Cysteine-Selective Modification of Peptides and Proteins via Desulfurative C-C Bond Formation.

The site-selective modification of peptides and proteins facilitates the preparation of targeted therapeutic agents and tools to interrogate biochemical pathways. Among the numerous bioconjugation techniques developed to install groups of interest, those that generate C(sp3 )-C(sp3 ) bonds are significantly underrepresented despite affording proteolytically stable, biogenic linkages. Herein, a visible-light-mediated reaction is described that enables the site-selective modification of peptides and proteins via desulfurative C(sp3 )-C(sp3 ) bond formation. The reaction is rapid and high yielding in peptide systems, with comparable translation to proteins. Using this chemistry, a range of moieties is installed into model systems and an effective PTM-mimic is successfully integrated into a recombinantly expressed histone.

Research of Dynamic Tensile Properties of Five Rocks under Three Loading Modes Based on SHPB Device.

The validity of calculating the dynamic tensile strength of rock materials based on dynamic Brazilian tests is problematic. In order to gain a deeper understanding of the effects of three typical loading methods on the damage mechanism of rock specimens in the dynamic Brazilian tests, five different rocks were selected for the study. In the constant incident energy dynamic Brazilian test, the loading modes had a significant effect on the loading rate and dynamic tensile strength of the specimen, with the highest loading rate and tensile strength of the specimens under mode-III loading, followed by mode-I loading and mode-II loading. A high-speed camera and the digital image correlation (DIC) technique were used to successfully capture the rupture process of the Brazilian disc during impact loading. The evolution of the displacement and strain fields of the specimen was obtained by DIC technique, and four typical failure patterns and two rupture characteristics in the dynamic Brazilian test were summarized. The loading mode determined the crack initiation position of the specimen in the dynamic Brazilian test. The results showed that the mode-III loading is the most consistent with the Brazilian test theory, while the mode-II loading violates the test principle.

Multiplexed lateral flow assay integrated with orthogonal CRISPR-Cas system for SARS-CoV-2 detection.

The development of field-deployable detection platform amenable for multiplexed genes testing will significantly improve the efficiency and reliability during point-of-care testing (POCT) applications. In this regard, an orthogonal CRISPR-Cas-mediated multiplexed lateral flow assay (designated as OC-MLFA) is proposed for SARS-CoV-2 genome detection. Taking the advantage of activation and cleavage preferences between Cas12a and Cas13a, orthogonal (two-independent-channel signal readout) CRISPR-Cas system is investigated. Lateral flow strips with two target lines are designed to accommodate the orthogonal CRISPR system. The interference between Cas12a and Cas13a channels can be effectively eliminated via the elaborate nucleic acids and lateral flow strips design. The high preamplification efficiency from reverse transcription recombinase polymerase amplification (RT-RPA) and Cas enzyme mediated trans-cleavage process bring the sensitivity of our OC-MLFA method to 10 copies per test (30 µL). Nasopharyngeal swab clinical samples with different cycle threshold (Ct) values according to the RT-PCR method were analyzed with the proposed OC-MLFA, during which 76 out of 76 detection accuracy was obtained. Featured with the multiplexed genes detection simultaneously in one reaction and colorimetric readout through single strip, the OC-MLFA we proposed herein ensures great accuracy and efficiency, which endows promising field-deployable POCT application feasibility.

A Novel Method of Multitype Hybrid Rock Lithology Classification Based on Convolutional Neural Networks.

Rock lithology recognition plays a fundamental role in geological survey research, mineral resource exploration, mining engineering, etc. However, the objectivity of researchers, rock variable natures, and tedious experimental processes make it difficult to ensure the accurate and effective identification of rock lithology. Additionally, multitype hybrid rock lithology identification is challenging, and few studies on this issue are available. In this paper, a novel multitype hybrid rock lithology detection method was proposed based on convolutional neural network (CNN), and neural network model compression technology was adopted to guarantee the model inference efficiency. Four fundamental single class rock datasets: sandstone, shale, monzogranite, and tuff were collected. At the same time, multitype hybrid rock lithologies datasets were obtained based on data augmentation method. The proposed model was then trained on multitype hybrid rock lithologies datasets. Besides, for comparison purposes, the other three algorithms, were trained and evaluated. Experimental results revealed that our method exhibited the best performance in terms of precision, recall, and efficiency compared with the other three algorithms. Furthermore, the inference time of the proposed model is twice as fast as the other three methods. It only needs 11 milliseconds for single image detection, making it possible to be applied to the industry by transforming the algorithm to an embedded hardware device or Android platform.

Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments.

Rockburst is a severe geological hazard that restricts deep mine operations and tunnel constructions. To overcome the shortcomings of widely used algorithms in rockburst prediction, this study investigates the ensemble trees, i.e., random forest (RF), extremely randomized tree (ET), adaptive boosting machine (AdaBoost), gradient boosting machine, extreme gradient boosting machine (XGBoost), light gradient boosting machine, and category gradient boosting machine, for rockburst estimation based on 314 real rockburst cases. Additionally, Bayesian optimization is utilized to optimize these ensemble trees. To improve performance, three combination strategies, voting, bagging, and stacking, are adopted to combine multiple models according to training accuracy. ET and XGBoost receive the best capabilities (85.71% testing accuracy) in single models, and except for AdaBoost, six ensemble trees have high accuracy and can effectively foretell strong rockburst to prevent large-scale underground disasters. The combination models generated by voting, bagging, and stacking perform better than single models, and the voting 2 model that combines XGBoost, ET, and RF with simple soft voting, is the most outstanding (88.89% testing accuracy). The performed sensitivity analysis confirms that the voting 2 model has better robustness than single models and has remarkable adaptation and superiority when input parameters vary or miss, and it has more power to deal with complex and variable engineering environments. Eventually, the rockburst cases in Sanshandao Gold Mine, China, were investigated, and these data verify the practicability of voting 2 in field rockburst prediction.

Mechanistic studies of reactive oxygen species mediated electrochemical radical reactions of alkyl iodides.

Mechanistic studies of a reactive oxygen species mediated electrochemical radical reaction of alkyl iodides are described. Hydroxyl radicals and ozone are identified to be the active species involved in the formation of alkyl radicals under mildly reducing potential (-1.0 V vs. Ag QRE) in buffered acidic conditions (pH 3.6).

Electrochemical radical reactions of alkyl iodides: a highly efficient, clean, green alternative to tin reagents.

An electrochemical 'redox-relay' system has been developed which allows the generation of C-centered radicals. Intermolecular 'tin-like' radical reactions can subsequently be conducted under the most benign of conditions. The yields and efficiency of the processes are competitive and even superior in most cases to comparable conditions with tributyltin hydride. The use of air and electricity as the promotor (instead of a tin or other reagent) combined with the aqueous reaction media make this a clean and 'green' alternative to these classic C-C bond forming processes.

Relation of renin-angiotensin system gene polymorphisms and expressions with the efficacy of antihypertensive drugs.

OBJECTIVE: To investigate the relation of renin-angiotensin system (RA3) gene polymorphisms and expressions with the clinical efficacy of antihypertensive drugs. METHODS: This randomized, single-blind study consisted of 90 patients with essential hypertension, who were divided into losartan, lisinopril and nisodipine groups with corresponding medications as indicated. The genotypes of angiotensin-converting enzyme (ACE) insertion/deletion, angiotensinogen (AGT) M235T polymorphism and expressions of ACE and AT1 receptor genes were examined individually. RESULTS: The basal level of mRNA expression of AT1 receptor was lower in patients with MM genotype of AGT gene than those in patients with MT 1 and TT genotypes, but between the latter two, no significant differences were found. The three antihypertensive drugs, when significantly lowering the blood pressure, reduced AT1 receptor mRNA expression concurrently. Losartan and lisinopril both decreased ACE mRNA expression levels that were positively correlated with the difference of the diastolic blood pressure whereas nisodipine elevated ACE mRNA expression, showing inverse correlation to the difference of thediastolic blood pressure. CONCLUSION: For patients with hypertension who have elevated basal levels of AT1 mRNA expression and AGT T allele or who retain high basal expression levels of ACE mRNA AT1 antagonists and ACE inhibitors that execute their action through RAS are preferentially selected, and in cases of low basal levels of ACE mRNA calcium antagonists are preferred.