Strigolactones positively regulate Verticillium wilt resistance in cotton via crosstalk with other hormones.

Verticillium wilt caused by Verticillium dahliae is a serious vascular disease in cotton (Gossypium spp.). V. dahliae induces the expression of the CAROTENOID CLEAVAGE DIOXYGENASE 7 (GauCCD7) gene involved in strigolactone (SL) biosynthesis in Gossypium australe, suggesting a role for SLs in Verticillium wilt resistance. We found that the SL analog rac-GR24 enhanced while the SL biosynthesis inhibitor TIS108 decreased cotton resistance to Verticillium wilt. Knock-down of GbCCD7 and GbCCD8b genes in island cotton (Gossypium barbadense) decreased resistance, whereas overexpression of GbCCD8b in upland cotton (Gossypium hirsutum) increased resistance to Verticillium wilt. Additionally, Arabidopsis (Arabidopsis thaliana) SL mutants defective in CCD7 and CCD8 putative orthologs were susceptible, whereas both Arabidopsis GbCCD7- and GbCCD8b-overexpressing plants were more resistant to Verticillium wilt than wild-type (WT) plants. Transcriptome analyses showed that several genes related to the jasmonic acid (JA)- and abscisic acid (ABA)-signaling pathways, such as MYELOCYTOMATOSIS 2 (GbMYC2) and ABA-INSENSITIVE 5, respectively, were upregulated in the roots of WT cotton plants in responses to rac-GR24 and V. dahliae infection but downregulated in the roots of both GbCCD7- and GbCCD8b-silenced cotton plants. Furthermore, GbMYC2 suppressed the expression of GbCCD7 and GbCCD8b by binding to their promoters, which might regulate the homeostasis of SLs in cotton through a negative feedback loop. We also found that GbCCD7- and GbCCD8b-silenced cotton plants were impaired in V. dahliae-induced reactive oxygen species (ROS) accumulation. Taken together, our results suggest that SLs positively regulate cotton resistance to Verticillium wilt through crosstalk with the JA- and ABA-signaling pathways and by inducing ROS accumulation.

FPS-ZM1 attenuates the deposition of lipid in the liver of diabetic mice by sterol regulatory element binding protein-1c.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) shares common pathogenic mechanisms of type 2 diabetes mellitus (T2DM) with upregulated advanced glycation end products (AGEs). Here, we aim to investigate the effect of FPS-ZM1, an inhibitor for receptor for AGEs (RAGE), on lipid deposition in the liver of mice. METHODS: KK-Ay mice were used as models of T2DM with NAFLD, while C57BL/6j mice were controls. Additionally, KK-Ay mice were treated with DMSO (with a concentration of 1%), with or without FPS-ZM1 (3 mg/kg/day, i.p). Lipid deposition in hepatocytes was observed using oil red O stain. Levels of AGEs and RAGE were measured. Sterol regulatory element-binding protein-1c (SREBP-1c), as well as nuclear factor κB p65 (p65 nfκb) and mitogen-activated protein kinase p38 (p38 MAPK), were also detected. RESULTS: Lipid deposition is increased in the hepatocytes of KK-Ay mice compared to C57BL/6j mice. In addition, not only were the levels of AGEs elevated in plasma, but also the levels of RAGE in liver tissue. Although total SREBP-1c levels did not change in the liver of diabetic mice, mature SREBP-1c increased in KK-Ay mice with diabetes mellitus. Moreover, diabetic mice showed increased levels of phosphorylated-p65 nfκb (p-p65 nfκb) and phosphorylated-p38 MAPK (p-p38 MAPK). On the contrary, FPS-ZM1 decreased lipid deposition in liver cells, as well as mature SREBP-1c, p-p65 nfκb and p-p38 MAPK levels in liver tissue. CONCLUSION: Generally, FPS-ZM1 may attenuate lipid deposition in hepatocytes of diabetic mice via SREBP-1c down-regulation. This may depend on the downregulation of p65 nfκb and p38 MAPK phosphorylation.

lncRNA7 and lncRNA2 modulate cell wall defense genes to regulate cotton resistance to Verticillium wilt.

In plants, long noncoding RNAs (lncRNAs) regulate disease resistance against fungi and other pathogens. However, the specific mechanism behind this regulation remains unclear. In this study, we identified disease resistance-related lncRNAs as well as their regulating genes and assessed their functions by infection of cotton (Gossypium) chromosome segment substitution lines with Verticillium dahliae. Our results demonstrated that lncRNA7 and its regulating gene Pectin methylesterase inhibitor 13 (GbPMEI13) positively regulated disease resistance via the silencing approach, while ectopic overexpression of GbPMEI13 in Arabidopsis (Arabidopsis thaliana) promoted growth and enhanced resistance to V. dahliae. In contrast, lncRNA2 and its regulating gene Polygalacturonase 12 (GbPG12) negatively regulated resistance to V. dahliae. We further found that fungal disease-related agents, including the pectin-derived oligogalacturonide (OG), could downregulate the expression of lncRNA2 and GbPG12, leading to pectin accumulation. Conversely, OG upregulated the expression of lncRNA7, which encodes a plant peptide phytosulfokine (PSK-α), which was confirmed by lncRNA7 overexpression and Ultra Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS) experiments. We showed that PSK-α promoted 3-Indoleacetic acid (IAA) accumulation and activated GbPMEI13 expression through Auxin Response Factor 5. Since it is an inhibitor of pectin methylesterase (PME), GbPMEI13 promotes pectin methylation and therefore increases the resistance to V. dahliae. Consistently, we also demonstrated that GbPMEI13 inhibits the mycelial growth and spore germination of V. dahliae in vitro. In this study, we demonstrated that lncRNA7, lncRNA2, and their regulating genes modulate cell wall defense against V. dahliae via auxin-mediated signaling, providing a strategy for cotton breeding.

Proposal for High-Energy Cutoff Extension of Optical Harmonics of Solid Materials Using the Example of a One-Dimensional ZnO Crystal.

We propose a novel approach based on the subcycle injection of carriers to extend the high-energy cutoff in solid-state high harmonics. The mechanism is first examined by employing the standard single-cell semiconductor Bloch equation (SC SBE) method for one-dimensional (1D) Mathieu potential model for ZnO subjected to the intense linearly polarized midinfrared laser field and extreme-ultraviolet pulse. Then, we use coupled solution of Maxwell propagation equation and SC SBE to propagate the fundamental laser field through the sample, and find that the high-harmonics pulse train from the entrance section of the sample can inject carriers to the conduction bands with attosecond timing, subsequently leading to a dramatic extension of high-energy cutoff in harmonics from the backside. We predict that for a peak intensity at 2×10^{11} W/cm^{2}, as a result of the self-seeding, the high-energy cutoff shifts from 20th (7.75 eV) order to around 50th (19.38 eV) order harmonics.

Revealing Molecular Strong Field Autoionization Dynamics.

The novel strong field autoionization (SFAI) dynamics is identified and investigated by channel-resolved angular streaking measurements of two electrons and two ions for the double-ionized CO. Comparing with the laser-assisted autoionization calculations, we demonstrate the electrons from SFAI are generated from the field-induced decay of the autoionizing state with a following acceleration in the laser fields. The energy-dependent photoelectron angular distributions further reveal that the subcycle ac-Stark effect modulates the lifetime of the autoionizing state and controls the emission of SFAI electrons in molecular frame. Our results pave the way to control the emission of resonant high-harmonic generation and trace the electron-electron correlation and electron-nuclear coupling by strong laser fields. The lifetime modulation of quantum systems in the strong laser field has great potential for quantum manipulation of chemical reactions and beyond.

Quantification of eucalyptol (1,8-cineole) in rat serum by gas chromatography-mass/mass spectrometry and its application to a rat pharmacokinetic study.

Eucalyptol (1,8-cineole) is a biologically active cyclic monoterpenoid. In a preliminary study, we used gas chromatography-mass spectrometry to detect eucalyptol in the serum and brain tissue of rats after oral administration. However, the absorption characteristics in vivo and pharmacokinetic parameters of eucalyptol have not been published to date. The present study aims to develop and validate a simple, sensitive GC-MS/MS method with quadrupole mass analyzer type for the quantitative analysis of eucalyptol in rat serum and apply it to a pharmacokinetic study. The assay showed linearity of concentration range from 50 to 5,000 pg/ml with a limit of quantitation of 50 pg/ml. Intra- and inter-day precision for eucalyptol were 4.4-13.0 and <15.0%, respectively, and accuracy was within 10% for quality control samples. The recovery and stability results showed that the method was accurate and stable for quantitative analysis. The developed analytical method was successfully applied to a pharmacokinetic study after a single oral administration of eucalyptol in rat subjects. The serum concentration-time profiles indicate that the absorption characteristics of eucalyptol after oral administration are similar to those for intravenous administration.

Phenolic Compounds from the Leaves of Castanopsis fargesii.

In the course of a phytochemical and chemotaxonomical investigation of Castanopsis species (Fagaceae), three new phenolic compounds, (3R,1'S)-[1'-(6″-O-galloyl-ß-d-gluco-pyranosyl)oxyethyl]-3-hydroxy-dihydrofuran-2(3H)-one (1), (2R,3S)-2-[2'-(galloyl)oxyethyl]-dihydroxybutanoic acid (2), and (3S,4S)-3-hydroxymethyl-3,4-dihydro-5,6,7-trihydroxy-4-(4'-hydroxy-3'-methoxyphenyl)-1H-[2]-benzopyran-1-one (3) were isolated from the fresh leaves of Castanopsis fargesii. In addition, a known phenolic glycoside, gentisic acid 5-O-α-l-rhamnopyranosyl-(1→2)-ß-d-glucopyranoside (4) was also isolated and identified. Their structures were elucidated by means of spectroscopic methods including one- and two-dimensional NMR techniques.

Identifying typical physical activity on smartphone with varying positions and orientations.

BACKGROUND: Traditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body. METHODS: By introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. RESULTS: The experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier. CONCLUSIONS: The utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.

Litchi Pericarp Extract Treats Type 2 Diabetes Mellitus by Regulating Oxidative Stress, Inflammatory Response, and Energy Metabolism.

Litchi pericarp is rich in polyphenols, and demonstrates significant biological activity. This study assessed the therapeutic effects of litchi pericarp extract (LPE) on type 2 diabetes mellitus in db/db mice. The results showed that LPE ameliorated symptoms of glucose metabolism disorder, oxidative stress, inflammatory response, and insulin resistance in db/db mice. The mechanistic studies indicated that LPE activates adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) and suppresses the protein expression of phosphoenolpyruvate carboxykinase (PEPCK), thereby reducing hepatic gluconeogenesis. Additionally, LPE facilitates the translocation of nuclear factor erythroid2-related factor 2 (Nrf2) into the cell nucleus, initiating the transcription of antioxidant factors superoxide dismutase (SOD) and NAD(P)H: quinone oxidoreductase 1 (NQO1), which alleviate oxidative stress and reduce oxidative damage. Furthermore, LPE blocks nuclear factor kappa-B (NF-κB) nuclear translocation and subsequent inflammatory response initiation, thereby reducing inflammation. These findings indicate that LPE addresses type 2 diabetes mellitus by activating the AMPK energy metabolic pathway and regulating the Nrf2 oxidative stress and NF-κB inflammatory signaling pathways.

Gene therapy and gene editing strategies in inherited blood disorders.

Gene therapy has shown significant potential in treating various diseases, particularly inherited blood disorders such as hemophilia, sickle cell disease, and thalassemia. Advances in understanding the regulatory network of disease-associated genes have led to the identification of additional therapeutic targets for treatment, especially for ß-hemoglobinopathies. Erythroid regulatory factor BCL11A offers the most promising therapeutic target for ß-hemoglobinopathies and reduction of its expression using the commercialized gene therapy product Casgevy was approved for use in the UK and USA in 2023. Notably, the emergence of innovative gene editing technologies has further broadened the gene therapy landscape, presenting new possibilities for treatment. Intensive studies indicate that base editing and prime editing, built upon CRISPR technology, enable precise single-base modification in hematopoietic stem cells for addressing inherited blood disorders ex vivo and in vivo. In this review, we present an overview of the current landscape of gene therapies, focusing on clinical research and gene therapy products for inherited blood disorders, evaluation of potential gene targets, and the gene editing tools employed in current gene therapy practices, which provides an insight for the establishment of safer and more effective gene therapy methods for a wider range of diseases in the future.

A novel diagnosis method combined dual-channel SE-ResNet with expert features for inter-patient heartbeat classification.

As the number of patients with cardiovascular diseases (CVDs) increases annually, a reliable and automated system for detecting electrocardiogram (ECG) abnormalities is becoming increasingly essential. Scholars have developed numerous methods of arrhythmia classification using machine learning or deep learning. However, the issue of low classification rates of individual classes in inter-patient heartbeat classification remains a challenge. This study proposes a method for inter-patient heartbeat classification by fusing dual-channel squeeze-and-excitation residual neural networks (SE-ResNet) and expert features. In the preprocessing stage, ECG heartbeats extracted from both leads of ECG signals are filtered and normalized. Additionally, nine features representing waveform morphology and heartbeat contextual information are selected to be fused with the deep neural networks. Using different filter and kernel sizes for each block, the SE-residual block-based model can effectively learn long-term features between heartbeats. The divided ECG heartbeats and extracted features are then input to the improved SE-ResNet for training and testing according to the inter-patient scheme. The focal loss is utilized to handle the heartbeat of the imbalance category. The proposed arrhythmia classification method is evaluated on three open-source databases, and it achieved an overall F1-score of 83.39 % in the MIT-BIH database. This system can be applied in the scenario of daily monitoring of ECG and plays a significant role in diagnosing arrhythmias.

Raman time-delay in attosecond transient absorption of strong-field created krypton vacancy.

Strong field ionization injects a transient vacancy in the atom which is entangled to the outgoing photoelectron. When the electron is finally detached, the ion is populated at different excited states with part of coherence information lost. The preserved coherence of matter after interacting with intense short pulses has important consequences on the subsequent nonequilibrium evolution and energy relaxation. Here we employ attosecond transient absorption spectroscopy to measure the time-delay of resonant transitions of krypton vacancy during their creation. We have observed that the absorptions by the two spin-orbit split states are modulated at different paces when varying the time-delay between the near-infrared pumping pulse and the attosecond probing pulse. It is shown that the coupling of the ions with the remaining field leads to a suppression of ionic coherence. Comparison between theory and experiments uncovers that coherent Raman coupling induces time-delay between the resonant absorptions, which provides insight into laser-ion interactions enriching attosecond chronoscopy.

Cardiologist-level interpretable knowledge-fused deep neural network for automatic arrhythmia diagnosis.

BACKGROUND: Long-term monitoring of Electrocardiogram (ECG) recordings is crucial to diagnose arrhythmias. Clinicians can find it challenging to diagnose arrhythmias, and this is a particular issue in more remote and underdeveloped areas. The development of digital ECG and AI methods could assist clinicians who need to diagnose arrhythmias outside of the hospital setting. METHODS: We constructed a large-scale Chinese ECG benchmark dataset using data from 272,753 patients collected from January 2017 to December 2021. The dataset contains ECG recordings from all common arrhythmias present in the Chinese population. Several experienced cardiologists from Shanghai First People's Hospital labeled the dataset. We then developed a deep learning-based multi-label interpretable diagnostic model from the ECG recordings. We utilized Accuracy, F1 score and AUC-ROC to compare the performance of our model with that of the cardiologists, as well as with six comparison models, using testing and hidden data sets. RESULTS: The results show that our approach achieves an F1 score of 83.51%, an average AUC ROC score of 0.977, and 93.74% mean accuracy for 6 common arrhythmias. Results from the hidden dataset demonstrate the performance of our approach exceeds that of cardiologists. Our approach also highlights the diagnostic process. CONCLUSIONS: Our diagnosis system has superior diagnostic performance over that of clinicians. It also has the potential to help clinicians rapidly identify abnormal regions on ECG recordings, thus improving efficiency and accuracy of clinical ECG diagnosis in China. This approach could therefore potentially improve the productivity of out-of-hospital ECG diagnosis and provides a promising prospect for telemedicine.

Arrhythmia, also known as an irregular heartbeat, is a common cardiovascular disease. Sometimes the presence of an arrhythmia can increase the risk of more serious heart conditions. Long-term monitoring of the heartbeat enables arrhythmia to be more easily diagnosed. To accurately detect arrhythmia, we developed a computational model that was able to detect six common types of arrhythmias from readings of the heart rate obtained using a device connected to a mobile phone. We showed that our model could diagnose these arrhythmias in over 270,000 people living in China. Our diagnostic system could enable arrhythmias to be diagnosed more easily outside of hospitals and therefore improve access to healthcare, particularly for those in remote settings.

Detection and quantification of etomidate and metomidate in human hairs by ultraperformance liquid chromatography with triple quadrupole mass spectrometry (UPLC-MS/MS).

PURPOSE: Intravenous narcotic agents, such as etomidate and metomidate, has been widely spread and abused in the world, including in Korea and China; thus, it is important to establish validated and sensitive analytical method for these compounds. Human hair as a biological sample has various advantages, including a wide detection window of drugs, compared to other typical samples, such as urine and blood in investigation. The purpose of this communication is to develop a reliable and useful method for the simultaneous detection and quantification of etomidate and metomidate in human hair samples by ultraperformance liquid chromatography combined with triple quadrupole mass spectrometry (UPLC-MS/MS), and to apply it for authentic samples in abuse cases. METHODS: The hair samples were washed with a detergent solution, followed by with water and acetone. After drying, they were cut into approximately 2 mm sections and then ground to powder by a low-temperature grinder. The 20 mg of hair powder plus internal standard in 1 mL of methanol was vortexed and then centrifuged to obtain the supernatant layer, followed by subjecting to analysis. RESULTS: The coefficient of determination (r2) values of the calibration curves of etomidate and metomidate in the hair samples were both more than 0.99 in the range of 1-500 ng/mg and 1-500 pg/mg, respectively. The limits of detection and lower limits of quantification were 0.5 and 1 pg/mg, respectively, for the both target compounds. Other tested validation data were all satisfactory. Etomidate and metomidate could be detected in the all hair samples and cigarette oil, which were seized by the police. The concentrations of etomidate and metomidate obtained from 10 samples from suspects were 5.48-45.7 ng/mg and 3.60-377 pg/mg, respectively. The concentrations of etomidate and metomidate in the cigarette oil were 95.8 µg/mg and 2.8 µg/mg, respectively. CONCLUSIONS: In this study, a simple and reliable analytical method for etomidate and metomidate in the human hair has been established. To the best of our knowledge, this is the first report to establish a method for the simultaneous detection and quantification of etomidate and metomidate in the human hair, and to apply it to authentic samples seized in authentic cases.

Study on the lignin-derived sp2-sp3 hybrid hard carbon materials and the feasibility for industrial production.

Hard carbon has been widely used in anode of lithium/sodium ion battery, electrode of supercapacitor, and carbon molecular sieve for CO2 capture and hydrogen storage. In this study the lignin derived hard carbon products are investigated, and the conclusions are abstracted as follows. (1) The lignin derived hard carbon products consist of microcrystal units of sp2 graphene fragments, jointed by sp3 carbon atoms and forming sp2-sp3 hybrid hard carbon family. (2) From the lignin precursors to the sp2-sp3 hybrid hard carbon products, most carbon atoms retain their original electron configurations (sp2 or sp3) and keep their composition in lignin. (3) The architectures of lignin-derived hard carbon materials are closely dependent on the forms of their lignin precursors, and could be preformed by different pretreatment techniques. (4) The carbonization of lignin precursors follows the mechanism "carbonization in situ and recombination nearby". (5) Due to the high carbon ratio and abundant active functional groups in lignin, new activation techniques could be developed for control of pore size and pore volume. In general lignin is an excellent raw material for sp2-sp3 hybrid hard carbon products, a green and sustainable alternative resource for phenolic resin, and industrial production for lignin derived hard carbon products would be feasible.

Design and Synthesis of a Polyketone Building Block with Vinyl Groups-9,10-Diethyl-9,10-ethenoanthracene-2,3,6,7(9H,10H)-tetraone-and a Preliminary Photoelectrical Property Study of Its Azaacene Derivatives.

Polyketone compounds are powerful building blocks to synthesize various organic functional materials. Despite that a great many number of planar and non-planar polyketone building blocks have been developed, one issue is that generally there are only ketone functional groups on the molecular skeleton, which will constrain their transformation and further limit the development of functional materials. In this work, we report the design and synthesis of a building block 9,10-diethyl-9,10-ethenoanthracene-2,3,6,7(9H,10H)-tetraone with additional vinyl functional groups. In addition, its azaacene derivatives were also synthesized, and their preliminary physicochemical properties were studied.

Saponins of Tomato Extract Improve Non-Alcoholic Fatty Liver Disease by Regulating Oxidative Stress and Lipid Homeostasis.

The present study investigated the impact of saponins of tomato extract (STE) on non-alcoholic fatty liver disease (NAFLD). The findings demonstrated that introducing STE in NAFLD mice revealed promising results in ameliorating symptoms of oxidative stress, lipid metabolism disorders, visceral fat deposition and fatty liver disease. Moreover, the mechanistic studies have demonstrated that STE delivers its effects by activating adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK), thereby suppressing downstream protein expression associated with fatty acid synthesis. In such conditions, lipid metabolism can be improved. Simultaneously, STE enhanced nuclear factor erythroid 2-related factor 2 (Nrf2) and entry into the nucleus and initiated the transcription of downstream antioxidant factors, thereby relieving oxidative stress induced by a high-fat diet and lowering oxidative damage to the liver. Such results imply that the administration of STE can be regarded as a viable treatment option for NAFLD, providing a mechanism that can regulate the AMPK and Nrf2 signaling pathways.

Knowledge Mapping of Drug Repositioning's Theme and Development.

Background: In recent years, the emergence of new diseases and resistance to known diseases have led to increasing demand for new drugs. By means of bibliometric analysis, this paper studied the relevant articles on drug repositioning in recent years and analyzed the current research foci and trends. Methodology: The Web of Science database was searched to collect all relevant literature on drug repositioning from 2001 to 2022. These data were imported into CiteSpace and bibliometric online analysis platforms for bibliometric analysis. The processed data and visualized images predict the development trends in the research field. Results: The quality and quantity of articles published after 2011 have improved significantly, with 45 of them cited more than 100 times. Articles posted by journals from different countries have high citation values. Authors from other institutions have also collaborated to analyze drug rediscovery. Keywords found in the literature include molecular docking (N=223), virtual screening (N=170), drug discovery (N=126), machine learning (N=125), and drug-target interaction (N=68); these words represent the core content of drug repositioning. Conclusion: The key focus of drug research and development is related to the discovery of new indications for drugs. Researchers are starting to retarget drugs after analyzing online databases and clinical trials. More and more drugs are being targeted at other diseases to treat more patients, based on saving money and time. It is worth noting that researchers need more financial and technical support to complete drug development.