Impact of agricultural irrigation and resettlement practices on carbon storage in arid inland river basins: A case study of the Shule river basin.

Agricultural irrigation and resettlement have significant impacts on carbon storage in arid inland river basins. With the background of "Comprehensive development measures for agricultural irrigation and resettlement in Shule River Basin (SRB)", this paper uses land use data to estimate regional carbon storage through InVEST model and revises the result by using net ecosystem productivity (NEP). The influence of land use change on carbon storage and the driving factors of carbon storage spatial differentiation were analyzed by using the optimal parameters geographical detector (OPGD). It can be inferred from the results that: (1) During 2000-2020, the increase of cropland and grassland area is the main type of land use change in the central oasis area of Yumen City and Guazhou County. Cumulative carbon storage increased by 1.75 × 107 t. (2) NEP in the central oasis area of Yumen City and Guazhou County showed a fluctuating upward trend, and it generally behaves as a carbon sink. The average annual NEP was 1.78 × 105 t, and the carbon sink increased by 0.95 × 105 t. (3) The main factors responsible for driving are vegetation, elevation, potential evapotranspiration, and precipitation. The explanatory power of each factor in carbon storage spatial differentiation was enhanced by the interaction between natural and anthropogenic factors. The interaction between vegetation and the human factor is more significant than that of the human single factor. (4) Agricultural irrigation and resettlement measures did not cause a decline in ecosystem carbon storage in Yumen City and Guazhou County in the central part of SRB. Conversely, the region's ecosystems have seen an increase in carbon storage as a result of the increase in cropland. (5) The introduction of the NEP modification method and the OPGD model improves the accuracy of carbon storage estimation and obtains better driving results in spatial differentiation. The study idea provides a new perspective for the estimation of carbon storage as a whole, and provides a reference basis for the formulation of ecological protection policies.

CropMetabolome: a comprehensive metabolome database for major crops cross eight categories.

Chemical compositions of crops are of great agronomical importance, as crops serve as resources for nutrition, energy, and medicines for human and livestock. For crop metabolomics research, the lack of crop reference metabolome and high-quality reference compound mass spectra, as well as utilities for metabolic profiling, has hindered the discovery and functional study of phytochemicals in crops. To meet these challenging needs, we have developed the Crop Metabolome database (abbreviated as CropMetabolome) that is dedicated to the construction of crop reference metabolome, repository, and dissemination of crop metabolomic data, and profiling and analytic tools for metabolomics research. CropMetabolome contains a metabolomics database for more than 50 crops (belonging to eight categories) that integrated self-generated raw mass spectral data and public-source datasets. The reference metabolome for 59 crop species was constructed, which have functions that parallel those of reference genome in genomic studies. CropMetabolome also contains 'Standard compound mass spectral library', 'Flavonoids library', 'Pesticide library', and a set of related analytical tools that enable metabolic profiling based on a reference metabolome (CropRefMetaBlast), annotation and identification of new metabolites (CompoundLibBlast), deducing the structure of novel flavonoid derivatives (FlavoDiscover), and detecting possible residual pesticides in crop samples (PesticiDiscover). In addition, CropMetabolome is a repository to share and disseminate metabolomics data and a platform to promote collaborations to develop reference metabolome for more crop species. CropMetabolome is a comprehensive platform that offers important functions in crop metabolomics research and contributes to improve crop breeding, nutrition, and safety. CropMetabolome is freely available at https://www.cropmetabolome.com/.

Tailored Fabrication of Full-Color Ultrastable Room-Temperature Phosphorescence Carbon Dots Composites with Unexpected Thermally Activated Delayed Fluorescence.

The development of single-system materials that exhibit both multicolor room-temperature phosphorescence (RTP) and thermally activated delayed fluorescence (TADF) with tunable after glow colors and channels is challenging. In this study, four metal-free carbon dots (CDs) are developed through structural tailoring, and panchromatic high-brightness RTP is achieved via strong chemical encapsulation in urea. The maximum lifetime and quantum yield reaches 2141 ms and 56.55%, respectively. Moreover, CDs-IV@urea, prepared via coreshell interaction engineering, exhibits a dual afterglow of red RTP and green TADF. The degree of conjugation and functional groups of precursors affects the binding interactions of the nitrogen cladding on CDs, which in turn stabilizes triplet energy levels and affects the energy gap between S1 and T1 (ΔEST) to induce multicolor RTP. The enhanced wrapping interaction lowers the ΔEST, promoting reverse intersystem crossing, which leads to phosphorescence and TADF. This strong coreshell interaction fully stabilizes the triplet state, thus stabilizing the material in water, even in extreme environments such as strong acids and oxidants. These afterglow materials are tested in multicolor, time, and temperature multiencryption as well as in multicolor in vivo bioimaging. Hence, these materials have promising practical applications in information security as well as biomedical diagnosis and treatment.

KINASE-INDUCIBLE DOMAIN INTERACTING 8 regulates helical pod morphology in Medicago truncatula.

Leguminosae exhibits a wide diversity of legume forms with varying degrees of spiral morphologies, serving as an ideal clade for studying the growth and development of spiral organs. While soybean (Glycine max) develops straight pods, the pod of the model legume Medicago truncatula is a helix structure. Despite the fascinating structures and intensive description of the pods in legumes, little is known regarding the genetic mechanism underlying the highly varied spirality of the legume pods. In this study, we found that KINASE-INDUCIBLE DOMAIN INTERACTING 8 (MtKIX8) plays a key role in regulating the pod structure and spirality in M. truncatula. Unlike the coiled and barrel-shaped helix pods of the wild type, the pods of the mtkix8 mutant are loose and deformed and lose the topologic structure as observed in the wild-type pods. In the pods of the mtkix8 mutant, the cells proliferate more actively and overly expand, particularly in the ventral suture, resulting in uncoordinated growth along the dorsal and ventral sutures of pods. The core cell cycle genes CYCLIN D3s are upregulated in the mtkix8 pods, leading to the prolonged growth of the ventral suture region of the pods. Our study revealed the key role of MtKIX8 in regulating seed pod development in M. truncatula and demonstrates a genetic regulatory model underlying the establishment of the helical pod in legumes.

Green Printing for Scalable Organic Photovoltaic Modules by Controlling the Gradient Marangoni Flow.

Despite the rapid development in the performances of organic solar cells (OSCs), high-performance OSC modules based on green printing are still limited. The severe Coffee-ring effect (CRE) is considered to be the primary reason for the nonuniform distribution of active layer films. To solve this key printing problem, the cosolvent strategy is presented to deposit the active layer films. The guest solvent Mesitylene with a higher boiling point and a lower surface tension is incorporated into the host solvent o-XY to optimize the rheological properties, such as surface tension and viscosity of the active layer solutions. And the synergistic effect of inward Marangoni flow generation and solution thickening caused by the cosolvent strategy can effectively restrain CRE, resulting in highly homogeneous large-area active layer films. In addition, the optimized crystallization and phase separation of active layer films effectively accelerate the charge transport and exciton dissociation of devices. Consequently, based on PM6:BTP-eC9 system, the device prepared with the co-solvent strategy shows the a power conversion efficiency of 17.80%. Moreover, as the effective area scales to 1 and 16.94 cm2, the recorded performances are altered to 16.71% and 14.58%. This study provides a universal pathway for the development of green-printed high-efficiency organic photovoltaics.

Polyethylene Upgrading to Liquid Fuels Boosted by Atomic Ce Promoters.

Hydrocracking catalysis is a key route to plastic waste upgrading, but the acid site-driven C-C cleavage step is relatively sluggish in conventional bifunctional catalysts, dramatically effecting the overall efficiency. We demonstrate here a facile and efficient way to boost the reactivity of acid sites by introducing Ce promoters into Pt/HY catalysts, thus achieving a better metal-acid balance. Remarkably, 100 % of low-density polyethylene (LDPE) can be converted with 80.9 % selectivity of liquid fuels over the obtained Pt/5Ce-HY catalysts at 300 °C in 2 h. For comparison, Pt/HY only gives 38.8 % of LDPE conversion with 21.3 % selectivity of liquid fuels. Through multiple experimental studies on the structure-performance relationship, the Ce species occupied in the supercage are identified as the actual active sites, which possess remarkably-improved adsorption capability towards short-chain intermediates.

RefMetaPlant: a reference metabolome database for plants across five major phyla.

Plants are unique with tremendous chemical diversity and metabolic complexity, which is highlighted by estimates that green plants collectively produce metabolites numbering in the millions. Plant metabolites play crucial roles in all aspects of plant biology, like growth, development, stress responses, etc. However, the lack of a reference metabolome for plants, and paucity of high-quality standard compound spectral libraries and related analytical tools, have hindered the discovery and functional study of phytochemicals in plants. Here, by leveraging an advanced LC-MS platform, we generated untargeted mass spectral data from >150 plant species collected across the five major phyla. Using a self-developed computation protocol, we constructed reference metabolome for 153 plant species. A 'Reference Metabolome Database for Plants' (RefMetaPlant) was built to encompass the reference metabolome, integrated standard compound mass spectral libraries for annotation, and related query and analytical tools like 'LC-MS/MS Query', 'RefMetaBlast' and 'CompoundLibBlast' for searches and profiling of plant metabolome and metabolite identification. Analogous to a reference genome in genomic research, RefMetaPlant provides a powerful platform to support plant genome-scale metabolite analysis to promote knowledge/data sharing and collaboration in the field of metabolomics. RefMetaPlant is freely available at https://www.biosino.org/RefMetaDB/.

Therapeutic targeting of vimentin by ALD-R491 impacts multiple pathogenic processes to attenuate acute and chronic colitis in mice.

BACKGROUND: Vimentin, an intermediate filament protein, crucially contributes to the pathogenesis of inflammatory bowel disease (IBD) by interacting with genetic risk factors, facilitating pathogen infection, and modulating both innate and adaptive immune responses. This study aimed to demonstrate preclinical proof-of-concept for targeting vimentin therapeutically in IBD across diverse etiologies. METHODS: The small molecule compound ALD-R491 was assessed for vimentin binding using microscale thermophoresis, off-target effects via Eurofins screening, and therapeutic effects in mice with dextran sulfate sodium (DSS)-induced acute colitis and in IL-10 KO with spontaneous colitis. Parameters measured included body weight, survival, disease activity, colon length, and histology. The study analyzed intestinal proinflammatory cytokines, Th17/Treg cells, and epithelial barrier molecules, along with gut microbiota profiling. RESULTS: ALD-R491 specifically bound vimentin with a dissociation constant (KD) of 328 ± 12.66 nM and no off-target effects. In the DSS model, orally administered ALD-R491 exhibited dose-dependent therapeutic effects, superior to 5-ASA and Tofacitinib. In the IL-10 KO model, ALD-R491 significantly delayed colitis onset and progression, with near-zero disease activity index scores over a 15-week treatment. ALD-R491 consistently showed in both models a reduced proinflammatory cytokine expression, including TNF-α, IL-1ß, IL-6, IL-17, IL-22, a rebalanced Th17/Treg axis by reducing RORγt while enhancing FoxP3 expression, and an improved epithelial barrier integrity by increasing intestinal expressions of Mucin-2, ZO-1 and Claudin5. The intestinal dysbiosis was restored with enriched presence of probiotics. CONCLUSIONS: Targeting vimentin exhibits significant therapeutic effects on various facets of IBD pathogenesis, representing a compelling approach for the development of highly effective treatments in IBD.

The quality of life in nasopharyngeal carcinoma radiotherapy: A longitudinal study.

Objective: This article aims to longitudinally compare nasopharyngeal carcinoma (NPC) patients' quality of life (QoL) during radiotherapy (RT) and identify QoL correlates. Methods: This study included 98 patients, with 85 completing full follow-up. Data were collected at baseline (T1), midpoint of RT (T2), and RT completion (T3), between October 2021 and November 2022. QoL was assessed using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30). RIOM severity was evaluated by the toxicity criteria of Radiation Therapy Oncology Group (RTOG). The nutritional status was evaluated using the Nutritional Risk Screening 2002 (NRS 2002), body mass index (BMI), and the Patient-Generated Subjective Global Assessment (PG-SGA). The generalized estimating equation described the QoL evolution and correlated it with RIOM, nutritional status, and other influential factors. Results: Significant deterioration was observed in various subscales of EORTC QLQ-C30 during RT, including global health status (GHS), physical function, role function, emotional function, fatigue, nausea/vomiting, pain, insomnia, appetite loss, and constipation (all P â€‹< â€‹0.05). Substantial deterioration was also observed in RIOM, nutritional status, and part of hematological indexes (all P â€‹< â€‹0.05). The decline of QoL was associated with gender, age, education level, chemotherapy regimen, Karnofsky performance status (KPS) score, RIOM severity, NRS 2002 score, PG-SGA score, and lymphocyte level (all P â€‹< â€‹0.05). Conclusions: QoL declined during RT and were associated with certain factors. Healthcare professionals should focus on alleviating treatment-related complications and identifying individuals at high risk of malnutrition early to improve outcomes for patients with NPC.

Dual-Site Metal Catalysts for Electrocatalytic CO2 Reduction Reaction.

Electrocatalytic CO2 reduction reaction (CO2 RR) is a promising and green approach for reducing atmospheric CO2 concentration and achieving high-valued conversion of CO2 under the carbon-neutral policy. In CO2 RR, the dual-site metal catalysts (DSMCs) have received wide attention for their ingenious design strategies, abundant active sites, and excellent catalytic performance attributed to the synergistic effect between dual-site in terms of activity, selectivity and stability, which plays a key role in catalytic reactions. This review provides a systematic summary and detailed classification of DSMCs for CO2 RR, describes the mechanism of synergistic effects in catalytic reactions, and also introduces in situ characterization techniques commonly used in CO2 RR. Finally, the main challenges and prospects of dual-site metal catalysts and even multi-site catalysts for CO2 recycling are analyzed. It is believed that based on the understanding of bimetallic site catalysts and synergistic effects in CO2 RR, well-designed high-performance, low-cost electrocatalysts are promising for achieving CO2 conversion, electrochemical energy conversion and storage in the future.

Nutrition management for patients with head and neck cancer during peri-radiotherapy: A systematic review and quality appraisal of clinical practice guidelines using the AGREE II instrument.

Objective: To evaluate the quality of clinical practice guidelines (CPGs) for nutrition management of patients with head and neck cancer (HNC) during peri-radiotherapy, as well as to summarize the nutrition recommendations fitting the subject. Methods: CPGs published in English, Chinese and German were identified from databases, guideline networks, and websites of nutritional associations from the databases' inception to March 8, 2022. Three independent appraisers used the Appraisal of Guidelines for Research and Evaluation II (AGREE II) Instrument to assess the quality of CPGs. The intraclass correlation coefficient (ICC) was used to calculate appraiser agreement. Results: 769 records were identified. After removing duplicates, 470 articles were screened. 12 CPGs were identified with nutrition-specific recommendations. 67% of CPGs were rated as high quality, and 33% as low quality. Recommendations were categorized into nutritional risk screening, nutrition assessment, nutrition counseling, nutrition interventions, nutrition intake, swallowing function management, weight management, exercise, multidisciplinary team, post-discharge care, nutrients, and pharmacologic interventions. Conclusion: We found discrepant recommendations in existing CPGs, including nutrition screening, nutrition assessment, nutrition intake, and nutrients. We also reported the absence of essential parts of CPGs, including the views of its target users, the statement of external review, the method to formulate the recommendations, strategies to improve uptake, and resource implications of applying the CPGs. CPGs with low quality should be improved in future updates based on currently available guideline development tools. Specialized CPGs on nutrition management for HNC patients during peri-radiotherapy should be developed. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/index.php, identifier CRD42022320322.

Origin and Genesis of the Permain Hydrocarbon in the Northeast of the Dongdaohaizi Depression, Junggar Basin, China.

Dongdaohaizi area is an important hydrocarbon-rich depression in the Junggar Basin. Early resource evaluation has revealed that it has superior hydrocarbon generation conditions. No major exploration breakthrough has been observed in the hydrocarbon from the Permian Pingdiquan Formation source rocks, which are widely distributed and have a large sedimentary thickness. The unclear recognition of the genesis, the sources, and the hydrocarbon evolution history of the formation seriously restricted further exploration and development. Sixty-four samples were acquired during the study, consisting of 30 source rocks, 13 crude oil samples, and 21 natural gas samples. Studying the geochemical characteristics of the source rock extract and the surrounding structural crude oil in the Dongdaohaizi Depression, the differences in the stable carbon isotope, the biomarker compound, and the molecular relative composition of the three sets of main source rock products in the research fields are summarized. The results reflect that the drying coefficient of natural gas in the study area is generally low, and the fractional distillation value of methane and ethane is 0.32, which is most likely due to the loss of oil and gas migration and the mixing of different types of natural gases. The carbon isotope value is relatively low, with the Pr/Ph being generally less than 3.0. The content of sterane C29 is the highest in the relative composition of steranes, followed by the content of sterane C28, which together account for more than 80% of the total sterane content, and then followed by a lower content of C27 sterane, accounting for only 5-20% of the total content, which generally conforms to the characteristics of Permian Pingdiquan Formation source rock products. The carbon isotope value of crude oil ranges from -30.94 to -28.31‰, which is different from the characteristics of typical Permian source rocks (values range from -34.49 to -28.21‰), while it is related to typical Carboniferous products (values range from -29.98 to -24.1‰), indicating that small amounts of Carboniferous source rock products were mixed in different degrees in the Dinan fault area. According to the distribution law of oil and gas, the geochemical characteristics and hydrocarbon sources were considered the oil source in the east of the Dongdaohaizi Depression, mainly from the source rocks of the Permian Pingdiquan Formation. The products of the peak period of hydrocarbon generation in the source rocks of the Pingdiquan Formation have not been transported to the high structural positions on a large scale to form reservoirs. They may still exist in the deep part of the Depression and the slope area. The low-amplitude structural and lithologic traps in the slope area of the Dongdahaizi Depression are promising targets for finding the products of the peak period of hydrocarbon generation. This is of great significance to reveal the Permain hydrocarbon evolution in the Junggar Basin and guide further research on the oil-source correlation of natural gas from the paleo-strata.

Evaluation of the Efficiency of MRI-Based Radiomics Classifiers in the Diagnosis of Prostate Lesions.

Objective: To compare the performance of different imaging classifiers in the prospective diagnosis of prostate diseases based on multiparameter MRI. Methods: A total of 238 patients with pathological outcomes were enrolled from September 2019 to July 2021, including 142 in the training set and 96 in the test set. After the regions of interest were manually segmented, decision tree (DT), Gaussian naive Bayes (GNB), XGBoost, logistic regression, random forest (RF) and support vector machine classifier (SVC) models were established on the training set and tested on the independent test set. The prospective diagnostic performance of each classifier was compared by using the AUC, F1-score and Brier score. Results: In the patient-based data set, the top three classifiers of combined sequences in terms of the AUC were logistic regression (0.865), RF (0.862), and DT (0.852); RF "was significantly different from the other two classifiers (P =0.022, P =0.005), while logistic regression and DT had no statistical significance (P =0.802). In the lesions-based data set, the top three classifiers of combined sequences in terms of the AUC were RF (0.931), logistic regression (0.922) and GNB (0.922). These three classifiers were significantly different from. Conclusion: The results of this experiment show that radiomics has a high diagnostic efficiency for prostate lesions. The RF classifier generally performed better overall than the other classifiers in the experiment. The XGBoost and logistic regression models also had high classification value in the lesions-based data set.

Pseudo-Planar Heterojunction Organic Photovoltaics with Optimized Light Utilization for Printable Solar Windows.

The existing conformation of the active layer is defective for employment of semitransparent organic solar cells (ST-OSCs) in solar windows. Herein, scalable solar windows are successfully printed by introducing a pseudo-planar heterojunction (PPHJ) structure. The PPHJ structure can effectively improve the average visible transmittance (AVT) value while boosting the power conversion efficiency (PCE) of semitransparent devices due to the reduced optical loss. The universality of the PPHJ structure in the preparation of ST-OSCs is proved. Furthermore, an inset of a superhydrophobic patterned soft insertion layer (PSIL) in the encapsulated window improves the waterproof performance without losing transparency. Accordingly, the semitransparent devices based on the 2,2'-((2Z,2'Z)-((12,13-bis(2-ethylhexyl)-3,9-diundecyl-12,13-dihydro-[1,2,5]thiadiazolo[3,4-e]thieno[2″,3″:4',5']thieno[2',3':4,5]pyrrolo[3,2-g]thieno[2',3':4,5]thieno[3,2-b]indole-2,10-diyl)bis(methanylylidene))bis(5,6-difluoro-3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile (Y6) system afford a maximal efficiency of 14.62%, with a considerable AVT of 20.42%, and the resultant solar windows achieve a stabilized efficiency of 13.34% with excellent waterproof performance. Moreover, the PCE of the unilateral broken solar windows retains 70.6% of the initial efficiency after being placed under simulated rainfall conditions for 1200 h at room temperature.

Comprehensive Genomic Survey, Evolution, and Expression Analysis of GIF Gene Family during the Development and Metal Ion Stress Responses in Soybean.

The GIF gene family is one of the plant transcription factors specific to seed plants. The family members are expressed in all lateral organs produced by apical and floral meristems and contribute to the development of leaves, shoots, flowers, and seeds. This study identified eight GIF genes in the soybean genome and clustered them into three groups. Analyses of Ka/Ks ratios and divergence times indicated that they had undergone purifying selection during species evolution. RNA-sequence and relative expression patterns of these GmGIF genes tended to be conserved, while different expression patterns were also observed between the duplicated GIF members in soybean. Numerous cis-regulatory elements related to plant hormones, light, and stresses were found in the promoter regions of these GmGIF genes. Moreover, the expression patterns of GmGIF members were confirmed in soybean roots under cadmium (Cd) and copper (Cu) stress, indicating their potential functions in the heavy metal response in soybean. Our research provides valuable information for the functional characterization of each GmGIF gene in different legumes in the future.

Expanding the Coverage of Metabolic Landscape in Cultivated Rice with Integrated Computational Approaches.

Genome-scale metabolomics analysis is increasingly used for pathway and function discovery in the post-genomics era. The great potential offered by developed mass spectrometry (MS)-based technologies has been hindered, since only a small portion of detected metabolites were identifiable so far. To address the critical issue of low identification coverage in metabolomics, we adopted a deep metabolomics analysis strategy by integrating advanced algorithms and expanded reference databases. The experimental reference spectra and in silico reference spectra were adopted to facilitate the structural annotation. To further characterize the structure of metabolites, two approaches were incorporated into our strategy, i.e., structural motif search combined with neutral loss scanning and metabolite association network. Untargeted metabolomics analysis was performed on 150 rice cultivars using ultra-performance liquid chromatography coupled with quadrupole-Orbitrap MS. Consequently, a total of 1939 out of 4491 metabolite features in the MS/MS spectral tag (MS2T) library were annotated, representing an extension of annotation coverage by an order of magnitude in rice. The differential accumulation patterns of flavonoids between indica and japonica cultivars were revealed, especially O-sulfated flavonoids. A series of closely-related flavonolignans were characterized, adding further evidence for the crucial role of tricin-oligolignols in lignification. Our study provides an important protocol for exploring phytochemical diversity in other plant species.

Vorinostat Corrects Cognitive and Non-Cognitive Symptoms in a Mouse Model of Fragile X Syndrome.

BACKGROUND: Fragile X syndrome (FXS) is caused by mutations in the FMR1 gene. It is a form of heritable intellectual disability and autism. Despite recent advance in elucidating disease mechanisms, there is no efficacious medication. Because de novo drug development is a lengthy process, repurposing the existing FDA-approved drugs offers an opportunity to advance clinical intervention for FXS. Our previous study with transcriptome analysis predicts potential therapeutic effects of vorinostat on FXS. METHODS: We analyzed the vorinostat-induced transcriptome changes and confirmed its similarity to that induced by trifluoperazine, which was previously shown to correct pathological outcomes associated with FXS. To validate the therapeutic efficacy, we examined vorinostat's effect on correcting the key behavioral and cellular symptoms in a mouse model of FXS. RESULTS: We found that vorinostat restores object location memory and passive avoidance memory in the Fmr1 knockout mice. For the non-cognitive behavioral symptoms, vorinostat corrected the autism-associated alterations, including repetitive behavior and social interaction deficits. In the open field test, vorinostat dampened hyperactivity in the center area of the arena. Surprisingly, vorinostat did not correct the abnormally elevated protein synthesis in cultured Fmr1 knockout hippocampal neurons, suggesting that different aspects of pathological outcomes may respond differently to a specific therapeutic intervention. CONCLUSIONS: We used the drug-induced transcriptome signature to predict new application of existing drugs. Our data reveal the therapeutic effects of the FDA-approved drug vorinostat in a mouse model of FXS.

Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast Cancer.

Aim: After neoadjuvant chemotherapy (NACT), tumor shrinkage pattern is a more reasonable outcome to decide a possible breast-conserving surgery (BCS) than pathological complete response (pCR). The aim of this article was to establish a machine learning model combining radiomics features from multiparametric MRI (mpMRI) and clinicopathologic characteristics, for early prediction of tumor shrinkage pattern prior to NACT in breast cancer. Materials and Methods: This study included 199 patients with breast cancer who successfully completed NACT and underwent following breast surgery. For each patient, 4,198 radiomics features were extracted from the segmented 3D regions of interest (ROI) in mpMRI sequences such as T1-weighted dynamic contrast-enhanced imaging (T1-DCE), fat-suppressed T2-weighted imaging (T2WI), and apparent diffusion coefficient (ADC) map. The feature selection and supervised machine learning algorithms were used to identify the predictors correlated with tumor shrinkage pattern as follows: (1) reducing the feature dimension by using ANOVA and the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation, (2) splitting the dataset into a training dataset and testing dataset, and constructing prediction models using 12 classification algorithms, and (3) assessing the model performance through an area under the curve (AUC), accuracy, sensitivity, and specificity. We also compared the most discriminative model in different molecular subtypes of breast cancer. Results: The Multilayer Perception (MLP) neural network achieved higher AUC and accuracy than other classifiers. The radiomics model achieved a mean AUC of 0.975 (accuracy = 0.912) on the training dataset and 0.900 (accuracy = 0.828) on the testing dataset with 30-round 6-fold cross-validation. When incorporating clinicopathologic characteristics, the mean AUC was 0.985 (accuracy = 0.930) on the training dataset and 0.939 (accuracy = 0.870) on the testing dataset. The model further achieved good AUC on the testing dataset with 30-round 5-fold cross-validation in three molecular subtypes of breast cancer as following: (1) HR+/HER2-: 0.901 (accuracy = 0.816), (2) HER2+: 0.940 (accuracy = 0.865), and (3) TN: 0.837 (accuracy = 0.811). Conclusions: It is feasible that our machine learning model combining radiomics features and clinical characteristics could provide a potential tool to predict tumor shrinkage patterns prior to NACT. Our prediction model will be valuable in guiding NACT and surgical treatment in breast cancer.

Spatiotemporal Resolved Live Cell Membrane Tracking through Photo-click Reactions Enriched in Lipid Phase.

A set of photo-switchable monopeptides derived from cis-ß-dibenzodiazocine-l-alanine (cis-DBDAA) have been designed and synthesized, which are capable of photo-click reacting with diaryltetrazoles or diarylsydnones in a hydrophobic phospholipid bilayer environment. The DBDAA monopeptides include both a hydrophobic tail on C-terminal, providing high affinity toward lipid membrane, and a modularized functional moiety on N-terminal, enabling rapid optimization of the self-assembly strength to form multifunctional supramolecules. With the cis-DBDAA monopeptides photo-switched into trans-configuration, we were able to disrupt the supramolecular assembly through an efficient photo-click reaction across the lipid bilayer of liposomes. We reveal that the performance of the photo-click reactions between the monopeptides and photo-generated nitrile imine intermediates is significantly enhanced by enrichment of both reactants in the hydrophobic membrane lamel of liposomes. Enrichment of the DBDAA monopeptide in lipid phase serves as a convenient method to introduce bioorthogonal chemical handles on live cell membranes, which enables fluorescence labelling of single cell's membrane with high spatiotemporal resolution to facilitate the studies on cell membrane dynamics.

Integrated metabolomics and transcriptomics study of traditional herb Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao reveals global metabolic profile and novel phytochemical ingredients.

BACKGROUND: Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao is one of the most common herbs widely used in South and East Asia, to enhance people's health and reinforce vital energy. Despite its prevalence, however, the knowledge about phytochemical compositions and metabolite biosynthesis in Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao is very limited. RESULTS: An integrated metabolomics and transcriptomics analysis using state-of-the-art UPLC-Q-Orbitrap mass spectrometer and advanced bioinformatics pipeline were conducted to study global metabolic profiles and phytochemical ingredients/biosynthesis in Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao. A total of 5435 metabolites were detected, from which 2190 were annotated, representing an order of magnitude increase over previously known. Metabolic profiling of Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao tissues found contents and synthetic enzymes for phytochemicals were significantly higher in leaf and stem in general, whereas the contents of the main bioactive ingredients were significantly enriched in root, underlying the value of root in herbal remedies. Using integrated metabolomics and transcriptomics data, we illustrated the complete pathways of phenylpropanoid biosynthesis, flavonoid biosynthesis, and isoflavonoid biosynthesis, in which some were first reported in the herb. More importantly, we discovered novel flavonoid derivatives using informatics method for neutral loss scan, in addition to inferring their likely synthesis pathways in Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao. CONCLUSIONS: The current study represents the most comprehensive metabolomics and transcriptomics analysis on traditional herb Astragalus membranaceus Bge. var. mongolicus (Bge.) Hsiao. We demonstrated our integrated metabolomics and transcriptomics approach offers great potentials in discovering novel metabolite structure and associated synthesis pathways. This study provides novel insights into the phytochemical ingredients, metabolite biosynthesis, and complex metabolic network in herbs, highlighting the rich natural resource and nutritional value of traditional herbal plants.