Novel Spatially Asymmetric Copper Bismuthate-Mediated Augmentation of Energy Conversion to Realize "Three-Step" Tumor Suppression.

The generally undesirable bandgap and electron-hole complexation of inorganic sonosensitizers limit the efficiency of reactive oxygen species (ROS) generation, affecting the effectiveness of sonodynamic therapy (SDT). Comparatively, the novel polyvinylpyrrolidone-modified copper bismuthate (PCBO) sonosensitizers are manufactured for a "three-step" SDT promotion. In brief, first, the strong hybridization between Bi 6s and O 2p orbitals in PCBO narrows the bandgap (1.83 eV), facilitating the rapid transfer of charge carriers. Additionally, nonequivalent [CuO4]6- layers reduce crystal symmetry, confer PCBO unique piezoelectricity, and improve electron-hole separation under ultrasonic (US) excitation. This allows PCBO to convert US energy into chemical energy to produce ROS, achieving the accumulation of abundant ROS, resulting in apoptosis and tumor suppression. Concurrently, PCBO also acts as a glutathione scavenger to reduce tumor antioxidant capacity and improve efficacy. To the best of authors understanding, this study reveals PCBO as an innovative piezoelectric sonosensitizer and provides a meaningful paradigm for designing energy conversion strategies for tumor suppression.

MAIT cells are associated with responsiveness to neoadjuvant immunotherapy in COPD-associated NSCLC.

BACKGROUND: Patients with non-small cell lung cancer (NSCLC) and chronic obstructive pulmonary disease (COPD) experience worse clinical outcomes but respond better to immunotherapy than patients with NSCLC without COPD. Mucosal-associated invariant T (MAIT) cells, a versatile population of innate immune T lymphocytes, have a crucial function in the response to infection and tumors. This study investigated the distribution of MAIT cells in COPD-associated NSCLC and their involvement in the immune response. METHODS: Flow cytometry, immunohistochemistry, and immunofluorescence were performed on tissue samples of patients with NSCLC, with or without COPD, treated with or without anti-programmed death 1 (PD1) immunotherapy. MAIT cells were stimulated with 5-OP-RU using a mouse subcutaneous tumor model. RESULTS: Tumors contained significantly more MAIT cells than paraneoplastic tissues, and CD8+ MAIT cells accounted for more than 90% of these cells. Patients with NSCLC and COPD had higher CD8+ MAIT cell counts than those with NSCLC without COPD. Additionally, patients with NSCLC and COPD displayed reduced expression of the activation marker, CD69, and functional markers, granzyme B (GZMB) and interferon γ (IFNγ), and higher expression of the immune exhaustion marker, PD1. Among patients who received immunotherapy, the proportion with a complete or partial response was higher in those with COPD than in those without COPD. In patients with NSCLC and COPD, the major pathologic response (MPR) group had higher MAIT levels than those in the no major pathologic response (NPR) group. In the mouse subcutaneous tumor model stimulation of MAIT cells using 5-OP-RU enhanced the antitumor effects of anti-PD1. CONCLUSIONS: In patients with NSCLC and COPD, response to immunotherapy is associated with accumulation of CD8+ MAIT cells showing immune exhaustion. These findings may contribute to innovative approaches for immunotherapy targeting CD8+ MAIT cells.

Application of Raman spectroscopy during pharmaceutical process development for determination of critical quality attributes in Protein A chromatography.

Raman spectroscopy is considered a Process Analytical Technology (PAT) tool in biopharmaceutical downstream processes. In the past decade, researchers have shown Raman spectroscopy's feasibility in determining Critical Quality Attributes (CQAs) in bioprocessing. This study verifies the feasibility of implementing a Raman-based PAT tool in Protein A chromatography as a CQA monitoring technique, for the purpose of accelerating process development and achieving real-time release in manufacturing. A system connecting Raman to a Tecan liquid handling station enables high-throughput model calibration. One calibration experiment collects Raman spectra of 183 samples with 8 CQAs within 25 h. After applying Butterworth high-pass filters and k-nearest neighbor (KNN) regression for model training, the model showed high predictive accuracy for fragments (Q2 = 0.965) and strong predictability for target protein concentration, aggregates, as well as charge variants (Q2≥ 0.922). The model's robustness was confirmed by varying the elution pH, load density, and residence time using 19 external validation preparative Protein A chromatography runs. The model can deliver elution profiles of multiple CQAs within a set point ± 0.3 pH range. The CQA readouts were presented as continuous chromatograms with a resolution of every 28 s for enhanced process understanding. In external validation datasets, the model maintained strong predictability especially for target protein concentration (Q2 = 0.956) and basic charge variants (Q2 = 0.943), except for overpredicted HCP (Q2 = 0.539). This study demonstrates a rapid, effective method for implementing Raman spectroscopy for in-line CQA monitoring in process development and biomanufacturing, eliminating the need for labor-intensive sample pooling and handling.

Simultaneous prediction of 16 quality attributes during protein A chromatography using machine learning based Raman spectroscopy models.

Several key technologies for advancing biopharmaceutical manufacturing depend on the successful implementation of process analytical technologies that can monitor multiple product quality attributes in a continuous in-line setting. Raman spectroscopy is an emerging technology in the biopharma industry that promises to fit this strategic need, yet its application is not widespread due to limited success for predicting a meaningful number of quality attributes. In this study, we addressed this very problem by demonstrating new capabilities for preprocessing Raman spectra using a series of Butterworth filters. The resulting increase in the number of spectral features is paired with a machine learning algorithm and laboratory automation hardware to drive the automated collection and training of a calibration model that allows for the prediction of 16 different product quality attributes in an in-line mode. The demonstrated ability to generate these Raman-based models for in-process product quality monitoring is the breakthrough to increase process understanding by delivering product quality data in a continuous manner. The implementation of this multiattribute in-line technology will create new workflows within process development, characterization, validation, and control.

The interplay between the circadian clock and abiotic stress responses mediated by ABF3 and CCA1/LHY.

Climate change is a global concern for all life on our planet, including humans and plants. Plants' growth and development are significantly affected by abiotic stresses, including adverse temperature, inadequate or excess water availability, nutrient deficiency, and salinity. The circadian clock is a master regulator of numerous developmental and metabolic processes in plants. In an effort to identify new clock-related genes and outputs through bioinformatic analysis, we have revealed that CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY) play a crucial role in regulating a wide range of abiotic stress responses and target ABSCISIC ACID RESPONSIVE ELEMENTS-BINDING FACTOR3 (ABF3), a key transcription factor in the plant hormone Abscisic acid (ABA)-signaling pathway. Specifically, we found that CCA1 and LHY regulate the expression of ABF3 under diel conditions, as well as seed germination under salinity. Conversely, ABF3 controls the expression of core clock genes and orchestrates the circadian period in a stress-responsive manner. ABF3 delivers the stress signal to the central oscillator by binding to the promoter of CCA1 and LHY. Overall, our study uncovers the reciprocal regulation between ABF3 and CCA1/LHY and molecular mechanisms underlying the interaction between the circadian clock and abiotic stress. This finding may aid in developing molecular and genetic solutions for plants to survive and thrive in the face of climate change.

IAS-FET: An intelligent assistant system and an online platform for enhancing successful rate of in-vitro fertilization embryo transfer technology based on clinical features.

BACKGROUND: Among all of the assisted reproductive technology (ART) methods, in vitro fertilization-embryo transfer (IVF-ET) holds a prominent position as a key solution for overcoming infertility. However, its success rate hovers at a modest 30% to 70%. Adding to the challenge is the absence of effective models and clinical tools capable of predicting the outcome of IVF-ET before embryo formation. Our study is dedicated to filling this critical gap by aiming to predict IVF-ET outcomes and ultimately enhance the success rate of this transformative procedure. METHODS: In this retrospective study, infertile patients who received artificial assisted pregnancy treatment at Gansu Provincial Maternity and Child-care Hospital in China were enrolled from 2016 to 2020. Individual's clinical information were studied by cascade XGBoost method to build an intelligent assisted system for predicting the outcome of IVF-ET, called IAS-FET. The cascade XGBoost model was trained using clinical information from 2292 couples and externally tested using clinical information from 573 couples. In addition, several schemes which will be of help for patients to adjust their physical condition to improve their success rate on ART were suggested by IAS-FET. RESULTS: The outcome of IVF-ET can be predicted by the built IAS-FET method with the area under curve (AUC) value of 0.8759 on the external test set. Besides, this IAS-FET method can provide several schemes to improve the successful rate of IVF-ET outcomes. The built tool for IAS-FET is addressed as a free platform online at http://www.cppdd.cn/ART for the convenient usage of users. CONCLUSIONS: It suggested the significant influence of personal clinical features for the success of ART. The proposed system IAS-FET based on the top 27 factors could be a promising tool to predict the outcome of ART and propose a plan for the patient's physical adjustment. With the help of IAS-FET, patients can take informed steps towards increasing their chances of a successful outcome on their journey to parenthood.

LINC00460-FUS-MYC feedback loop drives breast cancer metastasis and doxorubicin resistance.

Therapeutic resistance and metastasis largely contribute to mortality from breast cancer and therefore understanding the underlying mechanisms of such remains an urgent challenge. By cross-analysis of TCGA and GEO databases, LINC00460 was identified as an oncogenic long non-coding RNA, highly expressed in Doxorubicin resistant breast cancer. LINC00460 was further demonstrated to promote stem cell-like and epithelial-mesenchymal transition (EMT) characteristics in breast cancer cells. LINC00460 interacts with FUS protein with consequent enhanced stabilization, which further promotes MYC mRNA maturation. LINC00460 expression was transcriptionally enhanced by c-MYC protein, forming a positive feedback loop to promote metastasis and Doxorubicin resistance. LINC00460 depletion in Doxorubicin-resistant breast cancer cells restored sensitivity to Doxorubicin and increased the efficacy of c-MYC inhibitor therapy. Collectively, these findings implicate LINC00460 as a promising prognostic biomarker and potential therapeutic target to overcome Doxorubicin resistance in breast cancer.

Robust links in photoactive covalent organic frameworks enable effective photocatalytic reactions under harsh conditions.

Developing heterogeneous photocatalysts for the applications in harsh conditions is of high importance but challenging. Herein, by converting the imine linkages into quinoline groups of triphenylamine incorporated covalent organic frameworks (COFs), two photosensitive COFs, namely TFPA-TAPT-COF-Q and TFPA-TPB-COF-Q, are successfully constructed. The obtained quinoline-linked COFs display improved stability and photocatalytic activity, making them suitable photocatalysts for photocatalytic reactions under harsh conditions, as verified by the recyclable photocatalytic reactions of organic acid involving oxidative decarboxylation and organic base involving benzylamine coupling. Under strong oxidative condition, the quinoline-linked COFs show a high efficiency up to 11831.6 µmol·g-1·h-1 and a long-term recyclable usability for photocatalytic production of H2O2, while the pristine imine-linked COFs are less catalytically active and easily decomposed in these harsh conditions. The results demonstrate that enhancing the linkage robustness of photoactive COFs is a promising strategy to construct heterogeneous catalysts for photocatalytic reactions under harsh conditions.

Gypenoside XVII attenuates renal ischemia-reperfusion injury by inhibiting endoplasmic reticulum stress and NLRP3 inflammasome-triggered pyroptosis.

BACKGROUND: Renal ischemia-reperfusion (I/R) is one of the main causes of acute kidney injury (AKI), for which there is currently no effective treatment. Recently, the interaction between endoplasmic reticulum (ER) stress and pyroptosis during AKI has been investigated. AIM: The purpose of this study was to investigate the protective effects of Gypenoside XVII (GP-17) against I/R-induced renal injury. METHODS: In this study, mice were divided into 6 groups, sham group, I/R group, GP-17 low-, medium-, high-dose group, and positive control 4-PBA group. The renal I/R was performed in mice by clamping the bilateral renal pedicles for 40 min, and then reperfusing for 24 h. Blood and kidney samples were collected for analysis. RESULTS: The results showed that GP-17 improved renal function and alleviated renal histopathological abnormalities caused by I/R. In addition, GP-17 pretreatment significantly decreased the expression or phosphorylation of ER stress response proteins including BIP, p-PERK, and CHOP. Besides, GP-17 inhibited the expression of pyroptosis proteins including caspase-1, GSDMD, and apoptotic protein BAX. The inflammatory factor IL-1ß in these GP-17 pretreatment groups was also significantly reduced. CONCLUSION: GP-17 blocked NLRP3 inflammasome activation by inhibiting ERS, thereby inhibiting renal tubular cell pyroptosis and apoptosis, and prevented renal I/R injury.

Smartphone-based low-cost and rapid quantitative detection of urinary creatinine with the Tyndall effect.

This research aims to develop a robust and quantitative method for measuring creatinine levels by harnessing the enhanced Tyndall effect (TE) phenomenon. The envisioned sensing assay is designed for practical deployment in resource-limited settings or homes, where access to advanced laboratory facilities is limited. Its primary objective is to enable regular and convenient monitoring of renal healthcare, particularly in cases involving elevated creatinine levels. The creatinine sensing strategy is achieved based on the aggregation of gold nanoparticles (AuNPs) triggered via the direct crosslinking reaction between creatinine and AuNPs, where an inexpensive laser pointer was used as a handheld light source and a smartphone as a portable device to record the TE phenomenon enhanced by the creatinine-induced aggregation of AuNPs. After evaluation and optimization of parameters such as AuNP concentrations and TE measurement time, the subsequent proof-of-concept experiments demonstrated that the average gray value change of TE images was linearly related to the logarithm of creatinine concentrations in the range of 1-50 µM, with a limit of detection of 0.084 µM. Meanwhile, our proposed creatinine sensing platform exhibited highly selective detection in complex matrix environments. Our approach offers a straightforward, cost-effective, and portable means of creatinine detection, presenting an encouraging signal readout mechanism suitable for point-of-care (POC) applications. The utilization of this assay as a POC solution exhibits potential for expediting timely interventions and enhancing healthcare outcomes among individuals with renal health issues.

Corneal wound healing following infrared laser irradiation at the wavelengths of 1.319 and 10.6 µm.

OBJECTIVES: To investigate the wound healing of rabbit cornea following infrared laser irradiations at the wavelengths of 1.319 and 10.6 µm. MATERIALS AND METHODS: Twelve New Zealand rabbits were selected to establish a corneal injury model. The right and left eyes were irradiated with a neodymium-doped yttrium aluminum garnet laser at the wavelength of 1.319 µm (140 J/cm2 ) for 0.7 s and a CO2 laser at the wavelength of 10.6 µm (5.94 J/cm2 ) for 0.14 s, respectively. The incident spot diameter was 3 mm. Optical coherence tomography (OCT) was used to monitor injuries at 0 h, 0.5 h, 1 h, 3 h, 6 h, 12 h, 18 h, 24 h, 30 h, 36 h, 42 h, 48 h, 54 h, 60 h, 66 h, 3 d, 7 d, 14 d, 28 d, 3 m, and 6 m postexposure. Meanwhile, slit-lamp microscopy and histopathology were performed at 6 h, 24 h, 3 d, 7 d, 14 d, 28 d, 3 m, and 6 m postexposure. RESULTS: After the two types of infrared laser injuries, distinct white circular lesions on the corneal surface were directly observed. Deeper corneal injury, more severe edema, and faster migration of new epithelium were found for the wavelength of 1.319 µm, compared to the wavelength of 10.6 µm. CONCLUSIONS: OCT combined with histopathology and slit-lamp microscopy can clearly observe the dynamic process of corneal wound healing after infrared laser irradiation. The damage characteristics for the two different wavelengths were visibly different, but the whole wound healing process was similar. The obtained results may provide references for the diagnosis, treatment, and evaluation of laser-induced damages.

Establishment of a differential diagnosis method and an online prediction platform for AOSD and sepsis based on gradient boosting decision trees algorithm.

OBJECTIVE: The differential diagnosis between adult-onset Still's disease (AOSD) and sepsis has always been a challenge. In this study, a machine learning model for differential diagnosis of AOSD and sepsis was developed and an online platform was developed to facilitate the clinical application of the model. METHODS: All data were collected from 42 AOSD patients and 50 sepsis patients admitted to Affiliated Hospital of Xuzhou Medical University from December 2018 to December 2021. In addition, 5 AOSD patients and 10 sepsis patients diagnosed in our hospital after March 2022 were collected for external validation. All models were built using the scikit-learn library (version 1.0.2) in Python (version 3.9.7), and feature selection was performed using the SHAP (Shapley Additive exPlanation) package developed in Python. RESULTS: The results showed that the gradient boosting decision tree(GBDT) optimization model based on arthralgia, ferritin × lymphocyte count, white blood cell count, ferritin × platelet count, and α1-acid glycoprotein/creatine kinase could well identify AOSD and sepsis. The training set interaction test (AUC: 0.9916, ACC: 0.9457, Sens: 0.9556, Spec: 0.9578) and the external validation also achieved satisfactory results (AUC: 0.9800, ACC: 0.9333, Sens: 0.8000, Spec: 1.000). We named this discrimination method AIADSS (AI-assisted discrimination of Still's disease and Sepsis) and created an online service platform for practical operation, the website is http://cppdd.cn/STILL1/ . CONCLUSION: We created a method for the identification of AOSD and sepsis based on machine learning. This method can provide a reference for clinicians to formulate the next diagnosis and treatment plan.

Intelligent identification system of gastric stromal tumors based on blood biopsy indicators.

BACKGROUND: The most prevalent mesenchymal-derived gastrointestinal cancers are gastric stromal tumors (GSTs), which have the highest incidence (60-70%) of all gastrointestinal stromal tumors (GISTs). However, simple and effective diagnostic and screening methods for GST remain a great challenge at home and abroad. This study aimed to build a GST early warning system based on a combination of machine learning algorithms and routine blood, biochemical and tumour marker indicators. METHODS: In total, 697 complete samples were collected from four hospitals in Gansu Province, including 42 blood indicators from 318 pretreatment GST patients, 180 samples of gastric polyps and 199 healthy individuals. In this study, three algorithms, gradient boosting machine (GBM), random forest (RF), and logistic regression (LR), were chosen to build GST prediction models for comparison. The performance and stability of the models were evaluated using two different validation techniques: 5-fold cross-validation and external validation. The DeLong test assesses significant differences in AUC values by comparing different ROC curves, the variance and covariance of the AUC value. RESULTS: The AUC values of both the GBM and RF models were higher than those of the LR model, and this difference was statistically significant (P < 0.05). The GBM model was considered to be the optimal model, as a larger area was enclosed by the ROC curve, and the axes indicated robust model classification performance according to the accepted model discriminant. Finally, the integration of 8 top-ranked blood indices was proven to be able to distinguish GST from gastric polyps and healthy people with sensitivity, specificity and area under the curve of 0.941, 0.807 and 0.951 for the cross-validation set, respectively. CONCLUSION: The GBM demonstrated powerful classification performance and was able to rapidly distinguish GST patients from gastric polyps and healthy individuals. This identification system not only provides an innovative strategy for the diagnosis of GST but also enables the exploration of hidden associations between blood parameters and GST for subsequent studies on the prevention and disease surveillance management of GST. The GST discrimination system is available online for free testing of doctors and high-risk groups at https://jzlyc.gsyy.cn/bear/mobile/index.html .

Exploring the precision redox map during fasting-refeeding and satiation in C. elegans.

Fasting is a popular dietary strategy because it grants numerous advantages, and redox regulation is one mechanism involved. However, the precise redox changes with respect to the redox species, organelles and tissues remain unclear, which hinders the understanding of the metabolic mechanism, and exploring the precision redox map under various dietary statuses is of great significance. Twelve redox-sensitive C. elegans strains stably expressing genetically encoded redox fluorescent probes (Hyperion sensing H2O2 and Grx1-roGFP2 sensing GSH/GSSG) in three organelles (cytoplasm, mitochondria and endoplasmic reticulum (ER)) were constructed in two tissues (body wall muscle and neurons) and were confirmed to respond to redox challenge. The H2O2 and GSSG/GSH redox changes in two tissues and three organelles were obtained by confocal microscopy during fasting, refeeding, and satiation. We found that under fasting condition, H2O2 decreased in most compartments, except for an increase in mitochondria, while GSSG/GSH increased in the cytoplasm of body muscle and the ER of neurons. After refeeding, the redox changes in H2O2 and GSSG/GSH caused by fasting were reversed in most organelles of the body wall muscle and neurons. In the satiated state, H2O2 increased markedly in the cytoplasm, mitochondria and ER of muscle and the ER of neurons, while GSSG/GSH exhibited no change in most organelles of the two tissues except for an increase in the ER of muscle. Our study systematically and precisely presents the redox characteristics under different dietary states in living animals and provides a basis for further investigating the redox mechanism in metabolism and optimizing dietary guidance.

Corneal damage threshold induced by supercontinuum source: A further study.

OBJECTIVES: Previous report shows that corneal spot size is an important influence factor on damage threshold induced by supercontinumm (SC) source. However, damage thresholds were determined for the spot size of only 0.37 mm due to the low output of the employed SC source at that time. The objectives of this study are to determine the lowest possible corneal damage threshold at a large corneal spot size using a more powerful SC source and provide data for the future possible refinements of laser safety standards. MATERIALS AND METHODS: A series of experiments was conducted in the New Zealand white rabbit model to determine the corneal damage threshold induced by a 900-2000 nm SC source, with corneal 1/e beam diameter of about 1.2 mm. Slit-lamp biomicroscope was employed to reveal the corneal damage characteristics. By employing the action spectra determined through the analysis of current laser safety guidelines and standards, the effective damage threshold could be calculated. RESULTS: The determined damage threshold given in terms of the peak radiant exposure for the exposure duration of 0.14 s was 44.3 J/cm2 . At threshold level, corneal damages involved the epithelium and the shallower stroma. The safety factor between the effective damage threshold and the corresponding maximum permissible exposure (MPE) was about 45. CONCLUSIONS: Present corneal MPEs in the wavelength range of 700-1200 nm may be conservative and corneal damage thresholds for the infrared A wavelengths should be determined in future studies.

A review on edible insects in China: Nutritional supply, environmental benefits, and potential applications.

This review explored the potential of edible insects to address the challenges of malnutrition and food security. Although grain production in China has met the Food and Agriculture Organization standards, the shortage of protein supply is still a big issue. Moreover, expanding livestock farming is considered unsustainable and environmentally unfriendly. Edible insects have become an alternative with higher sustainable and ecological properties. There are 324 species of insects currently consumed in China, and they have high nutritional value, with a rich source of protein and unsaturated fatty acids. Insect farming provides numerous benefits, including green feeds for livestock, poultry, and aquaculture, sustainable organic waste management, as well as industrial and pharmaceutical raw materials. The food toxicological evaluations conducted in China indicated that edible insects are safe for general consumption by the Chinese, but allergies and other related food safety issues should not be ignored. Consumer acceptance is another barrier to overcome, with different schemas between China and Western countries. More research on the potential functions of edible insects and their product development may enhance their acceptance in China. Overall, incorporating edible insects into our diet is a promising solution to address challenges related to protein supply and food security. To ensure safety and sustainability, appropriate legislation, quality regulations, large-scale insect farms, and acceptable processing techniques are necessary. Moreover, more scientific research and social awareness are required to promote the culture and utilization of edible insects in China.

Automated calibration and in-line measurement of product quality during therapeutic monoclonal antibody purification using Raman spectroscopy.

Current manufacturing and development processes for therapeutic monoclonal antibodies demand increasing volumes of analytical testing for both real-time process controls and high-throughput process development. The feasibility of using Raman spectroscopy as an in-line product quality measuring tool has been recently demonstrated and promises to relieve this analytical bottleneck. Here, we resolve time-consuming calibration process that requires fractionation and preparative experiments covering variations of product quality attributes (PQAs) by engineering an automation system capable of collecting Raman spectra on the order of hundreds of calibration points from two to three stock seed solutions differing in protein concentration and aggregate level using controlled mixing. We used this automated system to calibrate multi-PQA models that accurately measured product concentration and aggregation every 9.3 s using an in-line flow-cell. We demonstrate the application of a nonlinear calibration model for monitoring product quality in real-time during a biopharmaceutical purification process intended for clinical and commercial manufacturing. These results demonstrate potential feasibility to implement quality monitoring during GGMP manufacturing as well as to increase chemistry, manufacturing, and controls understanding during process development, ultimately leading to more robust and controlled manufacturing processes.

Metabolomics and Transcriptomics Revealed a Comprehensive Understanding of the Biochemical and Genetic Mechanisms Underlying the Color Variations in Chrysanthemums.

Flower color is an important characteristic of ornamental plants and is determined by various chemical components, including anthocyanin. In the present study, combined metabolomics and transcriptomics analysis was used to explore color variations in the chrysanthemums of three cultivars, of which the color of JIN is yellow, FEN is pink, and ZSH is red. A total of 29 different metabolites, including nine anthocyanins, were identified in common in the three cultivars. Compared with the light-colored cultivars, all of the nine anthocyanin contents were found to be up-regulated in the dark-colored ones. The different contents of pelargonidin, cyanidin, and their derivates were found to be the main reason for color variations. Transcriptomic analysis showed that the color difference was closely related to anthocyanin biosynthesis. The expression level of anthocyanin structural genes, including DFR, ANS, 3GT, 3MaT1, and 3MaT2, was in accordance with the flower color depth. This finding suggests that anthocyanins may be a key factor in color variations among the studied cultivars. On this basis, two special metabolites were selected as biomarkers to assist in chrysanthemum breeding for color selection.

Highly Enhancing CO2 Photoreduction by Metallization of an Imidazole-linked Robust Covalent Organic Framework.

Converting CO2 into value-added chemicals to solve the issues caused by carbon emission is promising but challenging. Herein, by embedding metal ions (Co2+ , Ni2+ , Cu2+ , and Zn2+ ) into an imidazole-linked robust photosensitive covalent organic framework (PyPor-COF), effective photocatalysts for CO2 conversion are rationally designed and constructed. Characterizations display that all of the metallized PyPor-COFs (M-PyPor-COFs) display remarkably high enhancement in their photochemical properties. Photocatalysis reactions reveal that the Co-metallized PyPor-COF (Co-PyPor-COF) achieves a CO production rate as high as up to 9645 µmol g-1 h-1 with a selectivity of 96.7% under light irradiation, which is more than 45 times higher than that of the metal-free PyPor-COF, while Ni-metallized PyPor-COF (Ni-PyPor-COF) can further tandem catalyze the generated CO to CH4 with a production rate of 463.2 µmol g-1 h-1 . Experimental analyses and theory calculations reveal that their remarkable performance enhancement on CO2 photoreduction should be attributed to the incorporated metal sites in the COF skeleton, which promotes the adsorption and activation of CO2 and the desorption of generated CO and even reduces the reaction energy barrier for the formation of different intermediates. This work demonstrates that by metallizing photoactive COFs, effective photocatalysts for CO2 conversion can be achieved.

Evolution of chemosensory and detoxification gene families across herbivorous Drosophilidae.

Herbivorous insects are exceptionally diverse, accounting for a quarter of all known eukaryotic species, but the genomic basis of adaptations that enabled this dietary transition remains poorly understood. Many studies have suggested that expansions and contractions of chemosensory and detoxification gene families-genes directly mediating interactions with plant chemical defenses-underlie successful plant colonization. However, this hypothesis has been challenging to test because the origins of herbivory in many insect lineages are ancient (>150 million years ago (mya)), obscuring genomic evolutionary patterns. Here, we characterized chemosensory and detoxification gene family evolution across Scaptomyza, a genus nested within Drosophila that includes a recently derived (<15 mya) herbivore lineage of mustard (Brassicales) specialists and carnation (Caryophyllaceae) specialists, and several nonherbivorous species. Comparative genomic analyses revealed that herbivorous Scaptomyza has among the smallest chemosensory and detoxification gene repertoires across 12 drosophilid species surveyed. Rates of gene turnover averaged across the herbivore clade were significantly higher than background rates in over half of the surveyed gene families. However, gene turnover was more limited along the ancestral herbivore branch, with only gustatory receptors and odorant-binding proteins experiencing strong losses. The genes most significantly impacted by gene loss, duplication, or changes in selective constraint were those involved in detecting compounds associated with feeding on living plants (bitter or electrophilic phytotoxins) or their ancestral diet (fermenting plant volatiles). These results provide insight into the molecular and evolutionary mechanisms of plant-feeding adaptations and highlight gene candidates that have also been linked to other dietary transitions in Drosophila.