Plant Essential Oils: Dual Action of Toxicity and Egg-Laying Inhibition on Tetranychus urticae (Acari: Tetranychidae), Unveiling Their Potential as Botanical Pesticides.

Tetranychus urticae, a prominent pest mite in strawberry and vegetable cultivation in China, has developed escalating resistance due to extensive chemical pesticide application. Consequently, there is an urgent need to identify safe and efficacious methods to reduce resistance development. In this study, 38 commercially available plant essential oils (EOs) were screened for their acaricidal potential and ability to inhibit oviposition. The findings revealed that 13 EOs exhibited notable acaricidal activity, with lemon EO demonstrating the highest toxicity, followed by sage, patchouli, frankincense, lemongrass, palmarosa, and oregano EOs. In addition, 18 EOs displayed significant inhibitory effects on oviposition, with lemon EO exhibiting the highest inhibition rate (99.15%) and inhibition index (0.98). Subsequently, sage, frankincense, clove, lemongrass, oregano, patchouli, myrrh, black pepper, palmarosa, and geranium EOs also showed inhibition rates exceeding 50%. Despite black pepper, clove, myrrh, and oregano EOs demonstrating relatively low toxicity against T. urticae, they exhibited heightened efficacy in inhibiting oviposition and suppressing population expansion. This study conducted a comparative assessment of the acaricidal and oviposition inhibition activities of EOs and their principal constituents, thus providing a theoretical basis for the development of botanical acaricides against T. urticae.

Biochemical characteristics and potential application of a thermostable starch branching enzyme from Bacillus licheniformis.

Slowly digestible starch (SDS) has attracted increasing attention for its function of preventing metabolic diseases. Based on transglycosylation, starch branching enzymes (1,4-α-glucan branching enzymes, GBEs, EC 2.4.1.18) can be used to regulate the digestibility of starch. In this study, a GBE gene from Bacillus licheniformis (bl-GBE) was cloned, expressed, purified, and characterized. Sequence analysis and structural modeling showed that bl-GBE belong to the glycoside hydrolase 13 (GH13) family, with which its active site residues were conserved. The bl-GBE was highly active at 80 °C and a pH range of 7.5-9.0, and retained 90% of enzyme activity at 70 °C for 16 h. bl-GBE also showed high substrate specificity (80.88 U/mg) on potato starch. The stability and the changes of the secondary structure of bl-GBE at different temperature were determined by circular dichroism (CD) spectroscopy. The CD data showed a loss of 20% of the enzyme activity at high temperatures (80 °C), due to the decreased content of the α -helix in the secondary structure. Furthermore, potato starch treated with bl-GBE (300 U/g starch) showed remarkable increase in stability, solubility, and significant reduction viscosity. Meanwhile, the slowly digestible starch content of bl-GBE modified potato starch increased by 53.03% compared with native potato starch. Our results demonstrated the potential applications of thermophilic bl-GBE in food industries.

Smart Materials Prediction: Applying Machine Learning to Lithium Solid-State Electrolyte.

Traditionally, the discovery of new materials has often depended on scholars' computational and experimental experience. The traditional trial-and-error methods require many resources and computing time. Due to new materials' properties becoming more complex, it is difficult to predict and identify new materials only by general knowledge and experience. Material prediction tools based on machine learning (ML) have been successfully applied to various materials fields; they are beneficial for modeling and accelerating the prediction process for materials that cannot be accurately predicted. However, the obstacles of disciplinary span led to many scholars in materials not having complete knowledge of data-driven materials science methods. This paper provides an overview of the general process of ML applied to materials prediction and uses solid-state electrolytes (SSE) as an example. Recent approaches and specific applications to ML in the materials field and the requirements for building ML models for predicting lithium SSE are reviewed. Finally, some current obstacles to applying ML in materials prediction and prospects are described with the expectation that more materials scholars will be aware of the application of ML in materials prediction.

Omni-functional crystal: Advanced methods to characterize the composition and homogeneity of lithium niobate melts and crystals.

Lithium niobate (LN) is a type of multifunctional dielectric and ferroelectric crystal that is widely used in acoustic, optical, and optoelectronic devices. The performance of pure and doped LN strongly depends on various factors, including its composition, microstructure, defects, domain, and homogeneity. The structure and composition homogeneity can affect both the chemical and physical properties of LN crystals, including their density, Curie temperature, refractive index, and piezoelectric and mechanical properties. In terms of practical demands, both the composition and microstructure characterizations these crystals must range from the nanometer scale up to the millimeter and wafer scales. Therefore, LN crystals require different characterization technologies when verifying their quality for various device applications. Optical, electrical, and acoustic technologies have been developed, including x-ray diffraction, Raman spectroscopy, electron microscopy, and interferometry. To obtain detailed structural information, advanced sub-nanometer technologies are required. For general industrial demands, fast and non-destructive technologies are preferable. This review outlines the advanced methods used to characterize both the composition and homogeneity of LN melts and crystals from the micro- to wafer scale.

Stimuli-Responsive Hydrogels with Antibacterial Activity Assembled from Guanosine, Aminoglycoside, and a Bifunctional Anchor.

Multistimuli-responsive hydrogels with specific functions have attracted great interest for biomedical applications; however, these smart hydrogels usually require the presynthesis of macromolecular building blocks with multiple ligands and the integration of bioactive cargoes into the gels. Here, a multistimuli-responsive hydrogel with potent antibacterial activity by a combination of supramolecular assembly and iminoboronate chemistry is reported. The hydrogel consists of all-small-molecule building blocks including aminoglycoside, guanosine, potassium ion, and a bifunctional anchor bearing both boronic acid and aldehyde groups. Guanosines form quadruplexes in the presence of potassium ions via supramolecular assembly, and the bifunctional anchor connects aminoglycosides, a class of potent antibiotics to cis-diol groups on quadruplexes via dynamic iminoboronate chemistry, yielding a smart hydrogel containing abundant antibiotics. The hydrogel is sensitive to multistimuli such as heat, acids, oxidants, glucose and crown ether, which promote the release of antibiotics from the gels. Moreover, the prepared hydrogels show potent antibacterial activities both in vitro and in vivo. The results provide a new option to prepare antibacterial hydrogels with multistimuli responsiveness via facile chemistry using all-small-molecule building blocks.

A Retrospective Survey of Buprenorphine Substitute Treatment With Minimal Dosage in Heroin Use Disorder.

Objectives: It is widely accepted that buprenorphine maintenance treatment (BMT) with dosages above 8 mg daily is effective for patients with heroin use disorder. In this study, the authors evaluated the effectiveness of long-term BMT for heroin users in China, with dosages kept on a much smaller level. Methods: This is a retrospective observational study of 72 patients who had undergone detoxification and continued with buprenorphine maintenance between 2007 and 2016. Measurements such as self-reported relapse status, buprenorphine doses, protracted symptoms, general health condition, and self-reported side effects were included. Results: At the time of interview, 51 patients had remained abstinent at follow-up (including 13 who were opioid-free). The dosages of buprenorphine were 1.33 ± 0.88 (ranging 0.3-3.5) mg/day when maintenance treatment was initiated and 1.2 ± 0.8 (ranging 0.2-3.2) mg/day at the last follow-up. The remaining patients had either relapsed on heroin (n = 11) or switched to compulsory treatment (n=10). In general, abstinent patients had minimal protracted symptoms, especially in physical symptoms. Opioid-free abstainers were more likely to report good physical health than patients on buprenorphine. Predictors of worse outcomes (relapsed or switched to compulsory treatment) were lower education levels, younger age, and younger onset of illicit drug use. Conclusions: This study shows promising results of minimal-dosage BMT in treating heroin use disorder. We recommend further studies applying minimal-dosage BMT in China and worldwide.

A pH-responsive hydrogel with potent antibacterial activity against both aerobic and anaerobic pathogens.

Aminoglycosides are a family of antibiotics with a wide-spread antibacterial spectrum and high antibacterial activity. However, they are less effective against anaerobic pathogens due to the requirement of aerobic respiration to exert their antibacterial functions. Here, we prepared a pH-responsive hydrogel with potent antibacterial activities against both aerobic and anaerobic pathogens. The hydrogel was prepared by reacting oxidized dextran with aminoglycoside and an ornidazole analogue via an acid-labile Schiff base linkage. The prepared hydrogel was injectable, self-healing, biocompatible, and showed a pH-responsive drug release behavior. More importantly, the gel was efficient in killing both aerobic and anaerobic pathogens. This study provides a facile strategy to expand the antibacterial spectrum of aminoglycoside hydrogels.

Synthesis of boron-containing primary amines.

In this study, boron-containing primary amines were synthesized for use as building blocks in the study of peptoids. In the first step, Gabriel synthesis conditions were modified to enable the construction of seven different aminomethylphenyl boronate esters in good to excellent yields. These compounds were further utilized to build peptoid analogs via an Ugi four-component reaction (Ugi-4CR) under microwave irradiation. The prepared Ugi-4CR boronate esters were then successfully converted to the corresponding boronic acids. Finally, the peptoid structures were successfully modified by cross-coupling to aryl/heteroaryl chlorides via a palladium-mediated Suzuki coupling reaction to yield the corresponding derivatives in moderate to good yields.