developed for bacterial chromosome segments, to isolate megabase-sized human ecDNAs. We demonstrate strong enrichment of ecDNA molecules containing EGFR, FGFR2 and MYC from human cancer cells and NRAS ecDNA from human metastatic melanoma with acquired therapeutic resistance. Targeted enrichment of ecDNA versus chromosomal DNA enabled phasing of genetic variants, identified the presence of an EGFRvIII mutation exclusively on ecDNAs and supported an excision model of ecDNA genesis in a glioblastoma model. CRISPR-CATCH followed by nanopore sequencing enabled single-molecule ecDNA methylation profiling and revealed hypomethylation of the EGFR promoter on ecDNAs. We distinguished heterogeneous ecDNA species within the same sample by size and sequence with base-pair resolution and discovered functionally specialized ecDNAs that amplify select enhancers or oncogene-coding sequences

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Factor Analysis Invariant To Linear Transformations Of Data

Modeling data with Gaussian distributions is an important statistical problem. To obtain robust models one imposes constraints the means and covariances of these distributions [6, 4, 10, 8]. Constrained ML modeling implies the existence of optimal feature spaces where the constraints are more valid [2, 3]. This paper introduces one such constrained ML modeling technique called factor analysis invariant to linear transformations (FACILT) which is essentially factor analysis in optimal feature spaces. FACILT is a generalization of several existing methods for modeling covariances. This paper presents an EM algorithm for FACILT modeling

Techniques for capturing temporal variations in speech signals with processing

Fixed-rate feature extraction which is used in most current speech recognizers is equivalent to sampling the feature trajectories at a uniform rate. Often this sampling rate is well below the Nyquist rate and thus leads to distortions in the sampled feature stream due to aliasing. In this paper we explore various techniques, ranging from simple cepstral and spectral smoothing to ltering and data-driven dimensionality expansion using Linear Discriminant Analysis (LDA), to counter aliasing and the variable rate nature of information in speech signals. Smoothing in the spectral domain results in a reduction in the variance of the short term spectral estimates which directly translates to reduction in the variances of the Gaussians in the acoustic models. With these techniques we obtain modest improvements, both in word error rate and robustness to noise, on large vocabulary speech recognition tasks. 1

Surface and bulk reconstruction of CoW sulfides during pH-universal electrocatalytic hydrogen evolution

Electrocatalytic water splitting is an efficient means of producing energy carriers, such as H2. The hydrogen evolution reaction (HER) requires high-efficiency electrocatalysts. Understanding the active site structures of the HER electrocatalysts is essential for the rational design and development of water splitting devices. In this study, porous CoW sulfides were employed as model electrocatalysts for pH-universal HER. Multiple characterization studies, such as X-ray photoelectron spectroscopy, X-ray absorption spectroscopy and operando X-ray diffraction, were systematically used to investigate the reconstruction of the active species at the surface and in the bulk. The results show that during the HER, the structural transformation of the species CoW sulfides is strongly dependent on the pH of the electrolyte. Electrolytes of varying pH lead to varied reconstruction and influence the true catalytically active species responsible for the HER. The surface and the bulk of the electrocatalysts transform to different oxides/hydroxides when subjected to the HER. This is the first time that the pH-dependent bulk and surface structural evolution in the HER has been revealed. This study reveals the reconstruction and potential active site evolution of mixed-metal sulfides for the HER. We believe that the present study not only provides an idealized “pre-catalyst” for pH-universal highly-efficient HER, but also provides a thorough understanding about the identification of the real active sites and the mechanism of the structural evolution of the electrocatalysts during hydrogen evolution

Amorphous WO3WO_{3} Induced Lattice Distortion for a Low-Cost and Highly-Efficient Electrocatalyst for Overall Water Splitting in Acid

The development of highly active and durable catalysts for water oxidation under acidic conditions is necessary but challenging for renewable energy conversion. Ir-based catalysts are highly efficient for water oxidation in acid, but their large scale application is hindered by the high cost and scarcity of iridium. Herein, we use an amorphous WO$_3$ induced lattice distortion (AWILD) strategy to reduce the Ir content to only 2 wt% in the final material. The optimized hybrid nitrogen-doped carbon (NC)/WO$_3$/IrO$_2$ can efficiently catalyze water oxidation with a low overpotential of 270 mV at 10 mA cm$^{−2}$ current density $(η_{10})$ and a high turnover frequency of over 2 s$^{−1}$ at 300 mV overpotential in 0.5 M H$_2$SO$_4$, a performance that surpasses that of commercial IrO$_2$ significantly. Introducing the layer of amorphous WO$_3$ between IrO$_2$ nanoparticles and NC can distort the lattice of IrO$_2$, exposing more highly active sites for water oxidation. The AWILD effect compensates for the lower Ir content and dramatically reduces the cost of the catalyst without sacrificing the catalytic activity. Additionally, this catalyst also exhibits high activity in acid for hydrogen evolution with only 65 mV of $η_{10}$ attributed to the AWILD effect, exhibiting efficient bifunctionality as a Janus catalyst for overall water splitting. The AWILD approach provides a novel and efficient strategy for low-cost and highly efficient electrocatalysts for acidic overall water splitting with an extremely low content of noble metals