ChemFREE: a one-stop comprehensive platform for ecological and environmental risk evaluation of chemicals in one health world.

Addressing health and safety crises stemming from various environmental and ecological issues is a core focus of One Health (OH), which aims to balance and optimize the health of humans, animals, and the environment. While many chemicals contribute significantly to our quality of life when properly used, others pose environmental and ecological health risks. Recently, assessing the ecological and environmental risks associated with chemicals has gained increasing significance in the OH world. In silico models may address time-consuming and costly challenges, and fill gaps in situations where no experimental data is available. However, despite their significant contributions, these assessment models are not web-integrated, leading to user inconvenience. In this study, we developed a one-stop comprehensive web platform for freely evaluating the eco-environmental risk of chemicals, named ChemFREE (Chemical Formula Risk Evaluation of Eco-environment, available in http://chemfree.agroda.cn/chemfree/). Inputting SMILES string of chemicals, users will obtain the assessment outputs of ecological and environmental risk, etc. A performance evaluation of 2935 external chemicals revealed that most classification models achieved an accuracy rate above 0.816. Additionally, the $Q_{F1}^2$ metric for regression models ranges from 0.618 to 0.898. Therefore, it will facilitate the eco-environmental risk evaluation of chemicals in the OH world.

PlantPAD: a platform for large-scale image phenomics analysis of disease in plant science.

Plant disease, a huge burden, can cause yield loss of up to 100% and thus reduce food security. Actually, smart diagnosing diseases with plant phenomics is crucial for recovering the most yield loss, which usually requires sufficient image information. Hence, phenomics is being pursued as an independent discipline to enable the development of high-throughput phenotyping for plant disease. However, we often face challenges in sharing large-scale image data due to incompatibilities in formats and descriptions provided by different communities, limiting multidisciplinary research exploration. To this end, we build a Plant Phenomics Analysis of Disease (PlantPAD) platform with large-scale information on disease. Our platform contains 421 314 images, 63 crops and 310 diseases. Compared to other databases, PlantPAD has extensive, well-annotated image data and in-depth disease information, and offers pre-trained deep-learning models for accurate plant disease diagnosis. PlantPAD supports various valuable applications across multiple disciplines, including intelligent disease diagnosis, disease education and efficient disease detection and control. Through three applications of PlantPAD, we show the easy-to-use and convenient functions. PlantPAD is mainly oriented towards biologists, computer scientists, plant pathologists, farm managers and pesticide scientists, which may easily explore multidisciplinary research to fight against plant diseases. PlantPAD is freely available at http://plantpad.samlab.cn.

Fluorescent chemosensors facilitate the visualization of plant health and their living environment in sustainable agriculture.

Globally, 91% of plant production encounters diverse environmental stresses that adversely affect their growth, leading to severe yield losses of 50-60%. In this case, monitoring the connection between the environment and plant health can balance population demands with environmental protection and resource distribution. Fluorescent chemosensors have shown great progress in monitoring the health and environment of plants due to their high sensitivity and biocompatibility. However, to date, no comprehensive analysis and systematic summary of fluorescent chemosensors used in monitoring the correlation between plant health and their environment have been reported. Thus, herein, we summarize the current fluorescent chemosensors ranging from their design strategies to applications in monitoring plant-environment interaction processes. First, we highlight the types of fluorescent chemosensors with design strategies to resolve the bottlenecks encountered in monitoring the health and living environment of plants. In addition, the applications of fluorescent small-molecule, nano and supramolecular chemosensors in the visualization of the health and living environment of plants are discussed. Finally, the major challenges and perspectives in this field are presented. This work will provide guidance for the design of efficient fluorescent chemosensors to monitor plant health, and then promote sustainable agricultural development.

Meta-learning shows great potential in plant disease recognition under few available samples.

Plant diseases worsen the threat of food shortage with the growing global population, and disease recognition is the basis for the effective prevention and control of plant diseases. Deep learning has made significant breakthroughs in the field of plant disease recognition. Compared with traditional deep learning, meta-learning can still maintain more than 90% accuracy in disease recognition with small samples. However, there is no comprehensive review on the application of meta-learning in plant disease recognition. Here, we mainly summarize the functions, advantages, and limitations of meta-learning research methods and their applications for plant disease recognition with a few data scenarios. Finally, we outline several research avenues for utilizing current and future meta-learning in plant science. This review may help plant science researchers obtain faster, more accurate, and more credible solutions through deep learning with fewer labeled samples.

GIFTdb: a useful gene database for plant fruit traits improving.

Fruit traits are critical determinants of plant fitness, resource diversity, productive and quality. Gene regulatory networks in plants play an essential role in determining fruit traits, such as fruit size, yield, firmness, aroma and other important features. Many research studies have focused on elucidating the associated signaling pathways and gene interaction mechanism to better utilize gene resources for regulating fruit traits. However, the availability of specific database of genes related to fruit traits for use by the plant research community remains limited. To address this limitation, we developed the Gene Improvements for Fruit Trait Database (GIFTdb, http://giftdb.agroda.cn). GIFTdb contains 35 365 genes, including 896 derived from the FR database 1.0, 305 derived from 30 882 articles from 2014 to 2021, 236 derived from the Universal Protein Resource (UniProt) database, and 33 928 identified through homology analysis. The database supports several aided analysis tools, including signal transduction pathways, gene ontology terms, protein-protein interactions, DNAWorks, Basic Local Alignment Search Tool (BLAST), and Protein Subcellular Localization Prediction (WoLF PSORT). To provide information about genes currently unsupported in GIFTdb, potential fruit trait-related genes can be searched based on homology with the supported genes. GIFTdb can provide valuable assistance in determining the function of fruit trait-related genes, such as MYB306-like, by conducting a straightforward search. We believe that GIFTdb will be a valuable resource for researchers working on gene function annotation and molecular breeding to improve fruit traits.

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era.

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

HBI transcription factor-mediated ROS homeostasis regulates nitrate signal transduction.

Nitrate is both an important nutrient and a critical signaling molecule that regulates plant metabolism, growth, and development. Although several components of the nitrate signaling pathway have been identified, the molecular mechanism of nitrate signaling remains unclear. Here, we showed that the growth-related transcription factors HOMOLOG OF BRASSINOSTEROID ENHANCED EXPRESSION2 INTERACTING WITH IBH1 (HBI1) and its three closest homologs (HBIs) positively regulate nitrate signaling in Arabidopsis thaliana. HBI1 is rapidly induced by nitrate through NLP6 and NLP7, which are master regulators of nitrate signaling. Mutations in HBIs result in the reduced effects of nitrate on plant growth and ∼22% nitrate-responsive genes no longer to be regulated by nitrate. HBIs increase the expression levels of a set of antioxidant genes to reduce the accumulation of reactive oxygen species (ROS) in plants. Nitrate treatment induces the nuclear localization of NLP7, whereas such promoting effects of nitrate are significantly impaired in the hbi-q and cat2 cat3 mutants, which accumulate high levels of H2O2. These results demonstrate that HBI-mediated ROS homeostasis regulates nitrate signal transduction through modulating the nucleocytoplasmic shuttling of NLP7. Overall, our findings reveal that nitrate treatment reduces the accumulation of H2O2, and H2O2 inhibits nitrate signaling, thereby forming a feedback regulatory loop to regulate plant growth and development.

Minimal residual disease monitoring in childhood Philadelphia chromosome-positive acute lymphoblastic leukemia: prognostic significance and correlation between multiparameter flow cytometry and real-time quantitative polymerase chain reaction

Not available.

Flavonoid as a Potent Antioxidant: Quantitative Structure-Activity Relationship Analysis, Mechanism Study, and Molecular Design by Synergizing Molecular Simulation and Machine Learning.

In this work, a quantitative structure-antioxidant activity relationship of flavonoids was performed using a machine learning (ML) method. To achieve lipid-soluble, highly antioxidant flavonoids, 398 molecular structures with various substitute groups were designed based on the flavonoid skeleton. The hydrogen dissociation energies (ΔG1, ΔG2, and ΔG3) related to multiple hydrogen atom transfer processes and the solubility parameter (δ) of flavonoids were calculated using molecular simulation. The group decomposition results and the calculated antioxidant parameters constituted the ML data set. The artificial neural network and random forest models were constructed to predict and analyze the contribution of the substitute groups and positions to the antioxidant activity. The results showed the hydroxyl group at positions B4', B5', and B6' and the branched alkyl group at position C3 in the flavonoid skeleton were the optimal choice for improving antioxidant activity and compatibility with apolar organic materials. Compared to the pyrogallol group-grafted flavonoid, the designed potent flavonoid decreased ΔG1 and δ by 2.2 and 15.1%, respectively, while ΔG2 and ΔG3 kept the favorable lower values. These findings suggest that an efficient flavonoid prefers multiple ortho-phenolic hydroxyl groups and suitable sites with hydrophobic groups. The combination of molecular simulation and the ML method may offer a new research approach for the molecular design of novel antioxidants.

Mechanisms underlying LncRNA SNHG1 regulation of Alzheimer's disease involve DNA methylation.

Alzheimer's disease (AD) is a neurodegenerative disease associated with long non-coding RNAs and DNA methylation; however, the mechanisms underlying the role of lncRNA small nucleolar RNA host gene 1 (lncRNA SNHG1) and subsequent involvement of DNA methylation in AD development are not known. The aim of this study was to examine the regulatory mechanisms attributed to lncRNA SNHG1 gene utilizing 2 strains of senescence-accelerated mouse prone 8 (SAMP8) model of AD and compared to senescence-accelerated mouse resistant (SAMR) considered a control. Both strains of the mouse were transfected with either blank virus, psLenti-U6-SNHG1(low gene expression) virus, and psLenti-pA-SNHG1(gene overexpression) virus via a single injection into the brains for 2 weeks. At 2 weeks mice were subjected to a Morris water maze to determine any behavioral effects followed by sacrifice to extract hippocampal tissue for Western blotting to measure protein expression of p-tau, DNMT1, DNMT3A, DNMT3B, TET1, and p-Akt. No marked alterations were noted in any parameters following blank virus transfection. In SAMP8 mice, a significant decrease was noted in protein expression of DNMT1, DNMT3A, DNMT3B, and p-Akt associated with rise in p-tau and TET1. Transfection with ps-Lenti-U6-SNHG1 alone in SAMR1 mice resulted in a significant rise in DNMTs and p-Akt and a fall in p-tau and TET1. Transfection of SAMP8 with ps-Lenti-U6-SNHG1 blocked effects on overexpression noted in this mouse strain. However, knockdown of lncRNA SNHG1 yielded the opposite results as found in SAMR1 mice. In conclusion, the knockdown of lncRNA SNHG1 enhanced DNA methylation through the PI3K/Akt signaling pathway, thereby reducing the phosphorylation levels of tau in SAMP8 AD model mice with ameliorating brain damage attributed to p-tau accumulation with consequent neuroprotection.

Mapping cryptic binding sites of drug targets to overcome drug resistance.

The emergence of drug resistance is a primary obstacle for successful chemotherapy. Drugs that target cryptic binding sites (CBSs) represent a novel strategy for overcoming drug resistance. In this short communication, we explain and discuss how the discovery of CBSs and their inhibitors can overcome drug resistance.

Manipulating the Thermal Conductivity of the Graphene/Poly(vinyl alcohol) Composite via Surface Functionalization: A Multiscale Simulation.

The reverse non-equilibrium molecular dynamics simulation is used to investigate the influence of functional groups (FGs) on the thermal conductivity of a graphene/poly(vinyl alcohol) (PVA) composite, which considers non-polar (methyl) and polar (hydroxyl, amino, and carboxyl) groups. First, the polar groups can be more effective to improve the interfacial thermal conductivity than the non-polar group. This can be explained well by characterizing the interfacial Coulombic energy, number and lifetime of hydrogen bonds, vibrational density of states, and integrated autocorrelation of the interfacial heat power. Moreover, the hydroxyl group can improve the interfacial thermal conductivity more than the other groups, which can be rationalized by analyzing the surface roughness of graphene and the radial distribution function of FGs and the PVA chains. However, the introduction of FGs destroys the graphene structure, which consequently reduces the intrinsic thermal conductivity. Furthermore, by adopting the effective medium approximation model and finite element method, there exists a critical graphene length where the overall thermal conductivities are equal for the functionalized and pristine graphene. Finally, the distribution state of graphene is emphasized to be more vital in determining the overall thermal conductivity than the generally accepted interfacial thermal conductivity.

Genetic and evolutionary dissection of melatonin response signaling facilitates the regulation of plant growth and stress responses.

The expansion of gene families during evolution could generate functional diversity among their members to regulate plant growth and development. Melatonin, a phylogenetically ancient molecule, is vital for many aspects of a plant's life. Understanding the functional diversity of the molecular players involved in melatonin biosynthesis, signaling, and metabolism will facilitate the regulation of plant phenotypes. However, the molecular mechanism of melatonin response signaling elements in regulating this network still has many challenges. Here, we provide an in-depth analysis of the functional diversity and evolution of molecular components in melatonin signaling pathway. Genetic analysis of multiple mutants in plant species will shed light on the role of gene families in melatonin regulatory pathways. Phylogenetic analysis of these genes was performed, which will facilitate the identification of melatonin-related genes for future study. Based on the abovementioned signal networks, the mechanism of these genes was summarized to provide reference for studying the regulatory mechanism of melatonin in plant phenotypes. We hope that this work will facilitate melatonin research in higher plants and finely tuned spatio-temporal regulation of melatonin signaling.

Effect of Cross-Linking Density on Non-Linear Viscoelasticity of Vulcanized SBR: A MD Simulation and Experimental Study.

In recent years, there has been a growing interest in changes in dynamic mechanical properties of mixed rubber during dynamic shear, yet the influence of vulcanized characteristics on the dynamic shear behavior of vulcanized rubber, particularly the effect of cross-linking density, has received little attention. This study focuses on styrene-butadiene rubber (SBR) and aims to investigate the impact of different cross-linking densities (Dc) on dynamic shear behavior using molecular dynamics (MD) simulations. The results reveal a remarkable Payne effect, where the storage modulus experiences a significant drop when the strain amplitude (γ0) exceeds 0.1, which can be attributed to the fracture of the polymer bond and the decrease in the molecular chain's flexibility. The influence of various Dc values mainly resides at the level of molecular aggregation in the system, where higher Dc values impede molecular chain motion and lead to an increase in the storage modulus of SBR. The MD simulation results are verified through comparisons with existing literature.

Fabrication of Polyurethane Elastomer/Hindered Phenol Composites with Tunable Damping Property.

Vibration and noise-reduction materials are indispensable in various fields. Polyurethane (PU)-based damping materials can dissipate the external mechanical and acoustic energy through molecular chain movements to mitigate the adverse effects of vibrations and noise. In this study, PU-based damping composites were obtained by compositing PU rubber prepared using 3-methyltetrahydrofuran/tetrahydrofuran copolyether glycol, 4,4'-diphenylmethane diisocyanate, and trimethylolpropane monoallyl ether as raw materials with hindered phenol, viz., and 3,9-bis{2-[3-(3-tert-butyl-4-hydroxy-5-methylphenyl)proponyloxy]-1,1-dimethylethyl}-2,4,8,10-tetraoxaspiro[5.5]undecane (AO-80). Fourier transform infrared spectroscopy, thermogravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, and tensile tests were conducted to evaluate the properties of the resulting composites. The glass transition temperature of the composite increased from -40 to -23 °C, and the tan δMax of the PU rubber increased by 81%, from 0.86 to 1.56 when 30 phr of AO-80 was added. This study provides a new platform for the design and preparation of damping materials for industrial applications and daily life.

A refined management system focusing on medication dispensing errors: A 14-year retrospective study of a hospital outpatient pharmacy.

Objectives: This study aimed to evaluate the efficiency of a 14-year refined management system for the reduction of dispensing errors in a large-scale hospital outpatient pharmacy and to determine the effects of person-related and environment-related factors on the occurrence of dispensing errors. Methods: A retrospective study was performed. Data on dispensing errors, inventory and account management from 2008 to 2021 were collected from the electronic system and evaluated using the direct observation method and the Plan-Do-Check-Act (PDCA) cycle. Results: The consistency of the inventory and accounts increased substantially (from 86.93 % to 99.75 %) with the implementation of the refined management program. From 2008 to 2021, the total number of dispensing errors was reduced by approximately 96.1 %. The number of dispensing errors in quantity and name was reduced by approximately 98.2 % and 95.07 %, respectively. A remarkable reduction in the error rate was achieved (from 0.014 % to 0.00002 %), and the rate of dispensing errors was significantly reduced (0.019 % vs. 0.0003 %, p < 0.001). Across all medication dispensing errors, human-related errors decreased substantially (208 vs. 7, p < 0.05), as did non-human-related errors also (202 vs. 9, p < 0.05). There was a correlation between the occurrence of errors and pharmacists' sex (females generally made fewer errors than males), age (more errors were made by those aged 31-40 years), and working years (more errors were made by those with more than 11 years of work experience) from 2016 to 2021. The technicians improved during this procedure. Conclusions: Refined management using the PDCA cycle was helpful in preventing dispensing errors and improving medication safety for patients.

Clinical study of interstitial brachytherapy for 72 cases of recurrent cervical cancer.

Objective: To determine the application value of interstitial brachytherapy in the treatment of recurrent cervical cancer. Methods: A retrospective analysis was conducted on the clinical data of 72 patients with recurrent cervical cancer admitted to The Fourth Hospital of Hebei Medical University from September 2017 to April 2022. They were divided into two groups according to different brachytherapy methods: conventional after-load radiotherapy group and interstitial brachytherapy group. After treatment, regular outpatient reviews or telephone follow-ups were conducted to evaluate the efficacy, related toxic and side effects and prognostic factors. Results: The short-term efficacy of the interstitial brachytherapy group was significantly higher than that of the interstitial brachytherapy group (p<0.05). The one-year LC and two-year LC of the interstitial brachytherapy group were 94% and 90.6%, respectively, while those of the conventional after-load group were 74.5% and 67.8%, respectively, with a statistically significant difference (p<0.05). The clinical efficacy of peripheral recurrence was 13.9% in the interstitial brachytherapy group, and that in the conventional after-load group was 2.7%, with a statistically significant difference (p<0.05). There was a statistically significant difference in late toxic and side effects between the two groups (p<0.05). Prognostic factors: Multivariate analysis of the COX regression model showed that only the maximum tumor diameter was an independent prognostic factor for OS and PFS, while the recurrence site and brachytherapy method were the independent prognostic factors for LC. Conclusion: Interstitial brachytherapy radiotherapy touts various benefits in the treatment of patients with recurrent cervical cancer, such as good short-term efficacy, high local control rate, reduced incidence of advanced bladder and rectal toxicity, and improved quality of life.

Short Stature in Patients with Diamond-Blackfan Anemia: A Cross-Sectional Study.

OBJECTIVE: To systematically describe the short stature of patients with Diamond-Blackfan anemia and to explore factors affecting the height development of patients with Diamond-Blackfan anemia. STUDY DESIGN: This cross-sectional study was conducted at the Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, and the height, weight, and clinical data of 129 patients with Diamond-Blackfan anemia were collected from June 2020 to September 2020. RESULTS: The median height-age-z score (HAZ) of children affected by Diamond-Blackfan anemia was -1.54 (-6.36-1.96). Short stature was found in 37.98% of the patients. Specific Diamond-Blackfan anemia growth curves were developed for weight, height, and body mass index, separately for male and female patients. Multivariable logistic regression models showed that female sex (aOR 4.92; 95% CI 1.29-18.71; P = .0195), underweight (aOR 10.41, 95% CI 1.41-76.98, P = .0217), cardiovascular malformations (aOR 216.65; 95% CI 3.29-14279.79; P = .0118), and RPL11(aOR 29.14; 95% CI 1.18-719.10; P = .0392) or RPS26 (aOR 53.49; 95% CI 1.40-2044.30; P = .0323) mutations were independent risk factors for short stature. In the subgroup of patients who were steroid-dependent, patients with a duration of steroid therapy over 2 years (OR 2.95; 95% CI 1.00-8.66; P = .0494) or maintenance dose of prednisone >0.1 mg/kg per day (OR 3.30; 95% CI 1.02-10.72; P = .0470) had a higher incidence of short stature. CONCLUSIONS: Patients with Diamond-Blackfan anemia had a high prevalence of short stature. The risk of short stature increased with age and was associated with sex, underweight, congenital malformations, and RPL11 or RPS26 mutations. The duration of steroid therapy and maintenance dose of steroid was significantly associated with the incidence of short stature in steroid-dependent patients with Diamond-Blackfan anemia.

Barley transcription factor HvNLP2 mediates nitrate signaling and affects nitrogen use efficiency.

Plants have evolved complex mechanisms to adapt to the changing nitrogen levels in the environment. In Arabidopsis, more than a dozen nitrate signaling regulatory genes have been characterized, including the NODULE INCEPTION-LIKE PROTEIN (AtNLP) genes, which play essential roles in nitrate signaling. However, whether NLP genes in the Triticeae crops are involved in nitrate regulation and nitrogen use efficiency (NUE) remains unknown. Here, we isolated a barley (Hordeum vulgare L.) mutant, hvnlp2-1, from a TILLING (Targeting Local Lesions IN Genomes) population and constructed two RNAi lines, hvnlp2-2 and hvnlp2-3, to study the function of HvNLP2. The expression of the nitrate-responsive genes was substantially inhibited after nitrate treatment in the hvnlp2 mutants, indicating that HvNLP2 controls nitrate signaling. Nitrate content was significantly higher in the hvnlp2 mutants, which may result from the decreased assimilation of nitrogen caused by reduced nitrate reductase activity and expression of nitrate assimilatory genes. HvNLP2 is localized to the nucleus in the presence of nitrate. Further investigation showed that HvNLP2 binds to and activates the nitrate-responsive cis-elements. Moreover, hvnlp2 exhibited reduced biomass, seed yield, and NUE. Therefore, HvNLP2 controls nitrate signaling and plays an important role in NUE.

High Visceral Fat in Female Breast Cancer Patients Correlates with the Risk of Progression after Adjuvant Chemotherapy.

RATIONALE: Clinical and epidemiological evidence indicate that obesity is associated with the risk and progression of breast cancer. Body mass index (BMI) as a measure of adiposity does not precisely describe individual body composition and adipose tissue distribution. We aimed to investigate the association between body composition and the efficiency of adjuvant chemotherapy as well as post-treatment progress among female breast cancer patients. METHODS: Participants included 199 females with stage I-III breast cancer. Body composition, including body fat mass, visceral fat level, and skeletal muscle mass, was assessed based on the bioelectrical impedance analysis (BIA). The Kaplan-Meier survival curves, log-rank test, and Cox proportional-hazards model were used to estimate the effects of body composition as prognostic factors on survival. RESULTS: Postmenopausal women had a higher proportion of visceral fat compared to premenopausal women (64% vs. 33.87%, P < 0.001). Compared with those with normal visceral fat level, patients with high visceral fat level were older (P < 0.001), had higher body fat mass (p < 0.001), skeletal muscle mass (P = 0.013), minerals (P = 0.011), protein (P = 0.036), triglycerides (P = 0.038), cholesterol (P = 0.022), and low-density lipoprotein cholesterol (LDL-C) (P = 0.015). A more prolonged disease-free survival (DFS) was noted in patients with a normal visceral fat level as compared to patients with a high visceral fat level (hazard ratio [HR] 1.9, 95% CI 1-3.5; adjusted HR 1.77, 95% CI 0.932-3.36). CONCLUSIONS: A high visceral fat level in female patients with breast cancer is associated with a shorter DFS after adjuvant chemotherapy. Body composition alongside BIA provides a quick and noninvasive approach to identify breast cancer patients with a higher risk of cancer progression.