Inhibition of light-induced stomatal opening by allyl isothiocyanate does not require guard cell cytosolic Ca2+ signaling

The glucosinolate-myrosinase system is a well-known defense system that has been shown to induce stomatal closure in Brassicales. Isothiocyanates are highly reactive hydrolysates of glucosinolates, and an isothiocyanate, allyl isothiocyanate (AITC), induces stomatal closure accompanied by elevation of free cytosolic Ca2+ concentration ([Ca2+](cyt)) in Arabidopsis. It remains unknown whether AITC inhibits light-induced stomatal opening. This study investigated the role of Ca2+ in AITC-induced stomatal closure and inhibition of light-induced stomatal opening. AITC induced stomatal closure and inhibited light-induced stomatal opening in a dose-dependent manner. A Ca2+ channel inhibitor, La3+, a Ca(2+)chelator, EGTA, and an inhibitor of Ca2+ release from internal stores, nicotinamide, inhibited AITC-induced [Ca2+](cyt) elevation and stomatal closure, but did not affect inhibition of light-induced stomatal opening. AITC activated non-selective Ca2+-permeable cation channels and inhibited inward-rectifying K+ (K-in(+)) channels in a Ca2+-independent manner. AITC also inhibited stomatal opening induced by fusicoccin, a plasma membrane H+-ATPase activator, but had no significant effect on fusicoccin-induced phosphorylation of the penultimate threonine of H+-ATPase. Taken together, these results suggest that AITC induces Ca2+ influx and Ca2+ release to elevate [Ca2+](cyt), which is essential for AITC-induced stomatal closure but not for inhibition of K-in(+) channels and light-induced stomatal opening

New Capoamycin-Type Antibiotics and Polyene Acids from Marine Streptomyces fradiae PTZ0025

Capoamycin-type antibiotics (2–5) and polyene acids (6, 7) were isolated from marine Streptomyces fradiae strain PTZ0025. Their structures were established by extensive nuclear magnetic resonance (NMR) and high resolution electron spray ionization mass spectroscopy (HRESIMS) analyses and chemical degradation. Compounds 3, 4, 6, 7 were found to be new and named as fradimycins A (3) and B (4), and fradic acids A (6) and B (7). Compounds 3–5 showed in vitro antimicrobial activity against Staphylococcus aureus with a minimal inhibitory concentration (MIC) of 2.0 to 6.0 μg/mL. Interestingly, Compounds 3–5 also significantly inhibited cell growth of colon cancer and glioma with IC50 values ranging from 0.13 to 6.46 μM. Fradimycin B (4), the most active compound, was further determined to arrest cell cycle and induce apoptosis in tumor cells. The results indicated that fradimycin B (4) arrested the cell cycle at the G0/G1 phase and induced apoptosis and necrosis in colon cancer and glioma cells. Taken together, the results demonstrated that the marine natural products 3–5, particularly fradimycin B (4), possessed potent antimicrobial and antitumor activities

Nano-fumed silica as a novel pollutant that inhibits the algicidal effect of <i>p</i>-hydroxybenzoic acid on <i>Microcystis aeruginosa</i>

<p>Nanomaterials and/or contaminants are becoming more common in the developing world, but their effects on interspecific interactions are rarely reported, particularly in aquatic ecosystems. Thus, the present study determined the effects of the novel pollutant nano-fumed silica (NFS) on algal control by a macrophyte via the allelochemical <i>p</i>-hydroxybenzoic acid in a microcosm test. The allelochemical <i>p-</i>hydroxybenzoic acid caused significant decreases in chlorophyll <i>a</i>, but increased the amount of superoxide anion radicals (<math><msubsup>O<mn>2</mn><mrow><mo>∙</mo><mo>−</mo></mrow></msubsup></math>) and the electric conductivity in <i>Microcystis aeruginosa</i>. The 50% inhibitory concentration (IC₅₀) for <i>p</i>-hydroxybenzoic acid was 0.919 mmol/L in microalga during the exponential phase. Interestingly, NFS at 100–1600 mg/L had clear stimulatory effects on <i>M. aeruginosa</i>. When NFS at 800 mg/L was combined with different concentrations of <i>p</i>-hydroxybenzoic acid, the IC₅₀ for <i>p</i>-hydroxybenzoic acid was 1.045 mmol/L. Thus, NFS significantly reduced the algicidal effect exhibited by <i>p</i>-hydroxybenzoic acid on <i>M. aeruginosa.</i> Furthermore, NFS might act as a silicon nutrient and enhance allelopathic resistance in <i>M. aeruginosa</i> to inhibit the algicidal effects of macrophytes via allelopathy. These findings suggest that before algal control is considered using macrophyte allelopathy, it is essential to remove the pollutant NFS from polluted lakes.</p

High thermoelectric properties of Cu2TeAg2Te composite with Fe addition and non-stoichiometric Te

Cu2Te-based materials are a type of superionic conductor belonging to the class of phonon-liquid electron-crystal materials and have achieved high ZT values by doping and nanostructuring. However, it is easy to form copper vacancies in Cu2Te which leads to an excessive carrier concentration and then results in a low Seebeck coefficient. Hence, controlling copper ion migration and optimizing carrier concentration is essential to improve the thermoelectric performance of Cu2Te. This paper reports high-performance Cu2TeAg2Te composite with high application value in the low-middle temperature region, which is achieved by fine tuning the carrier concentration using Fe addition and non-stoichiometric Te, as well as controlling the thermal conductivity of composite. A high ZT of ∼1.2 is obtained in AgCu0.97Fe0.03Te0.96 at a low temperature of 573 K. Meanwhile, the phase transition mechanism of Cu2TeAg2Te and its effect on the thermoelectric transport performance are revealed that go beyond nanostructuring and single-doping, which provides a strong theoretical basis for research and performance improvement of thermoelectric materials in this system

Evaluation of Internet-based pharmaceutical care effect on young and middle-aged patients with hypertension by the principal component analysis and the Markov cohort during COVID-19 pandemic

Abstract Background Pharmaceutical care has the potential to improve hypertension control rates in young and middle-aged patients. Due the COVID-19 epidemic, standard intervention methods may not be applicable. We propose establishing an internet-based pharmaceutical care (IPC) route to improve blood pressure control in young and middle-aged patients with hypertension. An evaluation method based on Principal Component Analysis (PCA) and Orthogonal Partial Least-Discriminant Analysis (OPLS-DA) was established to evaluate the effect of the IPC method. Methods 1) Internet-based Pharmaceutical care (IPC) was provided by pharmacists mainly using Wechat software for one year after enrollment; 2) PCA and OPLS-DA were applied to analyze questionnaire reliability and data variability; 3) Markov cohort was used to evaluate the IPC effect. Results Ninety-seven young and middle-aged patients were enrolled. 96 patients received the IPC. 1) The blood pressure control rate increased to 71.88% after IPC in 96 patients. 2) After conducting PCA and OPLS-DA analysis, 10 questions in the questionnaire were significantly improved after the IPC. 3) Markov cohort results showed that patient survival after 28 cycles was 18.62 years and the quality-adjusted life year (QALY) was extended by 5.40 years. The cumulative cost-effectiveness ratio was ¥87.10 per QALY. Conclusions The IPC method could significantly improve the blood pressure control rate of patients. The questionnaire analysis method based on PCA and OPLS-DA is an effective method to evaluate the effect of the IPC method. The Markov cohort showed that the IPC had an effect on blood pressure control rate changes. Patients had a strong willingness to pay for IPC

Weakly Supervised Collaborative Learning for Airborne Pollen Segmentation and Classification from SEM Images

Existing pollen identification methods heavily rely on the scale and quality of pollen images. However, there are many impurities in real-world SEM images that should be considered. This paper proposes a collaborative learning method to jointly improve the performance of pollen segmentation and classification in a weakly supervised manner. It first locates pollen regions from the raw images based on the detection model. To improve the classification performance, we segmented the pollen grains through a pre-trained U-Net using unsupervised pollen contour features. The segmented pollen regions were fed into a deep convolutional neural network to obtain the activation maps, which were used to further refine the segmentation masks. In this way, both segmentation and classification models can be collaboratively trained, supervised by just pollen contour features and class-specific information. Extensive experiments on real-world datasets were conducted, and the results prove that our method effectively avoids impurity interference and improves pollen identification accuracy (86.6%) under the limited supervision (around 1000 images with image-level labels)