A highly selective electrochemical assay based on the Sakaguchi reaction for the detection of protein arginine methylation state

Protein arginine methylation is a common form of post-translational modification that plays an important role in many bioprocesses. However, research advances in this field have been severely hampered by the lack of a quick and sensitive method for detecting the arginine methylation state of a protein. In this work we propose a direct and sensitive electrochemical method for identifying the arginine methylation state. This novel assay combines an electrochemical technique with the Sakaguchi reaction, which is highly selective towards the arginine methylation state. We show that the presence of a methyl group on the arginine residue of a protein prevents the Sakaguchi reaction, while the unmethylated arginine residue selectively reacts with 8-hydroxyquinoline; the electrical signal of the reaction product is used for electrochemical detection. From this, a highly selective and simple electrochemical sensor has been developed based on (1) the high selectivity of the Sakaguchi reaction towards the arginine methylation state, and (2) the sensitive electrochemical signal generated by the linked 8-hydroxyquinoline. The assay described in this work thus provides a convenient tool for detection of protein arginine methylation, which may facilitate studies of the biological functions of protein arginine methylases and demethylases

Aptamer-Based Biosensor for Detection of Mycotoxins

Mycotoxins are a large type of secondary metabolites produced by fungi that pose a great hazard to and cause toxic reactions in humans and animals. A majority of countries and regulators, such as the European Union, have established a series of requirements for their use, and they have also set maximum tolerance levels. The development of high sensitivity and a specific analytical platform for mycotoxins is much in demand to address new challenges for food safety worldwide. Due to the superiority of simple, rapid, and low-cost characteristics, aptamer-based biosensors have successfully been developed for the detection of various mycotoxins with high sensitivity and selectivity compared with traditional instrumental methods and immunological approaches. In this article, we discuss and analyze the development of aptasensors for mycotoxins determination in food and agricultural products over the last 11 years and cover the literatures from the first report in 2008 until the present time. In addition, challenges and future trends for the selection of aptamers toward various mycotoxins and aptasensors for multi-mycotoxins analyses are summarized. Given the promising development and potential application of aptasensors, future research studies made will witness the great practicality of using aptamer-based biosensors within the field of food safety.Project of risk assessment on raw milk (GJFP2019026

Risk factors for recurrent IgA nephropathy after renal transplantation: A meta-analysis

Recurrent glomerulonephritis after renal transplantation is the third most common cause of allograft loss, the most frequent of which is associated with IgA nephropathy (IgAN). This study aims to provide a systematic review of the risk factors associated with recurrent IgAN after renal transplantation. We searched English and Chinese databases, including PubMed, Embase, Web of Science, CNKI, and others, and included all case-control studies involving risk factors for recurrent IgAN after renal transplantation from the databases’ establishment to March 2022. Data were analyzed using the Stata 12.0. A total of 20 case–control studies were included in the meta-analysis, with 542 patients with recurrent IgAN and 1385 patients without recurrent IgAN. The results showed that donor age (standardized mean difference [SMD] -0.13 [95% CI -0.26, -0.001]; P = 0.048), patient age at transplantation (SMD -0.41 [95% CI -0.53, -0.29]; P < 0.001), time from diagnosis to end-stage renal disease (SMD -0.42 [95% CI -0.74, -0.10]; P = 0.010), previous transplantation (odds ratio [OR] 1.73 [95% CI 1.06, 2.81]; P = 0.027), living donor (OR 1.86 [95% CI 1.34, 2.58]; P < 0.001), related donor (OR 2.64, [95% CI 1.84, 3.79]; P < 0.001), tacrolimus use (OR 0.71 [95% CI 0.52, 0.98]; P = 0.035), basiliximab use (OR 0.39 [95% CI 0.27, 0.55]; P < 0.001), proteinuria (SMD 0.42 [95% CI 0.13, 0.71]; P = 0.005) and serum IgA level (SMD 0.48 [95% CI 0.27, 0.69]; P < 0.001) were associated with recurrent IgAN after renal transplantation. In general, tacrolimus and basiliximab use were protective factors against recurrent IgAN after renal transplantation, whereas donor age, patient age at transplantation, time from diagnosis to end-stage renal disease, previous transplantation, living donor, related donor, proteinuria, and serum IgA level were risk factors for recurrent IgAN after renal transplantation. Clinical decision making should warrant further consideration of these risk factors

Risk factors for recurrent IgA nephropathy after renal transplantation: A meta-analysis

Recurrent glomerulonephritis after renal transplantation is the third most common cause of allograft loss, the most frequent of which is associated with IgA nephropathy (IgAN). This study aims to provide a systematic review of the risk factors associated with recurrent IgAN after renal transplantation. We searched English and Chinese databases, including PubMed, Embase, Web of Science, CNKI, and others, and included all case-control studies involving risk factors for recurrent IgAN after renal transplantation from the databases’ establishment to March 2022. Data were analyzed using the Stata 12.0. A total of 20 case–control studies were included in the meta-analysis, with 542 patients with recurrent IgAN and 1385 patients without recurrent IgAN. The results showed that donor age (standardized mean difference [SMD] -0.13 [95% CI -0.26, -0.001]; P = 0.048), patient age at transplantation (SMD -0.41 [95% CI -0.53, -0.29]; P < 0.001), time from diagnosis to end-stage renal disease (SMD -0.42 [95% CI -0.74, -0.10]; P = 0.010), previous transplantation (odds ratio [OR] 1.73 [95% CI 1.06, 2.81]; P = 0.027), living donor (OR 1.86 [95% CI 1.34, 2.58]; P < 0.001), related donor (OR 2.64, [95% CI 1.84, 3.79]; P < 0.001), tacrolimus use (OR 0.71 [95% CI 0.52, 0.98]; P = 0.035), basiliximab use (OR 0.39 [95% CI 0.27, 0.55]; P < 0.001), proteinuria (SMD 0.42 [95% CI 0.13, 0.71]; P = 0.005) and serum IgA level (SMD 0.48 [95% CI 0.27, 0.69]; P < 0.001) were associated with recurrent IgAN after renal transplantation. In general, tacrolimus and basiliximab use were protective factors against recurrent IgAN after renal transplantation, whereas donor age, patient age at transplantation, time from diagnosis to end-stage renal disease, previous transplantation, living donor, related donor, proteinuria, and serum IgA level were risk factors for recurrent IgAN after renal transplantation. Clinical decision making should warrant further consideration of these risk factors

Salp swarm optimization algorithm based MPPT design for PV-TEG hybrid system under partial shading conditions

This paper proposes an innovative strategy to integrate thermoelectric generator (TEG) and photovoltaic (PV) systems, aiming to enhance energy production efficiency by addressing the significant waste heat generated during traditional PV system operation. Additionally, photovoltaic-thermoelectric generator (PV-TEG) hybrid system encounters the dual challenge of partial shading conditions (PSC) and non-uniform temperature distribution (NTD). Thus, salp swarm optimization (SSA) is introduced to simultaneously tackle the negative impacts of PSC and NTD. In contrast to alternative meta-heuristic algorithms (MhAs) and conventional mathematical approaches, the streamlined and effective optimization mechanism inherent to SSA affords a shorter optimization time, while mitigating the risk of the PV-TEG hybrid system's optimization outcomes being confined to local maximum power points (LMPP). Furthermore, the optimization performance of SSA for PV-TEG hybrid systems is assessed via four case studies, including start-up test, stepwise variations in solar irradiation at constant temperature, stochastic change in solar irradiation, and field measured data for typical days in Hong Kong, in which simulation results show that SSA evinces unparalleled global exploration and local search capabilities, yielding heightened energy output (up to 43.75%) and effectively suppressing power fluctuations in the PV-TEG hybrid system (as evidenced by ΔVavg and ΔVmax)

Armeniacae semen amarum: a review on its botany, phytochemistry, pharmacology, clinical application, toxicology and pharmacokinetics

Armeniacae semen amarum—seeds of Prunus armeniaca L. (Rosaceae) (ASA), also known as Kuxingren in Chinese, is a traditional Chinese herbal drug commonly used for lung disease and intestinal disorders. It has long been used to treat coughs and asthma, as well as to lubricate the colon and reduce constipation. ASA refers to the dried ripe seed of diverse species of Rosaceae and contains a variety of phytochemical components, including glycosides, organic acids, amino acids, flavonoids, terpenes, phytosterols, phenylpropanoids, and other components. Extensive data shows that ASA exhibits various pharmacological activities, such as anticancer activity, anti-oxidation, antimicrobial activity, anti-inflammation, protection of cardiovascular, neural, respiratory and digestive systems, antidiabetic effects, and protection of the liver and kidney, and other activities. In clinical practice, ASA can be used as a single drug or in combination with other traditional Chinese medicines, forming ASA-containing formulas, to treat various afflictions. However, it is important to consider the potential adverse reactions and pharmacokinetic properties of ASA during its clinical use. Overall, with various bioactive components, diversified pharmacological actions and potent efficacies, ASA is a promising drug that merits in-depth study on its functional mechanisms to facilitate its clinical application

New Biological Insights Into How Deforestation in Amazonia Affects Soil Microbial Communities Using Metagenomics and Metagenome-Assembled Genomes

Deforestation in the Brazilian Amazon occurs at an alarming rate, which has broad effects on global greenhouse gas emissions, carbon storage, and biogeochemical cycles. In this study, soil metagenomes and metagenome-assembled genomes (MAGs) were analyzed for alterations to microbial community composition, functional groups, and putative physiology as it related to land-use change and tropical soil. A total of 28 MAGs were assembled encompassing 10 phyla, including both dominant and rare biosphere lineages. Amazon Acidobacteria subdivision 3, Melainabacteria, Microgenomates, and Parcubacteria were found exclusively in pasture soil samples, while Candidatus Rokubacteria was predominant in the adjacent rainforest soil. These shifts in relative abundance between land-use types were supported by the different putative physiologies and life strategies employed by the taxa. This research provides unique biological insights into candidate phyla in tropical soil and how deforestation may impact the carbon cycle and affect climate change