Regulation of Glandular Size and Phytoalexin Biosynthesis by a Negative Feedback Loop in Cotton.

Plants have evolved diverse defense mechanisms encompassing physical and chemical barriers. Cotton pigment glands are known for containing various defense metabolites, but the precise regulation of gland size to modulate defense compound levels remains enigmatic. Here, it is discovered that the VQ domain-containing protein JAVL negatively regulates pigment gland size and the biosynthesis of defense compounds, while the MYC2-like transcription factor GoPGF has the opposite effect. Notably, GoPGF directly activates the expression of JAVL, whereas JAVL suppresses GoPGF transcription, establishing a negative feedback loop that maintains the expression homeostasis between GoPGF and JAVL. Furthermore, it is observed that JAVL negatively regulates jasmonate levels by inhibiting the expression of jasmonate biosynthetic genes and interacting with GoPGF to attenuate its activation effects, thereby maintaining homeostatic regulation of jasmonate levels. The increased expression ratio of GoPGF to JAVL leads to enlarged pigment glands and elevated jasmonates and defense compounds, enhancing insect and pathogen resistance in cotton. These findings unveil a new mechanism for regulating gland size and secondary metabolites biosynthesis, providing innovative strategies for strengthening plant defense.

The Use of Real-World Evidence for Regulatory Decisions in China.

There is a growing demand for the use of high-quality real-world evidence (RWE) to support regulatory decision-making worldwide and in China, which highlights the need for conducting literature reviews to evaluate the available data and evidence. This study aims to review the use of RWE in Chinese regulatory decisions and to summarize relevant regulatory and methodological considerations to inform the future use of RWE in China. We identified policy documents, technical guidance documents, and cases on official Chinese government websites and extracted their contents separately. We consulted experts from the National Medical Products Administration (NMPA) and academic institutes and searched case-related articles for enrichment. We also searched and included articles related to the use of RWE/Real-world data in Chinese regulatory decisions. Six trial versions of technical guidance documents, 7 case studies, and 40 articles related to the Chinese regulatory decisions were included in this study. Based on the technical guidance, data quality, and appropriate study design and statistical analysis are the main concerns for RWE generation. The cases and articles related to regulatory decisions revealed 9 main concerns, including data sources and applicability, data quality, strength of existing evidence, appropriate study design and statistical analysis, regulated and transparent process for analysis and evidence generation, product safety and efficacy, product characteristics and clinical needs, ethical considerations and data security, and communicate adequately with regulatory authorities. Among these concerns, data issues are central. Preliminary attempts have been made by the NMPA to promote the use of RWE, but substantial challenges still remain.

Breast Tumor Tissue Image Classification Using Single-Task Meta Learning with Auxiliary Network.

Breast cancer has a high mortality rate among cancers. If the type of breast tumor can be correctly diagnosed at an early stage, the survival rate of the patients will be greatly improved. Considering the actual clinical needs, the classification model of breast pathology images needs to have the ability to make a correct classification, even in facing image data with different characteristics. The existing convolutional neural network (CNN)-based models for the classification of breast tumor pathology images lack the requisite generalization capability to maintain high accuracy when confronted with pathology images of varied characteristics. Consequently, this study introduces a new classification model, STMLAN (Single-Task Meta Learning with Auxiliary Network), which integrates Meta Learning and an auxiliary network. Single-Task Meta Learning was proposed to endow the model with generalization ability, and the auxiliary network was used to enhance the feature characteristics of breast pathology images. The experimental results demonstrate that the STMLAN model proposed in this study improves accuracy by at least 1.85% in challenging multi-classification tasks compared to the existing methods. Furthermore, the Silhouette Score corresponding to the features learned by the model has increased by 31.85%, reflecting that the proposed model can learn more discriminative features, and the generalization ability of the overall model is also improved.

Reference Values for Paravertebral Muscle Size and Myosteatosis in Chinese Adults, a Nationwide Multicenter Study.

RATIONALE AND OBJECTIVES: The paravertebral muscles, characterized by their susceptibility to severe size loss and fat infiltration in old age, lack established reference values for age-related variations in muscle parameters. This study aims to fill this gap by establishing reference values for paravertebral muscles in a Chinese adult population. MATERIALS AND METHODS: This cross-sectional study utilized the baseline data from the prospective cohort China Action on Spine and Hip (CASH). A total of 4305 community-dwelling participants aged 21-80 years in China were recruited between 2013 and 2017. Pregnant women, individuals with metal implants, limited mobility or diseases/conditions (spinal tumor, infection, etc.) affecting lumbar vertebra were excluded from the study. Psoas and paraspinal muscles were measured in quantitative computed tomography (QCT) images at the L3 and L5 levels using Osirix software. Age-related reference values for muscle area, density, and fat fraction were constructed as percentile charts using the lambda-mu-sigma (LMS) method. RESULTS: The paravertebral muscles exhibited an age-related decline in muscle area and density, coupled with an increase in muscle fat fraction. Between the ages of 25 and 75, the reductions in psoas and paraspinal muscle cross-sectional area at the L3 level were - 0.47%/yr and - 0.53%/yr in men, and - 0.19%/yr and - 0.23%/yr in women, respectively. Notably, accelerated muscle loss was observed during menopause and postmenopause in women (45-75 years) and intermittently during middle and old age in men (35-55 and 60-75 years). Besides, the age-related decreases in PSMA, PMA, and PSMD and the increases in PSMFF were more pronounced in L5 than in L3 CONCLUSION: This study shows distinct patterns of accelerated muscle loss were identified in menopausal and postmenopausal women and in middle-aged and old men. The findings contribute valuable information for future investigations on paravertebral muscle loss and myosteatosis.

Core atoms escape from the shell: reverse segregation of Pb-Al core-shell nanoclusters via nanoscale melting.

Melting is a phase transition that profoundly affects the fabrication and diverse applications of metal nanoclusters. Core-shell clusters offer distinctive properties and thus opportunities compared with other classes of nano-alloys. Molecular dynamics simulations have been employed to investigate the melting behaviour of Pb-Al core-shell clusters containing a fixed Pb147 core and varying shell thickness. Our results show that the core and shell melt separately. Surprisingly, core melting always drives the core Pb atoms to break out the shell and coat the nanoclusters in a reversed segregation process at the nanoscale. The melting point of the core increases with the shell thickness to exceed that of the bare core cluster, but the thinnest shell always supresses the core melting point. These results can be a reference for the future fabrication, manipulation, and exploitation of the core-shell nanoalloys chosen. The system chosen is ideally suited for experimental observations.

Effect of probiotic supplementation on cognition and depressive symptoms in patients with depression: A systematic review and meta-analysis.

BACKGROUND: Depression affects millions globally and often coexists with cognitive deficits. This study explored the potential of probiotics in enhancing cognition and ameliorating depressive symptoms in major depressive disorder patients. METHODS: Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol and the Population, Intervention, Comparator, Outcome, and Study design framework, we systematically reviewed randomized controlled trials examining probiotic effects on cognition and depressive symptoms. Searches spanned 7 databases from January 2010 to May 2022. Risk of bias was assessed using Revised Cochrane Risk of Bias 2.0, and meta-analysis was conducted with RevMan 5.4.1. Publication bias was evaluated via Egger test. RESULTS: In a systematic review on the effects of probiotic supplementation on cognition and depressive symptoms in depression patients, 635 records were initially identified, with 4 studies ultimately included. These randomized controlled trials were conducted across diverse regions, primarily involving females, with assessment periods ranging from 1 to 2 months. Concerning cognitive outcomes, a statistically significant moderate improvement was found with probiotic supplementation, based on the mean difference and its 95% confidence interval. However, for depressive symptoms, the overall effect was negligible and not statistically significant. A heterogeneity test indicated consistent findings across studies for both cognitive and depressive outcomes (I²â€…= 0% for both). The potential for publication bias was evaluated using the Egger linear regression test, suggesting no significant bias, though caution is advised due to the limited number of studies. CONCLUSION: Probiotics may enhance cognitive domains and mitigate depressive symptoms, emphasizing the gut-brain axis role. However, methodological variations and brief intervention durations call for more standardized, extensive research.

A dirigent protein complex directs lignin polymerization and assembly of the root diffusion barrier.

Functionally similar to the tight junctions present in animal guts, plant roots have evolved a lignified Casparian strip as an extracellular diffusion barrier in the endodermis to seal the root apoplast and maintain nutrient homeostasis. How this diffusion barrier is structured has been partially defined, but its lignin polymerization and assembly steps remain elusive. Here, we characterize a family of dirigent proteins (DPs) essential for both the localized polymerization of lignin required for Casparian strip biogenesis in the cell wall and for attachment of the strip to the plasma membrane to seal the apoplast. We reveal a Casparian strip lignification mechanism that requires cooperation between DPs and the Schengen pathway. Furthermore, we demonstrate that DPs directly mediate lignin polymerization as part of this mechanism.

Single-cell RNA sequencing reveals a hierarchical transcriptional regulatory network of terpenoid biosynthesis in cotton secretory glandular cells.

Plants can synthesize a wide range of terpenoids in response to various environmental cues. However, the specific regulatory mechanisms governing terpenoid biosynthesis at the cellular level remain largely elusive. In this study, we employed single-cell RNA sequencing to comprehensively characterize the transcriptome profile of cotton leaves and established a hierarchical transcriptional network regulating cell-specific terpenoid production. We observed substantial expression levels of genes associated with the biosynthesis of both volatile terpenes (such as ß-caryophyllene and ß-myrcene) and non-volatile gossypol-type terpenoids in secretory glandular cells. Moreover, two novel transcription factors, namely GoHSFA4a and GoNAC42, are identified to function downstream of the Gossypium PIGMENT GLAND FORMATION genes. Both transcription factors could directly regulate the expression of terpenoid biosynthetic genes in secretory glandular cells in response to developmental and environmental stimuli. For convenient retrieval of the single-cell RNA sequencing data generated in this study, we developed a user-friendly web server . Our findings not only offer valuable insights into the precise regulation of terpenoid biosynthesis genes in cotton leaves but also provide potential targets for cotton breeding endeavors.

Stereoelectronic Switches of Single-Molecule Junctions through Conformation-Modulated Intramolecular Coupling Approaches.

Stereoelectronic effects in single-molecule junctions have been widely utilized to achieve a molecular switch, but high-efficiency and reproducible switching remain challenging. Here, we demonstrate that there are three stable intramolecular conformations in the 9,10-diphenyl-9,10-methanoanthracen-11-one (DPMAO) systems due to steric effect. Interestingly, different electronic coupling approaches including weak coupling (through-space), decoupling, and strong coupling (through-bond) between two terminal benzene rings are accomplished in the three stable conformations, respectively. Theoretical calculations show that the molecular conductance of three stable conformations differs by more than 1 order of magnitude. Furthermore, the populations of the three stable conformations are highly dependent on the solvent effect and the external electric field. Therefore, an excellent molecular switch can be achieved using the DPMAO molecule junctions and external stimuli. Our findings reveal that modulating intramolecular electronic coupling approaches may be a useful manner to enable molecular switches with high switching ratios. This opens up a new route for building high-efficiency molecular switches in single-molecular junctions.

Selective adsorption of tetracycline and copper(II) on ion-imprinted porous alginate microspheres: performance and potential mechanisms.

A novel epichlorohydrin and thiourea grafted porous alginate adsorbent (UA-Ca/IIP) was synthesized using ion-imprinting and direct templating to remove copper ions (Cu(II)) and tetracycline (TC) in aqueous solution. UA-Ca/IIP demonstrated great selectivity for Cu(II) and TC among different coexisting anions (CO32-, PO43- and SO42-), cations (Ca2+, Mg2+ and NH4+), and antibiotics (oxytetracycline and sulfamethoxazole). The adsorption of TC and Cu(II) by UA-Ca/IIP was significantly affected by the pH of the solution, and the quantity of TC and Cu(II) adsorbed reached a maximum at pH 5. A pseudo-second-order model better fitted the kinetic data; the Langmuir model predicted the maximum adsorption quantities 3.527 mmol TC g-1 and 4.478 mmol Cu(II) g-1 at 298 K. Thermodynamic studies indicated that the TC and Cu(II) adsorption was more rapid at a higher temperature. Antagonistic and synergistic adsorption experiments showed that the adsorption capacity of TC would increase significantly with the increase of Cu(II) concentration. Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy indicated that along with the influence of pH, electrostatic interaction and complexation were the main mechanisms of TC and Cu(II) adsorption. Regeneration experiments revealed that TC and Cu(II) were removed efficiently and that UA-Ca/IIP was recyclable over the long term. These results show that the modified porous alginate microsphere is a green and recyclable adsorbent, which has good selectivity and high adsorption performance for the removal of TC and Cu(II).

Dirigent gene editing of gossypol enantiomers for toxicity-depleted cotton seeds.

Axial chirality of biaryls can generate varied bioactivities. Gossypol is a binaphthyl compound made by cotton plants. Of its two axially chiral isomers, (-)-gossypol is the bioactive form in mammals and has antispermatogenic activity, and its accumulation in cotton seeds poses health concerns. Here we identified two extracellular dirigent proteins (DIRs) from Gossypium hirsutum, GhDIR5 and GhDIR6, which impart the hemigossypol oxidative coupling into (-)- and (+)-gossypol, respectively. To reduce cotton seed toxicity, we disrupted GhDIR5 by genome editing, which eliminated (-)-gossypol but had no effects on other phytoalexins, including (+)-gossypol, that provide pest resistance. Reciprocal mutagenesis identified three residues responsible for enantioselectivity. The (-)-gossypol-forming DIRs emerged later than their enantiocomplementary counterparts, from tandem gene duplications that occurred shortly after the cotton genus diverged. Our study offers insight into how plants control enantiomeric ratios and how to selectively modify the chemical spectra of cotton plants and thereby improve crop quality.

Extending Plasmonic Enhancement Limit with Blocked Electron Tunneling by Monolayer Hexagonal Boron Nitride.

Fabricating ultrasmall nanogaps for significant electromagnetic enhancement is a long-standing goal of surface-enhanced Raman scattering (SERS) research. However, such electromagnetic enhancement is limited by quantum plasmonics as the gap size decreases below the quantum tunneling regime. Here, hexagonal boron nitride (h-BN) is sandwiched as a gap spacer in a nanoparticle-on-mirror (NPoM) structure, effectively blocking electron tunneling. Layer-dependent scattering spectra and theoretical modeling confirm that the electron tunneling effect is screened by monolayer h-BN in a nanocavity. The layer-dependent SERS enhancement factor of h-BN in the NPoM system monotonically increases as the number of layers decreases, which agrees with the prediction by the classical electromagnetic model but not the quantum-corrected model. The ultimate plasmonic enhancement limits are extended in the classical framework in a single-atom-layer gap. These results provide deep insights into the quantum mechanical effects in plasmonic systems, enabling the potential novel applications based on quantum plasmonic.

Nanoarchitecture factors of solid electrolyte interphase formation via 3D nano-rheology microscopy and surface force-distance spectroscopy.

The solid electrolyte interphase in rechargeable Li-ion batteries, its dynamics and, significantly, its nanoscale structure and composition, hold clues to high-performing and safe energy storage. Unfortunately, knowledge of solid electrolyte interphase formation is limited due to the lack of in situ nano-characterization tools for probing solid-liquid interfaces. Here, we link electrochemical atomic force microscopy, three-dimensional nano-rheology microscopy and surface force-distance spectroscopy, to study, in situ and operando, the dynamic formation of the solid electrolyte interphase starting from a few 0.1 nm thick electrical double layer to the full three-dimensional nanostructured solid electrolyte interphase on the typical graphite basal and edge planes in a Li-ion battery negative electrode. By probing the arrangement of solvent molecules and ions within the electric double layer and quantifying the three-dimensional mechanical property distribution of organic and inorganic components in the as-formed solid electrolyte interphase layer, we reveal the nanoarchitecture factors and atomistic picture of initial solid electrolyte interphase formation on graphite-based negative electrodes in strongly and weakly solvating electrolytes.

Breast Tumor Tissue Image Classification Using DIU-Net.

Inspired by the observation that pathologists pay more attention to the nuclei regions when analyzing pathological images, this study utilized soft segmentation to imitate the visual focus mechanism and proposed a new segmentation-classification joint model to achieve superior classification performance for breast cancer pathology images. Aiming at the characteristics of different sizes of nuclei in pathological images, this study developed a new segmentation network with excellent cross-scale description ability called DIU-Net. To enhance the generalization ability of the segmentation network, that is, to avoid the segmentation network from learning low-level features, we proposed the Complementary Color Conversion Scheme in the training phase. In addition, due to the disparity between the area of the nucleus and the background in the pathology image, there is an inherent data imbalance phenomenon, dice loss and focal loss were used to overcome this problem. In order to further strengthen the classification performance of the model, this study adopted a joint training scheme, so that the output of the classification network can not only be used to optimize the classification network itself, but also optimize the segmentation network. In addition, this model can also provide the pathologist model's attention area, increasing the model's interpretability. The classification performance verification of the proposed method was carried out with the BreaKHis dataset. Our method obtains binary/multi-class classification accuracy 97.24/93.75 and 98.19/94.43 for 200× and 400× images, outperforming existing methods.

Emerging role of ferroptosis in glioblastoma: Therapeutic opportunities and challenges.

Glioblastoma (GBM) is the most common malignant craniocerebral tumor. The treatment of this cancer is difficult due to its high heterogeneity and immunosuppressive microenvironment. Ferroptosis is a newly found non-apoptotic regulatory cell death process that plays a vital role in a variety of brain diseases, including cerebral hemorrhage, neurodegenerative diseases, and primary or metastatic brain tumors. Recent studies have shown that targeting ferroptosis can be an effective strategy to overcome resistance to tumor therapy and immune escape mechanisms. This suggests that combining ferroptosis-based therapies with other treatments may be an effective strategy to improve the treatment of GBM. Here, we critically reviewed existing studies on the effect of ferroptosis on GBM therapies such as chemotherapy, radiotherapy, immunotherapy, and targeted therapy. In particular, this review discussed the potential of ferroptosis inducers to reverse drug resistance and enhance the sensitivity of conventional cancer therapy in combination with ferroptosis. Finally, we highlighted the therapeutic opportunities and challenges facing the clinical application of ferroptosis-based therapies in GBM. The data generated here provide new insights and directions for future research on the significance of ferroptosis-based therapies in GBM.

Study on the Protective Effect of Schizandrin B against Acetaminophen-Induced Cytotoxicity in Human Hepatocyte.

Drug-induced liver injury (DILI) occurs frequently worldwide. Acetaminophen (APAP) is a common drug causing DILI. Current treatment methods are difficult to achieve satisfactory results. Therefore, there is an urgent need to provide safe and effective treatment for patients. Schizandrin B (Sch B), the main component of Schisandra, has a protective effect on liver. However, the potential mechanism of Sch B in the treatment of APAP induced liver injury has not been elucidated to date. In our research, we studied the effect of Sch B on protecting damaged liver cells and explored the potential mechanism underlying its ability to reduce APAP liver injury. We found that Sch B could reduce hepatocyte apoptosis, oxidative stress injury and inflammatory response. These effects were positively correlated with the dose of Sch B. Sch B regulated glucose 6-phosphate dehydrogenase expression by upregulating the expression of p21-activated kinase 4 and polo-like kinase 1. Sch B could inhibit the mitogen-activated protein kinase (MAPK)-c-Jun N-terminal kinase (JNK)-extracellular signal-regulated kinase (ERK) signaling pathway and regulate the expression of apoptosis-related proteins to reduce the incidence of cell apoptosis. In addition, Sch B reduced the expression levels of reactive oxygen species and inflammatory cytokines in hepatocyte. Consequently, we described for the first time that Sch B could not only activate the pentose phosphate pathway but also inhibit the MAPK-JNK-ERK signaling pathway, thereby achieving antioxidative and anti-inflammatory effects and inhibiting hepatocyte apoptosis. These findings indicated the potential use of Sch B in curing liver damage induced by APAP.

Molecular dynamics simulation of nanofilament breakage in neuromorphic nanoparticle networks.

Neuromorphic computing systems may be the future of computing and cluster-based networks are a promising architecture for the realization of these systems. The creation and dissolution of synapses between the clusters are of great importance for their function. In this work, we model the thermal breakage of a gold nanofilament located between two gold nanoparticles via molecular dynamics simulations to study on the mechanisms of neuromorphic nanoparticle-based devices. We employ simulations of Au nanowires of different lengths (20-80 Å), widths (4-8 Å) and shapes connecting two Au1415nanoparticles (NPs) and monitor the evolution of the system via a detailed structural identification analysis. We found that atoms of the nanofilament gradually aggregate towards the clusters, causing the middle of wire to gradually thin and then break. Most of the system remains crystalline during this process but the center is molten. The terminal NPs increase the melting point of the NWs by fixing the middle wire and act as recrystallization areas. We report a strong dependence on the width of the NWs, but also their length and structure. These results may serve as guidelines for the realization of cluster-based neuromorphic computing systems.

Exposure of zebra mussels to radial extracorporeal shock waves: implications for treatment of fracture nonunions.

BACKGROUND: Radial extracorporeal shock wave therapy (rESWT) is an attractive, non-invasive therapy option to manage fracture nonunions of superficial bones, with a reported success rate of approximately 75%. Using zebra mussels (Dreissena polymorpha), we recently demonstrated that induction of biomineralization after exposure to focused extracorporeal shock waves (fESWs) is not restricted to the region of direct energy transfer into calcified tissue. This study tested the hypothesis that radial extracorporeal shock waves (rESWs) also induce biomineralization in regions not directly exposed to the shock wave energy in zebra mussels. METHODS: Zebra mussels were exposed on the left valve to 1000 rESWs at different air pressure (between 0 and 4 bar), followed by incubation in calcein solution for 24 h. Biomineralization was evaluated by investigating the fluorescence signal intensity found on sections of the left and right valves prepared two weeks after exposure. RESULTS: General linear model analysis demonstrated statistically significant (p < 0.05) effects of the applied shock wave energy as well as of the side (left/exposed vs. right/unexposed) and the investigated region of the valve (at the position of exposure vs. positions at a distance to the exposure) on the mean fluorescence signal intensity values, as well as statistically significant combined energy × region and energy × side × region effects. The highest mean fluorescence signal intensity value was found next to the umbo, i.e., not at the position of direct exposure to rESWs. CONCLUSIONS: As in the application of fESWs, induction of biomineralization by exposure to rESWs may not be restricted to the region of direct energy transfer into calcified tissue. Furthermore, the results of this study may contribute to better understand why the application of higher energy flux densities beyond a certain threshold does not necessarily lead to higher success rates when treating fracture nonunions with extracorporeal shock wave therapy.

Synthesis, Characterization, and Catalytic Application of Palladium Complexes Containing Indolyl-NNN-Type Ligands.

In this study, a series of N-heterocyclic indolyl ligand precursors 2-Py-Py-IndH, 2-Py-Pz-IndH, 2-Py-7-Py-IndH, 2-Py-7-Pz-IndH, and 2-Ox-7-Py-IndH (L1H-L5H) were prepared. The treatment of ligand precursors with 1 equivalent of palladium acetate affords palladium complexes 1-5. All ligand precursors and palladium complexes were characterized by NMR spectroscopy and elemental analysis. The molecular structures of complexes 3 and 5 were determined by single crystal X-ray diffraction techniques. The application of those palladium complexes 1-5 to the Suzuki reaction with aryl halide substrates was examined.

Multi-variable classification model for valve internal leakage based on acoustic emission time-frequency domain characteristics and random forest.

To use acoustic-emission technology to detect leaks inside valves, the necessary first step is to model the valve-internal-leakage acoustic-emission signal (VILAES) mathematically. A multi-variable classification model that relates the VILAES characteristics and the leakage rate under varying pressure is built by combining time-frequency domain characteristics and the random-forest method. A Butterworth bandpass filter is used to preprocess the VILAES from a liquid medium, and the best frequency band for filtering is determined as being 140 kHz-180 kHz. Then, (i) the standard deviation, (ii) root mean square, (iii) wavelet packet entropy, (iv) peak standard-deviation probability density, and (v) spectrum area are calculated as the VILAES characteristics, and six parameters-the pressure and the five VILAES characteristics-are used as the inputs for the random-forest classification model. Analysis shows that the five VILAES characteristics increase with an increase in the leakage rate. The multi-variable classification model is established by random forest to determine whether the valve leakage is small, medium, or large. The random forest uses many decision trees to predict the final result. For the same experimental data, the accuracy and operating time of the multi-variable classification model are compared with those of a support-vector-machine classification method for the bandpass and wavelet packet filtering preprocessing methods. The results show that the modeling method based on the combination of time-frequency characteristics and random forest has shorter operating time and higher accuracy.