Benefits and risks of drug combination therapy for diabetes mellitus and its complications: a comprehensive review

Diabetes is a chronic metabolic disease, and its therapeutic goals focus on the effective management of blood glucose and various complications. Drug combination therapy has emerged as a comprehensive treatment approach for diabetes. An increasing number of studies have shown that, compared with monotherapy, combination therapy can bring significant clinical benefits while controlling blood glucose, weight, and blood pressure, as well as mitigating damage from certain complications and delaying their progression in diabetes, including both type 1 diabetes (T1D), type 2 diabetes (T2D) and related complications. This evidence provides strong support for the recommendation of combination therapy for diabetes and highlights the importance of combined treatment. In this review, we first provided a brief overview of the phenotype and pathogenesis of diabetes and discussed several conventional anti-diabetic medications currently used for the treatment of diabetes. We then reviewed several clinical trials and pre-clinical animal experiments on T1D, T2D, and their common complications to evaluate the efficacy and safety of different classes of drug combinations. In general, combination therapy plays a pivotal role in the management of diabetes. Integrating the effectiveness of multiple drugs enables more comprehensive and effective control of blood glucose without increasing the risk of hypoglycemia or other serious adverse events. However, specific treatment regimens should be tailored to individual patients and implemented under the guidance of healthcare professionals

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Long Cycle Life TiC Anode Fabricated via High-Energy Ball Mill for Li-Ion Battery

Nano-TiC and nano-WC anodes for Li-ion battery were manufactured by high-energy ball milling. Pure titanium powder and toluene are mixed with a high-energy ball mill to prepare TiC powder. The powder is calcined at 750°C/1 h and secondary ball milled to make a negative electrode for lithium-ion battery. The phase composition and micromorphology of TiC powder are analyzed and observed, and the charge-discharge cycle performance of TiC anode material is tested. The results show that there are TiH2 and WC impurities in the product after primary ball milling. After calcination and secondary ball milling, TiH2 impurities are removed and the TiC grain size is refined, and TiC powder is obtained with a grain size of 12.5 nm. The specific discharge capacity of the TiC anode is stable during the long cycle discharge. When the current density is 1 A/g, the specific discharge capacity can still be maintained at 110 mAh/g after 3000 cycles. The results show that TiC anode materials have excellent long-cycle performance and could be used as the frame material of Si anode materials. Nano-WC powders are prepared by a ball milling method to investigate the effect of WC impurities on the performance of TiC lithium batteries. The charge and discharge capacity at 0.5 A/g current density is similar to that of TiC anode. After 2000 cycles, the discharge-specific capacity is about 100 mA/g, which is slightly lower than TiC, and the final capacity is maintained at 230 mA/g, but its low discharge capacity affects the performance of the TiC battery after a long ball milling. The results show that the performance of the TiC anode after the first 50 h of ball milling is poor. The main reason is the agglomeration of TiC nanoparticles

Optimal Control for Multistage Nonlinear Dynamic System of Microbial Bioconversion in Batch Culture

In batch culture of glycerol biodissimilation to 1,3-propanediol (1,3-PD), the aim of adding glycerol is to obtain as much 1,3-PD as possible. Taking the yield intensity of 1,3-PD as the performance index and the initial concentration of biomass, glycerol, and terminal time as the control vector, we propose an optimal control model subject to a multistage nonlinear dynamical system and constraints of continuous state. A computational approach is constructed to seek the solution of the above model. Firstly, we transform the optimal control problem into the one with fixed terminal time. Secondly, we transcribe the optimal control model into an unconstrained one based on the penalty functions and an extension of the state space. Finally, by approximating the control function with simple functions, we transform the unconstrained optimal control problem into a sequence of nonlinear programming problems, which can be solved using gradient-based optimization techniques. The convergence analysis and optimality function of the algorithm are also investigated. Numerical results show that, by employing the optimal control, the concentration of 1,3-PD at the terminal time can be increased, compared with the previous results

Functional Connectivity Based Classification of ADHD Using Different Atlases

These days, computational diagnosis strategies of neuropsychiatric disorders are gaining attention day by day. It's critical to determine the brain's functional connectivity based on Functional-Magnetic-Resonance-Imaging(fMRI) to diagnose the disorder. It's known as a chronic disease, and millions of children amass the symptoms of this disease, so there is much vacuum for the researcher to formulate a model to improve the accuracy to diagnose ADHD accurately. In this paper, we consider the functional connectivity of a brain extracted using various time templates/Atlases. Local-Binary Encoding-Method (LBEM) algorithm is utilized for feature extraction, while Hierarchical- Extreme-Learning-Machine (HELM) is used to classify the extracted features. To validate our approach, fMRI data of 143 normal and 100 ADHD affected children is used for experimental purpose. Our experimental results are based on comparing various Atlases given as CC400, CC200, and AAL. Our model achieves high performance with CC400 as compared to other Atlase

Droplet-Based Microfluidic Preparation of Shape-Variable Alginate Hydrogel Magnetic Micromotors

This article introduces a facile droplet-based microfluidic method for the preparation of Fe3O4-incorporated alginate hydrogel magnetic micromotors with variable shapes. By using droplet-based microfluidics and water diffusion, monodisperse (quasi-)spherical microparticles of sodium alginate and Fe3O4 (Na-Alg/Fe3O4) are obtained. The diameter varies from 31.9 to 102.7 µm with the initial concentration of Na-Alginate in dispersed fluid ranging from 0.09 to 9 mg/mL. Calcium chloride (CaCl2) is used for gelation, immediately transforming Na-Alg/Fe3O4 microparticles into Ca-Alginate hydrogel microparticles incorporating Fe3O4 nanoparticles, i.e., Ca-Alg/Fe3O4 micromotors. Spherical, droplet-like, and worm-like shapes are yielded depending on the concentration of CaCl2, which is explained by crosslinking and anisotropic swelling during the gelation. The locomotion of Ca-Alg/Fe3O4 micromotors is activated by applying external magnetic fields. Under the rotating magnetic field (5 mT, 1–15 Hz), spherical Ca-Alg/Fe3O4 micromotors exhibit an average advancing velocity up to 158.2 ± 8.6 µm/s, whereas worm-like Ca-Alg/Fe3O4 micromotors could be rotated for potential advancing. Under the magnetic field gradient (3 T/m), droplet-like Ca-Alg/Fe3O4 micromotors are pulled forward with the average velocity of 70.7 ± 2.8 µm/s. This article provides an inspiring and timesaving approach for the preparation of shape-variable hydrogel micromotors without using complex patterns or sophisticated facilities, which holds potential for biomedical applications such as targeted drug delivery

Application of ORF3 Subunit Vaccine for Avian Hepatitis E Virus

Avian hepatitis E virus (HEV) is the main etiologic pathogen of chicken big liver and spleen disease which is widely prevalent in China in recent years. However, due to the lack of a highly effective culture system in vitro, a genetically engineered subunit vaccine is the main direction of vaccine development. In this study, ORF3 genes of VaHEV strain from laying hens and YT-aHEV strain from broilers were amplified, respectively, and ORF3 protein was successfully expressed by Escherichia coli prokaryotic expression system. The serum samples were collected periodically to detect avian HEV antibodies by indirect immunofluorescence after specific pathogen free chickens immunized with the two proteins and their mixed proteins, the results showed that all serum samples were positive for antibodies to avian HEV. The antibody-positive chickens were artificially challenged with the cell-adapted strain YT-aHEV strain. The chickens from the immunized control group were infected successfully; no fecal detoxification was detected in the immunized group. In this study, two representative strains of ORF3 subunit vaccines of laying hens and broilers were prepared by prokaryotic expression, the immune effects of different proteins of these were evaluated through immunization and challenge studies in vivo, which provided a new technical possibility for prevention and control of avian HEV

Fate of antibiotic resistance genes in cultivation substrate and its association with bacterial communities throughout commercial production of Agaricus bisporus

Animal manure is an important raw material for Agaricus bisporus production; however, it is also a reservoir for antibiotic residues, antibiotic resistance genes (ARGs), and antibiotic-resistant bacteria. Little is known about the influence of the commercial cultivation of A. bisporus on the dynamics of ARGs and the underlying mechanisms that cause their variations. In this study, we investigated the fate of 285 ARGs, 10 mobile genetic elements, and seven major categories of antibiotic residues in substrate and mushroom samples at different production phases. The results showed that commercial substrate preparation, particularly the pasteurization phase, was highly efficient in removing ARGs from the substrate. We further found that mycelium proliferation of A. bisporus contributed significantly to the removal of ARGs from the substrate and casing soil. The bacterial community is the key driver of changes in ARGs during the commercial cultivation of A. bisporus, which explained 46.67% of the variation in ARGs. Our results indicate that, despite the addition of animal manure, the risk of ARG dissemination to fruiting bodies and the environment is low. We propose that bioremediation by specific edible fungi might be a novel and promising method for scavenging antimicrobial resistance contamination from soil environment

Mutation-derived, genomic instability-associated lncRNAs are prognostic markers in gliomas

Background Gliomas are the most commonly-detected malignant tumors of the brain. They contain abundant long non-coding RNAs (lncRNAs), which are valuable cancer biomarkers. LncRNAs may be involved in genomic instability; however, their specific role and mechanism in gliomas remains unclear. LncRNAs that are related to genomic instability have not been reported in gliomas. Methods The transcriptome data from The Cancer Genome Atlas (TCGA) database were analyzed. The co-expression network of genomic instability-related lncRNAs and mRNA was established, and the model of genomic instability-related lncRNA was identified by univariate Cox regression and LASSO analyses. Based on the median risk score obtained in the training set, we divided the samples into high-risk and low-risk groups and proved the survival prediction ability of genomic instability-related lncRNA signatures. The results were verified in the external data set. Finally, a real-time quantitative polymerase chain reaction assay was performed to validate the signature. Results The signatures of 17 lncRNAs (LINC01579, AL022344.1, AC025171.5, LINC01116, MIR155HG, AC131097.3, LINC00906, CYTOR, AC015540.1, SLC25A21.AS1, H19, AL133415.1, SNHG18, FOXD3.AS1, LINC02593, AL354919.2 and CRNDE) related to genomic instability were identified. In the internal data set and Gene Expression Omnibus (GEO) external data set, the low-risk group showed better survival than the high-risk group (P < 0.001). In addition, this feature was identified as an independent risk factor, showing its independent prognostic value with different clinical stratifications. The majority of patients in the low-risk group had isocitrate dehydrogenase 1 (IDH1) mutations. The expression levels of these lncRNAs were significantly higher in glioblastoma cell lines than in normal cells. Conclusions Our study shows that the signature of 17 lncRNAs related to genomic instability has prognostic value for gliomas and could provide a potential therapeutic method for glioblastoma